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REGULATION OF GENE EXPRESSION BY THE ANDROGEN RECEPTOR AND HEDGEHOG PATHWAYS IN BREAST CANCER CELLS

VIVIAN YAR LI CHUA

B.SC. (HONS)

THIS THESIS IS PRESENTED FOR THE DEGREE OF DOCTOR OF

PHILOSOPHY OF THE UNIVERSITY OF WESTERN AUSTRALIA, SEPTEMBER

2015

SCHOOL OF PATHOLOGY AND LABORATORY MEDICINE

UNIVERSITY OF WESTERN AUSTRALIA

PERTH, WESTERN AUSTRALIA

Declaration

The work detailed in this thesis was performed by the candidate unless otherwise

specified. This thesis is submitted for the degree of Doctor of Philosophy at the

University of Western Australia and has not been submitted elsewhere for any other

degree.

PhD Candidate:

Vivian Yar Li CHUA

Date:______________

Principal Supervisor:

Adjunct Associate Professor Jacqueline BENTEL

Date:______________

Coordinating Supervisor:

Winthrop Professor Jennet HARVEY

Date:______________

Co-supervisor:

Professor Bu YEAP

Date:______________

TABLE OF CONTENTS Acknowledgements ............................................................................................................. i Awards ............................................................................................................................... ii Publications ....................................................................................................................... iii List of Figures .................................................................................................................... v List of Tables................................................................................................................... viii Abbreviations .................................................................................................................... ix Abstract ............................................................................................................................ xv

CHAPTER 1: GENERAL INTRODUCTION

1.1 The Human Mammary Gland .................................................................................. 1

1.2 Breast Cancer ............................................................................................................. 2

1.2.1 Classification of Breast Cancer ........................................................................... 3

1.3 Breast Cancer Risk Factors....................................................................................... 5

1.4 Regulation of Breast Cancer Growth ....................................................................... 8

1.4.1 Oestrogen Receptor (ER) ................................................................................... 8

1.4.2 Progesterone Receptor (PR) .............................................................................. 10

1.4.3 Human Epidermal Growth Factor-Like Receptor 2 (HER2) ............................ 11

1.4.4 Androgens and the Androgen Receptor ............................................................ 12

1.4.4.1 Androgens ................................................................................................. 12

1.4.4.2 The Androgen Receptor ............................................................................ 13

1.4.4.3 Androgens and the AR in Breast Cancer .................................................. 15

1.4.4.4 Androgens and AR Modulators as Therapies for Breast Cancer ............. 17

1.4.5 The Hedgehog Signalling Pathway ................................................................... 18

1.4.5.1 Hedgehog Signalling in Breast Cancer ..................................................... 20

1.4.5.2 Crosstalk between the Hedgehog Signalling Pathway and Hormone

Receptors .............................................................................................................. 21

1.5 Breast Cancer Treatment ........................................................................................ 22

1.6 The ABC Transporters ............................................................................................ 24

1.6.1 The ABC Transporter Superfamily ................................................................... 25

1.6.2 Physiological Roles of the ABC Transporters .................................................. 26

1.6.3 ABC Transporters in Cancer ............................................................................. 27

1.6.3.1 ABCB1 / P-glycoprotein (P-gp) ............................................................... 28

1.6.3.2 ABCG2 / Breast Cancer Resistance Protein (BCRP) ............................... 31

1.6.3.2.1 ABCG2 in Breast Cancer ................................................................. 33

1.6.3.2.2 ABCG2 Protein Structure and Synthesis ......................................... 33

1.6.3.3 ABCC / Multidrug Resistance Protein (MRP) ......................................... 35

1.6.4 Modulators of the ABC Transporters ................................................................ 36

1.7 Epithelial-to-Mesenchymal Transition (EMT) ...................................................... 37

1.7.1 Physiological Processes Mediating EMT .......................................................... 38

1.7.1.1 Cell-to-Cell Adhesion Complexes ............................................................ 39

1.7.1.2 Integrin-Mediated Focal Adhesions.......................................................... 41

1.7.1.3 Matrix Metalloproteinases (MMPs) ......................................................... 42

1.7.2 Regulation of EMT by Signalling Pathways .................................................... 42

1.7.2.1 TGFβ Pathway .......................................................................................... 42

1.7.2.2 The WNT Signalling Pathway .................................................................. 44

1.7.2.3 The Notch Signalling Pathway ................................................................. 47

1.7.3 EMT in Breast Cancer ....................................................................................... 49

1.8 Statement of Aims .................................................................................................... 52

CHAPTER 2: MATERIALS

2.1 Reagents .................................................................................................................... 53

2.1.1 Cell Culture ....................................................................................................... 53

2.1.2 Immunofluorescence Microscopy ..................................................................... 53

2.1.3 Flow Cytometry and Cell Sorting ..................................................................... 54

2.1.4 Western Blotting ................................................................................................ 54

2.1.5 Agarose Gel Electrophoresis, PCR, RT-qPCR, Sanger Sequencing ................. 54

2.1.6 General .............................................................................................................. 55

2.2 Laboratory Equipment ............................................................................................ 56

2.2.1 Cell Culture ....................................................................................................... 56

2.2.2 Immunofluorescence Microscopy ..................................................................... 57

2.2.3 Flow Cytometry and Cell Sorting ..................................................................... 57

2.2.4 Western Blotting ................................................................................................ 58

2.2.5 Agarose Gel Electrophoresis, PCR, RT-qPCR, Sanger Sequencing ................. 58

2.2.6 General .............................................................................................................. 59

2.3 Antibodies ................................................................................................................. 60

2.4 Commercial Kits....................................................................................................... 61

2.5 Computer Programmes ........................................................................................... 62

CHAPTER 3: METHODS

3.1 Cell Culture .............................................................................................................. 63

3.1.1 Maintenance of Breast Cancer Cell Lines ......................................................... 63

3.1.2 Cryopreservation of Cell Lines ......................................................................... 63

3.1.3 Thawing of Cell Lines ....................................................................................... 63

3.1.4 Isolation of Breast Cancer Stem-Like Cells ...................................................... 64

3.1.5 Treatment of Breast Cancer Cell Lines ............................................................. 64

3.1.5.1 MTS Proliferation Assay ......................................................................... 64

3.1.5.2 Immunofluorescence Microscopy............................................................. 65

3.1.5.3 Flow Cytometry ........................................................................................ 65

3.1.5.4 Western Blotting ....................................................................................... 66

3.1.5.5 RNA Extraction ........................................................................................ 67

3.1.5.6 Wound Healing Assays ............................................................................. 67

3.1.5.7 Biocoat™ Matrigel™ Invasion Assays ....................................................... 68

3.1.5.8 3D Matrigel™ Colony Formation Assays .................................................. 68

3.2 MTS Proliferation Assays ....................................................................................... 69

3.3 Immunofluorescence Microscopy ........................................................................... 70

3.4 Flow Cytometry ........................................................................................................ 70

3.5 Fluorescence-Activated Cell Sorting (FACS) ........................................................ 71

3.6 Subcellular Fractionation ........................................................................................ 72

3.7 Western Blotting ...................................................................................................... 72

3.7.1 Whole Cell Lysis ............................................................................................... 72

3.7.2 SDS-Polyacrylamide Gel Electrophoresis (SDS-PAGE) .................................. 72

3.7.3 Immunoblotting ................................................................................................. 73

3.8 Polymerase Chain Reaction (PCR) and Reverse Transcription Quantitative

PCR (RT-qPCR) ............................................................................................................ 74

3.8.1 RNA Extraction ................................................................................................ 74

3.8.2 Reverse Transcription ........................................................................................ 75

3.8.2.1 cDNA Synthesis Using Superscript™ III .................................................. 75

3.8.2.2 Preparation of cDNA Using the RT2 First Strand cDNA Synthesis Kit .. 75

3.8.3 Purification of cDNA ......................................................................................... 76

3.8.4 Primer Design .................................................................................................... 76

3.8.5 Polymerase Chain Reaction (PCR) .................................................................... 76

3.8.6 Agarose Gel Electrophoresis ............................................................................. 77

3.8.7 Reverse Transcription-Quantitative PCR (RT-qPCR) ...................................... 77

3.8.8 PCR Arrays ....................................................................................................... 78

3.9 Sanger Sequencing ................................................................................................... 80

CHAPTER 4: DHT AND CYCLOPAMINE EFFECTS ON THE EXPRESSION

AND FUNCTION OF ABCG2 IN MCF-7 AND T-47D CELLS 4.1 Introduction .............................................................................................................. 82

4.2 Results ....................................................................................................................... 89

4.2.1 DHT and Cyclopamine Regulation of Gene Expression in Breast Cancer Cells ..

.................................................................................................................................... 89

4.2.2 DHT and Cyclopamine Regulation of ABCG2 mRNA Levels in MCF-7 Cells ...

.................................................................................................................................... 90

4.2.3 DHT and Cyclopamine Regulation of ABCG2 Protein Levels in MCF-7 Cells ..

.................................................................................................................................... 94

4.2.4 Intracellular Localisation of ABCG2 in DHT and Cyclopamine Treated MCF-

7 Cells ......................................................................................................................... 95

4.2.5 DHT and Cyclopamine Effects on ABCG2 Protein Degradation ................... 102

4.2.6 DHT and Cyclopamine Regulation of ABCG2 Efflux Activity ..................... 121

4.2.6.1 DHT and Cyclopamine Effects on the Sensitivity of MCF-7 Cells to

Mitoxantrone ....................................................................................................... 131

4.2.7 Isolation of Breast Cancer Stem-Like Cells from MCF-7 Breast Cancer Cells ....

.................................................................................................................................. 134

4.2.7.1 DHT and Cyclopamine Effects on ABCG2 and AR Protein Levels in

Breast Cancer Stem-Like Cells ........................................................................... 136

4.2.7.2 Intracellular Localisation of ABCG2 in DHT and Cyclopamine Treated

Breast Cancer Stem-Like Cells ........................................................................... 143

4.3 Discussion ................................................................................................................ 148

CHAPTER 5: DHT AND CYCLOPAMINE REGULATION OF EMT IN MCF-7

AND T-47D CELLS

5.1 Introduction ............................................................................................................ 158

5.2 Results ..................................................................................................................... 164

5.2.1 DHT and Cyclopamine Regulation of EMT-Associated Genes in Breast

Cancer Cells ............................................................................................................. 164

5.2.1.1 Effects of DHT and Cyclopamine on ECM Remodelling ...................... 176

5.2.1.2 DHT and Cyclopamine Regulation of the WNT and TGFβ Pathways .. 177

5.2.1.3 Classification of DHT and Cyclopamine-Specific Pathways ................ 178

5.2.2 DHT and Cyclopamine Effects on MCF-7 Cell Migration and Invasion ....... 186

5.3 Discussion ................................................................................................................ 191

CHAPTER 6: GENERAL DISCUSSION ...................................................... 198

Future Directions ......................................................................................................... 210

REFERENCES ............................................................................................................. 215

APPENDICES

1: Buffers and Solutions ................................................................................................. 264

2: Description of Genes Screened in the RT2 Profiler EMT PCR Array (PAHS-090Z) .....

........................................................................................................................................ 273

3: EMT PCR Array Amplification and Melt Curves ..................................................... 277

4: RT2 Profiler EMT PCR Array Fold Regulation Data (MCF-7) ................................. 279

5: RT2 Profiler EMT PCR Array Fold Regulation Data (T-47D) .................................. 283

6: Description of Genes Screened in the RT2 Profiler Breast Cancer PCR Array (PAHS-131A) ............................................................................................................................. 287

i

ACKNOWLEDGEMENTS First and foremost, I would like to thank my principal supervisor, Dr Jacqueline Bentel

for accepting me as a PhD student, giving me this chance to continue my studies during

which I was able to grow as a person/scientist and also for helping me to realise things

that I never imagined I could accomplish. Thank you for being patient with me and I

can only ever repay you by continuing to do what you’ve taught or improve from that. I

would also like to acknowledge Winthrop Professor Jennet Harvey and Professor Bu

Yeap for taking on the role as my co-supervisors and for supporting, listening and

encouraging me throughout the years.

To all past and present members of the Bentel/Thomas Lab, Dr Marc Thomas, Dr

Jasmine Tay, Dr Alison Louw, my first mentor: Ebony Rouse, Jamie Rodgers, Abbie

Creamer, Danika Hope, Erin Bolitho and Agata Sadowska, thank you very much for

your patience, guidance, advice and company throughout these years.

Here, I would also like to acknowledge Dr Archa Fox (Harry Perkins Institute for

Medical Research) for use of the Nikon Eclipse fluorescence microscope, Associate

Professor Richard Allcock (Lotterywest State Biomedical Facility Genomics) for use of

the Roche Light Cycler, Mike Epis/Professor Peter Leedman (Harry Perkins Institute

for Medical Research) for allowing me to use the liquid handling robotics, Associate

Professor Nathan Pavlos (UWA) for his input into the fluorescence microscopy images,

Rom Krueger (Royal Perth Hospital Flow Cytometry Unit), for his guidance in the use

of the flow cytometer, Irma Larma, for her time and help with the cell sorter and

Professor Paul Rigby and Alysia Buckley for their assistance with the Nikon A1

confocal microscope.

To my family, Dad, Mum and Chris, thank you for always supporting me and providing

me with laughter and love. My only wishes to you are to be healthy and to live happily.

ii

AWARDS 1. I was recipient of the Basic Science Encouragement Award for my oral presentation

titled, “Interactions between the Androgen Receptor and Hedgehog Signalling

Pathways in Breast Cancer Cells” at the Young Investigators’ Day held by the Royal

Perth Hospital Medical Research Foundation on 31st October 2012.

2. I was awarded the Silver Prize sponsored by City of Perth and EMBL Australia for

my oral presentation titled, “Crosstalk Between the Androgen Receptor (AR) and

Hedgehog Signalling Pathways in Breast Cancer Cells” at the Australian Society for

Medical Research (ASMR) on 5th June 2013.

3. I was awarded the Basic Science Encouragement Award for my oral presentation

titled, “Regulation of Gene Expression by the Androgen Receptor (AR) and

Hedgehog Signalling Pathways in Breast Cancer Cells” at the Young Investigators’

Day held by the Royal Perth Hospital Medical Research Foundation on 3rd

September 2014.

iii

PUBLICATIONS (CONFERENCE ABSTRACTS AND PRESENTATIONS)

1. Chua, V., Roehrig, K., Harvey, J. and Bentel, J. Oral presentation titled: “Interaction between Androgen Receptor and Hedgehog Signalling in Breast Cancer Cells”, Australian Society for Medical Research (ASMR), June 2012.

2. Chua, V., Roehrig, K., Harvey, J. and Bentel, J. Oral presentation titled: “Androgen Receptor and Hedgehog Signalling Interaction in Breast Cancer”, Combined Biological Sciences Meeting (CBSM), August 2012.

3. Chua, V., Roehrig, K., Harvey, J. and Bentel, J. Oral presentation titled: “Interactions between the Androgen Receptor and Hedgehog Signalling Pathways in Breast Cancer Cells”, Young Investigators’ Day, Royal Perth Hospital Medical Research Foundation, October 2012.

4. Chua, V., Roehrig, K., Harvey, J. and Bentel, J. Oral presentation titled: “Crosstalk between the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Australian Society for Medical Research (ASMR), June 2013.

5. Chua, V., Roehrig, K., Harvey, J. and Bentel, J. Poster presentation titled: “Crosstalk between the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Combined Biological Sciences Meeting (CBSM), August 2013.

6. Chua, V., Roehrig, K., Harvey, J. and Bentel, J. Poster presentation titled: “Crosstalk between the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Australian Society for Biochemistry and Molecular Biology (ASBMB), September 2013.

7. Chua, V., Chong, C., Harvey, J. and Bentel, J. Oral presentation titled: “Crosstalk between the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Cancer Council WA, October 2013.

8. Chua, V., Harvey, J. and Bentel, J. Oral presentation titled: “Regulation of Gene Expression in Breast Cancer Cells by the Androgen Receptor (AR) and Hedgehog Signalling Pathways”, Young Investigators’ Day, Royal Perth Hospital Medical Research Foundation, October 2013.

9. Chua, V., Harvey, J. and Bentel, J. Poster presentation titled: “Crosstalk between the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, 6th Barossa National Conference, November 2013.

10. Chua, V., Harvey, J. and Bentel, J. Oral presentation titled: “Regulation of ABCG2 by the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Australian Society for Medical Research (ASMR), June 2014.

11. Chua, V., Harvey, J. and Bentel, J. Poster presentation titled: “Regulation of ABCG2 by the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Combined Biological Sciences Meeting (CBSM), August 2014.

iv

12. Chua, V., Harvey, J. and Bentel, J. Oral presentation titled: “Regulation of Gene Expression by the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Young Investigators’ Day, Royal Perth Hospital Medical Research Foundation, September 2014.

13. Chua, V., Harvey, J. and Bentel, J. Poster presentation titled: “Regulation of ABCG2 Expression and Function in Breast Cancer Cells”, National Breast Cancer Foundation Conference 2014, Sydney, Australia, September 2014.

14. Chua, V., Harvey, J. and Bentel, J. Poster presentation titled: “Regulation of the Drug Efflux Transporter, ABCG2, by the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, 15th IUBMB 24th FAOBMB-TSBMB Conference, Taipei, Taiwan, October 2014.

15. Chua, V., Harvey, J. and Bentel, J. Poster presentation titled: “Regulation of the ABCG2 Drug Efflux Transporter in Breast Cancer Cells”, 2015 American Association for Cancer Research (AACR) Conference, Philadelphia, USA, April 2015.

16. Chua, V., Harvey, J. and Bentel, J. Oral presentation titled: “Regulation of the ABCG2 Drug Efflux Transporter in Breast Cancer Cells”, Australian Society for Medical Research (ASMR), June 2015.

17. Chua, V., Yeap, B., Harvey, J. and Bentel, J. Poster presentation titled: “Regulation of the Drug Efflux Transporter ABCG2 by the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Combined Biological Sciences Meeting (CBSM), August 2015.

v

LIST OF FIGURES Figure Title Page

1.1 Anatomy of the human mammary gland in females 1

1.2 Schematic diagram of the mammary epithelium at puberty and during pregnancy 2

1.3 Classification of breast tumours 3

1.4 The androgen receptor signalling pathway 14

1.5 Correlation of AR expression in breast tumours and overall survival of patients 17

1.6 The Hedgehog signalling pathway 19

1.7 Structural domains of the ABC transporters 25

1.8 Efflux of chemotherapeutic agents by ABCB1, ABCC1, ABCC10 and ABCG2 29

1.9 Putative binding sites of transcription factors in the ABCB1 promoter 30

1.10 ABCG2/BCRP gene and protein map 31

1.11 Transcriptional regulation of ABCG2 31

1.12 Structural domains of the ABCG2 half-transporter 34

1.13 Post-translational modification and plasma membrane trafficking of ABCG2 35

1.14 Epithelial-to-mesenchymal transition (EMT) 39

1.15 Adhesion complexes between adjacent cells and the ECM 40

1.16 TGFβ signalling 44

1.17 The canonical WNT signalling pathway 45

1.18 The non-canonical WNT/planar cell polarity (PCP) pathway 46

1.19 The non-canonical WNT/Ca2+ pathway 47

1.20 The Notch signalling pathway 48

3.1 Layout of the RT2 Profiler Human EMT PCR Array (PAHS-090Z) 79

3.2 Loading of 384-well RT2 Profiler PCR Arrays (G Format) 80

4.1 DHT and cyclopamine effects on cell proliferation and expression of breast cancer-associated genes 91

4.2 Optimisation of ABCG2 qPCR conditions 96

4.3 ABCG2 mRNA levels in DHT and cyclopamine treated MCF-7 cells 98

4.4 DHT and cyclopamine regulation of ABCG2 protein levels 99

4.5 Optimisation of primary and secondary antibody concentrations for investigation of ABCG2 intracellular localisation by immunofluorescence microscopy

103

vi

4.6 Intracellular localisation of ABCG2 in MCF-7 cells 105

4.7 Effects of DHT and cyclopamine on the intracellular localisation of ABCG2 in MCF-7 cells 106

4.8 Optimisation of experimental conditions for treatment of MCF-7 cells with the proteasome inhibitor, MG132 111

4.9 MG132 effects on the regulation of ABCG2 protein in DHT and cyclopamine treated MCF-7 cells 113

4.10 Treatment of MCF-7 cells with the lysosome inhibitor, chloroquine 115

4.11 Effects of lysosomal inhibition on DHT and cyclopamine induced regulation of ABCG2 protein levels 117

4.12 Intracellular co-localisation of ABCG2 and lysosomes 119

4.13 ABCG2 exon 12 cDNA sequence in MCF-7 cells 123

4.14 Flow cytometric analysis of the intracellular levels of ABCG2 substrates, mitoxantrone (MX) and Rhodamine 123 (Rhd123) in MCF-7 cells

124

4.15 Efflux of Rhodamine 123 from MCF-7 cells 126

4.16 Optimisation of mitoxantrone concentration for investigation of ABCG2 efflux activity 128

4.17 DHT and cyclopamine effects on the efflux rate of mitoxantrone from MCF-7 cells 130

4.18 Standard curve for MTS proliferation assays 132

4.19 Sensitivity of MCF-7 cells to mitoxantrone following treatment with DHT and cyclopamine 133

4.20 Optimisation of Hoechst 33342 concentration for flow cytometry 137

4.21 Optimisation of CD44-APC and CD24-BV421 antibodies for flow cytometry 138

4.22 Isolation of breast cancer stem-like cells (Hoechst 33342lo/CD44hi/CD24lo) from MCF-7 cells 140

4.23 Confirmation of stem cell properties in the breast cancer stem-like cells (Hoechst 33342lo/CD44hi/CD24lo) 141

4.24 DHT and cyclopamine regulation of ABCG2 and AR protein levels in breast cancer stem-like cells isolated from MCF-7 cultures 145

4.25 Effects of DHT and cyclopamine on the intracellular localisation of ABCG2 in breast cancer stem-like cells isolated from MCF-7 cultures 146

5.1 Efficiency curves for AR and GAPDH qPCR in MCF-7 and T-47D cells 167

5.2 DHT and cyclopamine regulation of AR mRNA levels 169

5.3 DHT and cyclopamine regulation of EMT-associated genes in MCF-7 cells 170

5.4 DHT and cyclopamine regulation of EMT-associated genes in T-47D cells 172

vii

5.5 Classification of DHT and cycopamine regulated EMT-associated genes in MCF-7 and T-47D cells 179

5.6 Mapping of DHT and cyclopamine regulated EMT-associated genes in MCF-7 cells to canonical pathways 181

5.7 Mapping of DHT and cyclopamine regulated EMT-associated genes in T-47D cells to canonical pathways 183

5.8 Pathways associated with genes regulated by ≥1.5-fold following DHT and cyclopamine treatments of MCF-7 and T-47D cells 185

5.9 DHT and cyclopamine effects on MCF-7 cell migration 188

5.10 DHT and cyclopamine regulation of MCF-7 cell invasion 189

viii

LIST OF TABLES

Table Title Page

1.1 The seven subfamilies/subclasses of the ATP-binding cassette (ABC) superfamily 26

3.1 Antibody dilutions for immunoblotting 74

3.2 Primers for PCR and RT-qPCR 78

4.1 Regulation of ABCB1 and ABCG2 mRNA levels in MCF-7 and T-47D cells 93

5.1 Pathway enrichment associated with DHT and cyclopamine regulated genes in MCF-7 cells 174

5.2 Pathway enrichment associated with DHT and cyclopamine regulated genes in T-47D cells 175

ix

ABBREVIATIONS α Alpha

β Beta

γ Gamma

µ Micro

ºC Degrees celsius

2-ME 2-Mercaptoethanol

3D 3-Dimensional

7-AAD 7-Aminoactinomycin D

ABC ATP-binding cassette

ADH Atypical ductal hyperplasia

AJ Adherens junctions

ALDH Aldehyde dehydrogenase

ALH Atypical lobular hyperplasia

AP1 Activator protein 1

APC Adenomatous polyposis coli

AR Androgen receptor

ARE Androgen response element

BAD BCL2-associated death promoter 2

BCL2 B-cell lymphoma 2

BMP Bone morphogenetic protein

BRCA Breast cancer susceptibility gene

BSA Bovine serum albumin

β-TrCP Beta-transducin repeat containing protein

CAMK2 Calcium/calmodulin-dependent kinase 2

CDK Cyclin-dependent kinase

cDNA Complementary DNA

ChIP Chromatin immunoprecipitation

CK1 Casein kinase 1

x

CO2 Carbon dioxide

CSCs Cancer stem cells

CSS Charcoal-treated foetal calf serum

Ct Threshold cycle

DAAM1 Disheveled-associated activator of morphogenesis 1

DBD DNA-binding domain

DCIS Ductal carcinoma in situ

DHEA Dehydroepiandrosterone

DHEA-S Sulphate-conjugated dehydroepiandrosterone

DHT 5α-Dihydrotestosterone

DMSO Dimethyl sulfoxide

DNA Deoxyribonucleic acid

DSH Dishevelled

E2 17β-Oestradiol

ECL Enhanced chemiluminescence

ECM Extracellular matrix

EDTA Ethylenediaminetetraacetic acid

EGF Epidermal growth factor

EGFR Epidermal growth factor receptor

EMT Epithelial-to-mesenchymal transition

ER Oestrogen receptor

ERE Oestrogen response element

ERK Extracellular signal-regulated kinase

ERM Ezrin-radixin-moesin

EV Extracellular vesicle

F-actin Filamentous actin

FAK Focal adhesion kinase

FCS Foetal calf serum

FEA Flat epithelial atypia

xi

FGF Fibroblast growth factor

FN1 Fibronectin

FSC Forward scatter

FTC Fumitremorgin C

5-FU 5-Fluorouracil

FZD Frizzled

g Gram

GAPDH Glyceraldehyde-3-phosphate dehydrogenase

GLI Glioma-associated oncogene

GSK3β Glycogen synthase kinase 3β

GTF General transcription factors

h Hour

HAT Histone acetyltransferase

HDAC Histone deacetylase

HER2 Human epidermal growth factor-like receptor 2

HGF Hepatocyte growth factor

HRT Hormone replacement therapy

HSP Heat shock protein

IDC Invasive ductal carcinoma

IGF Insulin-like growth factor

IGFR Insulin-like growth factor receptor

JAM Junction adhesion molecule

JNK c-Jun N-terminal kinase

kDa Kilodalton

KLK Kallikrein

KRT Keratin/cytokeratin

L Litre

LBD Ligand-binding domain

LCIS Lobular carcinoma in situ

xii

LLC Large latency complex

LRP Lipoprotein receptor-related protein

M Molar

MAPK Mitogen-activated protein kinase

MCF-7 Michigan Cancer Foundation-7

MDR Multidrug resistance

MET Mesenchymal-to-epithelial transition

MFI Mean fluorescence intensity

MgCl2 Magnesium chloride

miRNA MicroRNA

MMP Matrix metalloproteinase

mRNA Messenger RNA

MRP Multidrug resistance-associated protein

MSD Membrane spanning domain

MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulphophenyl)-2H-tetrazolium)

MX Mitoxantrone

MXR Mitoxantrone resistance

n Nano

NDB Nuclear-binding domain

NES Nuclear export signal

NFκB Nuclear factor kappa B

NLS Nuclear localisation signal

NTD N-terminal domain

P4 Progesterone

PAI-1 Plasminogen activator inhibitor 1

PBS Phosphate buffered saline

PCP Planar cell polarity

PCR Polymerase chain reaction

PFS Progression-free survival

xiii

P-gp P-glycoprotein

PI3K Phosphoinositide 3-kinase

PKA Protein kinase A

PKB Protein kinase B

PKC Protein kinase C

PMSF Phenylmethanesulfonyl fluoride

PR Progesterone Receptor

PRE Progesterone response element

PS Penicillin/streptomycin

PTCH1 Patched homologue 1

R2 Correlation coefficient

RhoA Ras homologue gene family, member A

Rhd123 Rhodamine 123

RNA Ribonucleic acid

RNAPolII RNA polymerase 2

rpm Revolutions per minute

RTK Receptor tyrosine kinase

RT-qPCR Reverse transcription quantitative PCR

SAPK Stress-activated protein kinase

SARM Selective androgen receptor modulator

SDS-PAGE SDS-polyacrylamide gel electrophoresis

S.E.M. Standard error of the mean

SERM Selective oestrogen receptor modulator

SHH Sonic hedgehog

SMO Smoothened

SNAI1 Snail1

SNAI2 Snail2 or Slug

SP Side population

SRC Src kinase

SSC Side scatter

xiv

TBP TATA-binding protein

TBS Tris-buffered saline

TCF/LEF T-cell factor/lymphoid enhancer factor

TGF-β Transforming growth factor beta

TJ Tight junction

TKI Tyrosine kinase inhibitor

TMD Transmembrane domain

TNBC Triple-negative breast cancer

TNFα Tumour necrosis factor alpha

U Unit

UV Ultraviolet

VEGF Vascular endothelial growth factor

VIM Vimentin

ZO-1 Zona occludens 1

xv

ABSTRACT The androgen receptor (AR) is expressed in 70-90% of breast tumours and its increased

expression in oestrogen receptor (ER) expressing breast cancers is correlated with better

disease prognosis and longer relapse-free and overall survival. The Hedgehog signalling

pathway has also been implicated in breast cancer growth, with Hedgehog signalling

intermediates and Hedgehog-induced target genes overexpressed in both early stage and

aggressive breast tumours. The androgen, 5α-dihydrotestosterone (DHT) and the

Hedgehog pathway inhibitor, cyclopamine, inhibit proliferation of the MCF-7 and T-

47D breast cancer cell lines and this thesis has investigated genes and cellular processes

regulated by these agents that would potentially impede breast tumour progression. In

DHT and cyclopamine treated MCF-7 and T-47D cells, screening of gene expression

using RT2 Profiler Human Breast Cancer PCR Arrays identified decreased expression of

both the ABC transporters, ABCB1 and ABCG2, which facilitate the development of

drug resistance in cancer cells, and regulators of epithelial-to-mesenchymal transition

(EMT), a program associated with induction of cancer cell motility, invasiveness and

metastasis.

PCR array results were further investigated in MCF-7 cells by RT-qPCR, which

identified that 24 h of treatment with 10-8 M DHT and the combination of 10-8 M DHT

and 2 µM cyclopamine reduced ABCG2 levels by 30-35%, while cyclopamine alone

had little effects on ABCG2 mRNA levels. During 8 days of treatment with DHT or

DHT and cyclopamine, ABCG2 protein levels were progressively decreased, with the

levels more rapidly reduced in cultures co-treated with both DHT and cyclopamine.

Using immunofluorescence microscopy, ABCG2 protein was found to accumulate in

cell-to-cell junction complexes as well as in large cytoplasmic, aggresome-like vesicles,

both of which were diminished following treatment of MCF-7 cells for 4 days with

DHT or DHT and cyclopamine. Interestingly, cyclopamine, which also decreased

ABCG2-associated cell-to-cell junction complexes, induced ABCG2 accumulation into

the aggresome-like vesicles. As ABC transporters including ABCG2 are functionally

active when bound to the membrane surface, these findings indicated that DHT and

cyclopamine treatments inhibited ABCG2 efflux activity. In support of this hypothesis,

DHT, cyclopamine and DHT/cyclopamine treatment of MCF-7 cells delayed the efflux

of mitoxantrone, an ABCG2 substrate and chemotherapeutic agent. Correspondingly,

xvi

the IC50 of mitoxantrone was reduced by ~70% (p<0.05) in cyclopamine and

DHT/cyclopamine treated MCF-7 cells. In breast cancer stem-like cells derived from

the MCF-7 cell line, DHT alone and the combination of DHT and cyclopamine reduced

ABCG2 protein levels by 35-45% after 8 days, a result comparable to that observed in

parental MCF-7 cells. Cyclopamine, which decreased ABCG2 protein levels by ~10%,

induced ABCG2 accumulation into aggresome-like vesicles whereas DHT and

DHT/cyclopamine treatments decreased the levels of ABCG2 in both cell-to-cell

junction complexes and in aggresome-like vesicles.

DHT and cyclopamine regulation of EMT-associated genes was investigated in MCF-7

and T-47D cells using RT2 Profiler Human EMT PCR Arrays. These studies identified

that DHT, cyclopamine and DHT/cyclopamine treatments of MCF-7 and T-47D cells

downregulated expression of mesenchymal markers, including SNAI1, TWIST1 and

vimentin but upregulated expression of the epithelial marker, KRT19, that encodes

cytokeratin-19. Pathway analysis of regulated genes using REACTOME identified that

the treatments predominantly downregulated expression of genes encoding components

of extracellular matrix (ECM) remodelling and cell-to-ECM interactions (e.g. collagens,

(COL1A2 and COL5A2), SPARC, versican (VCAN), fibronectin (FN1), integrins (ITGA5

and ITGB1)) as well as intermediates of pro-EMT signalling cascades, WNT (WNT5B,

CTNNB1, FZD7) and TGFβ (TGFB1, SMAD2, SERPINE1). Collectively, these findings

suggested inhibition or reversal of EMT and in support of these results, DHT,

cyclopamine and DHT/cyclopamine treatments of MCF-7 cells were found to inhibit

cell migration determined by wound healing assays and cell invasion in 3D Matrigel™

colony formation assays.

Development of drug resistance and tumour metastasis are major causes of breast

cancer-associated morbidity and mortality. Results from this study provide evidence

that androgens and Hedgehog signalling inhibitors may delay emergence of drug

resistant and metastatic disease by decreasing the expression and function of the

ABCG2 drug efflux transporter and inhibiting EMT.

Chapter 1

General Introduction

Chapter 1: General Introduction

1

1.1 The Human Mammary Gland

Humans have two mammary glands or breasts on the anterior chest wall and in women,

each mammary gland consists of a ductal-lobular system which produces milk as a

source of nourishment and nutrients for the young offspring (Figure 1.1) (Ali and

Coombes 2002). At birth, the mammary gland develops as a rudimentary tree-like

structure of ducts converging to a primitive nipple and during puberty and pregnancy,

the mammary glands of females but not males undergo dynamic changes (Ali and

Coombes 2002).

Figure 1.1: Anatomy of the human mammary gland in females. The female mammary gland is a source of nutrition for the offspring, producing milk in each alveolus which drains into the extensive branches of primary and secondary ducts that converge at the nipple. The ductal-lobular structure is surrounded by components of the stroma and expands into the mammary fat pad during puberty and pregnancy (Ali and Coombes 2002).

Growth of the female mammary gland is slow from birth to puberty but at the onset of

puberty, in response to regulators such as hormones secreted from the pituitary gland

(e.g. prolactin, growth hormone (GH)) and the ovaries (oestrogen, progesterone) and

growth factors (e.g. insulin-like growth factor (IGF)), cap cells at the tips of ducts

(terminal end buds (TEBs)) begin to proliferate rapidly, resulting in the formation of

secondary branches of ducts and invasion of the ducts into the mammary fat pad (Figure

1.2) (Topper and Freeman 1980, Ruan and Kleinberg 1999, Gallego et al 2001). During

pregnancy, hormones especially prolactin and progesterone stimulate further

proliferation and differentiation of cells to develop alveoli at the ends of ducts which

also undergo extensive branching and invasion to fill the entire mammary fat pad

(Naylor et al 2003). An alveolus is comprised of a single layer of polarised, milk-

producing alveolar epithelial cells which envelop a circular lumen connected to the


2

primary ductal network (Figure 1.2) (Macias and Hinck 2012). A contractile layer of

myoepithelial cells lining the outer surface of alveolar cells and ducts facilitates

transport of milk towards the nipple. At weaning, when production of milk ceases, the

mammary epithelium undergoes involution, remodelling its architecture into a pre-

pregnancy structure, a process that involves degradation of cells via programmed cell

death or apoptosis (Marti et al 2001).

Figure 1.2: Schematic diagram of the mammary epithelium at (A) puberty and (B) during pregnancy. (A) Terminal end buds (TEBs) of mammary glands contain cap cells at the ends of ducts which undergo rapid proliferation, resulting in extension of the ductal structure into the mammary fat pad. (B) During pregnancy, further proliferation and differentiation of cells and branching of ducts lead to formation of alveoli, in which milk that is secreted by the alveolar epithelial cells, is drained into the ducts towards the nipple by the contractile activity of myoepithelial cells that surround the alveolar and ductal structures (Gajewska et al 2013).

1.2 Breast Cancer

Breast cancer predominantly affects women and, with ~1.7 million cases recorded in

2012, is the most frequently diagnosed cancer of females worldwide (Torre et al 2015).

The disease is also a leading cause of cancer-related death and accounts for ~15% of

cancer-related death of women (>500,000 cases in 2012), with half of these cases

reported in economically developed countries (Torre et al 2015). The prevalence of

breast cancer is proportionally higher in developed countries such as North America,

Australia, New Zealand and in northern and western European countries compared to

African and Asian countries, and this is at least in part due to differences in exposure to

breast cancer risk factors (Section 1.3) and availability of facilities for early breast

tumour detection in developed countries (Torre et al 2015). In Australia, breast cancer is


3

the most prevalent cancer of women and is the second leading cause of cancer-related

death of women following lung cancer. In 2014, 15,270 breast cancer cases and 3000

deaths were reported (AIHW 2014). The average age at first diagnosis is 60.7 years and

1 in 11 women are at risk of developing breast cancer by the age of 75 (AIHW 2014).

1.2.1 Classification of Breast Cancer

Breast cancer is a clinically heterogeneous and progressive disease that can present at

various stages with differing severity, metastatic potential and disease prognosis. Breast

tumours can be classified according to histological or molecular features, which are

used to determine disease prognosis and to select appropriate therapies (Section 1.5).

The two broad classes of breast cancer are the in situ or the more clinically aggressive

invasive (infiltrating) carcinomas (Figure 1.3).

Figure 1.3: Classification of breast tumours. Breast cancer is broadly classified into in situ or invasive (infiltrating) carcinomas. In situ carcinoma of ductal origin (ductal carcinoma in situ (DCIS)) is more common than lobular carcinoma in situ (LCIS) and can be subclassified into comedo, cribiform, micropapillary, papillary and solid forms. The different types of invasive carcinomas include tubular, ductal lobular, invasive lobular, infiltrating ductal, mucinous, medullary and infiltrating ductal tumours (Malhotra et al 2010).

The major subtypes of breast cancers are classified as ductal or lobular in origin and the

majority of cases are observed to have progressed from abnormal precursor or pre-

invasive lesions (Bombonati and Sgroi 2011). For example, flat epithelial atypia (FEA)


4

progresses into atypical ductal hyperplasia (ADH) and ductal carcinoma in situ (DCIS),

which are precursors of invasive ductal carcinoma (IDC), that accounts for 40-75% of

breast cancers. Similarly, invasive lobular carcinoma, which represents a smaller

proportion of breast cancers (5-15%) is predicted to originate mainly from precursors,

atypical lobular hyperplasia (ALH) and lobular carcinoma in situ (LCIS) (Wellings and

Jensen 1973, Oyama et al 2000). Histological testing is important for the classification

of breast cancers, however it is well established that individual breast cancer cases with

the same classification and the same stage may have different responses to treatments

and different outcomes. Genetic-based techniques such as comparative genomic

hybridisation (CGH) were originally shown to differentiate low-grade IDC cases, which

exhibited chromosomal losses in 16q and gains in 1q, 16p and 8q, from higher grade

IDC, which was characterised by chromosomal losses in 8p, 11q, 13q, 1p, 18q, gains in

8q, 17q, 20q and 16p as well as frequent high-level amplification of 17q12 and 11q13

(Roylance et al 2006).

Molecular classification of breast tumours using high-throughput gene expression

profiling assays (e.g. DNA microarrays) and unbiased hierarchical clustering led to

identification of 6 major subclasses of breast cancers; luminal A, luminal B, human

epidermal growth factor-like receptor 2 (HER2)-overexpressing, basal-like, claudin-

low, and normal-like breast tumours (Perou et al 1999, Sorlie et al 2001, Sorlie et al

2003, Prat et al 2010). The luminal subtypes of breast tumours, which express oestrogen

(ER) and progesterone (PR) receptors, are associated with better disease prognosis and

contain chromosomal deletions in 16q and gains in 1q, a genetic alteration profile that is

rare in ER-ve breast cancers such as the HER2-overexpressing and basal-like breast

tumour subtypes (Ciriello et al 2013). Luminal A breast cancers are associated with

longer overall survival compared to luminal B and were also shown to express high

levels of ERα, cytokeratins 8 (KRT8) and 18 (KRT18), GATA-binding protein 3

(GATA3), X-box binding protein 1, trefoil factor 3 and the oestrogen-regulated gene,

LIV-1 (Ciriello et al 2013).

In comparison to the luminal subtypes, HER2-overexpressing and basal-like breast

cancers are characterised by higher grade tumours with poorer relapse-free and overall

survival of patients (Sorlie et al 2001). In HER2-overexpressing breast cancers, genes in

the HER2 amplicon at chromosome position 17q22-24, which include HER2 and


5

growth factor receptor-bound protein 7 (GRB7), are amplified (Radhakrishna 2014).

The basal-like breast cancers share multiple genetic similarities with triple-negative

breast cancers, which lack expression of the hormone receptors, ER and PR as well as

HER2 (ER-ve/PR-ve/HER2-ve) (Sorlie et al 2001, Reis-Filho and Tutt 2008). However,

these subtypes of breast tumours are not entirely synonymous and this is supported by

findings which demonstrated five distinct TNBC subtypes, including two basal-like,

immunomodulatory, mesenchymal, mesenchymal stem-like and luminal androgen

receptor (LAR) subtypes (Lehmann et al 2011).

Claudin-low breast tumours are also ER-ve, PR-ve and HER2-ve and are associated

with poorer prognosis compared to the luminal subtypes. In line with this, claudin-low

breast cancers lack expression of the luminal differentiation markers (KRT18, KRT19,

oestrogen receptor 1 gene (ESR1), GATA3) but overexpress the epithelial-to-

mesenchymal transition (EMT) marker, vimentin and the EMT-associated transcription

factor, ZEB2 (Prat et al 2010). The normal breast-like breast cancers are less

reproducibly defined but have been associated with high histological grade of tumours,

expression of basal-like markers and low levels of expression of luminal genes (Sorlie

et al 2001). An alternative form of breast cancer classification has been demonstrated

previously which classified breast cancers according to expression of the androgen

receptor (AR). The three subtypes were ER alpha (ERα)+ve/AR+ve tumours which

correspond to luminal breast cancers, ERα-ve/AR-ve tumours, which include basal-like

breast cancers, and molecular apocrine ERα-ve/AR+ve breast cancers (Farmer et al

2005). The prognosis of these subtypes differ, with the ER+ve/AR+ve breast tumours

correlating with better prognosis of the disease compared to the ER-nonexpressing

AR+ve breast tumours (Section 1.4.4.3).

1.3 Breast Cancer Risk Factors

Breast cancer is a multifactorial disease, with endocrine, diet and lifestyle factors

proposed to increase lifetime risks for disease development. In a small proportion of

cases where familial clustering indicates genetic predisposition, several high penetrance

and a growing number of low penetrance genes have been identified and characterised

(Chen and Parmigiani 2007, Easton et al 2007, Apostolou and Fostira 2013). Lifetime

exposure of the mammary gland to ovarian hormones including oestrogen and


6

progesterone may increase breast cancer risk. During menarche, increased oestrogen

levels in the mammary glands stimulate the extension of mammary ducts as well as

rapid proliferation of mammary cells that remain undifferentiated until pregnancy and

lactation, during which cells fully differentiate (Bodicoat et al 2014). The presence of

undifferentiated cells in the mammary glands is proposed to increase the risk of

developing harmful mutations during DNA replication and therefore women who had

experienced early menarche, late pregnancy or late onset of menopause are at higher

risks of developing breast cancer (Bodicoat et al 2014). In support of this hypothesis,

women with irregular cycles of menstruation were shown to be less likely to develop

breast cancer due to decreased (life) time in the luteal phase of the menstrual cycle,

during which secretion of ovarian hormones is highest (Terry et al 2005). Additionally,

hormone replacement therapies (HRT) using oestrogens and/or progestins to relieve

menopausal symptoms or prevent osteoporosis have also been associated with increased

risk of breast cancer development (Rossouw et al 2002).

Diet, including consumption of alcohol and a sedentary lifestyle also contributes to the

development of breast cancer. Moderate consumption of alcohol (5-9.9g/day or 3-6

glasses of wine/week) has been associated with an increased risk of developing breast

cancer, and an additional 10g of alcohol per day further increases the risk by ~10%

(Chen et al 2011b). Alcohol consumption predominantly affects the breast cancer risk

of postmenopausal women and is usually associated with ER+ve/PR+ve breast cancers

(Suzuki et al 2005). High consumption of alcohol has been linked to increased

circulating levels of oestrogen and aromatase, the enzyme which converts androgen

precursors into oestrogens, and these findings support the involvement of oestrogens

and the ER signalling pathway in the development of breast cancer associated with

alcohol consumption (Purohit 2000). Carcinogenic bi-products linked to high alcohol

consumption such as reactive oxygen radicals, lipid peroxides and acetaldehyde

following metabolism of alcohol may also increase breast cancer risk (Meagher et al

1999).

High fat diets and low physical activity leading to high body mass index (BMI) also

increase breast cancer risk, especially in postmenopausal women, where production of

oestrogens is predominantly due to peripheral conversion of androgen precursors by

aromatase. Adipose tissues produce aromatase and it is proposed that postmenopausal


7

oestrogen production is higher in obese women, increasing the risk of developing breast

cancer (Liu et al 2013). In addition, buildup of fat in the abdomen and increasing BMI

have been associated with hyperinsulinemia and increased expression of insulin-like

growth factor 1 receptor (IGF1R) and IGF2, respectively. Together, these may stimulate

proliferation of mammary cells and increase the risk of breast cancer development

(Suga et al 2001).

The risk of developing breast cancer increases with the number of diagnoses in the

family, in particular first and second degree relatives or if relatives are diagnosed at a

younger age. Patients with breast cancers arising from hereditary genetic factors

(familial breast cancer) account for 5-7% of breast cancer cases and the most prevalent

cause of familial breast cancers, constituting ~25% of these cases is attributed to

germline mutation in one of the two breast cancer susceptibility genes, BRCA1 and

BRCA2 (Bradbury and Olopade 2007, Walsh et al 2010). Proteins encoded by BRCA1

and BRCA2 are involved in maintaining chromosomal stability, protecting the DNA

from damage, and repair of double-strand DNA breaks (Wu et al 2010). In individuals

carrying a mutation in BRCA1 or BRCA2, the estimated lifetime risk for breast cancer

development is 40-85% (Chen and Parmigiani 2007). Carriers of BRCA1 mutation also

have an elevated lifetime risk of 25-65% for development of ovarian cancer, while the

estimated lifetime risk for developing ovarian cancers in BRCA2 mutation carriers is 15-

20% (Chen and Parmigiani 2007).

A number of high penetrance but low frequency genes has also been identified which

when mutated in the germline, predispose to cancer, including breast cancer

development. These include TP53 and the phosphatase and tensin homologue gene

(PTEN), germline mutations of which cause the autosomal dominant inherited

disorders, Li Fraumeni syndrome and Cowden syndrome, respectively. TP53 mutation

carriers face a 90% estimated risk of developing cancers, with early onset breast cancer

(diagnosed before the age of 45) being the most common malignancy (Nichols et al

2001, Walsh et al 2006). Patients with Cowden syndrome have an estimated risk of 20-

50% for development of malignant breast cancer and 67% for development of benign

breast disease (Ngeow et al 2014). Other breast cancer susceptibility genes with

moderate penetrance include the gene encoding checkpoint kinase 2, CHEK2, and the

partner and localiser of BRCA2, PALB2, while the low penetrance and less common


8

breast cancer predisposing genes such as mitogen-activated protein kinase kinase kinase

1 (MAP3K1) and fibroblast growth factor receptor 2 (FGFR2) only slightly increase the

risk for breast cancer development (Easton et al 2007, Hunter et al 2007, Rahman et al

2007, Stracker et al 2009).

1.4 Regulation of Breast Cancer Growth

ER, PR and HER2 regulate breast cancer growth and progression, and are used as

markers of breast tumour classification and to predict responses to endocrine or targeted

therapies. The epidermal growth factor receptor (EGFR), androgen receptor (AR) and

embryogenic/developmental (e.g. Hedgehog) pathways also regulate breast tumour

growth, however their role in breast cancer formation or progression are less well

defined.

1.4.1 Oestrogen Receptor (ER)

The ER, a member of the nuclear receptor superfamily is expressed in 70-80% of breast

cancers (Allred et al 2009). Two ER isoforms, ERα and ERβ, mediate the effects of

oestrogens (e.g. 17β-oestradiol (E2)) and are encoded by independent genes, oestrogen

receptor gene 1 (ESR1) and 2 (ESR2), respectively. E2 is the predominant form of

oestrogen in premenopausal women and is produced primarily by the ovaries in

response to release of luteinising hormone (LH) and follicle-stimulating hormone (FSH)

from the pituitary gland under control of the hypothalamic peptide, gonadotropin-

releasing hormone (GnRH) (Barbieri 2014). E2 production from androgens (e.g.

androstenedione, testosterone) secreted from the ovaries and adrenal glands, is catalysed

by the aromatase enzyme that is encoded by the cytochrome P450 gene, CYP19 (Labrie

et al 2003, Silva et al 2006).

In the classical ER signalling pathway, oestrogens bind to ER, which leads to receptor

dimerisation and nuclear translocation of the dimers. In the nucleus, the ER dimers bind

to DNA sequences based on 13bp oestrogen responsive elements (ERE) that are

generally located in the promoters of target genes, leading to regulation of target gene

expression (Renoir et al 2013). ERα dimers recruit a number of regulatory protein

complexes including the general transcription factor, p300/CREB-binding protein

(p300/CBP), which facilitates chromatin remodelling and exhibits histone


9

acetyltransferase (HAT) activity that is required for ERα-mediated transcription of

genes (Kim et al 2001). ERα may alternatively activate transcription of genes whose

promoters do not contain a bona fide ERE via interactions with other transcription

factors such as AP1, Sp1, NF-κB, cAMP response element-binding protein (CREB),

p53 and STAT5 which bind to their cognate DNA elements (Thomas and Gustafsson

2011). E2 and ERα effects may also be mediated via non-genomic pathways such as by

ERα interaction with the cytoskeletal protein, p130Cas to activate c-Src and its

downstream pathway, ERK1/2 MAPK. Suppression of p130Cas by siRNA in the breast

cancer cell line, T-47D, abrogates E2-induced increases in c-Src expression and kinase

activity as well as phosphorylated levels of ERK1/2 MAPKs and cyclin D1 expression,

indicating that p130Cas is a critical component in ERα/c-Src non-genomic pathway

(Cabodi et al 2004).

E2-bound ERα and ERβ exhibit opposing effects on the proliferation of breast cancer

cells, with the E2/ERα complex stimulating while E2/ERβ inhibiting breast cancer cell

proliferation (Lindberg et al 2003). As such, the ratio of ERα and ERβ expression is an

important factor in determining the responsiveness of breast cancer cells to oestrogens.

In the ERα-expressing breast cancer cell lines, MCF-7 and T-47D, E2 promotes cell

proliferation but stable transfection of cells to overexpress ERβ results in inhibition of

E2-induced cell proliferation and reduced numbers of colonies in anchorage-

independent growth assays (Omoto et al 2003, Strom et al 2004). ERβ has also been

shown to antagonise E2/ERα-mediated gene transcription. Transfection of an ERβ

expression construct into MCF-7 and T-47D cells and treatment of the cells with E2

downregulated the expression of genes which were initially upregulated in E2-treated

(untransfected) MCF-7 and T-47D cells (Chang et al 2006, Williams et al 2008). These

genes included the cell proliferation-associated gene, c-MYC and the gene encoding

potassium channel subfamily K, member 5 (KCNK5) which regulates ion transport

(Williams et al 2008). As ERα mRNA and protein levels were decreased following

overexpression of ERβ in MCF-7 and T-47D cells, the effects may be mediated by

either or both increased ERβ transcriptional activity and reduced ERα transcriptional

activity due to decreased ERα expression (Chang et al 2006, Williams et al 2008).

Stimulation or inhibition of breast cancer cell proliferation by E2/ERα or E2/ERβ,

respectively, involves modulation of the expression of genes associated with cell


10

proliferation and apoptosis. In MCF-7 and T-47D cells, E2 treatment rapidly increased

expression of the cell cycle regulators, cyclin D1 and c-MYC within 4-5 hours of

treatment (Prall et al 1998, Wang et al 2011a). Cyclins E and A were also upregulated

in T-47D cells treated with E2, with overexpression of ERβ in the cells abrogating the

increase in cyclin E mRNA levels following E2 treatment (Strom et al 2004). Regulators

of apoptosis are also ER target genes and E2 treatment of MCF-7, T-47D and ZR-75-1

cells decreased apoptosis by inducing expression of the anti-apoptosis factors, BCL2

and BCL-XL (Kandouz et al 1999). While E2 stimulates the growth of ERα+ve breast

cancer cells, in ERα-ve breast cancer cell lines (e.g. MDA-MB-231) transfected with an

ERα expression construct, E2 inhibits proliferation and downregulates expression of

genes which encode cell cycle regulators including cdc2, cyclin B1, cyclin B2 and

cyclin G1 (Moggs et al 2005).

In addition to E2 effects on cell proliferation and survival, the ER pathway has been

implicated in the regulation of angiogenesis, which facilitates tumour growth by

providing a nutrient-rich microenvironment (Elkin et al 2004). In MCF-7 cells, E2

treatment has been shown to increase production of the pro-angiogenic factor, vascular

endothelial growth factor (VEGF) (Applanat et al 2008). Conversely, anti-oestrogens

such as tamoxifen (Section 1.5) decrease E2-induced tumour angiogenesis in mice

transplanted with MCF-7 cells (Lindahl et al 2011).

1.4.2 Progesterone Receptor (PR)

The PR which is expressed in 50-70% of breast tumours is also a member of the nuclear

receptor superfamily (Cui et al 2005). The two most frequently studied PR isoforms in

breast cancer are PRA and PRB, which are commonly co-expressed (Mote et al 2007).

Binding of progesterone to PR leads to the formation of PRA/PRB heterodimers or

PRA/PRA or PRB/PRB homodimers which translocate into the nucleus and bind to

progesterone responsive elements (PRE) to activate transcription of target genes

(Graham and Clarke 2002). A third and shorter PR isoform, PRC has also been

identified which lacks the first zinc finger of the DNA-binding domain but is capable of

stimulating PRA and PRB transcriptional activity (Wei et al 1996, Wei et al 1997).

Expression of PR, an ER target gene, is a marker of good prognosis in ERα-expressing

breast cancers and also predicts responses of these cancers to anti-oestrogens (e.g.

tamoxifen) (Bardou et al 2003, Onitilo et al 2009, Liu et al 2010, Purdie et al 2014).


11

Progesterone has been shown to induce breast cancer cell proliferation and tumour

growth. Treatment of mouse mammary tumour cell lines with progesterone or the

synthetic progestin, medroxyprogesterone acetate (MPA) increased proliferation, which

was abrogated by the anti-progestin, RU486 (Lamb et al 1999). Consistent with these

studies, the combination of oestrogen and progestin as part of hormone replacement

therapies for postmenopausal women was found to be associated with higher risks of

developing breast cancer compared to that in women who received the placebo or

oestrogen alone (Rossouw et al 2002, Chlebowski et al 2010).

Several recent studies, however, report anti-proliferative effects of progesterone,

especially on E2/ERα-induced proliferation. In human breast tumours propagated as

xenografts in mice, the combination of oestrogens and MPA led to inhibition of tumour

growth (Kabos et al 2012). Similarly, when MCF-7 and T-47D mouse xenografts were

co-treated with oestrogens and progesterone, tumours were smaller than those in mice

treated with oestrogen alone (Mohammed et al 2015). Tamoxifen and progesterone

similarly decreased tumour growth, and the combination of these agents resulted in a

more pronounced inhibition of tumour growth (Mohammed et al 2015). In that study, a

direct interaction between PR and ERα was identified in MCF-7 and T-47D cells, with

activation of PR by progesterone treatment inducing ERα binding predominantly to

PREs instead of EREs. This activated transcription of genes associated with cell death,

apoptosis and differentiation pathways, thereby supporting the anti-proliferative effects

of progesterone/PR (Mohammed et al 2015). Although progesterone and MPA are

reported to both stimulate and repress breast cancer cell proliferation, it is noted that in

studies which show anti-proliferative effects of MPA, high doses of MPA are used and

thus progesterone effects may be dose-dependent (Lamb et al 1999, Kabos et al 2012,

Mohammed et al 2015).

1.4.3 Human Epidermal Growth Factor-Like Receptor 2 (HER2)

Human epidermal growth factor-like receptor 2 (HER2) belongs to a family of four

membrane-bound tyrosine kinase receptors, HER1 or EGFR, HER2, HER3 and HER4

(Iqbal 2014). These receptors contain an extracellular ligand-binding domain, a

hydrophilic transmembrane domain and an intracellular tyrosine kinase domain which is

important for activating downstream signalling pathways. Unlike HER1, HER3 and

HER4, HER2 does not require binding of ligands to the receptor to facilitate


12

homodimerisation or heterodimerisation with other ligand-activated HER family

members (Dawson et al 2005). Dimerisation of HER2 leads to autophosphorylation of

tyrosine residues in the intracellular domain which triggers activation of pathways that

regulate cell proliferation, survival, angiogenesis and invasion such as the PI3K/AKT,

RAS/MAPK and phospholipase C gamma (PLCγ) pathways (Peles et al 1991, Olayioye

et al 1998). In contrast to HER2 heterodimers, HER2 homodimers are able to regulate

the RAS/MAPK pathway but are not capable of activating PI3K signalling as the

homodimers lack phosphorylated tyrosines in the intracellular domain which facilitate

docking of the receptors to the PI3K pathway adaptor protein, p85 (Soltoff et al 1994,

Muthuswamy et al 1999).

HER2 is overexpressed in 20-25% of breast tumours (Slamon et al 1987, Owens et al

2004). Amplification of the HER2 gene which leads to overexpression of the HER2

protein is associated with a higher histological grade of tumours, with increased risk of

disease recurrence and a poorer prognosis (Press et al 1993, Kim et al 2008). However,

patients with HER2-overexpressing breast cancers benefit from treatment with the anti-

HER monoclonal antibody, trastuzumab (Section 1.5). HER2 is overexpressed in up to

60-70% of ductal carcinoma in situ (DCIS) lesions and HER2 overexpression in pre-

invasive DCIS is proposed to promote progression to invasive breast cancer (Roses et al

2009, Harada et al 2011). This was supported by studies which showed that HER2

expression was associated with more rapid progression of DCIS to invasive ductal

carcinoma (Roses et al 2009, Harada et al 2011).

1.4.4 Androgens and the Androgen Receptor

1.4.4.1 Androgens

Androgens are 19-carbon steroid hormones that regulate male sexual characteristics and

masculinity (Somboonporn and Davis 2004, Shufelt and Braunstein 2008). In women,

androgens are also produced and levels of androgens exceed that of oestrogens, with

dehydroepiandrosterone (DHEA), sulphate-conjugated DHEA (DHEA-S),

androstendione and testosterone produced primarily by the ovaries and adrenal glands

(Burger 2002). Androgens can undergo aromatisation to oestrogens (e.g. E2) in the

presence of aromatase and may be converted to more biologically active androgens (e.g.

5α-dihydrotestosterone (DHT)) by 5α-reductase in peripheral tissues such as the

mammary glands, brain and liver (Labrie et al 2003).


13

Androgens have anti-proliferative effects on normal breast epithelial cells and the

balance between the levels of androgens and E2 is important during morphogenesis of

the human mammary gland (Rothman et al 2011). During the luteal phase of the

menstrual cycle, the increased E2-to-androgen ratio leads to proliferation of breast

epithelial cells, while in the follicular phase, during which the rate of apoptosis of the

breast epithelium is highest, E2 levels decline and the high E2-to-androgen ratio is

reduced (Rothman et al 2011). Studies in ovariectomised monkeys have indicated that

androgen effects may depend on the presence of oestrogens as treatment of monkeys

with testosterone or E2 alone increased breast epithelial cell proliferation but when both

agents were combined, E2-induced increases in cell proliferation were abrogated (Zhou

et al 2000, Dimitrakakis et al 2003).

1.4.4.2 The Androgen Receptor

The predominant androgen ligands, testosterone and DHT are both capable of binding

to the androgen receptor (AR), however DHT binds with higher affinity (Askew et al

2007). Similar to other steroid hormone receptors, including ERα and ERβ, the AR

belongs to the nuclear receptor superfamily and is comprised of 4 functional domains,

an N-terminal domain (NTD), a DNA-binding domain (DBD), a small hinge region and

a ligand-binding domain (LBD) (Rahman et al 2004, Bennett et al 2010). Androgen

effects in target cells are mediated via activation of AR transcriptional regulation of

gene expression, especially genes that are involved in physiological processes including

cell survival, cell proliferation and cell differentiation. In the absence of ligands, the AR

is held in complexes involving chaperones (e.g. heat shock proteins (HSPs)) and

cytoskeletal proteins (e.g. Filamin A), which direct the AR into a conformation that

facilitates binding of prospective ligands (Cardozo et al 2003, Shatkina et al 2003,

Bennett et al 2010).

In the circulation, testosterone exists either in its free form or is conjugated with

proteins such as albumin or sex steroid hormone-binding globulin (SHBG) (Burger

2002). Upon entering cells, testosterone may be converted into DHT by 5α-reductase.

Testosterone or DHT bind to the AR, resulting in conformational changes which trigger

dissociation of HSPs and cytoplasmic chaperone proteins, and promote recruitment of

co-regulators including ARA70 (Rahman et al 2004). Subsequently, the AR

homodimerises with another ligand-bound AR and translocates into the nucleus where it


14

binds via its DBD to androgen responsive elements (ARE), which are based on

palindromic sequences separated by 3 nucleotides (5’-AGAACANNNTGTTCT-3’). A

number of regulators are recruited such as histone acetyltransferases (HATs) and co-

regulators of chromatin remodelling, which trigger binding of TATA-binding protein

(TBP), general transcription factors (GTF) and RNA polymerase 2 (RNAPolII) for

initiation of transcription of androgen-responsive genes (Figure 1.4) (Khorasanizadeh

and Rastinejad 2001, Heinlein and Chang 2002, Verrijdt et al 2003).

Figure 1.4: The androgen receptor signalling pathway. In the circulation, testosterone is bound to plasma proteins including sex hormone-binding globulin (SHBG) and upon entering the cell, it may be converted to the non-aromatisable androgen, DHT by 5-reductase. Heat shock proteins (HSPs), which prepare the AR conformation for ligand binding, dissociate from the receptor upon binding of androgen ligands (e.g. DHT). AR dimerises with another ligand-bound AR and the AR dimers translocate into the nucleus where AR binds to androgen responsive elements (ARE) located in the regulatory regions of AR target genes. Co-regulators, the general transcriptional apparatus and RNA polymerase 2 (RNAPolII) are recruited to initiate gene transcription. (Feldman and Feldman 2001).

Following dissociation of androgen ligands from the AR, a nuclear export signal (NES)

located in the LBD facilitates translocation of the receptor into the cytoplasm either for

recycling following ligand binding or for degradation via the proteasome pathway.

Proteasomal degradation is induced by phosphorylation of specific AR residues that

promote ubiquitination of the AR by E3 ubiquitin ligases such as carboxyl-terminus of

Hsc70-interacting protein (CHIP) (He et al 2002, Gaughan et al 2005).


15

ARE sequences have been identified in a number of target genes that encode regulators

of cell proliferation and survival. For example, functional AREs have been

characterised at -200bp of the cyclin-dependent kinase inhibitor, p21Cip1/Waf1 promoter

(Lu et al 1999), between -570 to -556bp upstream of the transcription start site of the

cyclin D1 gene (Lanzino et al 2010) and between -1320 and -1420bp upstream of the

IGF-1 transcription start site (Wu et al 2007).

1.4.4.3 Androgens and the AR in Breast Cancer

Androgens have been reported to inhibit the growth of breast cancers and these effects

are similar to their roles in normal breast epithelial cells where androgens antagonise

E2/ER-induced increases in cell proliferation (Section 1.4.4.1). Natural (e.g. DHT,

androstenedione) and synthetic (e.g. R1881) androgens inhibit the proliferation of

AR+ve breast cancer cell lines including MCF-7, T-47D and ZR-75-1 (Dauvois et al

1991, Birrell et al 1995, Szelei et al 1997, Ando et al 2002, Ortmann et al 2002, Greeve

et al 2004, Macedo et al 2006). These effects are reversed by co-treatment of the cells

with anti-androgens or AR antagonists such as bicalutamide (casodex) and

hydroxflutamide, indicating that these effects are mediated by the AR (Dauvois et al

1991, Birrell et al 1995, Szelei et al 1997, Ando et al 2002, Macedo et al 2006).

Androgen-mediated inhibition of breast cancer cell proliferation involves

downregulation of expression of cell cycle regulators and upregulation of pro-apoptosis

factors. For example, DHT has been shown to increase the proportion of cells in G1

phase by impeding their progression into S-phase (Greeve et al 2004). This was

associated with decreased expression of cyclin D1 and increased expression of

p21Cip1/Waf1 and p27Kip1 (Greeve et al 2004, Lanzino et al 2010). DHT treatment of ZR-

75-1 cells has also been reported to downregulate the mRNA and protein levels of the

anti-apoptosis factor, BCL2, and to induce apoptosis in MCF-7, T-47D and ZR-75-1

cells (Kandouz et al 1999, Lapointe et al 1999). AR signalling directly induces the

expression of KLLN (killin), a DNA binding protein which increases TP53 and TP73

levels and promotes apoptotic cell death when overexpressed in MCF-7 cells (Wang et

al 2013). Androgen-induced inhibition of breast cancer cell proliferation may also be

mediated via inhibition of E2/ERα-induced cell proliferation and transcriptional activity,

and in MCF-7 and ZR-75-1 cells, DHT inhibited E2-stimulated cell proliferation and

also downregulated E2-induced expression of ERα target genes (Dimitrakakis et al


16

2003, Need et al 2012). Inhibition of E2 effects and ERα transcriptional activity by

ligand-bound AR requires a functional AR DBD, with this inhibition mediated via

direct interaction between the AR and ERα and AR binding to cellular EREs (Panet-

Raymond et al 2000, Peters et al 2009).

The AR is expressed in 70-90% of breast tumours including ER-ve breast tumours such

as molecular apocrine (ER-ve/HER2+ve/AR+ve) and a proportion of triple-negative

breast cancers (TNBC) (ER-ve/PR-ve/HER2-ve) (Moinfar et al 2003, Safarpour et al

2014). AR expression in breast tumours is more widespread compared to ER (70-80%)

and PR (50-70%) (Kuenen-Boumeester et al 1992) and its expression is associated with

longer relapse-free and overall survival in both ER+ve (Figure 1.5) and ER-ve breast

cancers (Isola 1993, Gonzalez et al 2008, Luo et al 2010, Park et al 2010, He et al 2012,

Kim et al 2015). Molecular clustering of TNBC has identified marked overlapping of

gene signatures between molecular apocrine/TNBC and luminal breast cancers, leading

to the proposal that these cancers may have evolved from luminal subtypes following

loss of ER expression (Farmer et al 2005, Lehmann et al 2011). In support of this

hypothesis, low levels of ER expression were detected in parental cells of the MFM-223

molecular apocrine cancer cell line, which were derived from the pleural effusion of a

breast cancer patient, and following extensive passaging of the cells, ER levels

decreased (Hackenberg et al 1991). Although AR expression in ER-ve breast tumours

has been shown to be associated with longer overall survival of patients (Kim et al

2015), androgens have been proposed to increase the growth of AR+ve/ER-ve breast

cancers, and in cell lines representing molecular apocrine breast cancers (MDA-MB-

453) and TNBC (SUM159PT, BT-549), knockdown of AR reduced cell proliferation,

anchorage-independent growth, cell migration and invasion (Hackenberg et al 1991, Ni

et al 2011, Barton et al 2015).

The mechanisms by which androgens stimulate ER-ve/AR+ve breast cancer cell

proliferation may include activation of ERα-like signalling, WNT and PI3K/AKT

pathways. DNA binding sites for AR in MDA-MB-453 cells overlapped significantly

with those bound by ERα and FOXA1, a transcription factor that is important for ERα

binding to DNA and for ER transcriptional activity (Hurtado et al 2011, Robinson et al

2011). This indicates that AR may have an ERα-like activity in ER-ve breast cancer.

Additionally, DHT has been shown to increase WNT7B mRNA and protein expression


17

as well as nuclear levels of the β-catenin protein in MDA-MB-453 cells, indicating

activation of WNT signalling (Ni et al 2011). Androgen-induced stimulation of

AR+ve/ER-ve breast cancer cell proliferation may also be mediated by the PI3K/AKT

pathway, with DHT shown to increase phosphorylation of AKT in MDA-MB-453 cells

(Ni et al 2011). While most studies have shown that androgens and the AR stimulate the

growth of AR+ve/ER-ve breast cancer cells, androgens have also been shown to inhibit

MDA-MB-453 cell growth in association with upregulation of PTEN expression,

suggesting that responses of cells to androgens may differ depending on experimental

conditions and potentially due to clonal variation of the cell lines used in the studies

(Wang et al 2011b).

Figure 1.5: Correlation of AR expression in breast tumours and overall survival of patients. AR+ve breast cancers were associated with longer overall survival compared to AR-ve breast cancers (Gonzalez et al 2008).

1.4.4.4 Androgens and AR Modulators as Therapies for Breast Cancer

Androgens such as testosterone propionate, fluoxymesterone and calusterone were

successfully used as breast cancer treatments in the 1970s (Labrie 2006). However, due

to their virilising side effects, liver toxicity that arose in a proportion of patients and the

development of anti-oestrogens, androgen usage in breast cancer management ceased.

More recently, selective androgen receptor modulators (SARM) such as enobosarm

(GTx-024) and GTx-027, have been developed, and these newer generation AR

modulators are associated with greater tissue specificity and may represent a novel

therapeutic strategy for ER+ve breast cancers (Gao and Dalton 2007). A phase 2 clinical

trial is ongoing for enobosarm in patients with metastatic ER+ve breast cancers

(ClinicalTrials.gov Identifier: NCT01616758).


18

As experimental studies indicate that androgens promote the proliferation of

AR+ve/ER-ve breast cancer cells, clinical trials have also been carried out or are

underway to determine the efficacy of AR antagonists including bicalutamide and

enzalutamide as breast cancer treatments (Gucalp et al 2013, Cochrane et al 2014,

Narayanan et al 2014, Barton et al 2015). A phase 2 clinical trial evaluating

bicalutamide in patients with AR+ve/ER-ve metastatic breast cancers reported that the

drug was well-tolerated, with minor side effects such as fatigue and hot flashes

(ClinicalTrials.gov Identifier: NCT00468715) (Gucalp et al 2013). A proportion of the

patients (~19%) had stable disease for >6 months following treatment with bicalutamide

and the median progression-free survival was 12 weeks, which was similar to trials

evaluating single and combination chemotherapy for triple-negative breast cancers

(O'Shaughnessy et al 2011, Carey et al 2012, Gucalp et al 2013).

1.4.5 The Hedgehog Signalling Pathway

Developmental pathways including the Hedgehog signalling pathway control human

embryonic development and cell/tissue homeostasis by modulating stem cell growth

and differentiation, cell proliferation, survival and migration. However, hyperactivation

of the Hedgehog pathway has been implicated in the development of human cancers

including breast cancer and this frequently involves ligand-dependent induction of the

canonical Hedgehog pathway or constitutive activation or mutation of downstream

Hedgehog signalling intermediates (Cohen 2010).

In the absence of Hedgehog ligands, Sonic Hedgehog (SHH), Indian Hedgehog (IHH)

or Desert Hedgehog (DHH), Patched homologue 1 (PTCH1) receptors inhibit the

activity and translocation to the tip of the primary cilium of a 7-pass transmembrane

protein, Smoothened (SMO). This allows a multiprotein complex consisting of protein

kinase A (PKA), casein kinase 1 (CK1) and glycogen synthase kinase 3β (GSK3β) to

phosphorylate the GLI transcription factors (GLI1, GLI2, GLI3) at the primary cilium,

creating a binding site for the E3 ubiquitin ligase, beta-transducin repeating containing

protein (β-TrCP), which ubiquitinates the GLI transcription factors to induce their

cleavage by the proteasomes. Truncated GLI proteins, which lack C-terminal

transcriptional activation domains, translocate into the nucleus and function as

transcriptional repressors of target genes (Figure 1.6) (Heretsch et al 2010, Wen et al

2010).


19

Figure 1.6: The Hedgehog signalling pathway. (A) In the absence of Hedgehog ligands, Patched homologue 1 (PTCH1) receptors block the transmembrane protein, Smoothened (SMO) from translocating to the primary cilium. As a result, the Hedgehog effectors, the GLI transcription factors (GLI1, GLI2, GLI3) are phosphorylated by a multiprotein complex comprised of protein kinase A (PKA), casein kinase 1 (CK1) and glycogen synthase kinase 3β (GSK3β) which creates a binding site for the E3 ubiquitin ligase, beta-transducin repeating containing protein (β-TrCP), triggering ubiquitination of the GLI proteins and proteasomal cleavage of GLI. Truncated GLI transcription factors migrate into the nucleus as GLI repressors and downregulate expression of Hedgehog target genes. (B) Binding of Sonic Hedgehog (SHH) to PTCH1 alleviates PTCH inhibition of SMO, thereby allowing SMO to travel to the tip of the primary cilium, where the PKA/CK1/GSK3β containing multiprotein complexes are prevented from phosphorylating GLI transcription factors. Active full-length GLI translocates into the nucleus, where it is able to activate target gene expression (Heretsch et al 2010).

In the presence of Hedgehog ligands (e.g. SHH), binding of SHH to PTCH1 on the

plasma membrane triggers localisation of SMO to the tip of the primary cilium where

SMO binds to the PKA, CK1 and GSK3β containing multiprotein complexes,

preventing phosphorylation of the GLI transcription factors (GLI1, GLI2 and GLI3) and

releasing full-length GLI into the cytoplasm. As such, the GLI transcription factors

retain their transcriptional activation domains and translocate into the nucleus where

they bind to consensus sequences (GACCACCCA) located in gene promoters and

transcriptionally activate the expression of target genes including Hedgehog

intermediates (e.g. PTCH1, GLI1), regulators of cell cycle progression (CCND1,

CCND2) and mediators of epithelial-to-mesenchymal transition (EMT) (e.g. SNAI1,


20

SNAI2 (SLUG)) (Figure 1.6) (Bonifas et al 2001, Heretsch et al 2010, Winklmayr et al

2010).

1.4.5.1 Hedgehog Signalling in Breast Cancer

A number of in vitro and in vivo studies have provided evidence for the role of aberrant

Hedgehog signalling in the regulation of breast tumorigenesis, breast cancer growth,

cancer stem cell growth, drug resistance and metastasis (Kubo et al 2004, Moraes et al

2007, ten Haaf et al 2009, Cui et al 2010). The Hedgehog signalling intermediates and

Hedgehog target genes, PTCH1, GLI1 and SHH are overexpressed in a proportion of

primary breast cancer specimens with the nuclear localisation of GLI1, which indicates

active Hedgehog signalling, providing evidence for increased activity of the Hedgehog

pathway in tumours compared to adjacent nonmalignant mammary epithelia (Kubo et al

2004). Expression of GLI1, SMO and SHH are also elevated in breast cancer cell lines

such as MCF-7, T-47D, MDA-MB-231 and SKBR3, with inhibition of cell proliferation

observed following treatment with the Hedgehog/SMO inhibitor, cyclopamine (Kubo et

al 2004, Mukherjee et al 2006). In vivo studies have also reported formation of breast

tumours following aberrant activation of the Hedgehog signalling pathway. In female

mice overexpressing Smo in the mammary epithelium, ductal dysplasias with excessive

budding and branching were observed and these phenotypes resembled human breast

hyperplasias (Moraes et al 2007). Similarly, overexpression of Gli1 in the mammary

epithelium of mice led to formation of hyperplastic regions and tumours of ductal,

squamous and solid forms (Fiaschi et al 2009). The Hedgehog signalling pathway also

stimulates breast tumour metastasis. In basal-like breast cancers, paracrine Hedgehog

signalling characterised by high SHH levels in the epithelium and high GLI1 expression

in the stroma was shown to stimulate tumour metastasis, with these effects mediated

principally by activation of Hedgehog signalling in the tumour-associated stroma

(O'Toole et al 2011).

Overexpression of the Hedgehog pathway intermediates, PTCH1 and GLI1, has been

reported in early (e.g. DCIS) and advanced (e.g. invasive ductal carcinoma) breast

tumours, which correlated with younger age at diagnosis (<50 years), poorly

differentiated tumours, lymph node metastasis and poorer overall survival (Moraes et al

2007, O'Toole et al 2011). Recent studies have proposed that Hedgehog signalling

mediates progression of pre-invasive breast lesions such as DCIS to invasive breast


21

cancers (Souzaki et al 2011). Furthermore, treatment of T-47D cells with recombinant

SHH N-terminal peptide was shown to increase cell invasion, supporting the hypothesis

that the Hedgehog pathway is capable of stimulating the invasiveness of breast cancer

(Souzaki et al 2011).

1.4.5.2 Crosstalk between the Hedgehog Signalling Pathway and Hormone

Receptors

Evidence of cross-talk between the Hedgehog and hormone receptor (e.g. ER, AR)

pathways has been reported. E2 has been shown to increase expression of GLI1 mRNA

in MCF-7 cells, while inhibition of ER signalling by the pure anti-oestrogen, ICI

182,780 was reported to suppress expression of SHH (Koga et al 2008). SHH was also

shown to bind to ERα in co-immunoprecipitation studies but combined targeting of the

ER and Hedgehog pathways with the anti-oestrogen, tamoxifen and Hedgehog

signalling inhibitor, cyclopamine stimulated MCF-7 cell proliferation and migration

(Sabol et al 2014). These findings indicated that combinations of drugs may exhibit

unexpected effects despite the abilities of tamoxifen and cyclopamine to inhibit breast

cancer cell proliferation individually.

Interactions between the AR and Hedgehog pathways have been investigated primarily

in prostate cancer cell lines where androgens stimulate rather than inhibit proliferation

(Shaw et al 2008, Chen et al 2009, Chen et al 2010, Chen et al 2011a). A direct

interaction between the AR and GLI transcription factors, GLI1 and GLI2 has been

reported in the prostate cancer cell line, LNCaP (Chen et al 2010, Chen et al 2011a).

Activation of Hedgehog signalling following androgen ablation therapies was proposed

to sustain the growth of castrate-resistant prostate tumours. In support of this

hypothesis, culture of LNCaP cells in the absence of androgens led to elevation of

PTCH1 and GLI1 levels, indicating activation of Hedgehog pathway transcriptional

activity (Chen et al 2011a). Gene microarray analysis of pathways upregulated in

androgen-independent LNCaP cells which were established by long term culture of

LNCaP cells in androgen-free medium and with the anti-androgen, flutamide, identified

the Hedgehog signalling pathway as a candidate mechanism supporting androgen-

independent prostate tumour growth (Liu et al 2014). Concurrent targeting of the

androgen and Hedgehog signalling pathways may therefore improve the efficacy of

prostate cancer management as evidenced by the synergistic suppression of proliferation


22

of castrate-resistant prostate cancer cells following treatment with cyclopamine and the

AR antagonist, pyrvinium pamoate (Gowda et al 2013).

1.5 Breast Cancer Treatment

The first-line of therapy for breast tumours is surgery, either mastectomy, a procedure

which removes the entire breast, or breast conserving surgeries such as lumpectomy,

quadrantectomy and segmentectomy, in which the tumour and immediately adjacent

tissues only are removed (Veronesi et al 2002). Following breast conserving surgery or

mastectomy, whole breast irradiation therapy is frequently administered to target

residual tumour cells and this combination has been shown to reduce tumour recurrence

and risk of disease-associated death (Darby et al 2011). Following surgery and radiation

therapy, patients may be treated with adjuvant therapies depending on the classification,

stage and grade of the tumour, and the age and other clinical features of the patient.

Adjuvant chemotherapy is used to treat large tumours (>1cm), node-positive and

metastatic breast cancers. The traditional forms of chemotherapy are the anthracyclines

(cyclophosphamide + methotrexate + 5-fluorouracil (CMF) or doxorubicin +

cyclophosphamide) and taxanes (paclitaxel or docetaxel) (Francis et al 2008). Other

chemotherapeutic agents include capecitabine, gemcitabine, iniparib and platinum-

based compounds such as carboplatin that may be administered as second-line

chemotherapy following disease progression subsequent to anthracycline and taxane

based regimens (Sparano et al 2010, O'Shaughnessy et al 2011).

Hormonal therapies are used to treat ER+ve and/or PR+ve breast tumours and may be

administered as sole agents or in combination with chemotherapy (Wilcken et al 2003,

Puhalla et al 2012). The major classes of hormonal therapies are the selective oestrogen

receptor modulators (SERMs) such as tamoxifen, raloxifene and toremifene, which

interact with the ER and competitively inhibit E2 from binding, and the aromatase

inhibitors, anastrazole, letrozole and exemestane, which block aromatase enzyme

activity and therefore oestrogen production (Demers 1994, Geisler et al 1996, Geisler et

al 1998). Luteinising hormone-releasing hormone (LHRH) agonists, which suppress

ovarian oestrogen production, or oophorectomy may be used in pre-menopausal women

where the ovaries are the main sources of hormones (Goel et al 2009). Tamoxifen has


23

been used as a first-line adjuvant therapy for ER+ve breast cancers since the 1970s, with

5 years or up to 10 years of continuous tamoxifen treatment recommended following

definitive treatments (e.g. surgery/radiotherapy), a regimen that was found to reduce the

risks of breast cancer recurrence (Davies et al 2013). For node-positive cancers and

tumours larger than 1cm, the combination of tamoxifen and chemotherapy

(cyclophosphamide, doxorubicin, 5-fluorouracil) is frequently used either concurrently

or sequentially (Albain et al 2009, Bedognetti et al 2011).

Aromatase inhibitors are particularly important for the treatment of postmenopausal

women with ER+ve breast cancers as the primary source of oestrogens is peripheral

conversion of androgen precursors to oestrogens via aromatase (Geisler et al 1996,

Geisler et al 1998). In comparison to tamoxifen, treatment with anastrazole has been

associated with increased disease-free survival and reduced rates of distant metastasis or

contralateral breast cancer, with lesser side effects (Howell et al 2005, Mouridsen et al

2009). In recent American Society of Clinical Oncology (ASCO) guidelines, 5 years of

aromatase inhibitor treatment was also recommended for premenopausal women

previously treated with tamoxifen for 5 years (Burstein et al 2014). This has been

supported in clinical trials where letrozole treatment following 5 years of tamoxifen was

shown to increase disease-free survival (Goss et al 2008, Mouridsen et al 2009, Dowsett

et al 2010).

Treatment of HER2-overexpressing breast cancers includes anti-HER2 therapies, most

commonly, trastuzumab (herceptin), an antibody that binds to the juxtamembrane

domain of HER2 (Cho et al 2003). For patients with HER2+ve locally advanced and

metastatic breast tumours, the combination of trastuzumab and chemotherapy such as

docetaxel alone or with vinorelbine or carboplatin have been associated with

improvement in progression-free survival and better overall survival (Andersson et al

2011, Valero et al 2011). For HER2+ve breast tumours which also express ER and PR,

combination treatments, for example, trastuzumab or the EGFR/HER2 tyrosine kinase

inhibitor, lapatinib with anastrazole or letrozole have been associated with longer

progression-free survival compared to aromatase inhibitors alone (Kaufman et al 2009,

Schwartzberg et al 2010). Following progression of tumours treated with first-line anti-

HER2 therapies, regimens including pertuzumab, an alternative anti-HER2 monoclonal

antibody or trastuzumab emtansine (T-DM1), a conjugate of trastuzumab and


24

maytansinoid, DM1, a microtubule-disrupting agent, have been shown to improve

progression-free survival (Blackwell et al 2012, Swain et al 2013, Krop et al 2014).

Despite advances in the development of targeted agents and combination therapies for

breast cancer, it is not uncommon that treatments fail due to intrinsic or acquired drug

resistance. Cellular processes and mechanisms that have been shown to facilitate drug

resistance include low drug bioavailability due to altered metabolism of therapeutic

drugs, overexpression of the ATP-binding cassette (ABC) drug efflux transporters

which limit intracellular accumulation of drugs (Section 1.6), mutations in drug targets

and activation of secondary growth regulatory pathways to compensate for inhibition of

pathways targeted by therapies (Housman et al 2014).

1.6 The ABC Transporters

Movement of compounds and molecules across the cell membrane is crucial for

homeostasis, the maintenance of a healthy cellular environment. For most membranes,

especially impermeable or lipid membranes, molecules are shuttled in or out of cells or

organelles including the mitochondria, endoplasmic reticulum (ER) and Golgi apparatus

by membrane transporters such as the ABC transporters (Vasiliou et al 2009). The ABC

transporters are ATP-dependent and are expressed in most organisms including

eukaryotes and prokaryotes (Higgins 1992). Depending on the cell type and substrate,

the ABC transporters act as importers and exporters in eukaryotes, whereas in

prokaryotes, ABC transporters mainly import substrates into cells (Vasiliou et al 2009).

A wide variety of molecules are shuttled via these transporters, including ions, sugars,

amino acids as well as therapeutic and chemotherapeutic drugs (Vasiliou et al 2009).

ABC transporter-mediated export of chemotherapeutic agents is a major cause of drug

resistance in cancers, and germline mutations in ABC transporter genes have also been

associated with diseases such as cystic fibrosis and ophthalmic diseases including

Stargardt’s disease and retinitis pigmentosa (Gadsby et al 2006, Vasiliou et al 2009,

Westerfeld 2010).


25

Figure 1.7: Structural domains of the ABC transporters. (A) ABC transporters are comprised of a cytoplasmic nucleotide-binding domain (NBD) and a membrane-spanning or transmembrane domain (MSD/TMD). (B) Full transporters (ABCB-type) contain 2 NBDs and 2 sets of TMDs that span the lipid bilayer of the plasma membrane. Half-transporters (ABCG-type) consist of only one NBD and one set of TMDs and form homodimers or heterodimers with another half transporter for functional activity (Sarkadi 2006).

The ABC transporters consist of a cytoplasmic nucleotide-binding domain (NDB)

which is made up of highly conserved motifs, the Walker A and B sequences, the H and

Q loops, and a transmembrane or membrane spanning domain (TMD/MSD) (Figure

1.7). Each TMD is encompassed by several hydrophobic α-helices. The NBDs bind

ATP and facilitate its hydrolysis for energy while the TMDs orchestrate movement of

the substrates across the membrane following substrate recognition (Higgins 1992,

Ambudkar et al 2006). Most transporters contain two NBDs and 2 sets of TMDs but a

small subgroup of ABC transporters including ABCG2, which belongs to the G subclass

of the ABC transporter superfamily (ABCG), are synthesised as half-transporters and

require dimerisation or multimerisation with other ABCG2 half-transporters or with

other ABC transporters for efflux activities (Figure 1.7) (Mo and Zhang 2012).

1.6.1 The ABC Transporter Superfamily

In humans, 49 members of the ABC superfamily of transporters have been identified.

These members are classified into 7 subfamilies or subclasses, ABCA, ABCB, ABCC,

ABCD, ABCE, ABCF and ABCG, with mutations in members of each subfamily

associated with various inherited diseases (Table 1.1) (Vasiliou et al 2009).

A B


26

Table 1.1: The seven subfamilies/subclasses of the ATP-binding cassette (ABC) superfamily (Vasiliou et al 2009).

ABC Transporter Subfamilies

Aliases Number of Genes Number of Pseudogenes

ABCA ABC1 12 5

ABCB MDR 11 4

ABCC MRP 13 2

ABCD ALD 4 4

ABCE OABP 1 2

ABCF GGN20 3 2

ABCG White 5 2

The ABCA or ABC1 subfamily has 12 members which are largely involved in lipid

trafficking (Table 1.1). Eleven members of the ABC transporters belong to the ABCB

subfamily, four of which are full-transporters while the other seven are half-

transporters. The first member of the ABCB subfamily, ABCB1, is the most extensively

studied ABC transporter due to its involvement in the development of multidrug

resistance in multiple types of malignancies (Section 1.6.3.1). The ABCC or MRP

subfamily contains 13 members, several of which are also highly associated with

multidrug resistance, while the ABCD or X-linked adrenoleukodystrophy (ALD)

transporter subfamily includes four half-transporter members which are usually

involved in trafficking of fatty acids. ABCE1 is the only member of the ABCE

subfamily and due to absence of a TMD, it is unlikely that it functions to shuttle

molecules across membranes. Similarly, the three currently known ABCF transporters

also lack TMDs and therefore their role as substrate transporters is also less likely. The

ABCG subfamily of transporters, which consists of at least 5 members is highly

associated with drug transport and multidrug resistance in multiple cancers including

breast cancer (Table 1.1) (Vasiliou et al 2009).

1.6.2 Physiological Roles of the ABC Transporters

ABC transporters are expressed in a wide range of human tissues including the placenta,

lungs, liver, testis and the brain microvasculature where they function as exporters of

mainly hydrophobic substrates including vitamins, sterols and steroid hormones. The

ABC transporters also protect cells and organs by expulsion of metabolites and toxins


27

that are harmful if allowed to accumulate intracellularly. For example, the liver

expresses ABCB1 and the bile salt pump, ABCB6 and is a major metaboliser of

xenobiotic compounds (Huls et al 2009). Water soluble metabolites are usually excreted

into urine by ABCB1, ABCC2 (MRP2), ABCC4 (MRP4) and ABCG2, all of which are

expressed on the apical surface of proximal tubule cells of the kidney, indicating their

significant role in the excretory system. In liver diseases such as primary biliary

cirrhosis and chronic hepatitis, increased expression of ABCB1 and ABCC3 is

observed, which is thought to represent a physiological response to protect against the

buildup of toxic bile substrates (Ros et al 2003). The ABC transporters also protect the

human foetus from harmful toxins. In the placenta, ABCG2 is expressed at high levels

on the chorionic epithelium of placental villi and is most likely responsible for limiting

exposure of the foetus to harmful toxins or substrates in the maternal circulation

(Maliepaard et al 2001, Ceckova et al 2006). Consistent with this, foetal exposure to

topotecan and dietary toxins was found to be elevated in Abcg2 knockout mice (Abcg2-

/-) (Jonker et al 2000). Further in vivo studies have shown the importance of the ABC

transporters in eliminating toxic metabolites such as porphyrins or degraded chlorophyll

products, as Abcg2-/- mice developed serious phototoxic skin lesions or photoporphyria

when exposed to UV rays following feeding with a chlorophyll-containing alfalfa diet.

This is due to toxic accumulation of pheophorbide A, a type of porphyrin and

breakdown product of chlorophyll (Jonker et al 2002). Plasma levels of the food

carcinogen, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine (PhIP) are also elevated

in Abcg2-/- mice due to decreased intestinal, fecal and hepatobiliary excretion of this

compound which is usually exported by ABCG2 (van Herwaarden et al 2003).

1.6.3 ABC Transporters in Cancer

ABC transporters are major contributors to the development of multidrug resistance

(MDR) in diseases such as cancer. This is primarily attributed to overexpression of

individual ABC transporters in cancer cells and their ability to export a variety of

substrates including therapeutic drugs and chemotherapeutic agents (Kathawala et al

2015). In addition, ABC transporter-mediated drug resistance has been associated with

the cancer stem cell subpopulation of tumour cells, outgrowth of which leads to

treatment failure and cancer relapse (Section 4.1) (Ding et al 2010, Jiang et al 2012,

Zhang et al 2013a). ABCB1, ABCG2, ABCC1 and ABCC10 are the most extensively

studied ABC transporters due to their overexpression in multiple types of cancers. It is

proposed that elucidation of their roles in conferring multidrug resistance in tumours


28

will facilitate the development of novel therapies to delay or inhibit multidrug resistance

mediated by these transporters.

ABCB1 or P-glycoprotein (P-gp) was the first human ABC transporter identified and

belongs to the first group of the B subfamily (ABCB1) of the ABC transporters. It was

originally isolated in 1986 from a colchicine-resistant keratin-forming tumour cell line

(KB) selected with vinblastine and is encoded by the MDR1 gene (Roninson et al 1986).

In 1992, a second human ABC transporter, multidrug resistance-associated protein 1

(MRP1) or ABCC1 was isolated from the adriamycin-resistant promyelocytic cell line,

HL60/Adr while another member of the MRP family of transporters, MRP7 or ABCC10

was characterised in 2001 (Cole et al 1992, Hopper et al 2001). ABCG2 or breast

cancer resistance protein (BCRP), identified in 1998, belongs to the second group of the

G subfamily of ABC transporter proteins (Doyle et al 1998). ABCG2 was isolated from

a multidrug resistant breast cancer cell line, MCF-7/AdrVp which was selected for

resistance to doxorubicin and verapamil but lacked expression of ABCB1 and ABCC1

(Doyle et al 1998). Simultaneously, two other groups reported isolation of the same

gene but conferred different names to their constructs; mitoxantrone-resistance (MXR)

which was detected in MCF-7 cells and ABCP which was overexpressed in placental

cells (Allikmets et al 1998, Miyake et al 1999).

1.6.3.1 ABCB1 / P-glycoprotein (P-gp)

The ABCB1 or P-glycoprotein (P-gp) gene is located on chromosome 7p21 and contains

28 exons. It encodes a 170 kDa protein comprising of 1280 amino acids and is

expressed predominantly in epithelial cells on apical surfaces of the lower

gastrointestinal tract, proximal tubules of the kidney, liver hepatocytes, the adrenal

glands, placental trophoblasts and capillary endothelial cells of the testes and brain

(Kathawala et al 2015). At these surfaces and typical of the ABC transporters, ABCB1

has a high affinity for binding and export of a diverse array of chemicals and

hydrophobic compounds including chemotherapeutic agents, HIV-protease inhibitors,

antibiotics, anti-depressants and analgesics (Sarkadi 2006). Although a proportion of

these substrates are also transported by other types of ABC transporters, several belong

to drug resistance profiles unique to ABCB1 such as the chemotherapeutic agents,

taxanes (e.g. paclitaxel), colchicine and vinca alkaloids (e.g. vincristine), which are


29

preferentially effluxed by ABCB1 compared to other transporters (Figure 1.8)

(Kathawala et al 2015).

Figure 1.8: Efflux of chemotherapeutic agents by ABCB1, ABCC1, ABCC10 and ABCG2. ABCB1 and ABCC10 preferentially export taxanes (e.g. paclitaxel) and vinca alkaloids (e.g. vincristine), while ABCC1 mediates export of anthracyclines (e.g. doxorubicin), topotecan and vincristine. ABCB1 has also been shown to export anthracyclines (e.g. doxorubicin, daunorubicin), antibiotics (e.g. actinomycin D) and tyrosine kinase inhibitors (TKIs) (e.g. imatinib, nilotinib). ABCG2 primarily exports anthracyclines (e.g. mitoxantrone, doxorubicin), SN-38, TKIs, methotrexate and flavopiridol (Kathawala et al 2015).

Due to the ability of ABCB1 to efflux a variety of therapeutic agents, cells

overexpressing ABCB1 are often associated with loss of sensitivity to multiple drug

agents. For example, ABCB1 on the luminal surface of microvessel endothelium of the

blood brain barrier (BBB) actively exports chemotherapeutic drugs and as a result, these

drugs are prevented from entering the brain and reaching their target cells or tissues

(e.g. brain cancers such as glioblastomas) (Fellner et al 2002, Hubensack et al 2008).

Therapeutic agents actively exported by ABCB1 include drugs used to treat epilepsy

and antibiotics/antiviral drugs used in the management of infections of the central

nervous system including HIV (Cooray et al 2002, Zhang et al 2003). ABCB1/MDR1

knockout mice (Mrd1a-/-) accumulate higher levels of ABCB1 substrates in the brain,

including the neurotoxic pesticide ivermectin and chemotherapeutic agent, vinblastine,

and the mice are also more sensitive to the effects of these drugs compared to mice

expressing wild-type ABCB1 (Schinkel et al 1997). In addition to drug bioavailability

in the brain, ABCB1 expressed in other areas of the human body limits absorption of

therapeutic drugs such as topotecan. This has been observed following co-


30

administration of oral topotecan and the P-gp inhibitor, GF120918 to patients who had

solid tumours, where increased oral absorption and bioavailability of topotecan was

induced (Kruijtzer et al 2002). Inhibition of P-gp also decreases the excretion of toxic

metabolites. For example, in the gastrointestinal tract, administration of cyclosporin A,

an immunosuppressive drug which also inhibits P-gp, decreased excretion of irinotecan

hydrochloride (CPT-11) and its metabolite, SN-38 (Arimori et al 2003).

The ABCB1 promoter lacks a TATA box but instead contains an Initiator (Inr) element

essential for transcriptional activation. The proximal promoter region, which spans from

-200bp to +43bp, contains a number of putative Sp1 binding sites as well as binding

sites for transcription factors that potentially regulate ABCB1 transcription (Figure 1.9)

(Scotto 2003, Sarkadi 2006). These include GC-box interacting proteins such as early

growth response protein 1 (EGR1) and Wilms tumour protein (WT1), CAAT-box

interacting proteins, c-Fos, NFκB, and the inverted CCAAT box interacting proteins,

nuclear factor Y (NF-Y) and Y box-binding protein 1 (YB-1) (Figure 1.9) (Sarkadi

2006). The tumour suppressor protein p53 was also found to bind to a head-to-tail (HT)

site in the ABCB1 promoter and when p53 binding to the promoter was disrupted, p53-

induced repression of ABCB1 transcription was lost (Johnson et al 2001b). MDR1

promoter-enhancer factor (MEF1) binds to a region between -118bp and -111bp of the

ABCB1 promoter (Ogretmen and Safa 2000), while heat shock transcription factor 1

(HSF1) binds to elements between -152bp to -178bp of the promoter, often in response

to stress stimuli such as heat shock (Figure 1.9) (Vilaboa et al 2000).

Figure 1.9: Putative binding sites of transcription factors in the ABCB1 promoter. The ABCB1 promoter is TATA-less but contains an Initiator (Inr) element essential for regulation of ABCB1 transcription. Transcription factors whose binding sites have been identified in the ABCB1 promixal promoter region include p53, c-Fos, NFκB, nuclear factor Y (NF-Y), Y box-binding protein 1 (YB-1) and heat shock transcription factor 1 (HSF1) (Scotto 2003).


31

1.6.3.2 ABCG2 / Breast Cancer Resistance Protein (BCRP)

ABCG2 is located at chromosome 4q22, the gene spans 66kb and consists of 16 exons

and 15 introns. The first exon contains the 5’-untranslated region (5’-UTR) and the

transcription start site is situated in exon 2 (Figure 1.10) (Bailey-Dell et al 2001). The

ABCG2 gene encodes a full-length 72 kDa protein of 655 amino acids (Doyle and Ross

2003). Similar to ABCB1, the ABCG2 gene promoter lacks a TATA box within 100bp

upstream of the transcription start site but contains a CCAAT box in the 5’ region and

several putative Sp1 and transcription factor binding sites (Figure 1.10, 1.11) (Bailey-

Dell et al 2001).

Figure 1.10: The ABCG2/BCRP gene and protein. The ABCG2 gene consists of 16 exons and 15 introns, with the ABCG2 protein translated from exons 2 to 16 (Bailey-Dell et al 2001).

Figure 1.11: Transcriptional regulation of ABCG2. Transcription factors and signalling pathway intermediates such as the Hedeghog pathway effector, GLI1, and TGFβ signalling mediators, SMAD2/3, ER, PR and hypoxia-inducible factor 1 alpha (HIF-1α) regulate ABCG2 transcription via binding to their cognate binding sequences located in the ABCG2 promoter (Natarajan et al 2012).

An ERE and PRE have been identified between -243bp and -115bp of the ABCG2

promoter and ERα has been shown to bind to the ERE located in this region, inducing

ABCG2 mRNA and protein expression in breast cancer cell lines (Figure 1.11; Section

4.1) (Ee et al 2004a, Ee et al 2004b, Yasuda et al 2006). Stress due to hypoxia or low

oxygen conditions has also been shown to stimulate ABCG2 transcription and this

involves direct interaction of hypoxia-inducible factor 1 alpha (HIF-1α) with hypoxia


32

response elements (HRE) in the ABCG2 promoter (Figure 1.11) (Krishnamurthy et al

2004). Binding sites for signalling pathway intermediates such as the Hedgehog

pathway effector, GLI1 and mediators of the TGFβ pathway, SMAD2 and SMAD3

have similarly been identified in the ABCG2 promoter (Figure 1.11) (Section 4.1)

(Ehata et al 2011, Singh et al 2011).

ABCG2 is widely expressed, for example, in the apical membrane of placental

syncytiotrophoblasts, liver hepatocytes, intestinal mucosal cells, endothelial cells of the

blood brain barrier (BBB), the ovaries, prostate cells and the proximal tubules of the

kidney (Sarkadi 2006). Similar to other members of the ABC transporter superfamily,

ABCG2 primarily exports hydrophobic and amphiphilic compounds. In addition to

these endogenous compounds, ABCG2 is also an active exporter of a variety of drugs

and its elevated expression is associated with the development of multidrug resistance

in cancer (Nakanishi 2012, Kathawala et al 2015). ABCG2 substrates include

chemotherapeutic agents such as mitoxantrone, camptothecins and their analogues,

flavopiridol, topoisomerase 1 inhibitors (e.g. topotecan), irinotecan and its metabolite,

SN-38, and the antifolate agent, methotrexate (Figure 1.8) (Maliepaard et al 2001,

Kathawala et al 2015). Fluorescent compounds or dyes such as Rhodamine 123,

BODIPY-prazosin, Hoechst 33342 and pheophorbide A are also actively exported by

ABCG2 and due to their fluorescence, are useful as probes for examining ABCG2

efflux activities (Mao and Unadkat 2015).

Consistent with their abilities to export multiple chemotherapeutic drugs, the ABC

transporters including ABCG2 are overexpressed in multiple types of cancers, for

example, haematological and lymphoid malignancies including acute myeloid

leukaemia as well as solid tumours including breast, lung, colon, and gastric carcinomas

(Natarajan et al 2012). In acute lymphoblastic leukaemia (ALL), elevated ABCG2

mRNA expression has been associated with shorter survival (Suvannasankha et al

2004). Similarly, in solid tumours, overexpression of ABCG2 has been correlated with

lower response rates to chemotherapy, and lower progression-free and overall survival

(Diestra et al 2002, Yoh et al 2004, Lee et al 2012).


33

1.6.3.2.1 ABCG2 in Breast Cancer

Although ABCG2 was first isolated in a breast cancer cell line, ABCG2 does not appear

to be highly expressed in human breast tumours and is not extensively characterised.

Using immunohistochemistry and semi-quantitative RT-PCR, low to undetectable

ABCG2 levels were detected in breast tumours and these were not correlated with

clinical features of the tumours, treatment responses or disease prognosis (Kanzaki et al

2001, Faneyte et al 2002). In a later study, ABCG2 expression in primary breast tumour

samples detected using RT-PCR was shown to be associated with lower response rates

to anthracycline-based chemotherapy consisting of 5-fluoroacil, adriamycin/epirubicin

and cyclophosphamide, although results did not reach statistical significance (Burger et

al 2003). Similarly, in a cohort of Chinese breast cancer patients, ~50% of the patient

specimens were shown to express ABCG2 and this was also correlated with resistance

to 5-fluorouracil (5-FU) (Yuan et al 2008). More recently, ABCG2 expression in the

small population of breast cancer stem cells has been described and may represent the

major function of ABCG2 in breast tumours (Section 4.1).

1.6.3.2.2 ABCG2 Protein Structure and Synthesis

Unlike ABCB1, ABCG2 is a half-transporter and is composed of a NBD and a set of

TMDs which consists of six α-helices (TM1-TM6) (Figure 1.12) (Nakanishi 2012).

Homo- or heterodimerisation of two half-transporters is crucial for functional activation

of ABCG2 as a plasma membrane transporter. Fluorescence resonance energy transfer

(FRET) and crystallography studies have shown that ABCG2 assembles into

homodimers or homooligomers and a functional tetrameric complex of four ABCG2

homodimers has also been demonstrated (McDevitt et al 2006, Ni et al 2010).

Activation of ABCG2 as a full transporter at the plasma membrane involves several

post-translational regulatory events (summarised in Figure 1.13) (Natarajan et al 2012).

Homodimerisation of ABCG2 is initially believed to involve disulphide bond linkages

at cysteine 603, although others have reported intact and functional ABCG2 despite loss

of this cysteine residue (Ni et al 2010, Haider et al 2011). Following synthesis, ABCG2

also undergoes N-linked glycosylation at asparagine 596, which is located in the

extracellular loop between helices TM5 and TM6 of the ABCG2 transmembrane

domain. In addition, formation of intramolecular disulphide bonds between cysteine 592

and 608 is required to maintain protein stability (Figure 1.13) (Diop and Hrycyna 2005,


34

Henriksen et al 2005). Mature oligomeric and fully glycosylated ABCG2 transporters

are usually degraded via the lysosomal degradation pathway, whereas hypoglycosylated

and mis-folded ABCG2 are preferentially targeted for proteasomal degradation (Figure

1.13) (Wakabayashi et al 2007).

Figure 1.12: Structural domains of the ABCG2 half-transporter. Half-transporters such as ABCG2 are comprised of a NBD and a set of TMDs which consists of 6 α-helices (TM1-TM6). In the extracellular loop 3 (ECL3) region between TM5 and TM6 are cysteine residues at positions 592, 603 and 608, which have been shown to regulate formation of disulphide bonds between ABCG2 dimers, and asparagine at position 596 which is required for N-linked glycosylation of ABCG2 (Nakanishi 2012).

Substrate specificity of ABCG2 is regulated by the identity of amino acid 482 of the

ABCG2 protein, and wild-type ABCG2 primarily exports mitoxantrone but is a weak

exporter of Rhodamine 123 (Honjo et al 2001, Robey et al 2003). A single nucleotide

change at position 482 from an arginine in wild-type ABCG2 (e.g. in the MCF-7 breast

cancer cell line) to either a glycine (R482G) or threonine (R482T), which was identified

in cells selected for resistance to chemotherapy (e.g. MCF-/AdVp3000), increases the

ability of ABCG2 to transport substrates other than mitoxantrone, including Rhodamine

123, doxorubicin and anthracyclines (Honjo et al 2001, Robey et al 2003). Additional

structural studies have determined that the COOH terminus of the ABCG2

transmembrane domain, which functions as an interface for drug-transporter

interactions, is positioned in close proximity to amino acid 482 in the mature protein

and is capable of altering interactions of substrates with the transporters (Ejendal et al

2006).


35

Figure 1.13: Post-translational modification and plasma membrane trafficking of ABCG2. ABCG2 is N-glycosylated and undergoes homodimerisation via formation of intramolecular disulphide bonds to form mature ABCG2 that functions as a substrate exporter at the plasma membrane. Mature ABCG2 is usually degraded by the lysosomes but mis-folded and/or hypoglycosylated ABCG2 may be targeted for degradation by the proteasomal pathway (Natarajan et al 2012).

1.6.3.3 ABCC / Multidrug Resistance Protein (MRP)

The ABCC or MRP members of the ABC superfamily of transporters, ABCC1 (MRP1)

and ABCC10 (MRP7) are most extensively studied for their roles in multidrug

resistance. ABCC1 encodes a 190 kDa transporter protein which when overexpressed in

cancer cells leads to resistance to a diverse array of chemotherapeutic agents that are

also able to be effluxed by other ABC transporters including ABCB1 and ABCG2

(Krishnamachary and Center 1993). These agents include anthracyclines (e.g.

doxorubicin), topotecan, vinca alkaloids (e.g. vincristine), methothrexate, and

mitoxantrone, although taxanes (e.g. paclitaxel, docetaxel), which are known ABCB1

substrates, are not exported by ABCC1 (Figure 1.8) (Kathawala et al 2015). Confirming

the importance of ABCC1, embryonic fibroblasts from ABCC1 (MRP1) knockout mice

(Mrp1-/-) exhibited greater sensitivity to vincristine compared to fibroblasts isolated

from wild-type mice (Johnson et al 2001a).


36

The ABCC10 gene is located at chromosome 6p21.1 and encodes a 171 kDa transporter

protein which consists of three TMDs and two NBDs. ABCC10 is ubiquitously

expressed in the human body including the gastrointestinal tract, kidney, colon, heart,

brain and pancreas (Hopper et al 2001, Kathawala et al 2015). Unlike ABCC1,

ABCC10 is an active exporter of taxanes as well as vincristine and gemcitabine, and

mouse embryo fibroblasts isolated from ABCC10 knockout mice (Abcc10-/-)

accumulated higher levels of the chemotherapeutic drugs, docetaxel and paclitaxel

(Hopper-Borge et al 2011). Consistent with these findings, increased lethality of

Abcc10(-/-) mice was observed following treatment with paclitaxel (Hopper-Borge et al

2011).

1.6.4 Modulators of the ABC Transporters

Due to the significant contribution of the ABC transporters to the development of

multidrug resistance in cancers, up to 3 generations of modulators or inhibitors of ABC

transporter expression and/or function have been developed and tested in pre-clinical

and clinical studies. The first generation of ABC transporter inhibitors included

verapamil, cyclosporine A (CSA) and quinine, however these agents were unsuitable for

clinical use primarily due to high toxicity and low efficacy in patients. A phase III

randomised study in 1995 showed that a combination of verapamil and the

chemotherapeutic agents, vincristine, doxorubicin or dexamethasone did not exhibit

beneficial effects but was associated with cardiotoxicity (Dalton et al 1995). Second

generation ABC transporter modulators such as valspodar and biricodar were

subsequently developed and also tested in clinical trials. Although these agents showed

higher efficacy than the first generation of modulators, they were associated with

development of side effects in patients including ataxia and dizziness (Friedenberg et al

2006). A number of third generation ABC transporter modulators (e.g. zosuquidar

(LY335979) and tariquidar (XR9576)) have also been developed. In clinical trials for

metastatic and locally recurrent breast cancer, non-Hodgkin’s lymphoma and acute

myeloid leukaemia, co-administration of zosuquidar and chemotherapy was safe but did

not improve progression-free and overall survival (Fracasso et al 2004, Morschhauser et

al 2007, Ruff et al 2009, Cripe et al 2010). Tariquidar in combination with docetaxel

has been evalueted in lung and ovarian cancer patients and similarly, results were not

sufficiently pronounced to warrant continuation of the trial (Kelly et al 2011). Specific

inhibitors of ABCG2 including the micotoxin, fumitremorgin C (FTC), and its more

potent and less toxic analogue, KO143, which impedes ABCG2 function and ATPase


37

activity by binding with higher affinity to ABCG2 in a competitive manner, have been

used extensively in pre-clinical studies. (Allen et al 2002). FTC and KO143 have not

been evaluated in clinical trials likely due to toxicity associated with these compounds,

especially FTC, which induces tremors, convulsions and toxicity to the central nervous

system of animals (Nishiyama and Kuga 1989, Nishiyama and Kuga 1990).

A number of tyrosine kinase inhibitors including the BCR-ABL (breakpoint cluster

region-Abelson tyrosine kinase) inhibitors, imatinib and nilotinib, and the EGFR

inhibitors, lapatinib, erlotinib and gefitinib, inhibit ABC transporter function by

blocking ATP binding and availability (Dai et al 2008, Shen et al 2009). Several of

these agents are also substrates of the ABC transporters and may induce competitive

inhibition of ABC transporter function for other substrates (Burger et al 2004, Shen et

al 2009). For example, lapatinib was reported to impede ABCB1 and ABCG2 efflux

activities in vitro, resulting in intracellular accumulation of the ABC substrates,

doxorubicin or mitoxantrone in ABCB1 and ABCG2 overexpressing MCF-7 cells,

although ABCB1 and ABCG2 mRNA and protein levels were unchanged (Dai et al

2008). Consistent with these results, lapatinib also enhanced the inhibitory effects of

paclitaxel on the growth of ABCB1-overexpressing KBv200 cell xenografts in nude

mice (Dai et al 2008). Although pharmacological targeting of ABC transporters is a

logical treatment strategy for cancer, in particular to prevent or overcome drug

resistance, the important functions of ABC transporters at the blood brain barrier and

their pivotal physiological roles in the kidney and liver have limited their clinical use.

1.7 Epithelial-to-Mesenchymal Transition (EMT)

Epithelial-to-mesenchymal transition (EMT) is a reversible physiological process

involving separation of epithelial cells that are usually interconnected in organised

structures by cell-to-cell and cell-to-extracellular matrix (ECM) bonds and

transformation of these cells to irregular-shaped mesenchymal-like cells which are more

motile and invasive (Yilmaz and Christofori 2009). Physiologically, EMT is crucial in

embryonic development, for example, during gastrulation, which leads to development

of the mesoderm and endoderm, and for neural crest formation, during which

mesenchymal cells migrate to various sites of the body to develop into more specialised

tissue-specific cells such as glial and neuronal cells of the central nervous system,


38

adrenal glandular cells and melanocytes (Nistico et al 2012). In adults, EMT contributes

to wound healing and remodelling of tissues such as the mammary gland, in which

lobular and ductal cells undergo specialised differentiation and proliferation at the onset

of puberty (Silberstein 2001, Nistico et al 2012). However, when the EMT programme

is perturbed or hyperactivated, it can result in a number of pathological conditions

including inflammation, fibrosis and cancer progression (Nistico et al 2012).

1.7.1 Physiological Processes Mediating EMT

The initiation and progression of EMT involves a sequence of events that is associated

with reduced expression and function of epithelial-specific and cell-to-cell adhesion

molecules (e.g. E-cadherin, claudins, occludin and cytokeratin) and increased

expression of mesenchymal markers (e.g. N-cadherin, vimentin, fibronectin), core EMT

transcription factors (e.g. SNAI1, SLUG, ZEB1, ZEB2) and basic helix-loop-helix

proteins (e.g. TWIST1, TWIST2) (Figure 1.14) (Huber et al 2005, Tsai and Yang

2013). The EMT transcription factors including SNAI1 and SLUG are capable of

repressing expression of the epithelial marker, E-cadherin by binding to E-box

sequences located in the promoter of the E-cadherin gene, CDH1 (Figure 1.14) (Batlle

et al 2000, Hajra et al 2002).

In response to pro-EMT signals including activation of the transforming growth factor β

(TGFβ), WNT and NOTCH pathways (Section 1.7.2.1, 1.7.2.2, 1.7.2.3), cell-to-cell

adhesion complexes (Section 1.7.1.1) which normally form strong bonds between

neighbouring cells are dissociated. Subsequently, cell surface receptors bind to ECM

components, resulting in the formation of focal adhesion complexes (Section 1.7.1.2)

that re-organise the structure of the intracellular actin cytoskeleton, which is connected

to the cell-to-cell adhesion complexes in epithelial cells. This leads to changes in cell

morphology and formation of protrusions (e.g. invadopodia, lamellipodia) at cell edges

to facilitate cell migration. In order for cells to invade into the surrounding ECM and

stroma, the ECM is degraded by serine proteases such as matrix metalloproteinases

(MMPs) (Section 1.7.1.3) and epithelial cells transdifferentiate into mesenchymal-like

cells which adhere poorly to other cells and are more motile (Figure 1.14) (Lamouille et

al 2014).


39

Figure 1.14: Epithelial-to-mesenchymal transition (EMT). Following activation of the EMT programme, a series of physiological events including tight junction dissociation, loss of apical-basal polarity, cytoskeletal re-organisation, cell migration and degradation of the basement membrane facilitate transformation of organised structures of epithelial cells into motile and fibroblast-like mesenchymal cells. The hallmarks of EMT include downregulated expression of epithelial markers (E-cadherin, claudins, occludins, zona occludens 1 (ZO-1), desmoplakin, cytokeratins) and upregulation of mesenchymal marker expression (N-cadherin, fibronectin, vimentin) (Aroeira et al 2007).

1.7.1.1 Cell-to-Cell Adhesion Complexes

Re-organisation of cell-to-cell adhesion complexes is a crucial step during EMT that

results in dissociation of the strong bonds which normally exist between neighbouring

epithelial cells and fibroblasts. Examples of these complexes include the adherens

junctions (zonula adherens), desmosomes (macula adherens) and tight junctions (zonula

occludens) (Figure 1.15) (Kawauchi 2012).

The two different forms of adherens junctions are the cadherins such as E-cadherin and

N-cadherin, and the nectins and nectin-like proteins (Kawauchi 2012). Nectins are

immunoglobulin-like molecules which are connected to the actin cytoskeleton through

afadin, an actin-binding protein. In contrast, the intracellular domains of cadherins

interact with β-catenin and p120-catenin, with β-catenin recruiting α-catenin to mediate

connection of the catenin/cadherin complex to the intracellular actin cytoskeleton via

actin binding proteins such as vinculin and EPLIN (Figure 1.15) (Abe and Takeichi

2008, Kawauchi 2012).

Similar to the adherens junctions, desmosomes and tight junctions also enforce cell

adhesion and are connected to the actin cytoskeleton. Desmosomal components, which


40

are abundant in the skin and myocardium are composed of non-classical cadherins such

as desmogleins and desmocolins which bind to intracellular plakoglobin, plakophilin

and desmoplakin to connect the cell adhesion proteins to actin microfilaments (Figure

1.15). Plakoglobin, plakophilin 2 (PKP2) and desmogleins have also been reported to

strengthen cadherin and desmosome based cell adhesion via a different mechanism

involving the E-cadherin/β-catenin complexes (Lewis et al 1997). Tight junctions are

characteristically located at the apical section of the lateral membrane of epithelial and

endothelial cells and examples of molecules comprising this family of junction proteins

include zona occludens 1 and 2 (e.g. ZO-1, ZO-2), members of the claudin family (e.g.

claudin-1, claudin-7), occludin and junction adhesion molecule (JAM) (Figure 1.15)

(Kawauchi 2012). In addition to their role in controlling the integrity of cell-to-cell

adhesion, tight junctions also regulate cellular absorption of essential ions such as

sodium (Na+), chloride (Cl-), calcium (Ca2+), and magnesium (Mg2+) to maintain

electrolyte balance via transport of these ions through small intercellular spaces at tight

junctions between epithelial cells (paracellular diffusion) (Tang and Goodenough 2003).

Figure 1.15: Adhesion complexes between adjacent cells and the ECM. Cells are interconnected by (A) tight junctions (TJ), adherens junctions (AJ), gap junctions and desmosomes which are often disrupted during EMT. (B) Nectins and cadherins are adherens junction proteins whereas (C) desmocollin and desmoglein are desmosomal proteins and (D) claudins, junctional adhesion molecule (JAM) and occludins are tight junction proteins. (E) During EMT, cell surface proteins such as the integrins bind to components of the ECM to stimulate cell invasion. Activated integrins bind to downstream proteins such as talin, focal adhesion kinase (FAK) and vinculin which are linked to filamentous actin (F-actin). As the cell adhesion proteins are linked to the intracellular actin cytoskeleton or F-actin and intermediate filaments, disruption of cell-to-cell adhesion leads to reassembly of the actin cytoskeleton and changes in cell morphology (Kawauchi 2012).


41

1.7.1.2 Integrin-Mediated Focal Adhesions

Formation of focal adhesions involving the integrins serves two purposes: to act as a

bridge between the ECM and intracellular actin cytoskeleton and for signal transduction

to regulate cell proliferation, survival and motility. In humans, the integrin family of

transmembrane proteins contains 18 α-chains and 8 β-chains which form at least 24

combinations of α-β heterodimers (Kawauchi 2012). Components of the ECM such as

fibrillar collagens (collagens I-III, V, XI), proteoglycans (e.g. aggrecan, versican,

decorin) and glycoproteins (e.g. laminins, elastin, fibronectin) bind to cell surface

receptors including the integrins and increase formation of focal adhesions at

filamentous actin (F-actin)-based adhesion sites or hemidesmosomes which are

intermediate filament-based (Figure 1.15). Overproduction and deposition of collagen

and crosslinking of collagen by lysyl oxidase (LOX) and LOX-like (LOXL) enzymes,

which leads to stiffening of the ECM, also stimulates formation of focal adhesions and

consequently increases activation of intracellular signalling pathways (Xiao and Ge

2012).

Focal adhesion complexes are composed of intracellular molecules such as talin,

vinculin, zyxin, SRC, focal adhesion kinase (FAK), paxilin and p130Cas. The

connection between focal adhesions and the intracellular actin cytoskeleton is mediated

via talin which binds to the cell surface β1 integrins as well as vinculin, an adaptor

protein that interacts with α-actinin, paxilin, vinexin and vasodilator-stimulated

phosphoprotein (VASP) once its conformation is switched to an active open structure.

α-Actinin and vinculin, in turn, bind to F-actin (Figure 1.15) (Kawauchi 2012).

Additionally, integrins regulate cell proliferation, survival and migration via activation

of other intracellular pathways/intermediates such as the focal adhesion kinases (FAKs),

the SRC family of kinases, MAPK, NFκB and WNT/β-catenin pathways (Kuwada and

Li 2000, Mitra et al 2005, Chung et al 2009, Groulx et al 2014). For example,

interaction of paxilin with FAK leads to formation of complexes consisting of FAK, a

SRC kinase and Grb2, which activates the downstream growth regulatory RAS/MAPK

pathway. Alternatively, vinexin may bind to an activator of Ras, Sos, to activate the c-

Jun N-terminal kinase/stress-activated kinase (JNK/SAPK) pathway (Figure 1.15)

(Akamatsu et al 1999).


42

In order for cells to undergo spreading and migration, formation of focal adhesions

anchors cells to the ECM and provides the forces crucial for pushing the cells forward

in the direction of migration. Subsequently, turnover of the focal adhesions is required

for cells to become motile and migrate from their stationary positions (Webb et al

2002). Overexpression of the actin-binding protein, vinculin, but not other molecules,

has been reported to inhibit cell migration by inducing the maturation and stabilisation

of focal adhesions (Rodriguez Fernandez et al 1992, Saunders et al 2006).

1.7.1.3 Matrix Metalloproteinases (MMPs)

Invasion of cells into the extracellular spaces or stroma requires ECM component-

degrading enzymes such as the matrix metalloproteinases (MMPs) to detach cell-to-cell

and cell-to-ECM adhesions as well as to create a track or pathway in the ECM for cells

to migrate. The 23 human MMPs are divided into collagen-cleaving MMPs or

collagenases (MMP1, MMP8, MMP13), gelatin (denatured collagen)-cleaving MMPs

or gelatinases (MMP2, MMP9) and MMPs that degrade a variety of ECM components,

the stromelysins (MMP3, MMP10, MMP11) and matrilysins (MMP7) (Radisky and

Radisky 2010). These proteolytic enzymes cleave their substrates via direct binding to

specific domains of the target molecules. For example, type 1 collagens bind to the N-

terminal domain of gelatinases whereas stromelysins and collagenases interact with

collagens at the C-terminal domains of the enzymes (Allan et al 1991, Murphy et al

1992, Allan et al 1995).

1.7.2 Regulation of EMT by Signalling Pathways

EMT is regulated by a number of pathways that are also associated with cell and tissue

development and cancer. The major pro-EMT pathways include the TGFβ, WNT and

NOTCH signalling pathways, activation of which modulates the expression of the EMT

markers, vimentin and fibronectin, the core EMT transcription factors, SNAI1, SLUG

and TWIST1, as well as the cell-to-ECM components, integrins and collagens.

1.7.2.1 TGFβ Pathway

The TGFβ signalling pathway is an important regulator of cellular processes including

cell proliferation, cell differentiation, apoptosis, migration and invasion (Talbot et al

2012). In the canonical TGFβ pathway, the cytokine TGF-β, which is secreted as a

precursor molecule (latent TGF-β) in large latency complexes (LLCs), binds to the cell


43

surface receptor, TGF-β receptor 2 (TGFβ-RII) following its release from the LLCs

(Figure 1.16). Along with TGF-β receptor 3 (TGFβ-RIII), ligand-bound TGF-β

receptors form heterotrimeric complexes with and transphosphorylate TGF-β receptor 1

(TGFβ-RI), which in turn phosphorylate the downstream ligand-specific receptor-

activated SMADs (R-SMADs), SMAD2 and SMAD3. R-SMADs then form

heteromeric complexes with SMAD4, a co-SMAD molecule, and translocate into the

nucleus where they function as transcription factors (Figure 1.16) (Talbot et al 2012).

As SMAD proteins bind with low affinity to DNA, transcription factors and co-

regulators such as p300/CBP, forkhead activin signal transducer-1 (FOXH1), E26

transformation-specific 1 (ETS1), AP-1 and AP-2 bind to SMAD to regulate

transcription of genes (Chen et al 1997, Janknecht et al 1998, Zhang et al 1998,

Koinuma et al 2009). Examples of TGFβ pathway-regulated target genes include those

associated with EMT (e.g. vimentin, SNAI1, SLUG), the human plasminogen activator

inhibitor-type 1 gene (PAI-1 or SERPINE1), collagens (e.g. COL1A2), and integrins

(e.g. ITGA5) (Chen et al 1998, Dennler et al 1998, Lai et al 2000, Romano and Runyan

2000, Peinado et al 2003, Yoshida et al 2013).

In addition to their regulation by the SMAD-dependent TGFβ pathway, signalling by

TGFβ also regulates apoptosis, cell migration, invasion and EMT via other pathways

that are independent of SMAD. These include activation of the Rho family of GTPases

(e.g. RhoA/Rock1), and MAP kinases such as ERK1/2, c-JUN N-terminal kinase (JNK)

and p38 kinases (Engel et al 1999, Yue and Mulder 2000, Yu et al 2002, Ozdamar et al

2005). For example, TGFβ-induced alteration of cell-to-cell adhesion during EMT can

be mediated via interaction of TGFβ-RI with Par6, a regulator of epithelial cell polarity

and tight junction assembly. This results in phosphorylation of Par6 which triggers

interaction of Par6 with an E3 ubiquitin ligase, SMAD ubiquitylation regulatory factor 1

(SMURF1), to target the regulator of actin cytoskeleton, RhoA, for degradation, leading

to dissociation of tight junctions (Ozdamar et al 2005). The TGFβ pathway is also

capable of activating the p38 MAPK pathway, independent of SMAD, to mediate a

TGFβ-induced EMT-like programme. In mouse mammary epithelial cells (NMuMG),

TGF-β1 treatment led to formation of spindle-shaped cells and downregulation of E-

cadherin expression in cell junctions, and these phenotypes were inhibited when cells

were co-treated with the p38 kinase inhibitor, SB203580 (Yu et al 2002).


44

Figure 1.16: TGFβ signalling. TGF-β released from large latency complexes (LLCs) binds to TGF-β receptor 2 (TGFβ-RII) which, in association with TGF-β receptor 3 (TGFβ-RIII), forms heterotrimeric complexes with and transphosphorylates TGF-β receptor 1 (TGFβ-RI). SMAD2/3 proteins are phosphorylated by these complexes and conjugate with SMAD4 to initiate their nuclear translocation and transcriptional regulation of genes. SMAD-independent pathways regulated by TGFβ include the Traf6-TAK1-p38/JNK, RhoA-Rock1 and Par6 pathways, all of which may regulate cell proliferation, migration and invasion (Talbot et al 2012).

1.7.2.2 The WNT Signalling Pathway

Both canonical and non-canonical WNT signalling pathways play crucial roles in the

regulation of cell survival, proliferation, migration and invasion. In the canonical WNT

pathway, binding of canonical WNT ligands (e.g. WNT2, WNT2B, WNT8B, WNT3A,

WNT6, WNT9A, WNT10B) to their receptor complexes composed of a 7-

transmembrane domain receptor, Frizzled (Fz) (e.g. FZD1, FZD7) and lipoprotein

receptor-related protein 5/6 (LRP5/6) promotes plasma membrane localisation of a

cytosolic protein complex containing Axin, a negative regulator of WNT signalling.


45

This allows binding of Axin to a conserved sequence in the cytoplasmic tail of LRP5/6

which leads to activation and membrane localisation of a phosphoprotein, Dishevelled

(DSH) (Mao et al 2001, Zeng et al 2008). DSH inhibits the activity of the enzyme

GSK3β, thereby preventing phosphorylation and degradation of β-catenin, which is

normally mediated by a destruction complex that contains Axin, adenomatous polyposis

coli (APC), GSK3β and casein kinase 1 (CK1) (Figure 1.17). As a result, β-catenin is

able to translocate into the nucleus where it binds to and functions as a co-activator of

T-cell factor/lymphoid enhancer factor (TCF/LEF) complexes to increase expression of

WNT target genes, for example, cyclin D and c-MYC (He et al 1998, Shtutman et al

1999, Komiya and Habas 2008). In the absence of WNT signalling, the destruction

complexes remain in the cytosol where CK1 and GSK3β phosphorylate β-catenin,

promoting its targeting by the E3 ubiquitin ligase, β-TrCP and proteasomal-mediated

degradation (Figure 1.17) (Komiya and Habas 2008).

Figure 1.17: The canonical WNT signalling pathway. In the absence of WNT signalling, the destruction complex consisting of Axin, adenomatous polyposis coli (APC), GSK3β and casein kinase 1 (CK1) phosphorylates β-catenin in the cytoplasm and induces binding of E3 ubiquitin ligases that promote proteasomal-mediated degradation of β-catenin. Binding of WNT ligands to Fz receptors releases β-catenin from the destruction complexes, resulting in accumulation of β-catenin in the cytoplasm and subsequently its nuclear translocation. In the nucleus, β-catenin acts as a co-activator of T-cell factor/lymphoid enhancer factor (TCF/LEF)-mediated WNT target gene expression (Komiya and Habas 2008).


46

Non-canonical WNT signalling, which is independent of β-catenin-mediated

transcriptional regulation of genes, includes the planar cell polarity (PCP) (Figure 1.18)

and WNT/Ca2+ (Figure 1.19) pathways. In the PCP pathway, binding of non-canonical

WNT ligands (e.g. WNT5A, WNT5B, WNT11) or WNT4 and WNT7B, which are able

to regulate both canonical and non-canonical WNT signalling, to Fz receptors (e.g.

FZD3, FZD4, FZD6) activates downstream pathways, involving the small GTPases,

Rho and Rac (Figure 1.18) (Benhaj et al 2006, Komiya and Habas 2008). In WNT/Rho

signalling, DSH forms complexes with and activates Dishevelled associated activator of

morphogenesis 1 (Daam1) which then activates Rho-associated kinases (ROCK) and

myosin to modulate the structure of the actin cytoskeleton (Figure 1.18) (Komiya and

Habas 2008). In contrast, activation of Rac is Daam1-independent and results in the

regulation of JNK signalling to modulate actin polymerisation and gastrulation (Figure

1.18) (Komiya and Habas 2008).

Figure 1.18: The non-canonical WNT/planar cell polarity (PCP) pathway. Signals from WNT binding to Fz receptors induce formation of Dishevelled (Dsh) and Dishevelled associated activator of morphogenesis 1 (Daam1) complexes which activate either the actin-binding protein, profilin or the small GTPases Rho and Rac to modulate the actin cytoskeleton and induce cytoskeletal re-arrangement (Komiya and Habas 2008).

The WNT/Ca2+ pathway is important in embryogenesis, for example, where it functions

as a critical regulator of cellular processes including EMT and cell migration in the

formation of the dorsal axis, cardiogenesis and gastrulation. In this pathway, signals

from WNT and Fz stimulate release of Ca2+ from the endoplasmic reticulum (ER) that

activate Ca2+-sensitive proteins including protein kinase C (PKC) and


47

calcium/calmodulin-dependent kinase 2 (CAMK2) (Kuhl et al 2000, Sheldahl et al

2003). PKC has a role in the control of cell-sorting behaviour in the mesoderm during

gastrulation via activation of the small GTPase CDC42, while CAMK2 is able to

activate the TGFβ-activated kinase (TAK1) which stimulates Nemo-like kinase (NLK)

activity and downregulates β-catenin/TCF transcriptional activity via direct binding to

the TCF4 transcription factor (Figure 1.19) (Ishitani et al 1999, Winklbauer et al 2001).

Figure 1.19: The non-canonical WNT/Ca2+ pathway. Binding of WNT ligands to Fz receptors induces activation of Dishevelled (Dsh) which stimulates the release of Ca2+ from the endoplasmic reticulum (ER). WNT signalling regulates a number of developmental process via multiple pathways that are mediated by activation of calcineurin, protein kinase C (PKC) and calcium/calmodulin-dependent kinase 2 (CAMK2). Calcineurin stimulates the activity of the transcription factor, nuclear factor of activated T cells (NFAT), PKC activates the small GTPase CDC42 while CAMK2 antagonises the transcriptional activation of β-catenin/TCF via activation of TGFβ-activated kinase (TAK1) and Nemo-like kinase (NLK), which directly inhibits TCF4 (Komiya and Habas 2008).

1.7.2.3 The Notch Signalling Pathway

NOTCH signalling is another developmental pathway shown to regulate cell

proliferation, differentiation, apoptosis and EMT. The NOTCH pathway is activated


48

following interactions of canonical ligands, Delta or Serrate/Jagged (Jagged1 and

Jagged2) with NOTCH receptors (NOTCH 1-4) in adjacent cells. This promotes

cleavage of the receptors by γ-secretase to release the NOTCH intracellular domain

(NICD) which translocates into the nucleus where it binds to the transcriptional

repressor, CBF-1, Suppressor of Hairless and Lag-2 (CSL) to de-repress and co-activate

the transcription of NOTCH target genes such as the Hairy enhancer of split (Hes)

family members (Figure 1.20) (Wang and Zhou 2013).

Figure 1.20: The Notch signalling pathway. At junctions between adjacent cells, binding of Notch ligands (Delta/Jagged) to their receptors induces ubiquitination of the intracellular domain of Notch receptors and their cleavage by metalloproteases and gamma-secretase. This leads to the release of Notch intracellular domains (NICDs) into the cytoplasm and their translocation into the nucleus where they bind to CSL transcription factors. In the presence of transcriptional coactivators, expression of Notch target genes (e.g. helix-loop-helix transcription factors, HRT/Herp transcription factors, p21, NRARP, deltex-1) is increased (Talbot et al 2012).

SLUG is an example of a NOTCH target gene, and in the nonmalignant breast epithelial

cell line, MCF10A, SLUG expression is upregulated following constitutive activation of

NOTCH (Leong et al 2007). SLUG downregulates E-cadherin mRNA and protein

expression and induces an EMT-like programme involving dissociation of cell–cell

adhesions and formation of cells with a spindle-shaped morphology (Leong et al 2007).

NOTCH effects on EMT may also be mediated via activation of the TGFβ and NFκB

signalling pathways (Zavadil et al 2004, Wang et al 2006), with downregulation of

NOTCH1 by siRNA reversing NOTCH1-induced increases in pancreatic cancer cell


49

invasion in association with decreased binding of NFκB to DNA and reduced

expression of MMP9 (Wang et al 2006).

1.7.3 EMT in Breast Cancer

The process of tumour metastasis involves a series of events, a proportion of which may

be regulated by induction of an EMT process. Cancer-associated EMT facilitates

migration and invasion of tumour cells which, after entry into the blood or lymphatic

circulation (intravasation), may be transported to a secondary site. Following

extravasation, where the tumour cells invade through the vessel wall into the underlying

tissue, EMT signals are lost and reversal of EMT or mesenchymal-to-epithelial

transition (MET) is instigated, permitting formation of micrometastases. MET is

essential for cancer cell dissemination and proliferation at a new site as EMT regulators

(e.g. SNAI1) inhibit cell division by reducing the expression of the cell cycle regulator,

cyclin D (Vega et al 2004).

Loss of E-cadherin expression is one of the hallmarks of EMT (Section 1.7.1).

Decreased expression of E-cadherin is correlated with cancer aggressiveness and

metastasis, with lower levels of E-cadherin expressed in advanced stage tumours (e.g.

lymph node-positive breast cancer) (Younis et al 2007). Formation of β-catenin/E-

cadherin complexes at cell-to-cell junctions is important for maintaining epithelial

integrity, and increased nuclear β-catenin in breast tumours, which indicates activation

of β-catenin/WNT signalling, is associated with poorer treatment outcomes and worse

disease prognosis (Yoshida et al 2001). An EMT signature is characteristic of the more

aggressive basal-like breast cancers, and includes elevated expression of both

mesenchymal markers (vimentin, smooth muscle actin, N-cadherin, cadherin 11) and

molecules which stimulate ECM remodeling and invasion (SPARC, laminin, fascin),

but reduced levels of epithelial markers (E-cadherin, cytokeratins) (Sarrio et al 2008).

Altered cell-to-cell adhesion structures regulate EMT progression and in cancers

including breast tumours, lower expression of tight junction proteins has been

demonstrated in metastatic tumours, with poorly differentiated and higher grade breast

tumours shown to express lower levels of ZO-1 (Martin et al 2004, Martin et al 2010).

The EMT core transcription factor, SNAI1 has also been reported to downregulate

occludin mRNA levels, while claudin-1 expression was suppressed only at the protein


50

level, indicating regulation by post-translational modification (Ohkubo and Ozawa

2004).

In order to stimulate cell migration and invasion, a number of regulators of cell-to-ECM

and matrix metalloproteinases are also altered in tumours. The integrins have different

roles in breast tumour migration and invasion depending on their heterodimerisation

partners. Expression of the α6β4 integrins has been associated with larger and higher

grade tumours and αvβ3 integrins were found to induce bone metastasis of breast

tumours (Diaz et al 2005, Takayama et al 2005). In an in vivo mouse model of HER2-

overexpressing breast cancer, knockdown of β4 integrin by expression of a dominant

negative mutant of this integrin subunit was associated with inhibition of tumorigenesis

and metastasis (Guo et al 2006). High mRNA and protein expression of the β6 integrin

subunit in breast tumours is also associated with poor survival of patients and distant

metastases (Moore et al 2014). In contrast, in the poorly differentiated Mm5MT cell

line, a mouse mammary tumour virus (MMTV)-induced tumorigenic breast cancer cell

line, exogenous expression of α2β1 integrins transitioned the spindle-shaped and motile

cells into cells with more epithelial-like and less invasive phenotypes, indicating that

α2β1 integrins have an inhibitory effect on EMT and metastasis (Zutter et al 1995).

Similarly, low expression of α5β1 integrin has been associated with poor differentiation

of breast adenocarcinomas (Zutter et al 1990), although contrasting studies have also

reported pro-invasive effects of α5β1 integrins that are implicated in EMT in mammary

epithelial cells (Maschler et al 2005). For example, knockdown of steroid receptor

coactivator-1 (SRC-1) in mouse mammary tumour cell lines reduced cell migration

which was associated with downregulation of the expression of ITGA5, a gene encoding

the α5 integrin, and decreased ability of cells to assemble focal adhesion complexes for

cell migration. (Qin et al 2011). Elevated expression of α5β1 integrins has also been

shown to increase breast cancer cell invasion via modulation of MMP-1 and MMP-2

collagenase activity (Jia et al 2004, Morozevich et al 2009).

Due to the ability of MMPs to induce cell invasion into the surrounding stroma and

ECM, MMPs have been hypothesised to play important roles in the progression of

DCIS to invasive cancers. In support of this hypothesis, expression of MMP9, MMP26

and tissue inhibitor of metalloproteinases, TIMP-2 and TIMP-4 were higher in DCIS

compared to adjacent nonmalignant breast epithelium and invasive ductal carcinomas


51

(Zhao et al 2004). In invasive breast tumours, MMPs were shown to be expressed at

high levels in intratumoral stromal fibroblasts and fibroblasts at the invasive front of

breast tumours (Del Casar et al 2009). In breast cancer cell lines, MMP2, MMP9 and

MMP14 were found to be expressed at higher levels in more invasive (MDA-MB-231

and Hs578T) compared to less invasive (MCF-7, ZR-75-1) cell lines, while MMP1 and

MMP7 were overexpressed only in the more invasive MDA-MB-231 cell line

(Kousidou et al 2004, Figueira et al 2009).

Abnormal activation of pro-EMT signalling pathways is implicated in breast cancer cell

migration, invasion and tumour metastasis. Expression of TGF-β1 has been reported in

human mammary carcinomas with the levels shown to be higher at the leading edges of

the tumours and in lymph node metastases (Dalal et al 1993). In vitro, TGF-β1

treatment of MCF-7 cells was shown to induce a fibroblast-like phenotype, reduce cell-

to-cell interactions and promote cell migration and invasion, while transplantation into

rats of 13762NF mammary adenocarcinoma clone MTLN3 cells that had been pre-

treated with TGF-β1 increased formation of lung metastases (Welch et al 1990, Zhang

et al 2013b).

Similarly, both WNT/β-catenin and non-canonical WNT signalling pathways stimulate

breast tumour metastasis often in association with overexpression of WNT signalling

intermediates (e.g. WNT ligands, Fz receptors) (Wu et al 2012, MacMillan et al 2014).

Knockdown of WNT3A in herceptin-resistant SKBR3 and BT-474 breast cancer cell

lines, in which WNT signalling is hyperactivated, led to inhibition of cell invasion,

decreased nuclear localisation of β-catenin and reversal of EMT, with N-cadherin

expression downregulated and E-cadherin upregulated (Wu et al 2012). WNT5A, a

ligand of the non-canonical WNT signalling pathways also stimulates breast cancer

metastasis. This is supported by in vitro studies using cell lines derived from patients

with invasive mammary carcinomas where transfection of the cells with a WNT5A

expression construct stimulated cell migration and invasion, which were associated with

upregulation of MMP3 (MacMillan et al 2014). The NOTCH signalling pathway

increases expression of EMT transcription factors (e.g. SLUG), and in the breast cancer

cell lines, MCF-7 and MDA-MB-231, ectopic expression of the NOTCH intracellular

domain (NICD) resulted in increased cell invasion, while knockdown of NOTCH1


52

reversed EMT and cell invasion in vitro and in vivo in mice injected with NOTCH1

shRNA-transfected MDA-MD-231 cells (Bolos et al 2013, Shao et al 2015).

1.8 Statement of Aims

The androgen receptor (AR) and Hedgehog signalling pathways alter the expression of

genes that encode positive and negative regulators of breast cancer cell proliferation,

differentiation, survival and motility. A direct interaction between the AR and the

Hedgehog signalling effectors, the GLI transcription factors has been reported,

suggesting potential cross-talk between the pathways (Chen et al 2010, Chen et al

2011a). Androgens including DHT inhibit the proliferation of AR+ve/ER+ve/PR+ve

breast cancer cells and inhibition of the Hedgehog signalling pathway with the SMO

inhibitor, cyclopamine, has similarly been shown to decrease breast cancer cell

proliferation. (Greeve et al 2004, Macedo et al 2006, Mukherjee et al 2006, Zhang et al

2009). Expression of breast cancer-associated genes following DHT and/or cyclopamine

treatment of the MCF-7 and T-47D breast cancer cell lines, which was investigated

using RT2 Profiler Human Breast Cancer PCR Arrays, identified marked

downregulation of transcripts encoding the ABC drug efflux transporter, ABCG2,

overexpression of which is associated with drug resistance and is a hallmark of breast

cancer stem cells (Kim et al 2002, Engelmann et al 2008). Expression of EMT

regulators was also decreased in DHT and cyclopamine treated cells, indicating that

EMT-associated processes including migration and invasion are also inhibited (Yilmaz

and Christofori 2009, Lamouille et al 2014). Based on these preliminary findings, the

aims of this thesis were:-

1. To investigate DHT and cyclopamine effects on the expression and function of

ABCG2 in MCF-7 and T-47D cells

2. To evaluate DHT and cyclopamine-induced regulation of EMT in MCF-7 and T-

47D cells

Chapter 2

Materials

Chapter 2: Materials

53

2.1 Reagents

2.1.1 Cell Culture

CellTiter 96® AQueous One Solution cell proliferation assay

Promega, USA

Charcoal-treated foetal calf serum (CSS) Serana Australia, Australia

Foetal calf serum (FCS) Serana Australia, Australia

MCF-7 breast cancer cell line American Type Culture Collection, USA

Penicillin (10,000 U/mL)/streptomycin (10,000 μg/mL)

Life Technologies, USA

RPMI 1640 medium (with L-glutamine) ICN Biochemicals Inc, USA

T-47D breast cancer cell line American Type Culture Collection, USA

Trypsin-EDTA Life Technologies, USA

2.1.2 Immunofluorescence Microscopy

Bovine serum albumin Sigma, USA

Chlorobutanol BDH Biochemicals, UK

Hoechst 33258 Sigma, USA

Horse serum Life Technologies, USA

Formaldehyde BDH Biochemicals, UK

Immersion oil Nikon, Japan

Lysotracker Red Life Technologies, USA

Nail polish (clear) Manicare, Australia

Phalloidin tetramethylrhodamine B isothiocyanate (Phalloidin red)

Sigma, USA

Polyvinyl alcohol BDH Biochemicals, UK

Sodium azide Aldrich Chemical Company, USA

Sodium dihydrogen orthophosphate dihydrate BDH Biochemicals, UK


54

Triton-X 100 Sigma, USA

2.1.3 Flow Cytometry and Cell Sorting

7-Aminoactinomycin D A.G. Scientific, USA

Hoechst 33342 (bisBenzimide H 33342 trihydrochloride)

Sigma, USA

Mitoxantrone Pfizer, Australia

Rhodamine 123 Sigma, USA

2.1.4 Western Blotting

Acrylamide (37.5:1), 40% (w/v) Amresco, USA

Colour Plus® pre-stained protein marker New England Biolabs, UK

Developer solution A& B Agfa, Belgium

ECL reagent GE Healthcare, USA

Glycine Amresco, USA

2-Mercaptoethanol (2-ME) BDH Biochemicals, UK

NP40 (Igepal) Sigma, USA

Phenylmethylsulphonyl fluoride (PMSF) Roche, Australia

Protease inhibitor cocktail tablets A.G. Scientific, USA

Skim milk powder Bonlac Foods Ltd, Australia

Sodium dodecyl sulphate (SDS) BioRad, USA

Sucrose BDH Biochemicals, UK

Tween-20 Sigma, USA

2.1.5 Agarose Gel Electrophoresis, PCR, RT-qPCR, Sanger Sequencing

1kb Plus DNA ladder™ Life Technologies, USA

Agarose Amresco, USA

Big Dye® Terminator v3.1 cycle sequencing kit Applied Biosystems, USA


55

dNTP set (dATP, dTTP, dCTP, dGTP) Promega, USA

Ethidium bromide ICN Biochemicals Inc, USA

GoTaq® qPCR master mix Promega, USA

Magnesium chloride Life Technologies, USA

Oligo(dT) Promega, USA

Platinum® Taq DNA polymerase Life Technologies, USA

Primers: ABCG2 Sense: 5’-GTT TCA GCC GTG GAA CTC TTT G-3’ Anti-sense: 5’-GCA TCT GCC TTT GGC TTC AAT-3’

Geneworks, Australia

Primers: AR Sense: 5’-CCT GGC TTC CGC AAC TTA CAC-3’ Anti-sense: 5’-GGA CTT GTG CAT GCG GTA CTC A-3’


Primers: β-actin Sense: 5’-GCT GAT CCA CAT CTG CTG GAA-3’ Anti-sense: 5’-ATT GCC GAC AGG ATG CAG AA-3’


Primers: GAPDH Sense: 5’-TGA GGT CAA TGA AGG GGT C-3’ Anti-sense: 5’-GTG AAG GTC GGA GTC AAC G-3’


RNasin® ribonuclease inhibitor Promega, USA

RT2 SYBR green qPCR master mix Qiagen, Australia

Sodium acetate BDH Biochemicals, UK

2.1.6 General

Baxter water Baxter, Australia

Boric acid, sodium decahydrate (borax) Amresco, USA

Bromophenol blue BDH Biochemicals, UK

Chloroquine Sigma, USA


56

Cyclopamine LC Laboratories, USA

5α-Dihydrotestosterone (DHT) Sigma, USA

Disodium hydrogen orthophosphate BDH Biochemicals, UK

Dimethyl sulfoxide (DMSO) Braun Medical, USA

EDTA BDH Biochemicals, UK

Ethanol Rowe Scientific, Australia

Glacial acetic acid Sigma, USA

Glycerol Sigma, USA

Hydrochloric acid BDH Biochemicals, UK

Isopropanol Merck, Australia

KO143 hydrate Sigma, USA

Matrigel™ (growth factor reduced) BD Biosciences, USA

Methanol Labserv, Australia

MG132 A.G. Scientific, USA

Potassium chloride BDH Biochemicals, UK

Potassium dihydrogen orthophosphate BDH Biochemicals, UK

Sodium chloride Sigma, USA

Sodium hydroxide BDH Biochemicals, UK

Sodium hydroxide pellets Sigma, USA

Toluidine blue O Amresco, USA

Tris Amresco, USA

2.2 Laboratory Equipment

2.2.1 Cell Culture

Acrocap™ filter unit (with 0.2 μm Supor® membrane)

Pall Corporation, Mexico

Acrodisc™ syringe filter (with 0.2 μm Supor® Pall Corporation, Mexico


57

membrane)

CellStar® culture flask (25 cm2) Greiner Bio-One, Germany

CellStar® culture flask (75 cm2) Greiner Bio-One, Germany

CellStar® culture plate (6-well) Greiner Bio-One, Germany




CellStar® petri dish (100×20 mm) Greiner Bio-One, Germany

CO2 humidified incubator Sanyo, Japan

Nikon Eclipse TS1000 phase contrast microscope

Nikon, Japan

5 mL Sterile tubes Sarstedt, Australia




Powerpette® turbo pipette controller Jencons, UK

Tucsen® IS500 camera Xintu Photonics, China

2.2.2 Immunofluorescence Microscopy

Lean-lite lightbox Lean Pty Ltd, Australia

Microscope cover glass (22×22 mm) Menzel-Glaser, Germany

Microscope slide (26×76 mm) Knittel Glass, Germany

Nikon A1 confocal laser microscope Nikon, Japan

Nikon Eclipse Ti-E microscope Nikon, Japan

2.2.3 Flow Cytometry and Cell Sorting

BD FACSCanto™ II BD Biosciences, USA

BD Influx™ Cell Sorter BD Biosciences, USA


58

Canto tube TechnoPlas, Australia

Falcon™ tube with cell strainer cap (35 µm nylon mesh)

Falcon, USA

2.2.4 Western Blotting

Agfa CP1000 developer Agfa, Belgium

CL-Xposure™ clear blue X-ray film Thermo Fisher Scientific, USA

Mini Protean® Tetra Cell BioRad, USA

Nitrocellulose membrane Amersham Biosciences, UK Whatman International, USA

Ortho regular CURIX screens (autoradiography cassette)

Agfa, Belgium

PTC-100™ programmable thermal controller MJ Research Inc, USA

Sonicator Branson, USA

Whatman® 3MM filter paper Whatman International, USA

2.2.5 Agarose Gel Electrophoresis, PCR, RT-qPCR, Sanger Sequencing

384-well PCR microtitre plate Axygen Inc, USA

Agarose gel electrophoresis gel tank Fisher Biotec, Australia

C1000™ Thermal cycler BioRad, USA

Corbett liquid handling robot Corbett Life Science, Australia

3730 DNA Analyser Thermo Fisher Scientific, USA

Gel Doc 2000 EQ BioRad, USA

Light Cycler® 480 Roche, Australia

Nanodrop® ND-1000 spectrophotometer Thermo Fisher Scientific, USA

Qik Spin microcentrifuge United Biosciences, Australia

Qubit® fluorometer Life Technologies, USA

Rotorgene-6000 Corbett Life Science, Australia

RT2 Profiler Human Breast Cancer PCR Array Qiagen, Australia


59

(PAHS-131Z)

RT2 Profiler Human EMT PCR Array (PAHS-090Z)

Qiagen, Australia

2.2.6 General

384-well Labofuge T centrifuge Heraeus Sepatech, USA

Aluminium foil KaterMaster, Australia

Autoclave steriliser AMSCO, USA

BioCoat™ Matrigel™ invasion chambers Corning, USA

Centrifuge (5415C, 5415R, 5810R) Eppendorf, Australia

Cling wrap KaterMaster, Australia

Conductive tips (1000 µL) Tecan, USA

Document scanner (HP2500 Precision) Hewlett Packard Pty Ltd, Australia

-20ºC Freezer Westinghouse, USA

-80ºC Freezer Forma Scientific, USA

Latex examination gloves Ansell, Australia

Magnetic stirrer Industrial Equipment and Control Pty Ltd, Australia

Microcentrifuge tube (0.2 mL) Eppendorf, Australia



Milipore masterflex pump Cole-Parmer, USA

Multi-channel pipette (20-200 μL) Axygen Inc, USA

Needle (23G) Terumo, Japan

Olympus BX43 microscope Olympus, USA

Parafilm Pechiney, USA

pH Cube pH-mV-temperature meter TPS, Australia

Pipette tips (0.1-10 μL) Axygen Inc, USA

Pipette tips (0.1-200 μL) Sarstedt, Australia


60

Pipette tips (200-1000 μL) Quality Scientific Plastics, USA

Power Pac 300 electrophoresis power supply BioRad, USA

Shaker Hoefer Scientific, USA

120 mL Specimen container Thermo Fisher Scientific, Australia

Surgical blade Swann-Morton, England

Syringe (1 mL) Becton, Dickinson and Company, Belgium

Syringe (50 mL) Terumo, Japan

Transfer pipette Samco Scientific, USA

UVM 340 Microplate reader Asys, UK

Vortex Select BioProducts, USA

Waterbath Thermoline Scientific, Australia

2.3 Antibodies

Alexafluor® 488 goat anti-mouse IgG Life Technologies, USA

Alexafluor® 546 goat anti-mouse IgG Life Technologies, USA

Anti-ABCG2 (BXP-21), produced in mouse Abcam, USA

Anti-AR, produced in mouse (Clone: AR441) Dako, Australia

Anti-α-tubulin, produced in mouse (Clone: DM1A)

Sigma, USA

Anti-β-actin, goat polyclonal IgG (Clone: I-19) Santa Cruz Biotech Inc, USA

Anti-goat IgG-HRP, produced in donkey Santa Cruz Biotech Inc, USA

Anti-histone H3, produced in mouse Cell Signalling, USA

Anti-mouse IgG-HRP GE Healthcare, USA

Allophycocyanin (APC) anti-human CD44 (Clone: C26), produced in mouse

BD Biosciences, USA

Brilliant Violet™ 421 (BV421) anti-human CD24 (Clone: ML5), produced in mouse

BD Biosciences, USA


61

Phycoerythrin (PE) anti-human CD24 (Clone: ML5), produced in mouse

BD Biosciences, USA

2.4 Commercial Kits

QIAquick® PCR purification kit 2 mL collection tubes QIAquick® spin columns Buffer PB Buffer PE Buffer EB

Qiagen, Australia

RNase-free DNase set DNase1 (lyophilised) (1500 kunitz units) Buffer RDD

RNase-free water

Qiagen, Australia

RNeasy® mini kit

2 mL collection tubes 1.5 mL microcentrifuge tubes RNeasy® mini spin columns Buffer RLT Buffer RW1 Buffer RPE (concentrate) RNase-free water

Qiagen, Australia

RT2 First strand cDNA kit GE (5× gDNA elimination buffer) RNase-free water BC3 (5× RT buffer 3) P2 (Primer and external control mix) RE3 (RT enzyme mix 3)

Qiagen, Australia

Superscript™ III first strand synthesis

Superscript™ III 0.1 M DTT 5× First strand buffer

Life Technologies, USA


62

2.5 Computer Programmes

Adobe® Photoshop CS Adobe, USA

AutoQuant X3 Media Cybernetics, USA

BD FACSDiva 6.0 BD Biosciences, USA

cellSens™ software Olympus, USA

Chromas Lite 2.1.1 Technelysium, Australia

EndNote™ X5 Thomson Reuters, USA

FlowJo FlowJo, USA

Image J National Institute of Health (NIH)

ISCapture software Xintu Photonics, China

KIM software Asys, UK

Light Cycler® 480 software 1.5 Roche, Australia

Microsoft Office™ (Excel, Powerpoint, Word) Microsoft, USA

NIS-Elements™ Nikon, Japan

Prism® 5.0 GraphPad, USA

Quantity One® BioRad, USA

Rotorgene-6000 software 1.8 Corbett Life Science, Australia

RT2 Profiler PCR array data analysis version 3.4 Qiagen, Australia

TScratch 1.0 The MathWorks, Inc., USA

Chapter 3

Methods

Chapter 3: Methods

1, 2, 3 etc reference to Appendix 1 (Buffers and Solutions)

3.1 Cell Culture

The human breast adenocarcinoma cell lines, MCF-7 and T-47D, used in this thesis

were obtained from the American Type Culture Collection. MCF-7 cells were originally

isolated in 1973 from the pleural effusion of a breast cancer in a 69 year old Caucasian

female (Soule et al 1973). T-47D cells were cultured from the pleural effusion of a

breast cancer in a 54 year old woman in 1979 (Keydar et al 1979).

3.1.1 Maintenance of Breast Cancer Cell Lines

MCF-7 and T-47D cells were routinely cultured in 75 cm2 cell culture flasks in RPMI

1640 medium supplemented with 10% foetal calf serum (FCS), 10,000 U/mL penicillin

and 10,000 μg/mL streptomycin (PS) (RPMI/10%FCS/PS)41 at 37ºC and 5% CO2 in

humidified incubators. Culture medium was replaced every 2-3 days and cells were

passaged at 80-90% confluency every 5-8 days. To passage cells, medium was

aspirated, cells were rinsed with 2-3 mL PBS32 then incubated with 1-2 mL trypsin-

EDTA at 37ºC for 2-3 min to dislodge cells. Trypsinisation was inhibited by the

addition of 3-5 mL RPMI/10%FCS/PS41 and the cell suspension was aliquotted into

new culture flasks or plates as required. MCF-7 and T-47D cells were passaged

routinely at dilutions of 1:5 and 1:6, respectively.

3.1.2 Cryopreservation of Cell Lines

To cryopreserve MCF-7 and T-47D cells, RPMI/10%FCS/PS41 medium supplemented

with 10% DMSO was prepared and stored at 4ºC, MCF-7 and T-47D cells were

trypsinised (Section 3.1.1) and the cell suspensions centrifuged at 260 g for 5 minutes at

room temperature. Supernatants were aspirated, the cell pellets were resuspended on ice

in RPMI/10%FCS/PS41 containing 10% DMSO at 3 mL per 75 cm2 flask and 1 mL

aliquots of the cell suspensions were added to cryovials. Cryovials were placed in

insulated containers overnight at -80ºC, then transferred to liquid nitrogen.

3.1.3 Thawing of Cell Lines

To thaw cells, cryovials were placed in a 37ºC waterbath until cell suspensions were

just thawed, then the cell suspensions were immediately added dropwise into a 75 cm2

culture flask containing 10 mL pre-warmed RPMI/10%FCS/PS41. Flasks were

Chapter 3: Methods

64

incubated overnight at 37ºC, 5% CO2 to allow the cells to adhere prior to replacement of

the culture medium.

3.1.4 Isolation of Breast Cancer Stem-Like Cells

Breast cancer stem-like cells were isolated from the MCF-7 cell line using fluorescence-

activated cell sorting (FACS) (Section 3.5) (Kim et al 2002, Engelmann et al 2008). To

prepare cultures, MCF-7 cells grown in 75 cm2 culture flasks were incubated at 37ºC

and 5% CO2 in 10 mL RPMI/10%FCS/PS41 containing 5 µg/mL Hoechst 3334223 for 60

minutes, the cells were trypsinised and the trypsin inactivated by addition of

RPMI/10%FCS/PS41 (Section 3.1.1). Cell suspensions containing 60×106 cells were

centrifuged at 260 g for 5 minutes at room temperature, supernatants were aspirated and

1 mL RPMI 1640 medium containing 2% FCS, 10,000 U/mL penicillin and 10,000

μg/mL streptomycin (RPMI/2%FCS/PS)41 was added to the cell pellets. Cells were

incubated with 1:5 (v/v) allophycocyanin (APC)-conjugated anti-CD44 (CD44-APC)

and 1:5 (v/v) phycoerythrin (PE)-conjugated anti-CD24 (CD24-PE) or 1:50 (v/v)

Brilliant Violet™ 421 (BV421) anti-CD24 (CD24-BV421) antibodies for 30 minutes on

ice, then 5 mL RPMI/2%FCS/PS41 was added to the cell suspensions, which were

centrifuged at 260 g for 5 minutes at 4ºC. Supernatants were removed, cell pellets were

re-suspended in 6 mL RPMI/2%FCS/PS41 and cells were analysed by FACS (Section

3.5).

3.1.5 Treatment of Breast Cancer Cell Lines

3.1.5.1 MTS Proliferation Assay

To prepare cultures for MTS proliferation assays, MCF-7 cells were trypsinised and the

trypsin inactivated using RPMI/2%FCS/PS41 (Section 3.1.1). Cells were seeded into 96-

well plates at 1000 cells/well in 200 μL RPMI/2%FCS/PS41 and cultured for 1-2 days at

37ºC and 5% CO2. To commence treatment of the cells, 100 μL medium was removed

from each well and 100 μL RPMI/2%FCS/PS41 containing additives to give final

concentrations of 0.1% (v/v) ethanol (vehicle control), 10-8 M DHT12 and/or 2 μM

cyclopamine10 was added to the appropriate wells, with sextuplet wells prepared for

each treatment group. Every 2 days, 100 µL of the medium was replaced in each well.

For assessment of mitoxantrone effects on the cells, 100 μL medium was removed from

each well at day 4 of treatment and replaced with 100 μL of the appropriate medium

supplemented with mitoxantrone to obtain final concentrations of 0 µM, 0.0001 µM,

Chapter 3: Methods

65

0.001 µM, 0.01 µM, 0.1 µM, 1 µM, 3 µM, 5 µM or 10 μM mitoxantrone. The cells

were incubated for 4 days, with the medium replaced every 2 days, then cell numbers

were estimated using MTS proliferation assays (Section 3.2).

3.1.5.2 Immunofluorescence Microscopy

To culture cells for immunofluorescence microscopy, cleaned glass coverslips were

placed into 6-well plates and UV-sterilised for 20-30 minutes before 2 mL

RPMI/10%FCS/PS41 was added to each well and the plates incubated at 37ºC, 5% CO2

for ~2 h. MCF-7 cells were trypsinised (Section 3.1.1) and 4×105 cells were seeded onto

each coverslip. Plates were cultured at 37ºC and 5% CO2 for 1-2 days, medium was

changed to RPMI 1640 containing 5% charcoal-treated foetal calf serum (CSS) and

antibiotics (RPMI/5%CSS/PS)40 for 24 h, then the medium was replaced with 2 mL

RPMI/5%CSS/PS40 containing 0.1% (v/v) ethanol (vehicle control), 10-8 M DHT12, 2

μM cyclopamine10 or 10-8 M DHT and 2 μM cyclopamine. Cultures were incubated for

4 days prior to fixation and analysis by immunofluorescence microscopy (Section 3.3).

For staining of cells with the lysosome marker, Lysotracker Red, MCF-7 cultures grown

on glass coverslips in 6-well plates (as described above) were incubated with 50 nM

Lysotracker Red, prepared in 2 mL RPMI/5%CSS/PS40, for 20 minutes at 37ºC, 5%

CO2. Staining of Lysotracker Red was evaluated by immunofluorescence microscopy

(Section 3.3).

3.1.5.3 Flow Cytometry

To prepare cells for flow cytometric analysis of the intracellular levels of Rhodamine

123 or mitoxantrone, MCF-7 cells were trypsinised (Section 3.1.1), 2×105 cells were

added to 25 cm2 flasks and cultured in 5 mL RPMI/10%FCS/PS41 at 37ºC, 5% CO2 for

3-4 days or until cells had reached ~70% confluency. The cells were then incubated in 5

mL RPMI/10%FCS/PS41 containing 0.5 µg/mL Rhodamine 12338 or 1 µM mitoxantrone

for 60 minutes at 37ºC, 5% CO2. Culture medium was replaced with 5 mL

RPMI/10%FCS/PS41 and cells were cultured for 1-24 h prior to trypsinisation (Section

3.1.1). To investigate DHT and cyclopamine regulation of mitoxantrone intracellular

fluorescence, MCF-7 cells grown 25 cm2 flasks were incubated in RPMI/5%CSS/PS40

for 24 h before 0.1% (v/v) ethanol (vehicle control), 10-8 M DHT12, 2 µM cyclopamine10

or 10-8 M DHT and 2 µM cyclopamine was added. Culture media were replaced every 2

Chapter 3: Methods

66

days and after 8 days of treatment, the media were replaced with RPMI/5%CSS/PS40

containing the appropriate additives and 1 µM mitoxantrone. After a further 60 minutes

of incubation at 37ºC and 5% CO2, culture media were aspirated from the flasks and

replaced with RPMI/5%CSS/PS40 containing the appropriate additives but without

mitoxantrone for 60 minutes during which cells were trypsinised every 15 minutes. To

trypsinise cells for flow cytometry (Section 3.4), culture media were aspirated from the

culture flasks, cells were rinsed with ice-cold PBS32, then trypsinised (Section 3.1.1).

RPMI/5%CSS/PS40 was added to inactivate the trypsin and 1×106 cells were transferred

into Canto tubes. Tubes were centrifuged at 260 g for 5 minutes at 4ºC, the supernatants

were aspirated and the cell pellets were re-suspended in 500 μL ice-cold PBS32. Cell

suspensions were incubated on ice for 30 minutes with 5 µL 7-aminoactinomycin D (7-

AAD)2 which stains non-viable cells. The Canto tubes were again centrifuged at 260 g

for 5 minutes at 4ºC, the supernatants removed and the cell pellets re-suspended in 500

μL ice-cold PBS32 prior to flow cytometric analysis (Section 3.4).

3.1.5.4 Western Blotting

For preparation of cultures for western blotting, MCF-7 cells were trypsinised (Section

3.1.1), seeded into 6-well plates at 3×105 cells/well and incubated for 1-2 days in 2 mL

RPMI/10%FCS/PS41 at 37ºC, 5% CO2. The medium was then replaced with 2 mL

RPMI/5%CSS/PS40 and after 24 h, the culture medium was aspirated and cultures were

incubated in 2 mL RPMI/5%CSS/PS40 containing 0.1% (v/v) ethanol (vehicle control),

10-8 M DHT12, 2 μM cyclopamine10 or 10-8 M DHT and 2 µM cyclopamine. Cells were

harvested after 0-8 days of treatment for subcellular fractionation (Section 3.6) or

western blotting (Section 3.7).

For MG132 treatment of MCF-7 cells, cells were seeded at 3×105 cells/well into 6-well

plates and cultured for 1-2 days in 2 mL RPMI/10%FCS/PS41. The culture medium was

then replaced with 2 mL RPMI/5%CSS/PS40 and after 24 h, cultures were treated with

0.1% (v/v) ethanol (vehicle control), 10-8 M DHT12, 2 μM cyclopamine10 or 10-8 M DHT

and 2 μM cyclopamine for 2 days prior to addition of 2 μM MG13228 and incubation for

a further 6 h. Cells were then lysed for western blotting (Section 3.7).

For chloroquine treatment of MCF-7 cells, cells were plated into 6-well plates at 1×105

cells/well in 2 mL RPMI/10%FCS/PS41, then culture medium was replaced with 2 mL

Chapter 3: Methods

67

RPMI/5%CSS/PS40 for 24 h and subsequently cells were cultured in 2 mL

RPMI/5%CSS/PS40 containing 0.1% (v/v) ethanol (vehicle control), 10-8 M DHT12, 2

μM cyclopamine10 or 10-8 M DHT and 2 µM cyclopamine for 4 days. At day 4 of the

treatments, 25 μM chloroquine8 was added to the cultures, which were incubated for 6,

24 and 48 h prior to harvesting of the cells for western blotting (Section 3.7).

3.1.5.5 RNA Extraction

To extract RNA from MCF-7 and T-47D cells, cells were trypsinised (Section 3.1.1),

plated at 1:8 dilution into 100 mm petri dishes containing 10 mL RPMI/10%FCS/PS41

and cultured overnight at 37ºC, 5% CO2. The following day, culture medium was

changed to RPMI/5%CSS/PS40 for 24 h and then replaced with RPMI/5%CSS/PS40

containing 0.1% (v/v) ethanol (vehicle control), 10-8 M DHT12, 2 μM cyclopamine10 or

10-8 M DHT and 2 µM cyclopamine. RNA was isolated from cells after 24 h of

treatment (Section 3.8.1).

3.1.5.6 Wound Healing Assays

For evaluation of MCF-7 cell migration by wound healing assays, cells were trypsinised

(Section 3.1.1), seeded into 100 mm petri dishes at 4×105 cells/dish and cultured in 10

mL RPMI/10%FCS/PS41 for 1-2 days. Culture medium was then replaced with 10 mL

RPMI/2%FCS/PS41 and after 24 h, 0.1% (v/v) ethanol (vehicle control), 10-8 M DHT12,

2 µM cyclopamine10 or 10-8 M DHT and 2 µM cyclopamine was added to the dishes and

cells were cultured for 4 days with the medium replaced every 2 days. A sterile pipette

tip was used to create wound areas by scratching the cell monolayer, then culture

medium was replaced to remove non-adherent cells. Cell migration into the wound

areas was quantitated by capturing images of the wound areas at 0, 24, 48 and 72 h of

treatment using a Nikon Eclipse TS1000 phase contrast microscope equipped with a

Tucsen® IS500 camera and ISCapture software, and the percentages of wound area

covered by cells were calculated using TScratch. The rate of wound closure was

obtained by determining the wound widths at times 0, 24, 48 and 72 h, calculating the

difference in wound widths between time 0 (time=0) and each of the later timepoints,

then dividing these differences by the wound width at t=0 (×100 = % wound closure).

Chapter 3: Methods

68

3.1.5.7 BioCoat™ Matrigel™ Invasion Assays

Assays using BioCoat™ Matrigel™ Invasion Chambers were performed according to the

manufacturer’s protocol. Briefly, BioCoat™ Matrigel™ Invasion Chambers were thawed

in 24-well plates for 15 minutes at room temperature to allow the Matrigel™ to gel and

subsequently transferred to wells containing 500 µL RPMI/5%CSS/PS40. 500 µL

RPMI/5%CSS/PS40 was then added to the chambers and the plates were incubated at

37ºC, 5% CO2 for ≥2 h to equilibrate the Matrigel™. MCF-7 cells were trypsinised, the

trypsin inactivated by addition of RPMI/2%FCS/PS41 (Section 3.1.1), and to seed 5×104

cells/chamber, 1 mL suspensions of cells containing 10×104 cells were prepared in

RPMI/2%FCS/PS41. Medium in the chambers was aspirated, the chambers were

transferred to wells containing 750 µL RPMI/10%FCS/PS41 which had been pre-

incubated at 37ºC, 5% CO2 for ~2 h, 500 µL of the cell suspension was added to each

chamber and the plates were incubated for 24 or 48 h. To stain the cells that had invaded

through the Matrigel™ and the underlying filter into the lower chamber of the plate,

medium was removed from the chamber and using a cotton swab, the upper surface of

the membrane was scrubbed to remove the Matrigel™ and cells that had not invaded

through the Matrigel™ layer. Cells that had invaded through the Matrigel™ to the under-

side of the filter were stained in 24-well plates by incubating the membrane in 500 µL

100% methanol for 2 minutes, 500 µL 1% Toluidine blue O53 for 10 minutes, then 2× 2

minutes in 1mL ddH2O. Cotton swabs were used to remove excess debris and moisture

from the upper membrane surface and each membrane was excised from the chamber

using a surgical blade, placed onto a drop of immersion oil on microscope slides,

covered with a glass coverslip and sealed using clear nail polish. Filters were imaged

using an Olympus BX43 microscope equipped with cellSens™ software and numbers of

cells were counted manually.

3.1.5.8 3D Matrigel™ Colony Formation Assays

To investigate MCF-7 cell invasion by 3D Matrigel™ colony formation assays, growth

factor reduced Matrigel™ was thawed on ice for 1-2 h, then 200 µL Matrigel™ per well

was added to 24-well plates, which were incubated at 37ºC, 5% CO2 for ≥30 minutes to

coat the wells with Matrigel. MCF-7 cells were trypsinised, the trypsin was inactivated

with RPMI/2%FCS/PS41 (Section 3.1.1) and aliquots of 1×104 cells in 1.5 mL

microcentrifuge tubes were centrifuged at 260 g for 5 minutes at 4ºC. Supernatants were

aspirated and cell pellets were re-suspended in 300 µL Matrigel™ containing 0.1% (v/v)

Chapter 3: Methods

69

ethanol (vehicle control), 10-8 M DHT12, 2 µM cyclopamine10 or 10-8 M DHT and 2 µM

cyclopamine. The cell suspensions were immediately added to the Matrigel™-coated

wells and cultures were incubated at 37ºC and 5% CO2 for ~30 minutes to allow the

Matrigel™ to gel. 200 µL RPMI/2%FCS/PS41 containing the appropriate treatments

(0.1% (v/v) ethanol, 10-8 M DHT12, 2 µM cyclopamine10 or 10-8 M DHT and 2 µM

cyclopamine) was added to the Matrigel™ cultures and the plates were cultured for 10

days, with culture medium replaced every 2 days. At the end of the treatment period,

images of colonies were captured in 10 fields per well using a Nikon Eclipse TS1000

phase contrast microscope equipped with a Tucsen® IS500 camera and ISCapture

software. Colony size was quantitated using Image J by measuring the number of pixels

occupied by each colony.

3.2 MTS Proliferation Assays

MTS proliferation assays were performed using a CellTiter 96® AQueous One Solution

Kit according to manufacturer’s protocol. Briefly, 100 μL culture medium was removed

from each well of 96-well plates (Section 3.1.5.1) and replaced with 20 μL MTS

reagent. The culture plates were incubated at 37ºC for 4 h protected from light and the

absorbance of formazan generated from MTS by viable cells was measured at 490 nm

using a UVM 340 microplate reader equipped with KIM software. Absorbance values

from blank wells, which did not contain cells, were subtracted from experimental wells

and cell numbers were extrapolated from a standard curve. To prepare standard curves,

cells were seeded at 250 to 30,000 cells per well in quadruplicate wells in 96-well plates

and incubated at 37ºC, 5% CO2 for 20-24 h prior to analysis by MTS assay. Mean

absorbance values were plotted against cell density and a linear trend line was fitted

through the values. To calculate cell numbers from standard curves, the linear

regression equation y=mx+c (y: absorbance, x: cell number) was used. Mitoxantrone

dose-response curves were constructed in Prism®, with IC50 values for mitoxantrone or

dose of mitoxantrone required for 50% inhibition of cell proliferation extrapolated from

the dose-response curves.

Chapter 3: Methods

70

3.3 Immunofluorescence Microscopy

To prepare MCF-7 cells cultured on coverslips for immunofluorescence microscopy

(Section 3.1.5.2), medium was removed from 6-well plates, cells were rinsed twice with

1-2mL PBS32 and then incubated at room temperature with 4% formaldehyde22 for 15

minutes. Cells were washed for 3× 5 minutes with PBS32, permeabilised in 0.2% (v/v)

Triton-X 10061 for 5 minutes, washed for 3× 5 minutes with PBS32 and then incubated

for 30 minutes in Blocking Buffer4. After blocking, cells were washed 3× 5 minutes

with PBS32, then incubated overnight at 4ºC with the ABCG2 primary antibody diluted

at 1:500 (v/v) in PBS/1% BSA34, in humidified containers. The following day, cells

were rinsed for 5× 5 minutes with PBS32 at room temperature, after which all

procedures were performed in minimal light. Cells were incubated for 90 minutes with

the cell nuclear stain, Hoechst 33258 diluted at 1:4000 (v/v) in PBS/1% BSA34 and

Alexafluor® 488- or Alexafluor® 546-conjugated anti-mouse secondary antibodies

which were diluted at 1:400 (v/v) in PBS/1% BSA34. Cells were rinsed 3× 5 minutes

and then incubated for 45 minutes with Phalloidin Red36 diluted at 1:2000 (v/v) in

PBS/1% BSA33 or with 0.1% (v/v) DMSO diluted in PBS/1% BSA34 for cells not

stained with Phalloidin Red. Cells were rinsed with PBS32 for 5× 5 minutes before

coverslips were mounted on microscope slides using Mounting Medium29 and the edges

of the coverslips sealed using nail polish. Slides were stored at 4ºC prior to imaging

with a Nikon Eclipse Ti-e fluorescence microscope or a Nikon A1 confocal microscope.

Hoechst 33258 (excitation, 346 nm; emission, 460 nm), and Alexafluor® 488 (green)

(excitation, 488 nm; emission, 519 nm) were detected using DAPI and FITC filters,

respectively, whereas Phalloidin Red (excitation, 540 nm; emission, 565 nm),

Alexafluor® 546 (red) (excitation, 561 nm; emission, 572 nm) and Lysotracker Red

(excitation, 577 nm; emission, 590 nm) were detected using TRITC filters. Using the z-

stack feature in the image acquisition software, NIS-Elements™, 10-11 images at an

optical thickness of 0.5 μm per image that were serially captured from the top to the

bottom of cells were merged using AutoQuant X3. Images were coloured using Adobe®

Photoshop CS.

3.4 Flow Cytometry

Intracellular levels of Rhodamine 123 and mitoxantrone were evaluated using a BD

FACSCanto™ II flow cytometer equipped with BD FACSDiva 6.0 software. 7-AAD

Chapter 3: Methods

71

and Rhodamine 123 fluorescence signals were detected by a blue laser excitation source

(488 nm) and emission filters were 650 nm long pass for 7-AAD and 530/30 nm band

pass for Rhodamine 123. Mitoxantrone fluorescence was excited by a red laser (635

nm) and signals were detected by a 670/30 nm bandpass emission filter. MCF-7 cells

prepared for flow cytometry (Section 3.1.5.3) were dispersed by passing through a 23 G

needle and 1 mL syringe prior to flow cytometric analysis. Geometric mean of

fluorescence intensities (MFIs) of Rhodamine 123 and mitoxantrone were determined

using Flowjo.

3.5 Fluorescence-Activated Cell Sorting (FACS)

Following staining of MCF-7 cells with Hoechst 33342, CD44-APC and CD24-PE

antibodies (Section 3.1.4), breast cancer stem-like cells which accumulate low levels of

Hoechst 33342 (Hoechst 33342lo), due to elevated expression of ABC transporters (Kim

et al 2002, Patrawala et al 2005, Engelmann et al 2008, Yin et al 2008), and express

high levels of CD44 and low levels of CD24 (CD44hi/CD24lo) (Al-Hajj et al 2003) were

isolated from MCF-7 cells using a BD Influx™ Cell Sorter. Hoechst 33342 was excited

using an ultraviolet (UV) laser (350 nm) with Hoechst-blue signals detected by a 450/50

nm bandpass filter and Hoechst-red signals detected by a 675/50 nm bandpass filter.

CD44-APC was detected using a 660/20 nm emission filter following excitation by a

red laser (650 nm), and to detect CD24-PE, a blue laser excitation source (488 nm) and

575/26 nm emission filter were used. CD24-BV421 was detected using a purple laser

(405 nm) and a 450/50 nm bandpass filter. Prior to analysis of MCF-7 cells using the

BD Influx™ Cell Sorter, cell clumps were removed by passing the cell suspension

through Falcon™ tubes with cell strainer caps containing 35 µm nylon mesh. Isolated

breast cancer stem-like cells were seeded at 5000 cells/well into 24-well plates for

immunoblotting (Section 3.7) or onto glass coverslips, which had been UV-sterilised

and placed into 6-well plates, for immunofluorescence microscopy (Section 3.3). Cells

were cultured in 1-2 mL RPMI/10%FCS/PS41 for 3-4 days before culture medium was

replaced with RPMI/5%CSS/PS40. After 24 h, RPMI/5%CSS/PS40 containing a final

concentration of 0.1% (v/v) ethanol, 10-8 M DHT12, 2 µM cyclopamine10 or 10-8 M DHT

and 2 µM cyclopamine was added to cultures. For immunoblotting (Section 3.7), cells

were treated for 8 days and for immunofluorescence microscopy (Section 3.3), cells

were treated for 4 days.

Chapter 3: Methods

72

3.6 Subcellular Fractionation

For subcellular fractionation, cells cultured in 6-well plates (Section 3.1.5.4) were

placed on ice, medium was aspirated from the wells, the cells were rinsed with 1-2 mL

ice-cold PBS32 and 400 μL cell lysis buffer7 was added to each well. Cells were scraped

using a rubber policeman, collected into pre-chilled 1.5 mL microcentrifuge tubes then

incubated on ice for 20 minutes with vigorous pipetting of the lysates every 5 minutes to

enhance cell lysis. Cell nuclei were pelleted by centrifugation at 2320 g for 5 minutes at

4ºC and the supernatants, which contained cytoplasmic proteins, were transferred into

pre-chilled 1.5 mL microcentrifuge tubes then stored at -20ºC. Cell pellets were rinsed

in 400 μL ice-cold PBS32, tubes were centrifuged at 2320 g for 5 minutes at 4ºC and

supernatants were discarded. Pellets were resuspended in 250 μL nuclear lysis buffer30,

the solution sonicated for 4× 15 seconds on ice, centrifuged at 14,500 g, 4ºC for 10

minutes and the supernatants containing nuclear proteins were transferred into pre-

chilled 1.5 mL microcentrifuge tubes and stored at -20ºC. The remaining pellets, which

contained cell membranes and vesicles which had not been lysed were collected in

whole cell lysis buffer64 and stored at -20ºC.

3.7 Western Blotting

3.7.1 Whole Cell Lysis

Lysis of cells as whole cell extracts for western blotting was performed at room

temperature in a fume cupboard. MCF-7 cells cultured in 6-well plates (Section 3.1.5.4)

were rinsed with 1-2 mL PBS32 and 250-600 µL whole cell lysis buffer64 was added to

each well. Breast cancer stem-like cells cultured in 24-well plates (Section 3.5) were

rinsed with 1 mL PBS32 and lysed in 100-200 µL whole cell lysis buffer64. Cells were

scraped into 1.5 mL microcentrifuge tubes using a rubber policeman, and cell lysates

were repeatedly passed through a 23 G needle and 1 mL syringe to reduce viscosity,

then stored at -20ºC or analysed by SDS-polacrylamide gel electrophoresis (SDS-

PAGE) (Section 3.7.2) and immunoblotting (Section 3.7.3).

3.7.2 SDS-Polyacrylamide Gel Electrophoresis (SDS-PAGE)

SDS-PAGE was performed using a Mini Protean® Tetra Cell (BioRad) according to the

manufacturer’s protocol. Briefly, 12% separating gel mixture43 was prepared and poured

Chapter 3: Methods

73

between glass gel plates until ~0.5 cm below the level of the wells, the gel solution was

overlayed with ddH2O and the gel incubated at room temperature for 45-60 minutes to

polymerise. Following removal of ddH2O, 4% stacking gel mixture48 was prepared and

poured over the separating gels, well combs were inserted and the gels were left to

polymerise at room temperature for 30-45 minutes. Prepared gels were assembled into

the apparatus in tanks containing 1× western running buffer63.

In preparation for SDS-PAGE, 15-20 μL cell lysates were combined with appropriate

volumes of 10× western loading buffer62, heated at 95ºC for 5-7 minutes, allowed to

cool to room temperature then loaded into the wells. A well containing 5 μL Colour

Plus® pre-stained protein marker was included in each gel, and gels were

electrophoresed at 200 V for ~1 h. Following electrophoresis, gels were removed from

the glass casting plates, stacking gels removed and the separating gels placed into cold

transfer buffer58. All transfer components were similarly pre-soaked in cold transfer

buffer58. From the negative electrode (black) of the transfer cassettes, transfer

sandwiches were assembled with a scotch brite, 2× filter paper, the gel, nitrocellulose

filter, 2× filter paper and a scotch brite. The transfer cassettes were closed, placed into

transfer tanks containing cold transfer buffer58 and proteins were transferred overnight

at 30V and at room temperature.

3.7.3 Immunoblotting

For immunoblotting, nitrocellulose membranes were blocked in Tris-buffered saline

(TBS) containing 3% skim milk powder (TBS/3% Blotto56) for 90 minutes at room

temperature, then incubated with primary antibodies diluted in TBS containing Tween-

20 (TBST)55 and 1% skim milk powder (TBST/1% Blotto57) either overnight at 4ºC for

ABCG2 immunoblots or at room temperature for 90 minutes for AR and β-actin

immunoblots (Table 3.1). Following primary antibody incubation, nitrocellulose

membranes were washed at room temperature with TBST55 for 3× 10 minutes and

incubated at room temperature with the appropriate secondary antibodies diluted in

TBST/1% Blotto57 for 90 minutes (Table 3.1). Nitrocellulose membranes were washed

with TBST55 for 3× 10 minutes, incubated with Enhanced Chemiluminescence (ECL)

reagent17 for 5 minutes then wrapped in cling wrap, exposed to X-ray film for 10

seconds to 5 minutes as required and the films developed using an Agfa CP1000

developer. Films were scanned using an HP2500 Precision document scanner and

Chapter 3: Methods

74

quantitated using Quantity One® software, with levels of proteins of interest normalised

against corresponding β-actin levels from the same lanes and expressed as a proportion

of vehicle controls where appropriate.

Table 3.1: Antibody Dilutions for Immunoblotting

Primary Antibodies Mouse anti-human ABCG2 1:750 Mouse anti-human AR 1:1000 Goat anti-human β-actin 1:3000

Secondary Antibodies Anti-mouse IgG Anti-goat IgG

1:10,000 1:30,000

3.8 Polymerase Chain Reaction (PCR) and Reverse Transcription

Quantitative PCR (RT-qPCR)

3.8.1 RNA Extraction

RNA was extracted from cells using an RNeasy® Mini Kit according to manufacturer’s

protocol. For RNA extraction from cell pellets, cells grown in petri dishes (Section

3.1.5.5) were trypsinised (Section 3.1.1) then 8-9 mL RPMI/5%CSS/PS40 was added to

inactivate the trypsin, the cell suspensions were transferred to 10mL tubes which were

centrifuged at 260 g for 5 minutes at room temperature, supernatants were aspirated and

the cell pellets were stored at -80ºC. To lyse cells in pellets, the appropriate volume of

Buffer RLT for RNA extraction (350 μL Buffer RLT for <5×106 cells or 600 μL Buffer

RLT for 5×106-1×107 cells) was added to the pellets and the suspensions were

transferred to 1.5 mL microcentrifuge tubes. For direct lysis of cells, culture medium

was removed from petri dishes (Section 3.1.5.5), 600 μL Buffer RLT was added and

cells were scraped using a rubber policeman and collected into 1.5 mL microcentrifuge

tubes.

Following cell lysis, viscosity of the lysates was reduced by passing the solution

repeatedly through a 23 G needle and 1mL syringe, an equal volume of 70% ethanol19

was added to each lysate and the solution transferred to RNeasy® spin columns in 2 mL

Chapter 3: Methods

75

collection tubes, which were centrifuged at 8000 g for 15 seconds at room temperature.

The flow-throughs were discarded and 350 μL Buffer RW1 was added to each of the

spin columns, which were again centrifuged for 15 seconds at 8000 g and room

temperature and flow throughs discarded. For DNase treatment, 10 μL 2.72 kunitz

units/µL DNase13 was combined with 70 μL Buffer RDD, and the solution added

directly to the spin columns, which were incubated at room temperature for 15 minutes.

350 μL Buffer RW1 was added to the spin columns, the columns were centrifuged at

8000 g for 15 seconds and flow throughs were discarded. The spin columns were

washed twice with 500 μL Buffer RPE, with the columns centrifuged at 8000 g for 15

sec after the first wash and for 2 minutes following the second wash. The columns were

then transferred to fresh 2 mL collection tubes, centrifuged again at 8000 g for 1 minute

and then placed into sterile 1.5 mL microcentrifuge tubes. To elute RNA, 30-50 μL

RNase-free water was added to the columns, the columns were centrifuged for 1 minute

at 8000 g and RNA was stored at -80ºC.

3.8.2 Reverse Transcription

cDNA synthesis for RT-qPCR assays was performed using Superscript™ III, whereas a

RT2 First Strand cDNA Synthesis Kit was used to prepare cDNA for RT2 Profiler PCR

Arrays.

3.8.2.1 cDNA Synthesis Using Superscript™ III

To synthesise cDNA using Superscript™ III, 1 μL 500 µg/mL oligo(dT), 1 μg RNA and

1 μL 10 mM dNTP16 were combined in a 0.2 mL microcentrifuge tube and made up to

14 μL with ddH2O. The solution was then heated at 65ºC for 5 minutes, immediately

incubated on ice for at least 1 minute and a master mix containing 4 μL 5× First-Strand

Buffer, 1 μL 0.1M DTT and 1 μL Superscript™ III was added to each tube. The mixture

was combined by pipetting, incubated at 50ºC for 60 minutes, then at 70ºC for 15

minutes to inactivate the enzyme.

3.8.2.2 Preparation of cDNA Using the RT2 First Strand cDNA Synthesis Kit

For synthesis of cDNA using the RT2 First Strand Kit, a genomic DNA (gDNA)

Elimination Mixture was prepared by combining 1 μg RNA, 2 μL Buffer GE and the

solution was made up to 10 µL with ddH2O. The solution was mixed by pipetting,

incubated at 42ºC for 5 minutes and placed on ice for ≥1 minute. An RT cocktail

Chapter 3: Methods

76

containing 4 μL Buffer BC3, 1 μL Buffer P2, 2 μL Buffer RE3 and 3 μL ddH2O was

prepared, added to each sample and the solution combined by pipetting. Tubes were

again incubated at 42ºC for 15 minutes and the reaction was terminated by incubation at

95ºC for 5 minutes. cDNA samples were diluted with 91 μL RNase-free water or stored

overnight at -20ºC.

3.8.3 Purification of cDNA

cDNA samples were purified at room temperature using a QIAquick® PCR purification

kit as described in the manufacturer’s protocol. Briefly, five volumes of Buffer PB was

added to each cDNA, and the solution was added to QIAquick® spin columns in 2 mL

collection tubes, which were centrifuged for 30-60 seconds at 12,000 g. The flow

throughs were discarded and the columns were washed by addition of 750 μL Buffer PE

and centrifugation for 30-60 seconds at 12,000 g. The flow throughs were removed and

the columns were again centrifuged for 30-60 seconds at 12,000 g to remove residual

Buffer PE. To elute the cDNA, the spin columns were transferred into clean 1.5 mL

microcentrifuge tubes, 40-50 μL Buffer EB was added to each column, the columns

were incubated at room temperature for 1 minute, then centrifuged for 30-60 seconds at

12,000 g. Purified cDNA was stored at -20ºC.

3.8.4 Primer Design

Primer sequences for ABCG2 were obtained from a previous study (Nakanishi et al

2003), while primers for the AR and reference genes, GAPDH and β-actin were

designed using Primer-BLAST (Ye et al 2012) and checked using Oligo Calc (Kibbe

2007) (Table 3.2).

3.8.5 Polymerase Chain Reaction (PCR)

To prepare 25 μL PCRs, 5 µL 5× PCR buffer35, MgCl227 (Table 3.2), 15 ρmol sense and

anti-sense primers (Table 3.2), 0.1 µL 5 U/µL Platinum® Taq DNA polymerase and

ddH2O (final reaction volume 25 µL) were prepared as a master mix and added to 0.2

mL microcentrifuge tubes. 10 ng cDNA was added to the appropriate tubes and PCR

amplification was performed in C1000™ Thermal Cyclers as follows:- 95ºC/4 minutes,

then 35 cycles of (i) 95ºC/30 seconds, (ii) 60-65ºC/30 seconds (Table 3.2), (iii) 72ºC/1

minute, and a final elongation step of 72ºC for 4 minutes. Each PCR run included a

Chapter 3: Methods

77

negative control, which did not contain cDNA. Following amplification, PCR products

were analysed by agarose gel electrophoresis (Section 3.8.6) or stored at -20ºC.

3.8.6 Agarose Gel Electrophoresis

To prepare gels for agarose gel electrophoresis, 2% (w/v) agarose1 was heated in a

microwave to melt the agarose, cooled at room temperature to ~70ºC, the solution

poured into casting trays containing gel combs and the gel incubated at room

temperature for 45-60 minutes to solidify. For electrophoresis, 5-10 µL PCR products

(Section 3.8.5) were combined with the appropriate volume of 6× DNA loading buffer15

and added to wells. Each gel contained a lane with 5 µL 1kb Plus DNA ladder™ 14. Gels

were electrophoresed in 1× TAE buffer52 at room temperature for ~30 minutes at 100 V.

Following electrophoresis, gels were visualised using a BioRad Gel Doc 2000EQ with

Quantity One® software.

3.8.7 Reverse Transcription-Quantitative PCR (RT-qPCR)

For RT-qPCR, 20 μL reactions contained 2× GoTaq® qPCR master mix, 4 ρmol sense

and anti-sense primers (Table 3.2), 2 ng cDNA and ddH2O. qPCR was performed in 0.2

mL tubes in a Rotorgene-6000 as follows:- 95ºC/5 minutes, then 40 cycles of (i)

95ºC/15 seconds, (ii) 60-65ºC/30 seconds (Table 3.2), then 95ºC/1 minute, 40ºC/1

minute and a melt curve from 58ºC to 95ºC at a ramp rate of 0.5ºC/sec. Negative

controls, which did not contain cDNA, and efficiency curves for target and reference

genes were included in every qPCR. To construct efficiency curves, qPCRs containing

serial dilutions of 2ng cDNA were prepared and following PCR amplification, mean

threshold cycle (Ct) values were plotted against log cDNA concentration in Excel, a

linear curve was fitted through the points and the slope (m) of the linear curve from the

linear regression equation (y=mx+c) was used to calculate the amplification efficiency

(E).

E: 10-1/slope

For calculation of relative expression of target genes, mean Ct values for target and

reference genes were obtained and the following Pfaffl equation was used:

Ratio: (Etarget) ∆Ct target (control-sample)/ (Eref) ∆Ct ref (control-sample)

Etarget and Eref refer to amplification efficiencies for target and reference genes,

respectively, whereas ∆Ct target or ref (control-sample) is the difference in Ct values of

Chapter 3: Methods

78

target or reference genes between control (e.g. vehicle control) and experimental

samples.

Table 3.2: Primers for PCR and RT-qPCR

Gene Primer Sequences Annealing Temperature

Amplified PCR

product (bp)

MgCl2 (mM)

ABCG2

Sense: 5’-GTT TCA GCC GTG GAA CTC TTT G-3’ Anti-sense: 5’-GCA TCT GCC TTT GGC TTC AAT-3’

60ºC 191 3.5

AR

Sense: 5’-CCT GGC TTC CGC AAC TTA CAC-3’ Anti-sense: 5’-GGA CTT GTG CAT GCG GTA CTC A-3’

65ºC 168 3

β-actin

Sense: 5’-GCT GAT CCA CAT CTG CTG GAA-3’ Anti-sense: 5’-ATT GCC GAC AGG ATG CAG AA-3’

60ºC 150 2

GAPDH

Sense: 5’-TGA GGT CAA TGA AGG GGT C-3’ Anti-sense: 5’-GTG AAG GTC GGA GTC AAC G-3’

60ºC 112 2

3.8.8 PCR Arrays

In this study, high-throughput screening of EMT-associated genes in MCF-7 and T-47D

cells was performed using RT2 Profiler Human EMT PCR Arrays according to the

manufacturer’s protocol. The arrays contained optimised primers for analysis of 84

EMT-associated genes, five housekeeping genes (β-actin (ACTB), beta-2-microglobulin

(B2M), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), hypoxanthine

phosphoribosyltransferase 1 (HPRT1) and ribosomal protein large, P0 (RPLP0)), a

human genomic DNA control (HGDC), reverse transcription controls (RTC) and PCR

positive controls (PPC) (Figure 3.1, Appendix 2). To prepare cDNA for the PCR arrays,

RNA extracted from MCF-7 and T-47D cells treated for 24 h with 0.1% (v/v) ethanol

(vehicle control), 10-8 M DHT12, 2 µM cyclopamine10 or 10-8 M DHT and 2 µM

cyclopamine (Section 3.8.1), was reverse transcribed (Section 3.8.2.2), added to 550 µL

2× RT2 SYBR green master mix and made up to 1100 µL with RNase-free ddH2O. The

solution was mixed by pipetting then 10 μL per well was loaded into the PCR array

1

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79

Chapter 3: Methods

80

plates using a Corbett liquid handling robot and conductive tips (Figure 3.2). The array

plates were sealed with optical adhesive films, centrifuged at 1620 g for 7-10 seconds at

room temperature and qPCR performed in a Light Cycler® 480 as follows:- 95ºC/10

minutes with a ramp rate of 4.8ºC/second, then 45 cycles of (i) 95ºC/15 seconds with a

ramp rate of 1ºC/second and (ii) 60ºC/1 minute with a ramp rate of 1ºC/second. This

was followed by a final incubation at 60ºC for 15 seconds with a ramp rate of

4.8ºC/second, then a melt curve with increase of the temperature to 95ºC at a ramp rate

of 0.03ºC/second in continuous acquisition mode. Ct values were obtained and uploaded

to the SABiosciences web-based data analysis program at

http://www.sabiosciences.com/dataanalysis.php using downloadable Excel templates.

Figure 3.2: Loading of 384-well RT2 Profiler PCR Arrays (G Format). cDNA (10 µL per well) from each of the MCF-7 and T-47D treatment groups (1: 0.1% (v/v) ethanol, 2: 10-8 M DHT, 3: 2 μM cyclopamine, 4: 10-8 M DHT + 2 μM cyclopamine) was loaded into the wells as indicated (according to the manufacturer’s protocol).

3.9 Sanger Sequencing

Sequencing reactions each contained 8 µL 2.5× buffer, 0.5 µL Big Dye® Terminator

(BDT), ddH2O (prepared as a master mix), 4 ng purified PCR products (Section 3.8.3,

3.8.5) and 3 ρmol sense or anti-sense primer (Table 3.2). Sequencing was performed in

C1000™ Thermal Cyclers under the following cycling conditions: 25 cycles of (i)

95ºC/15 seconds, (ii) 60ºC/10 seconds, (iii) 60ºC/4 minutes. To precipitate sequencing

reactions, 50 µL 95% ethanol19 and 2 µL sodium acetate44 were added to each reaction,

the tubes vortexed, incubated on ice for 10 minutes and centrifuged at 16,168 g for 30

minutes at 4ºC. Supernatants were removed using a pipette, 250 µL 70% ethanol19 was

added to each tube, and the tubes were centrifuged at 16,168 g for 5 minutes at 4ºC.

Supernatants were again removed using a pipette and pellets were air dried at room

Chapter 3: Methods

81

temperature for 15 minutes. Sequencing was performed using 3730 DNA analysers and

sequencing chromatograms were viewed using Chromas Lite software and analysed

using BLAST® (Mount 2007).

Chapter 4

DHT AND CYCLOPAMINE EFFECTS ON THE

EXPRESSION AND FUNCTION OF ABCG2 IN

MCF-7 AND T-47D CELLS

Chapter 4

82

4.1 Introduction

Breast cancer growth is regulated by a number of signalling pathways and their

interaction facilitates progression of the disease to cancers of poorer prognosis. The

androgen receptor (AR) is expressed in 70-90% of breast tumours and is generally

associated with better disease prognosis and longer overall survival of patients, while

the Hedgehog signalling pathway is hyperactivated in breast cancer cells and breast

tumours (Kubo et al 2004, Gonzalez et al 2008). Androgens (e.g. testosterone, 5α-

dihydrotestosterone (DHT)) and Sonic Hedgehog (SHH) activate their respective AR

and Hedgehog signalling pathways, resulting in the regulation of cell proliferation, cell

survival, differentiation and motility (Section 1.4.4, 1.4.5). This occurs via

transcriptional regulation of target genes that encode mediators of cell survival

pathways and physiological processes such as the cell cycle (Bonifas et al 2001, Bolton

et al 2007). Cross-talk between the AR and Hedgehog signalling pathways has been

reported previously, with the AR shown to directly interact with the Hedgehog/GLI

transcription factors leading to reciprocal regulation of expression of target genes

between the two pathways (Chen et al 2011a, Sirab et al 2012a). Findings from a more

recent study using prostate cancer cells also provided evidence that combined targeting

of the AR and Hedgehog signalling pathways may improve therapeutic outcomes where

cancers exhibit active AR and Hedgehog signalling (Gowda et al 2013).

The ABC drug efflux transporters are major contributors to the development of drug

resistance and treatment failure in breast cancer, and overexpression of the transporters

in tumours has been associated with elevated efflux of therapeutic agents (e.g.

chemotherapeutic drugs) from cancer cells (Kruijtzer et al 2002, Burger et al 2003,

Robey et al 2007, Kathawala et al 2015). ABCB1 and ABCG2, in particular, have been

extensively studied for their roles in the development of chemoresistance and in a small

sub-population of cancer cells termed cancer stem cells (Lou and Dean 2007, Ding et al

2010, Jiang et al 2012). Cancer stem cells have been identified in many tumour types

including blood cancers (e.g. acute myeloid leukaemia (AML)) and solid tumours (e.g.

breast tumours) (Lapidot et al 1994, Al-Hajj et al 2003). These cells exhibit

characteristics of tissue stem cells including quiescence (slow cell division), self-

renewing capabilities and the ability to differentiate into multiple cell lineages

(pluripotency) (Dontu et al 2003). As such, cancer stem cells are capable of undergoing

symmetrical division to give rise to two daughter cancer stem cells or asymmetrical

Chapter 4

83

division to “differentiate” into the majority of cancer cells which form the tumour bulk.

Although only a small subpopulation (<1%) of cancer cells exhibit characteristics of

cancer stem cells, these cells can promote tumour relapse, disease progression, drug

resistance and metastasis (Visvader and Lindeman 2008, Han et al 2013). Therefore,

development of therapeutic approaches to control or eliminate cancer stem cells may

provide a more effective strategy in the management of cancers and improve

progression-free and overall survival of patients.

Cancer stem cells may be identified by appropriate expression of cell surface markers

such as CD44 and CD24 in breast and pancreatic tumours, CD133 (breast, brain and

other cancers), and CD34 and CD38 in acute myeloid leukaemia (AML) cells (Lapidot

et al 1994, Al-Hajj et al 2003, Singh et al 2004). In human breast tumours, cells which

express high levels of CD44, low levels of CD24 and absence of Lineage markers (Lin-

ve) (CD44hi/CD24lo/Lin-ve) are enriched in breast cancer stem cells (Al-Hajj et al 2003).

CD44hi/CD24lo/Lin-ve cells were shown to exhibit a 10 to 50 fold increase in the

capacity to develop tumours compared to other non stem-like cells (e.g.

CD44hi/CD24hi/Lin-ve cells) when transplanted into NOD/SCID mice, re-capitulating the

heterogeneous population of cancer cells in the original tumour and thereby indicating

stem-like differentiation of the CD44hi/CD24-ve/lo/Lin-ve cells into multiple cell lineages

(Al-Hajj et al 2003).

Although expression of CD44 and CD24 are sound markers for breast cancer stem cells,

a combination of additional markers may be more reliable in the purification of breast

cancer stem cells (Ginestier et al 2007, Croker et al 2009). Cells with high aldehyde

dehydrogenase (ALDH) activity have been reported to contain stem/progenitor-like

properties such as an increased ability to form tumours in vivo (Hess et al 2004,

Ginestier et al 2007). Culture of ALDHhi cells isolated from normal human breast and

from human breast carcinomas formed mammospheres in suspension cultures and when

transplanted into the mammary fat pad of NOD/SCID mice, ALDHhi but not ALDHlo

cells formed tumours, indicating their tumorigenic potential (Ginestier et al 2007).

CD44hi/CD24lo breast cancer stem-like cells are reported to include both ALDHhi and

ALDHlo cells, and ALDHhi/CD44hi/CD24lo cells, but not ALDHlo/CD44hi/CD24lo cells

were capable of forming tumours in mice (Ginestier et al 2007, Croker et al 2009).

Chapter 4

84

These studies therefore indicated that a combination of CD44 and CD24 expression and

ALDH activity may more reliably distinguish breast cancer stem cells.

Expression of the ABC transporters has been implicated in maintaining cancer stem cell

growth. In MCF-7 cells which were selected for resistance to doxorubicin (MCF-

7/MDR), elevated expression of ABCB1 was associated with increased proportions of

CD44hi/CD24lo cancer stem-like cells compared to parental (unselected) MCF-7 cells

(Calcagno et al 2010). Cancer stem-like cells have been isolated from a number of

malignancies including breast, lung and pancreatic cancers via flow cytometric

identification of cells with low intracellular levels of the fluorescent ABC transporter

substrate, Hoechst 33342 (Kim et al 2002, Patrawala et al 2005, Engelmann et al 2008,

Yin et al 2008). These cells constitute a small subpopulation of cancer stem cells termed

“side population” (SP) cells which overexpress the ABC transporters, ABCB1 and

ABCG2, and are enriched for stem cell characteristics (Ho et al 2007, Wang et al

2009b, Calcagno et al 2010).

Culture of SP cells in suspension cultures resulted in formation of floating

mammospheres, a stem-like characteristic that was not evident in cultures of non-SP

cells (Hoechst 33342hi) (Engelmann et al 2008). SP but not non-SP cells were also

capable of differentiation into mixed populations of cells (Hoechst 33342hi and Hoechst

33342lo) following long term culture, and transplantation of SP cells into NOD/SCID

mice resulted in formation of tumours, supporting the tumorigenic potential and stem-

like properties of these cells (Patrawala et al 2005, Yin et al 2008). SP cells isolated

from the MCF-7 breast cancer cell line are reported to constitute ~7.5% of the total cell

population and a high proportion of these cells (~80%) were CD44hi and CD24lo,

providing strong evidence that the population was enriched for stem-like cells

(Engelmann et al 2008). As the ABC transporters are able to export chemotherapeutic

drugs (e.g. mitoxantrone, doxorubicin), their increased expression in cancer stem cells is

likely to contribute to the proposed role of this cancer cell subpopulation in the

development of drug resistance and tumour relapse (Lou and Dean 2007, Robey et al

2007, Visvader and Lindeman 2008).

A number of regulators of ABCG2 transcription, post-translational modification and

trafficking to the plasma membrane or other cellular compartments have been identified

Chapter 4

85

and these processes contribute to the synthesis of mature transporters that are

functionally active (Section 1.6.3.2.2). Steroid hormones such as 17β-oestradiol (E2)

and progesterone (P4) stimulate ABCG2 expression (Ee et al 2004a, Imai et al 2005,

Yasuda et al 2006, Wang et al 2008b), although several studies have shown that

sulphated conjugates of hormones (e.g. DHEA, 17β-oestradiol-17D-glucuronide) are

substrates exported by ABCG2 (Imai et al 2003, Suzuki et al 2003). E2 increased

ABCG2 mRNA and protein levels in the ER+ve BeWo human placental

choriocarcinoma and T-47D breast cancer cell lines (Ee et al 2004a, Yasuda et al 2006),

and a putative ERE has been characterised in the ABCG2 promoter which may account

for E2-induced increases in ABCG2 expression (Ee et al 2004b). However,

downregulation of ABCG2 mRNA and protein expression following E2 treatment has

also been described in BeWo cells, potentially resulting from use of different isolates or

passage number of cells between studies (Ee et al 2004a, Imai et al 2005, Wang et al

2006a). In MCF-7 cells, which express ERα, E2 did not alter ABCG2 mRNA but

decreased ABCG2 protein levels (Imai et al 2005). The decrease in ABCG2 levels was

associated with enhanced sensitivity of the cells to SN-38, an inhibitor of topoisomerase

I, and increased intracellular accumulation of topotecan in parental and in ABCG2-

overexpressing MCF-7 cells. These effects were shown to be mediated by ERα as the

ER-antagonist, tamoxifen reversed E2-mediated downregulation of ABCG2 protein

levels (Imai et al 2005). In contrast to BeWo cells, this study indicated that in MCF-7

cells, E2 did not alter ABCG2 transcription but induced post-translational modifications

of ABCG2 that decreased stability and maturation of the protein.

Progesterone (P4) also stimulates ABCG2 mRNA and protein expression (Wang et al

2006a, Yasuda et al 2009). In particular, P4 increased ABCG2 mRNA expression and

stimulated ABCG2 promoter activity in progesterone receptor isoform B (PRB)-

transfected but not in PRA-transfected BeWo cells, indicating that P4 effects on ABCG2

expression are mediated via PRB (Wang et al 2008b). In addition, PRB-stimulated

ABCG2 promoter activity was abrogated by PRA, supporting the previously reported

ability of PRA to suppress PRB activity (Wang et al 2008b). The Hedgehog/GLI

signalling pathway has been demonstrated in several cell types including human

embryonic kidney epithelial cells (293T), B-cell lymphoma (BJAB, SUDHL2) and

primary mediastinal B-cell lymphoma (PMBL) (U2940) cells, to upregulate ABCG2

expression, which involves binding of GLI1 to a single GLI binding site characterised

in the ABCG2 5’ promoter (Singh et al 2011). Elevated levels of ABCG2 mRNA and

Chapter 4

86

protein following treatment of 293T cells with the recombinant SHH N-terminal peptide

was abrogated by the Hedgehog inhibitor, cyclopamine-KAAD, supporting stimulation

of ABCG2 expression by the Hedgehog signalling pathway (Singh et al 2011).

ABCG2 expression may be regulated via post-translational modification of the

transporters which alters their maturity, stability and function. For example, the pro-

inflammatory cytokines, interleukin 6 (IL-6) and TNF-α did not have significant effects

on ABCG2 mRNA levels but increased ABCG2 protein expression, which was

hypothesised to be due to post-translational modification of the proteins (Mosaffa et al

2009). Pim-1L, a serine/threonine kinase, has been shown to induce phosphorylation of

ABCG2 at threonine 362, which was proposed to alter the conformation and subsequent

dimerisation or oligomerisation of ABCG2, with knockdown of Pim-1L expression in

drug-resistant prostate cancer cells abolishing ABCG2 multimer formation (Xie et al

2008). In support of these results, mutation of ABCG2 at threonine 362 (T362A)

inhibited ABCG2 trafficking to the plasma membrane and its drug export activity,

indicating the importance of threonine 362 for ABCG2 function (Xie et al 2008).

ABCG2 expression and function may be repressed by regulators which induce rapid

degradation of ABCG2 via the lysosomal or proteasomal degradation pathway

(Nakagawa et al 2009, Peng et al 2010). Compounds such as xanthines (e.g. caffeine,

theophylline, dyphilline) decreased ABCG2 protein levels by inducing ABCG2

degradation via the lysosome, and co-treatment of xanthine-treated MCF-7 cells

overexpressing ABCG2 (MCF-7/MX100) with the lysosome inhibitor, ammonium

chloride (NH4Cl) were able to restore ABCG2 protein levels (Ding et al 2012). In

association with these findings, xanthines increased the intracellular accumulation of

mitoxantrone and re-sensitised MCF-7/MX100 cells to mitoxantrone cytotoxicity (Ding

et al 2012). A novel ABCG2 inhibitor, PZ-39 stimulated endocytosis and lysosomal

degradation of ABCG2, with PZ-39 shown to bind directly to the ABCG2 protein (Peng

et al 2010). These studies provide evidence for a number of ABCG2 regulators that alter

ABCG2 expression and function by inducing degradation of the transporters via

common degradation pathways such as the lysosomal pathway.

Tyrosine kinase inhibitors (TKIs) such as lapatinib (Tykerb) and apatinib (YN968D1)

modulate ABCG2 function by binding to ATP-binding sites of ABCG2, potentially

Chapter 4

87

downregulating ATP-dependent functions of ABCG2 which include transport of

substrates. Photoaffinity labelling of ABCB1 and ABCG2 with [125I]

iodoarylazidoprazosin (IAAP) was inhibited by apatinib, suggesting that apatinib

interacts or binds to the ABC transporters, with apatinib binding at higher affinity to

ABCG2 substrate binding sites compared to ABCB1 substrate binding sites (Dai et al

2008, Mi et al 2010). Lapatinib and apatinib did not markedly alter ABCG2 mRNA and

protein expression but reversed the resistance of MCF-7 cells overexpressing ABCB1

and ABCG2 (e.g. MCF-7/ADR and MCF-7/FLV1000) to the cytotoxic effects of

doxorubicin and mitoxantrone, indicating that the TKIs inhibited ABC transporter

function without affecting ABC transporter expression (Dai et al 2008, Mi et al 2010).

Inhibition of ABC transporter localisation to the membrane surface, where the ABC

transporters function as drug efflux transporters, has been associated with increased

sensitivity of cells to drugs that are substrates of those transporters (Mizuarai et al 2004,

Robey et al 2007, Nakanishi 2012, To and Tomlinson 2013, Kathawala et al 2015). An

alternate mechanism of ABCG2-mediated drug resistance may involve ABCG2

localisation in membrane of extracellular vesicles (EV) located between neighbouring

cells that have been identified in mitoxantrone-resistant MCF-7 cells (MCF-7/MX)

(Ifergan et al 2005, Goler-Baron and Assaraf 2011). In that study, it was shown that

accumulation of ABCG2 substrates including mitoxantrone and topotecan into EV

structures sequestered these drugs from reaching intracellular targets, resulting in

resistance (Goler-Baron and Assaraf 2011). The formation of these vesicles may involve

PI3K/AKT signalling and treatment of MCF-7/MX cells with the PI3K/AKT pathway

inhibitor, LY294002 decreased the size and number of ABCG2-localising EV structures

and induced retention of ABCG2 and the ABCG2 substrate, riboflavin in the cell

cytoplasm (Goler-Baron et al 2012). LY294002 stimulated the sensitivity of cells to

topotecan, with the IC50 for topotecan decreased following treatment (Goler-Baron et al

2012), indicating that changes in ABCG2 cellular localisation impact the drug efflux

activity of the transporters.

The non-aromatisable androgen, DHT, and the Hedgehog pathway inhibitor,

cyclopamine have been shown previously to inhibit the growth of the ER+ve and PR+ve

breast cancer cell lines, MCF-7 and T-47D (Greeve et al 2004, Kubo et al 2004). Initial

studies in this thesis confirmed these findings and demonstrated using RT2 Profiler

Chapter 4

88

Human Breast Cancer Arrays that treatment of MCF-7 and T-47D cells with DHT,

cyclopamine, or DHT and cyclopamine downregulated the expression of breast cancer-

associated genes, including the mRNAs encoding the ABC transporters, ABCB1 and

ABCG2. This study has investigated DHT and cyclopamine induced regulation of

ABCG2 mRNA and protein expression, as well as ABCG2 function which was

evaluated by measuring the efflux rate of ABCG2 substrates from cells and sensitivity

of cells to cytotoxic ABCG2 substrates due to intracellular accumulation of the

substrates.

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89

4.2 Results

4.2.1 DHT and Cyclopamine Regulation of Gene Expression in Breast Cancer Cells

Prior to commencement of this PhD project (as part of my Honours project), effects of

the androgen, 5α-dihydrotestosterone (DHT) and the Hedgehog pathway inhibitor,

cyclopamine on gene expression were investigated in the MCF-7 and T-47D breast

cancer cell lines, which express functional AR and Hedgehog pathways (Horwitz et al

1975, Liberato et al 1993, Mukherjee et al 2006, Chua 2011, Aka and Lin 2012). DHT

and cyclopamine have independently been reported to inhibit the proliferation of breast

cancer cells including MCF-7 and T-47D cells (Greeve et al 2004, Kubo et al 2004) and

similarly, decreased proliferation of MCF-7 and T-47D cells was observed following 8

days of treatment with 10-8 M DHT or 2 µM cyclopamine, or co-treatment with 10-8 M

DHT and 2 µM cyclopamine (Figure 4.1A) (Chua 2011). These concentrations of DHT

and cyclopamine were shown previously to inhibit proliferation of breast cancer cells

but not to result in cell death (Chua 2011).

DHT and cyclopamine regulation of gene expression in MCF-7 and T-47D cells was

investigated using RT2 Profiler Human Breast Cancer PCR Arrays (SABiosciences),

which screens expression of 84 breast cancer-associated genes. Analysis of results of

the arrays using the SABiosciences web-based programme revealed that treatment of

MCF-7 and T-47D cells with the combination of 10-8 M DHT and 2 µM cyclopamine

for 24 h predominantly downregulated gene expression, with 28 genes downregulated

by ≥1.5-fold in both MCF-7 and T-47D cells. Genes which were downregulated

following DHT and cyclopamine treatments encoded inducers of cell proliferation,

including promoters of cell cycle progression, cyclin D1 (CCND1), cyclin D2 (CCND2)

and the MYC proto-oncogene, as well as anti-apoptosis factors, AKT1, APC, BCL2-

associated death promoter 2 (BAD), JUN and RASSF1 (Figure 4.1B).

Other genes found to be downregulated by DHT and cyclopamine co-treatment of the

cells were regulators of EMT (Section 1.7, Figure 4.1B), with DHT and cyclopamine-

induced downregulation of TGFB1, SRC and TWIST1 indicating reversal of EMT,

which can occur during mesenchymal-to-epithelial transition (MET) (Figure 4.1B).

Markers of the luminal breast cancer subtype, FOXA1, GATA3 and ESR1 were also

downregulated by co-treatment of MCF-7 and T-47D cells with DHT and cyclopamine

(Figure 4.1B). These markers are often used clinically in untreated cancers to predict

Chapter 4

90

responses of breast tumours to endocrine therapies such as the anti-oestrogen, tamoxifen

(Section 1.5). The implications of their downregulated expression in breast cancer cells

treated with DHT and cyclopamine are unknown at this time however androgen-induced

antagonism of the oestrogen responsiveness of breast cancer cells has been reported

previously (Peters et al 2009, Need et al 2012). Of interest, mRNA levels of the drug

efflux transporters, ABCB1 and ABCG2 were also markedly downregulated in both

MCF-7 and T-47D cells treated with the combination of DHT and cyclopamine (Figure

4.1B).

DHT and cyclopamine regulation of the ABC transporters, ABCB1 and ABCG2, was

investigated in this thesis study. As shown in Table 4.1, the threshold cycles (Ct value)

for ABCB1 exceeded 30 cycles (33.86 cycles in MCF-7 and 34.36 cycles in T-47D

cells) and for ABCG2, the Ct value was above 30 cycles in T-47D cells (33.54 cycles),

however in MCF-7 cells, the Ct value for ABCG2 was 27.73. Following analysis of the

genes using the web-based programme provided by manufacturer of the arrays (Section

3.8.8), the fold regulation of ABCB1 in MCF-7 cells was reported as “B” because the Ct

values for ABCB1 in both control and experimental samples exceeded 30 cycles,

thereby indicating low ABCB1 expression in MCF-7 cells. In addition, fold regulation

for both ABCB1 and ABCG2 was also reported as “B” in T-47D cells as Ct values were

>30 cycles (33 – 40 cycles), suggesting that ABCB1 and ABCG2 were expressed at very

low levels in T-47D cells, although ABCB1 and ABCG2 mRNA levels were

dowregulated following DHT and cyclopamine treatments (Table 4.1). As such, DHT

and cyclopamine regulation of ABCG2 expression and function were investigated using

MCF-7 cells.

4.2.2 DHT and Cyclopamine Regulation of ABCG2 mRNA Levels in MCF-7 Cells

Analysis of the RT2 Profiler Human Breast Cancer PCR Array data revealed that DHT

and cyclopamine individually reduced the mRNA levels of ABCG2 by 1.2 to 1.4 fold in

MCF-7 cells, while the combination of DHT and cyclopamine further reduced ABCG2

levels by 1.99 fold compared to the vehicle control (Table 4.1). To validate DHT and

cyclopamine induced downregulation of ABCG2 mRNA levels in MCF-7 cells using

RT-qPCR, RNA was extracted from MCF-7 cells (Section 3.8.1), reverse transcribed

(Section 3.8.2.1), with cDNA quality verified by GAPDH PCR (Section 3.8.5, 3.8.6; not

shown).

Chapter 4

91

(A)

(B) (i)

Anti-Apoptosis

Cell Cycle

EMT

DNA Damage

MC

F-7

(24h

rs)

AKT1 APC BAD CDKN1A JUN MUC1 SFN TP73 TWIST1 APC CCND2 CDKN1A JUN MYC RASSF1 SFN APC BRCA2 CDKN1A MAPK1 SFN TP73 ABCB1 ABCG2 SRC TGFB1 TWIST1 ESR1 FOXA1 GATA3 KRT8 ERBB2 GRB7 NOTCH1 ID1 SRC TGFB1 TWIST1

Xenobiotic Transporters

Breast Cancer Classification Markers

Control (0.1% (v/v) ethanol (vehicle)) 10-8 M DHT

2 μM Cyclopamine

10-8 M DHT + 2 μM Cyclopamine

0

5

10

15

Cel

l Num

ber

(×10

4 )

Treatment (8 days)

MCF-7

0

10

20

30

40

50

Cel

l Num

ber

(×10

4 )

Treatment (8 days)

T-47D

Chapter 4

92

(ii)

Figure 4.1: DHT and cyclopamine effects on cell proliferation and expression of breast cancer-associated genes. (A) Proliferation of MCF-7 and T-47D cells was estimated by MTS assays after 8 days of treatment with 10-8 M DHT, 2 µM cyclopamine or 10-8 M DHT and 2 µM cyclopamine. Control cultures contained 0.1% (v/v) ethanol (vehicle). Results = mean ± S.E.M. (B) Heatmap of DHT and cyclopamine regulated genes in (i) MCF-7 and (ii) T-47D cells determined using RT2 Profiler Human Breast Cancer PCR Arrays. Green signals indicate downregulation, while red signals indicate upregulation of gene expression. DHT and cyclopamine treatments up- or downregulated by ≥1.5-fold a number of genes including anti-apoptosis factors, cell cycle regulators, the ABCB1 and ABCG2 (xenobiotic) transporters, regulators of epithelial-to-mesenchymal transition (EMT) and breast cancer classification markers.

Magnitude of log2 (Fold Change)

0 -2.432 2.432

Xenobiotic Transporters

T-47

D (2

4hrs

)

Anti-Apoptosis

Cell Cycle

EMT

Breast Cancer Classification Markers

ABCG2 ABCB1

BCL2 MYC AKT1 BAD APC JUN RASSF1 CCND1 SFN JUN RASSF1 PTEN TP53 BCL2 MYC

XBP1

SNAI2 TGFB1 TWIST1 NOTCH1 SRC TFF3 FOXA1 KRT18 SLC39A6

KRT8 ESR1 GATA3

ATM1 BRCA1 BRCA2 MGMT SFN TP53 TP73

DNA Damage

Chapter 4

93

Table 4.1: Regulation of ABCB1 and ABCG2 mRNA levels in MCF-7 and T-47D cells.

ABCB1 ABCG2

Average threshold cycle (Ct)

Fold up/down regulation

(status)

Average threshold cycle (Ct)

Fold up/down regulation

(status)

MCF-7

Vehicle control (0.1% (v/v) Ethanol)

33.86 - 27.73 -

10-8 M DHT 35.13 -2.45 (B) 28.06 -1.40 (OKAY)

2 µM Cyclopamine 33.57 1.19 (B) 27.97 -1.21 (OKAY)

10-8 M DHT + 2 µM Cyclopamine

37.44 -1.49 (B) 29.28 -1.99 (OKAY)

T-47D

Vehicle control (0.1% (v/v) Ethanol)

34.36 - 33.54 -

10-8 M DHT 35.81 -1.01 (B) 34.97 -1.75 (B)

2 µM Cyclopamine 40 -1.45 (B) 34.66 -2.02 (B)

10-8 M DHT + 2 µM Cyclopamine

37.11 -1.77 (B) 40 -3.12 (B)

Threshold cycles (Ct) and fold up- or downregulation of ABCB1 and ABCG2 mRNA levels in DHT and cyclopamine treated MCF-7 and T-47D cells compared to vehicle controls (0.1% (v/v) ethanol). A status (OKAY, A, B or C) was assigned to the fold regulation according to Ct values. ‘OKAY’ indicates that Ct values do not exceed 30 cycles; ‘A’ indicates that the average Ct is relatively high (>30 cycles) in either the control or experimental sample and Ct is low (<30 cycles) in the other sample; ‘B’ indicates low gene expression with Ct values exceeding 30 cycles in both control and experimental samples; ‘C’ indicates that gene expression may be very low or undetectable with Ct values in both control and experimental samples above the defined cut-off value of 35 cycles.

Chapter 4

94

To amplify ABCG2 cDNA (~187 bp), qPCR conditions including annealing temperature

and MgCl2 concentration were initially optimised, with gradient PCRs indicating

optimum annealing temperatures between 59ºC to 63.3ºC and an annealing temperature

of 60ºC used in subsequent studies (Figure 4.2A). To optimise MgCl2 concentration for

ABCG2 qPCR, efficiency curves were constructed from reactions containing cDNA

(2ng) diluted 10-fold to 1:1000 and increasing concentrations of MgCl2 (2-3.5 mM)

(Section 3.8.7). Melt curves with sharp peaks were observed for reactions containing all

MgCl2 concentrations, indicating appropriate amplification specificity, however ABCG2

qPCR amplification efficiencies were highest in reactions containing 3.5 mM MgCl2

(98.4%), which was used in subsequent studies (Figure 4.2B). qPCR conditions for the

housekeeping gene, β-actin had been optimised previously in the laboratory (data not

shown) (Section 3.8.7). Efficiency curves constructed for β-actin indicated that β-actin

qPCR efficiency was 97.0% (data not shown). Efficiency values for both ABCG2 and β-

actin qPCRs were within the accepted range for calculation of ABCG2 mRNA levels

using the Pfaffl method (Section 3.8.7).

Quantitation of ABCG2 mRNA levels following 24 h treatments of MCF-7 cells with

10-8 M DHT, 2 µM cyclopamine or a combination of 10-8 M DHT and 2 µM

cyclopamine indicated that in comparison to the vehicle control (0.1% (v/v) ethanol),

DHT treatment reduced ABCG2 mRNA levels by 34.8±0.044% while in cyclopamine-

treated MCF-7 cells, ABCG2 mRNA levels did not change (Figure 4.3). Following DHT

and cyclopamine co-treatment, ABCG2 mRNA levels were reduced by 30.8±0.041%

compared to the vehicle control, a similar reduction to that detected in MCF-7 cells

treated with DHT alone. Therefore, these experiments broadly confirmed results of the

PCR arrays, with DHT and DHT/cyclopamine treatments decreasing ABCG2 mRNA

levels and cyclopamine treatment inducing minimal effects on ABCG2 mRNA

expression.

4.2.3 DHT and Cyclopamine Regulation of ABCG2 Protein Levels in MCF-7 Cells

DHT and cyclopamine effects on ABCG2 protein levels were evaluated by western

blotting (Section 3.7). Prior to the commencement of these studies, ABCG2 primary

antibody concentrations were optimised by western blotting of whole cell lysates

derived from MCF-7 and T-47D cells using 1:1000, 1:750 and 1:500 dilutions of the

ABCG2 antibody (BXP-21 clone) (Figure 4.4A). The molecular weight of ABCG2 is

Chapter 4

95

reported to be 70-72 kDa based on analysis of the protein by SDS-PAGE under

denaturing conditions (Xu et al 2004, Diop and Hrycyna 2005). Similar to findings

from these reports, a prominent band at ~70 kDa was observed in MCF-7 but not T-47D

cell lysates at all ABCG2 antibody concentrations (Figure 4.4A). This correlated with

findings from the breast cancer PCR arrays which showed low endogenous ABCG2

expression in T-47D cells, with qPCR Ct values of >30 cycles in contrast to Ct values of

27.73 cycles in MCF-7 cells (Table 4.1). Additional bands at ~65 kDa, ~46 kDa and ~7

kDa were also detected in the western blots (Figure 4.4A). ABCG2 undergoes post-

translational modification, principally N-glycosylation, which increases protein stability

(Nakagawa et al 2009). Detection of ABCG2-immunoreactive proteins of lower

molecular weights, particularly, at ~65 kDa, which is similar to previously published

ABCG2 western blots from HeLa cells treated with peptide-N-glycosidase F (PNGase

F) or tunicamycin, which cleave N-linked glycans from glycoproteins, may indicate

incompletely glycosylated ABCG2 or ABCG2 degradation products (Diop and Hrycyna

2005, Nakagawa et al 2009). From these initial studies, a 1:750 dilution of ABCG2 was

chosen for subsequent investigation of ABCG2 protein expression.

DHT and cyclopamine regulation of ABCG2 protein levels was evaluated in MCF-7

cells following treatment with 10-8 M DHT, 2µM cyclopamine or 10-8 M DHT and 2 µM

cyclopamine for 0-8 days. ABCG2 levels were quantitated by densitometry, normalised

to corresponding β-actin levels for each lysate and expressed as a ratio of ABCG2 levels

at day 0 (Figure 4.4B). During the 8 days of treatment, DHT progressively decreased

ABCG2 protein levels, which were ~95% of controls at 24 h, but reduced to ~20% of

controls by day 8. Although cyclopamine had little effects on ABCG2 protein levels

which fluctuated around 100% at all timepoints, the combination of DHT and

cyclopamine treatments led to a more rapid reduction in ABCG2 protein levels

compared to DHT-treated cells, with ABCG2 levels reduced to ~55% of controls after

24 h of DHT/cyclopamine treatments and reaching a similar nadir of ~27% during the 8

days of treatment (Figure 4.4B).

4.2.4 Intracellular Localisation of ABCG2 in DHT and Cyclopamine Treated

MCF-7 Cells

Full ABCG2 transporters localise predominantly to the plasma membrane where they

are functionally active as efflux transporters (Nakanishi 2012). As such, reduced

Chapter 4

96

(A)

(B)

2 mM MgCl2

2.5 mM MgCl2

1. 65ºC 2. 64.5ºC 3. 63.3ºC 4. 61.4ºC 5. 59ºC 6. 57ºC 7. 55.7ºC 8. 55ºC 9. Negative control (no cDNA)

1 2 3 4 5 6 7 8 9 ABCG2

(~187 bp)

3 mM MgCl2

Chapter 4

97

MgCl2 Efficiency (%) 2 mM 84.2

2.5 mM 86.0 3 mM 85.9

3.5 mM 98.4

Figure 4.2: Optimisation of ABCG2 qPCR conditions. RNA extracted from MCF-7 cells was reverse transcribed into cDNA. (A) To optimise ABCG2 PCR conditions, ABCG2 PCRs were performed using annealing temperatures between 55-65ºC and 2 mM MgCl2, with products separated in 2% agarose gels. (B) ABCG2 was amplified by qPCR in reactions of 10-fold dilutions of 2 ng cDNA. Annealing temperature was 60ºC and reactions with increasing concentrations of MgCl2 (2-3.5 mM) were prepared to optimise MgCl2 concentration for ABCG2 qPCR. Efficiency curves were generated for each of the PCRs and qPCR amplification efficiencies were calculated from these efficiency curves for each MgCl2 concentration.

3.5 mM MgCl2

Chapter 4

98

Figure 4.3: ABCG2 mRNA levels in DHT and cyclopamine treated MCF-7 cells. ABCG2 mRNA levels were quantitated by RT-qPCR in RNA isolated from MCF-7 cells following 24 h of treatment with 10-8 M DHT, 2 μM cyclopamine, 10-8 M DHT and 2 µM cyclopamine, or 0.1% (v/v) ethanol (vehicle control). Expression of ABCG2 was normalised to corresponding levels of β-actin. Duplicate samples were prepared in each experiment and results are expressed as mean ± S.E.M. of normalised ABCG2 mRNA levels from at least 3 independent experiments. Statistical significance relative to controls was calculated using the Mann-Whitney U test, *p<0.05.

0

0.2

0.4

0.6

0.8

1

1.2

Control 10-8M DHT 2µMCyclopamine

10-8M DHT +2µM

Cyclopamine

Nor

mal

ised

AB

CG

2 m

RN

A L

evel

s

Treatment (24hrs)

* *

10-8 M DHT + 2 µM

Cyclopamine

2 µM Cyclopamine

10-8 M DHT Control

Chapter 4

99

(A)

(B) (i)

Day

10-8 M DHT

0 1 2 4 6 8

00.20.40.60.8

11.2

0 1 2 4 6 8Nor

mal

ised

AB

CG

2 Pr

otei

n L

evel

s

Days

ABCG2 (70 kDa)

β-actin (44 kDa)

~70 kDa ~46 kDa

~7 kDa

1:500 ABCG2

1:750 ABCG2

1:1000 ABCG2

~40 kDa

Chapter 4

100

(ii)

(iii)

Figure 4.4: DHT and cyclopamine regulation of ABCG2 protein levels. (A) ABCG2 immunoblotting was optimised using whole cell lysates from MCF-7 and T-47D cells and increasing concentrations of ABCG2 antibodies. (B) ABCG2 protein levels in MCF-7 cells following 8 days of treatment with (i) 10-8 M DHT, (ii) 2 µM cyclopamine or (iii) 10-8 M DHT and 2 µM cyclopamine were determined by immunoblotting, with levels normalised against β-actin blots for each sample. Experiments were repeated three times and representative blots are shown.

0 1 2 4 6 8

2 μM Cyclopamine

Day

00.20.40.60.8

11.21.4

0 1 2 4 6 8Nor

mal

ised

AB

CG

2 Pr

otei

n L

evel

s

Days

ABCG2 (70 kDa)

β-actin (44 kDa)

0 1 2 4 6 8

10-8 M DHT + 2 μM Cyclopamine

Day

00.20.40.60.8

11.2

0 1 2 4 6 8

Nor

mal

ised

AB

CG

2 Pr

otei

n L

evel

s

Days

ABCG2 (70 kDa)

β-actin (44 kDa)

Chapter 4

101

ABCG2 localisation at the plasma membrane indicates comparatively decreased

ABCG2 efflux activity. To investigate DHT and cyclopamine effects on the intracellular

localisation of ABCG2, immunofluorescence microscopy was used to localise ABCG2

in situ. For these studies, primary and secondary antibodies for detection of ABCG2

were optimised using immunofluorescence microscopy, with (background) signals from

cells stained with Alexafluor® 488-conjugated anti-mouse secondary antibodies (no

primary antibody) dull in contrast to the higher non-specific signals from the

Alexafluor® 546-conjugated anti-mouse secondary antibodies (Figure 4.5A). Therefore,

secondary antibodies conjugated with Alexafluor® 488 were used for detection of

ABCG2 intracellular localisation.

To determine the optimum concentration of the ABCG2 primary antibody (BXP-21

clone) for immunofluorescence microscopy, MCF-7 cells were immunostained with

either 1:750 or 1:500 dilutions of the ABCG2 antibody and Alexafluor® 488-conjugated

anti-mouse secondary antibodies (Section 3.3). At the 1:750 dilution of ABCG2

antibody, staining was weak and the localisation of ABCG2 was unclear in these cells

(Figure 4.5B). In contrast, at a 1:500 dilution of the ABCG2 antibody, diffuse ABCG2

immunoreactivity was observed in the nucleus and cytoplasm of cells, with strong

ABCG2 signals accumulating in cell-to-cell membrane junctions (yellow arrows) as

well as in round vesicles (red arrows) in the cytoplasm of cells (Figure 4.5B). A 1:500

dilution of ABCG2 antibody was used for subsequent immunofluorescence microscopy

studies. To further investigate ABCG2 localisation in MCF-7 cells and to verify its

apparent nuclear and cytoplasmic localisation, subcellular fractionation was performed

(Section 3.6). For these studies, proteins were isolated from nuclear and cytoplasmic

fractions of MCF-7 cells as well as the residual cell pellet, which would contain proteins

from the cell membrane, and ABCG2 protein levels were evaluated by western blotting

(Section 3.6, 3.7). ABCG2 protein bands at ~70 kDa were detected in nuclear and

membrane fractions of MCF-7 cells (Figure 4.6). In contrast, ~70 kDa ABCG2-

immunoreactive bands were not observed in cytoplasmic fractions, although diffuse

cytoplasmic ABCG2 staining had been detected by immunofluorescence microscopy

(Figure 4.5, 4.7). Detection of ABCG2 signals at lower molecular weights in all

fractions may indicate protein cleavage or degradation occurring during processing for

these studies or as a normal part of the intracellular turnover of ABCG2. The clear

selectivity of histone H3 and α-tubulin in nuclear and cytoplasmic fractions,

respectively, indicated lack of cross-contamination of these proteins, while detection of

Chapter 4

102

histone H3 in membrane fractions suggested that not all nuclei were ruptured under

these conditions (Figure 4.6). However overall, results of these experiments supported

initial findings from analysis of the intracellular localisation of ABCG2 using

immunofluorescence microscopy. Further studies will be required to determine whether

the ABCG2-containing cytoplasmic vesicles would be ruptured in the buffers used, or

whether they would remain intact and their contents collected in the final membrane

fractions.

As the downregulation of ABCG2 protein levels induced by DHT and the combination

of DHT and cyclopamine treatments of MCF-7 cells was evident at day 4 of the

treatments, DHT and cyclopamine regulation of the intracellular localisation of ABCG2

was assessed following treatment of MCF-7 cells with 10-8 M DHT and/or 2 µM

cyclopamine for 0-4 days (Section 3.3). In control MCF-7 cultures treated with vehicle

(0.1% (v/v) ethanol) alone, strong accumulation of ABCG2 signals in cell-to-cell

junction complexes (yellow arrows) and in round cytoplasmic vesicles (red arrows) was

evident, with the marker of filamentous actin (F-actin), Phalloidin Red shown to co-

localise with the ABCG2+ve cell-to-cell junction complexes as well as ABCG2-

containing cytoplasmic vesicles, in particular around the edges of these vesicles (Figure

4.7). In MCF-7 cultures treated with 10-8M DHT, ABCG2 staining in cell-to-cell

junction complexes as well as in cytoplasmic vesicles was diminished and these results

were similarly observed in DHT/cyclopamine co-treated cells, suggesting that DHT and

the combination of DHT and cyclopamine reduced ABCG2 function at the membrane

(Figure 4.7). In MCF-7 cells treated with 2µM cyclopamine, ABCG2-associated cell-to-

cell junction complexes decreased but interestingly, cyclopamine induced ABCG2

accumulation in cytoplasmic vesicles, indicating that cyclopamine may also be reducing

ABCG2 efflux function but via a distinct mechanism (Figure 4.7).

4.2.5 DHT and Cyclopamine Effects on ABCG2 Protein Degradation

Degradation or turnover of proteins is critical for clearing of mis-folded or damaged

proteins as well as for controlling the cellular content of proteins. The two most

common protein degradation pathways in humans are the ubiquitin/proteasome system

and the lysosomal pathway. The large cytoplasmic ABCG2-containing vesicles in

MCF-7 cells that co-localised with F-actin closely resembled aggresomes (Wakabayashi

et al 2007) (Figure 4.7). Following events such as non-rapid clearing of proteins or

Chapter 4

103

(A)

(B)

Hoechst 33258 (blue) Merge Alexafluor® 488 (green)

Alexafluor® 546 (red) Hoechst 33258 (blue) Merge

ABCG2 (green)

Hoechst 33258 (blue)

ABCG2 + Hoechst 33258

1:750 ABCG2 1:500 ABCG2

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104

Figure 4.5: Optimisation of primary and secondary antibody concentrations for investigation of ABCG2 intracellular localisation by immunofluorescence microscopy. (A) MCF-7 cells cultured on coverslips were immunostained with 1:400 Alexafluor® 488 (green) or 1:400 Alexafluor® 546 (red) labelled anti-mouse secondary antibodies. (B) ABCG2 primary antibody was tested at concentrations of 1:750 or 1:500, which was detected using 1:400 Alexafluor® 488 (green) labelled anti-mouse secondary antibodies. Cell nuclei were stained with Hoechst 33258 (blue) and immunostaining was evaluated using a Nikon Eclipse Ti-e fluorescence microscope. Scale bar: 30 µm. Yellow and red arrows indicate ABCG2 signals in cell-to-cell junction complexes and in round cytoplasmic vesicles, respectively.

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Figure 4.6: Intracellular localisation of ABCG2 in MCF-7 cells. Proteins isolated from the cell membrane, cytoplasm and nuclear fractions of MCF-7 cell lysates were immunoblotted for ABCG2. α-tubulin and histone H3 western blots were used as loading controls for cytoplasmic and nuclear proteins, respectively. Representative blots are shown.

Lanes 1 and 2: MCF-7 (nuclear fraction) Lanes 3 and 4: MCF-7 (cytoplasmic fraction) Lanes 5 and 6: MCF-7 (membrane fraction) Lane 7: MCF-7 whole cell lysate

Histone H3 (15 kDa)

ABCG2 (~70kDa)

α-tubulin (52 kDa)

~46 kDa ~58 kDa

~35 kDa

1 2 3 4 5 6 7

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106

10-8 M DHT

2 µM Cyclopamine

10-8 M DHT + 2 µM

Cyclopamine

ABCG2 (green) F-actin (red) ABCG2 + F-actin +

Hoechst 33258

Vehicle Control

(0.1% (v/v) ethanol)

Negative Control

(no 1º Ab)

ABCG2 (green) Hoechst 33258 (blue) ABCG2 + Hoechst 33258

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107

Figure 4.7: Effects of DHT and cyclopamine on the intracellular localisation of ABCG2 in MCF-7 cells. MCF-7 cells grown on coverslips were treated with 10-8 M DHT, 2 μM cyclopamine or 10-8 M DHT + 2 μM cyclopamine for 4 days, then immunostained with ABCG2 primary and Alexafluor® 488-conjugated anti-mouse secondary antibodies. Filamentous actin (F-actin, red) and nuclei (blue) were stained with Phalloidin Red and Hoechst 33258, respectively. Negative controls were stained with secondary antibodies alone. ABCG2 accumulated in cell-to-cell junction complexes (yellow arrow) and in round cytoplasmic vesicles (red arrow) in MCF-7 cells. Experiments were repeated three times and representative results are shown. Scale bar: 30 µm.

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108

inhibition of degradation pathways including the proteasome, proteins that are tagged

for degradation can accumulate into aggregates or aggresomes (Garcia-Mata et al 2002,

Zaarur et al 2014). As such, it was feasible that the large cytoplasmic ABCG2-

containing vesicles may be associated with degradation of ABCG2 proteins. In initial

studies, proteasomal degradation of ABCG2 was investigated using the proteasome

inhibitor, MG132.

To optimise MG132 treatment of MCF-7 cells, cultures were treated with increasing

concentrations of 1-3 µM MG132 for 6, 8 or 24 h prior to collection of cell lysates for

ABCG2 immunoblotting (Figure 4.8). These concentrations of MG132 did not induce

marked cell death in cultures at all timepoints tested. After 6 and 8 h of MG132

treatment, normalised ABCG2 levels were similar to those in untreated controls (1.1 to

1.4 fold) and similarly at 24 h, ABCG2 levels were 0.9 to 1.1 fold of those in control

cultures (Figure 4.8). These data indicated that the proteasome may not be involved in

the degradation of endogenous ABCG2 protein, and are in agreement with previous

reports indicating that only mutant or mis-folded ABCG2 proteins lacking disulphide

bonds are preferentially degraded by the proteasome (Wakabayashi et al 2007). To

investigate involvement of the proteasome in the regulation of ABCG2 levels in DHT

and cyclopamine treated MCF-7 cells, cultures were pre-treated with 10-8 M DHT

and/or 2 µM cyclopamine for 2 days, which reduced ABCG2 protein levels (Figure 4.4)

prior to addition of 2 µM MG132 to the cultures for 6 h. In support of results obtained

during optimisation of MG132 treatment of cells (Figure 4.8), ABCG2 protein levels

were not altered in vehicle control cultures (0.1% (v/v) ethanol) following addition of

MG132 (Figure 4.9). Similarly, in cyclopamine-treated MCF-7 cells, in which ABCG2

protein expression was ~1.28 fold that in controls, MG132 treatment decreased these

levels by ~20%. In comparison to controls, DHT and the combination of DHT and

cyclopamine reduced ABCG2 protein levels by ~15% and ~40%, respectively, and

treatment of these cells with MG132 further decreased ABCG2 levels in DHT-treated

cells by ~10% but increased ABCG2 protein levels by 36% in cells co-treated with

DHT and cyclopamine (Figure 4.9). These results showed only modest effects of

proteasomal inhibition of ABCG2 protein levels and in addition were difficult to

reproduce in replicate experiments.

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Degradation of proteins via the lysosomal pathway involves fusion of proteins or

protein-containing organelles such as the endosomes and autophagosomes by the

lysosomes, in which proteins are degraded by acid hydrolases (Dunn 1990, Alberts et al

2002). Several lines of evidence indicate that lysosomes are recruited to and degrade

proteins in aggresomes (Iwata et al 2005a, Iwata et al 2005b, Zaarur et al 2014). To

investigate whether ABCG2 degradation involves the lysosomal pathway, regulation of

ABCG2 protein expression by the lysosome inhibitor, chloroquine was assessed. To

optimise chloroquine concentration and duration of treatment, MCF-7 cells that had

been treated with the combination of 10-8 M DHT and 2 µM cyclopamine for 4 days

were cultured with 25 µM, 50 µM or 100 µM chloroquine for 6, 24 and 48 h prior to

lysis of the cells for immunoblotting. Minimal cell toxicity or cell death was observed in

cultures treated with the lowest concentration of chloroquine (25 µM), which led to a

gradual increase in ABCG2 protein levels that were initially downregulated by ~80%

(compared to vehicle controls) following 4 days of DHT and cyclopamine co-treatment

of MCF-7 cells (Figure 4.10A). After addition of chloroquine to DHT and cyclopamine-

treated cultures for 48 h, ABCG2 protein was restored to levels that were similar to

vehicle/untreated controls. This result was in agreement with a previous study which

showed that ABCG2 is predominantly degraded by the lysosomal pathway

(Wakabayashi et al 2007). At the higher concentration of 50 µM chloroquine, ABCG2

protein levels were progressively decreased in cultures that had been pre-treated with

DHT and cyclopamine, with levels reduced to ~13% of vehicle controls at the 48 h

timepoint (Figure 4.10B). In cultures treated with highest concentration of chloroquine

(100 µM), changes in ABCG2 protein expression after 48 h of chloroquine treatment

were not able to be assessed as the extensive cell death and detachment of cells from the

culture surface resulted in low protein yields. At 6 and 24 h post addition of 100 µM

chloroquine to the cultures, ABCG2 levels were comparable to levels observed in cells

treated with DHT and cyclopamine alone (Figure 4.10B).

Chloroquine treatment of control (vehicle-treated) MCF-7 cells increased ABCG2

protein levels by up to 1.6-1.7-fold after 24 h but these levels declined following

treatment with 25 µM chloroquine for 48 h, potentially due to non-specific cytotoxicity

induced by lysosomal inhibition for this length of time (Figure 4.11A). In MCF-7

cultures pre-treated for 4 days with DHT and the combination of DHT and cyclopamine,

ABCG2 levels were decreased by 35% and 45%, respectively, a result similar to

previous findings (Figure 4.4, 4.11B, 4.11D). Addition of 25 µM chloroquine to DHT-

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110

treated cultures led to the progressive reduction of ABCG2 levels, with ABCG2 protein

levels decreased by 72% compared to vehicle controls after 48 h (Figure 4.11B). In

DHT and cyclopamine co-treated cells, ABCG2 protein levels were further reduced at 6

and 24 h post addition of chloroquine but by 48 h, up to ~2-fold increases in these levels

were observed (Figure 4.11D). Similar to DHT-treated cells, 25 µM chloroquine

treatment of cyclopamine-treated MCF-7 cells gradually decreased ABCG2 protein

levels during 48 h of co-culture (Figure 4.11C). Although these findings suggested

involvement of the lysosome in regulation of ABCG2 levels, results were again difficult

to reproduce, potentially due to toxicity of chloroquine in MCF-7 cells.

To further investigate these findings, intracellular localisation of the ABCG2-containing

cytoplasmic vesicles and the lysosomes, which were stained by Lysotracker Red, was

evaluated by immunofluorescence microscopy. Optimisation of the concentration and

duration of Lysotracker Red staining was carried out by incubating MCF-7 cells with 50

nm or 100 nm Lysotracker Red for 10, 20 or 30 minutes prior to fixation and

preparation of cells for immunofluorescence microscopy (Section 3.3). Punctate

staining of Lysotracker Red in the cell cytoplasm was evident after 10 and 20 minutes

of incubation of MCF-7 cells with 50 nM Lysotracker Red (Figure 4.12A). Similar

punctate staining was observed in cultures incubated with 100 nM Lysotracker Red for

10 minutes although the intensity of Lysotracker Red was stronger in these cultures

compared to those incubated with 50 nM Lysotracker Red (Figure 4.12A, 4.12B).

Prolonged incubation of the cells with Lysotracker Red resulted in formation of

Lysotracker Red-containing aggregates, which may indicate over-staining of the cells

(Figure 4.12A, 4.12B). For subsequent studies, cells were stained for 20 minutes with

50 nM Lysotracker Red.

To investigate whether the ABCG2-containing cytoplasmic vesicles co-localise with the

lysosomes, 50 nM Lysotracker Red was added for 20 minutes to MCF-7 cultures pre-

treated with 0.1% (v/v) ethanol (vehicle control) or 2 µM cyclopamine for 4 days which

was previously shown to induce accumulation of ABCG2 into cytoplasmic vesicles

(Figure 4.7). In both the vehicle control and cyclopamine-treated MCF-7 cells, co-

localisation of ABCG2 signals, especially in ABCG2-containing cytoplasmic vesicles,

and Lysotracker Red was not observed (Figure 4.12C), thereby indicating that ABCG2

in the vesicles did not fuse to lysosomes for lysosomal degradation.

Chapter 4

111

(A)

(B)

(C)

β-actin (44 kDa)

ABCG2 (70 kDa)

0 1 2 3 MG132 (µM)

6 h

00.20.40.60.8

11.2

0 1 2 3Nor

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AB

CG

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[MG132] (µM)

β-actin (44 kDa)

ABCG2 (70 kDa) 0 1 2 3 MG132 (µM)

8 h

00.20.40.60.8

11.21.4

0 1 2 3Nor

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AB

CG

2 Pr

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s

[MG132] (µM)

β-actin (44 kDa) ABCG2 (70 kDa)

0 1 2 3 MG132 (µM)

24 h

00.20.40.60.8

11.2

0 1 2 3Nor

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AB

CG

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[MG132] (µM)

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112

Figure 4.8: Optimisation of experimental conditions for treatment of MCF-7 cells with the proteasome inhibitor, MG132. MCF-7 cells cultured in 6-well plates were treated with increasing concentrations of MG132 (1-3 µM) for (A) 6, (B) 8 or (C) 24 h and cell lysates were collected for western blotting. ABCG2 protein levels were normalised to corresponding β-actin levels and expressed as a ratio of ABCG2 levels in untreated MCF-7 cells (0 µM MG132). Experiments were repeated three times and representative blots are shown.

Chapter 4

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(A)

(B)

(C)

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11.2

Nor

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AB

CG

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s Treatment

β-actin (44 kDa)

ABCG2 (70 kDa)

- + MG132 (2 µM)

Vehicle Control

Vehicle Control

β-actin (44 kDa)

ABCG2 (70 kDa)

- + MG132 (2 µM)

DHT (2 days)

00.20.40.60.8

11.2

Nor

mal

ised

AB

CG

2 Pr

otei

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evel

s

Treatment

β-actin (44 kDa)

ABCG2 (70 kDa)

- + MG132

Cyclopamine (2 days)

Vehicle Control

00.20.40.60.8

11.21.4

Nor

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AB

CG

2 Pr

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evel

s

Treatment

Chapter 4

114

(D)

Figure 4.9: MG132 effects on the regulation of ABCG2 protein in DHT and cyclopamine treated MCF-7 cells. MCF-7 cells cultured for 2 days with (A) 0.1% (v/v) ethanol (vehicle control), (B) 10-8 M DHT, (C) 2 µM cyclopamine or (D) 10-8 M DHT and 2 µM cyclopamine were treated for 6 h with 2 µM MG132 prior to protein isolation and ABCG2 immunoblotting. ABCG2 protein levels were normalised to β-actin levels and expressed as a proportion of normalised ABCG2 protein levels in controls. Experiments were repeated at least three times and representative results are shown.

β-actin (44 kDa)

ABCG2 (70 kDa)

- + MG132 (2 µM)

DHT + Cyclopamine

(2 days) Vehicle Control

00.20.40.60.8

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AB

CG

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Treatment

Chapter 4

115

00.20.40.60.8

11.21.4

Nor

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AB

CG

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Treatment

00.20.40.60.8

11.2

Nor

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AB

CG

2 Pr

otei

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s

Treatment

(A)

(B)

ABCG2 (70 kDa)

β-actin (44 kDa)

24h 48h Vehicle Control

DHT + Cyclopamine (4 days)

6h 0h

100 µM Chloroquine

ABCG2 (70 kDa)

β-actin (44 kDa)


6h 24h 24h 48h Vehicle Control

50 µM Chloroquine

6h 0h

25 µM Chloroquine

Chapter 4

116

Figure 4.10: Treatment of MCF-7 cells with the lysosome inhibitor, chloroquine. MCF-7 cells were cultured with ethanol (0.1% (v/v), vehicle control) or a combination of 10-8

M DHT and 2 µM cyclopamine for 4 days. At 6, 24 and 48 h prior to harvesting of the cells, (A) 25 µM, (B) 50 µM or 100 µM chloroquine was added to the cultures. Due to chloroquine-induced cytotoxicity, cells were treated with 100 µM chloroquine for 6 and 24 h only. ABCG2 protein levels determined by immunoblotting were normalised against β-actin immunoblots for each lane and compared to ABCG2 protein levels in vehicle-treated controls. Experiments were repeated at least three times and representative blots are shown.

Chapter 4

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00.20.40.60.8

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AB

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0.8

1

1.2

Nor

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AB

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Treatment

(A)

(B)

(C)

β-actin (44 kDa)

ABCG2 (70 kDa)

- Chloroquine (25 µM)

Vehicle Control

24h 6h 48h

00.20.40.60.8

11.21.41.61.8

Nor

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AB

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Treatment

β-actin (44 kDa)

ABCG2 (70 kDa)

Vehicle Control - Chloroquine (25 µM)

Cyclopamine (4 days)

24h 6h 48h

β-actin (44 kDa) ABCG2 (70 kDa)


DHT (4 days)

24h 6h

h

48h

Chapter 4

118

(D)

Figure 4.11: Effects of lysosomal inhibition on DHT and cyclopamine induced regulation of ABCG2 protein levels. MCF-7 cells were pre-treated for 4 days with (A) 0.1 (v/v) ethanol (vehicle control), (B) 10-8 M DHT, (C) 2 µM cyclopamine or (D) 10-8

M DHT + 2 µM cyclopamine prior to addition of 25 µM chloroquine for 6, 24 and 48 h and protein extraction for immunoblotting. ABCG2 protein levels were normalised to β-actin and expressed as a proportion of ABCG2 protein levels in vehicle treated controls. Experiments were repeated at least three times and representative results are shown.

0

0.2

0.4

0.6

0.8

1

1.2

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AB

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β-actin (44 kDa)

ABCG2 (70 kDa)



24h 6h 48h

Chapter 4

119

(A)

(B)

Lysotracker Red Hoechst 33258 (blue) Merge

10 min

20 min

30 min

Lysotracker Red Hoechst 33258 (blue) Merge

10 min

20 min

30 min

Chapter 4

120

(C)

Figure 4.12: Intracellular co-localisation of ABCG2 and lysosomes. To optimise use of the lysosomal marker, Lysotracker Red, MCF-7 cells cultured on glass coverslips were incubated with (A) 50 nM or (B) 100 nM Lysotracker Red for 10, 20 or 30 minutes. (C) MCF-7 cells pre-treated for 4 days with 0.1% (v/v) ethanol (vehicle control) or 2 µM cyclopamine were incubated with 50 nM Lysotracker Red for 20 minutes, then immunostained for ABCG2 (green). Cell nuclei (blue) were stained using Hoechst 33258. Coverslips were viewed by immunofluorescence microscopy. Scale bar: 30 µm.

Lysotracker Red ABCG2 (green) Lysotracker Red/

ABCG2/Hoechst 33258

Vehicle Control

2 µM Cyclopamine

(4 days)

Chapter 4

121

Interestingly, the punctate staining of Lysotracker Red was found to be in close

proximity around the ABCG2 cytoplasmic vesicles (Figure 4.12C). A similar

localisation of the lysosomes around aggresomes has been reported in previous studies

(Korolchuk et al 2011, Zaarur et al 2014) and was crucial for lysosomal-mediated

degradation of proteins in the aggresomes. Based on the findings reported previously

(Korolchuk et al 2011, Zaarur et al 2014), clustering of Lysotracker Red around the

ABCG2-containing cytoplasmic vesicles indicate that proteins in these vesicles

including ABCG2 may be degraded by the lysosomes.

4.2.6 DHT and Cyclopamine Regulation of ABCG2 Efflux Activity

The amino acid at position 482 in the third transmembrane domain (TMD3) of ABCG2

protein plays a critical role in ABCG2 efflux activity and specificity for export of

substrates including the fluorescent molceules, Rhodamine 123 and mitoxantrone

(Honjo et al 2001, Robey et al 2003, Ejendal et al 2006). A base substitution resulting

in changes from arginine of wild-type ABCG2, to glycine (Gly482) or threonine (Thr482)

in ABCG2 variants increases the specificity of ABCG2 for Rhodamine 123 and

mitoxantrone efflux, while ABCG2 with arginine at position 482 preferentially exports

mitoxantrone (Honjo et al 2001). That study identified that ABCG2 (Arg482) in parental

MCF-7 cells, but showed that MCF-7 cells selected for resistance to adriamycin and

verapamil (MCF-7/AdVp3000) expressed ABCG2 with Thr482 (Honjo et al 2001).

To determine ABCG2 sequence in the MCF-7 cells used for these studies, the ABCG2

coding sequence was analysed by Sanger sequencing (Section 3.9). Sequencing of the

PCR products indicated that arginine (Arg), encoded by “AGG” (positions 1792 to 1794

of the coding sequence) was present at position 482 of the ABCG2 amino acid sequence

(Figure 4.13B). According to findings published by Honjo and colleagues, these cells

would preferentially export mitoxantrone in comparison to Rhodamine 123 (Honjo et al

2001). This was confirmed by measurement of export of the ABCG2 substrates,

Rhodamine 123 and mitoxantrone from MCF-7 cells by flow cytometric analysis of

intracellular levels of the fluorescent substrates (Section 3.4).

In these experiments, forward scatter (FSC) and side scatter (SSC) plots were used for

gating the MCF-7 cell population (Figure 4.14), from which viable MCF-7 cells were

identified by exclusion of 7-aminoactinomycin D (7-AAD), a marker that binds to non-

Chapter 4

122

viable cells. Background fluorescence was estimated using negative controls consisting

of MCF-7 cells which had not been incubated with mitoxantrone or Rhodamine 123 and

was used to differentiate background signals in cell populations that had been incubated

with mitoxantrone or Rhodamine 123 (Figure 4.14). Fluorescence signals of the

ABCG2 substrates (Rhodamine 123 and mitoxantrone) in the viable cells were gated in

7-AAD vs mitoxantrone plots (Figure 4.14), results of which were used to construct

histograms quantitating of the mean fluorescence intensity (MFI) of mitoxantrone or

Rhodamine 123 (Figure 4.14).

To evaluate the export rate of Rhodamine 123 and mitoxantrone from MCF-7 cells,

cells were incubated with 0.5 µg/mL Rhodamine 123 or 0.5, 1 and 5 µM mitoxantrone

for 60 minutes to allow passive diffusion of the molecules into the cells. Cultures were

then incubated in substrate-free medium (efflux phase) for a further 1-24 h, during

which export of substrates was monitored by determining the remaining intracellular

fluorescence levels of the substrates (Section 3.4). After 2, 4 and 18 h, no marked

changes were observed for Rhodamine 123 mean fluorescent intensities (MFIs) in

comparison to Rhodamine 123 fluorescence at time 0 of the efflux phase, with

Rhodamine 123 MFI increased slightly by 2.7-3.3% after 2 and 4 h of efflux and

decreased by 1.6% after 18 h (Figure 4.15). Prolonged culture of the cells (24 h) led to

reduction of Rhodamine 123 fluorescent intensity by 27%, indicating that the efflux of

Rhodamine 123 from MCF-7 cells was weak, a result that is in line with previous

findings (Figure 4.15) (Honjo et al 2001). In contrast, export of mitoxantrone from

MCF-7 cells was more evident and the mean fluorescence intensity of mitoxantrone was

decreased by ~25% following 1 h of efflux in cells which were pre-incubated with 0.5

µM and 5 µM mitoxantrone. In cells incubated with 1 µM mitoxantrone, mitoxantrone

fluorescence levels were reduced by ~34% after 1 h of mitoxantrone efflux (Figure

4.16).

To investigate DHT and cyclopamine effects on ABCG2 efflux activity, MCF-7

cultures that had been pre-treated with 10-8 M DHT, 2 µM cyclopamine or 10-8 M DHT

+ 2 µM cyclopamine for 8 days were incubated with 1 µM mitoxantrone for 60 minutes.

Cells were then cultured for 60 minutes in mitoxantrone-free medium, during which

intracellular mitoxantrone mean fluorescence intensity (MFI) was quantitated every 15

minutes by flow cytometry (Section 3.4). In vehicle control treated MCF-7 cells,

Chapter 4

123

(A)

(B)

61 AAAACTGTTATCTGATTTATTACCCATGAGGATGTTACCAAGTATTATATTTACCTGTAT 120

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

1764 AAAACTGTTATCTGATTTATTACCCATGAGGATGTTACCAAGTATTATATTTACCTGTAT 1823

Figure 4.13: ABCG2 exon 12 cDNA sequence in MCF-7 cells. (A) mRNA extracted from MCF-7 cells was reverse transcribed, ABCG2 exons 11 to 13 were PCR-amplified and PCR products were electrophoresed in a 2% agarose gel. (B) Purified ABCG2 PCR products were sequenced by Sanger sequencing, which identified that codon 482 in exon 12, AGG, would encode arginine.

Arginine

~150 bp

Chapter 4

124

(A) (i)

SSC

FSC

MCF-7

Mitoxantrone (MX) Fluorescence

7-AA

D F

luor

esce

nce

MX+ve/7-AAD-ve

MX-ve/7-AAD-ve

MX-ve/7-AAD+ve

(ii)


7-AA

D F

luor

esce

nce

MX+ve/7-AAD-ve

(iii)

Cou

nt


MX+ve/7-AAD-ve

(iv)

Chapter 4

125

Figure 4.14: Flow cytometric analysis of intracellular levels of the ABCG2 substrates, (A) mitoxantrone (MX) and (B) Rhodamine 123 (Rhd123) in MCF-7 cells. MCF-7 cells were incubated with 1µM mitoxantrone or 0.5 µg/mL Rhodamine 123 for 60 minutes prior to trypsinisation and staining with the cell viability marker, 7-AAD. (i) Forward (FSC) and side scatter (SSC) plots were used to identify the MCF-7 cell population. (ii) Background fluorescence was determined from MCF-7 cells that had not been incubated with mitoxantrone or Rhodamine 123 (iii) 7-AAD vs MX or 7-AAD vs Rhd123 plots were constructed to detect mitoxantrone (MX+ve/7-AAD-ve) or Rhodamine 123 (Rhd123+ve/7-AAD-ve) fluorescence signals in viable cells. (iv) MX or Rhd123 mean fluorescence intensity (MFI) was quantitated from corresponding fluorescence histograms.

SSC

FSC

MCF-7

(B) (i)

7-AA

D F

luor

esce

nce

Rhodamine123 Fluorescence

Rhd123+ve/7-AAD-ve

Rhd123-ve/7-AAD-ve

Rhd123-ve/7-AAD+ve

(ii) 7-

AAD

Flu

ores

cenc

e

Rhodamine 123 Fluorescence

Rhd123+ve/7-AAD-ve

(iii)


Cou

nt Rhd123+ve/7-AAD-ve

(iv)

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126

(A)

(B)

(C)

Cou

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Efflux (0h) Efflux (2h)

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Mea

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Chapter 4

127

(D) Figure 4.15: Efflux of Rhodamine 123 from MCF-7 cells. MCF-7 cells were incubated with 0.5 µg/mL Rhodamine 123 for 60 minutes and Rhodamine 123 mean fluorescence intensity (MFI) of cells was evaluated by flow cytometry at 0 h (Efflux (0h)) or following a further (A) 2, (B) 4, (C) 18 or (D) 24 h of culture in Rhodamine 123-free culture medium. Rhodamine 123 MFI (%) was expressed as a proportion of Rhodamine 123 fluorescence at 0 h of efflux. Experiments were repeated at least three times and representative results are shown.

Cou

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128

(A)

(B)

(C)

0.5 µM Mitoxantrone

0

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120


Mito

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(MFI

) (%

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1 µM Mitoxantrone

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)

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Mito

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Mea

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(MFI

) (%

)

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5 µM Mitoxantrone


Chapter 4

129

Figure 4.16: Optimisation of mitoxantrone concentration for investigation of ABCG2 efflux activity. MCF-7 cells were incubated with (A) 0.5 µM, (B) 1 µM or (C) 5 µM mitoxantrone for 60 minutes and mitoxantrone mean fluorescence intensity (MFI) was evaluated by flow cytometry at time 0 or following a further 60 minutes of incubation in mitoxantrone-free medium. Mitoxantrone MFI (%) was expressed as a proportion of mitoxantrone fluorescence at 0 h of efflux. Experiments were repeated at least three times and representative results are shown.

Chapter 4

130

020406080

100120

0 15 30 45 60

Mito

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Mea

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(MFI

), %

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Vehicle Control

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Figure 4.17: DHT and cyclopamine effects on the efflux rate of mitoxantrone from MCF-7 cells. MCF-7 cells which were pre-treated for 8 days with 0.1% (v/v) ethanol (vehicle control), 10-8 M DHT, 2 µM cyclopamine or the combination of 10-8 M DHT and 2 µM cyclopamine were incubated with 1 µM mitoxantrone for 60 minutes then cultured for a further 60 minutes in mitoxantrone-free culture medium during which mitoxantrone fluorescence was evaluated every 15 minutes (0, 15, 30, 45 and 60 minutes). Mitoxantrone mean fluorescence intensity (MFI) (%) was plotted as a ratio of mitoxantrone MFI at time 0 of efflux. Experiments were repeated at least seven times and the mean results ± S.E.M. are shown. Statistical significance relative to controls was calculated using the Mann-Whitney U test, *p<0.05.

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EtOHDHTCyclopamineDHT+Cyclopamine

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*

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mitoxantrone MFI was progressively decreased to ~80% and ~61% of MFI at time 0

after 15 and 60 minutes, respectively (Figure 4.17). In cells which were pre-treated with

DHT, cyclopamine and the combination of DHT and cyclopamine, the decrease in

mitoxantrone MFI during the 60 minute efflux period was reduced compared to

controls, with intracellular mitoxantrone fluorescence decreased to 94-98% after 15

minutes and 71-75% after 60 minutes (Figure 4.17). These results indicated that DHT

and cyclopamine treatments delayed the export rate of the ABCG2 substrate,

mitoxantrone from MCF-7 cells.

4.2.6.1 DHT and Cyclopamine Effects on the Sensitivity of MCF-7 Cells to

Mitoxantrone

The chemotherapeutic agent, mitoxantrone is a cytotoxic drug which inhibits the

proliferation of rapidly dividing cells by intercalating DNA (Varadwaj et al 2010). As

flow cytometric analyses showed that the efflux of mitoxantrone from MCF-7 cells was

delayed in cells treated with DHT and/or cyclopamine, resulting in higher intracellular

levels of mitoxantrone (Figure 4.17), the responsiveness of cells to mitoxantrone and its

associated cytotoxicity was investigated using MTS viability assays (Section 3.2). For

these studies, a standard curve of cell number against absorbance values of formazan

(490 nm), a soluble dye formed from MTS by viable cells, was constructed in order to

extrapolate cell numbers in experimental culture wells (Figure 4.18).

To investigate DHT and cyclopamine regulation of mitoxantrone cytotoxicity in MCF-7

cells, cells were pre-treated with 10-8 M DHT, 2 µM cyclopamine or 10-8 M DHT + 2

µM cyclopamine for 8 days, then increasing concentrations of mitoxantrone (0.0001-10

µM) were added to the cultures. After 4 days, cell viability estimated using MTS assays

was used to construct mitoxantrone dose-response curves, from which the IC50 values

for mitoxantrone, or the concentration of mitoxantrone that caused 50% inhibition of

cell proliferation, were extrapolated (Section 3.2). The IC50 value for mitoxantrone in

vehicle control (0.1% (v/v) ethanol) MCF-7 cultures was 1.388 µM (Figure 4.19).

Treatment of cells with 10-8 M DHT led to a minor effect on the IC50 values for

mitoxantrone which decreased by ~8% compared to the vehicle control. In contrast, in

cells treated with 2 µM cyclopamine and the combination of DHT and cyclopamine,

mitoxantrone IC50 values were significantly reduced by ~70% compared to the vehicle

control (Figure 4.19). These results indicated that cyclopamine and the combination of

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132

Figure 4.18: Standard curve for MTS proliferation assays. Increasing densities of MCF-7 cells (250 to 30,000 cells) were cultured overnight and cell numbers were quantitated using a CellTiter 96® AQueous One Solution Kit which measures the absorbance of formazan at 490 nm. A standard curve of the average absorbance values from quadruplicate wells (± S.E.M.) against cell seeding densities was constructed, with a trend line fitted through the values. The assay was repeated three times and representative results are shown.

y = 6E-05x + 0.1038 R² = 0.9736

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(A)

(B)

Figure 4.19: Sensitivity of MCF-7 cells to mitoxantrone following treatment with DHT and cyclopamine. MCF-7 cells pre-treated with 0.1% (v/v) ethanol (vehicle control), 10-

8 M DHT, 2 μM cyclopamine or 10-8 M DHT + 2 µM cyclopamine for 4 days were incubated with increasing concentrations of mitoxantrone (0-10 μM) and cell viability was measured on day 8 using MTS assays. (A) Dose-response curves of mitoxantrone in DHT and/or cyclopamine-treated MCF-7 cells. (B) IC50 for mitoxantrone extrapolated from the dose-response curves. Experiments were repeated 8 times. Statistical significance was calculated relative to vehicle control by the Mann-Whitney U test, *p<0.05.

0

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EtOH DHT Cyclop DHT+Cyclop

Mito

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Cyclopamine

Vehicle Control

10-8 M DHT 2 µM Cyclopamine

* *

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DHT and cyclopamine increased the sensitivity of MCF-7 cells to the cytotoxic effects

of mitoxantrone. Although the efflux rate of mitoxantrone was delayed in DHT-treated

MCF-7 cells, the treatment did not enhance the responsiveness of the cells to

mitoxantrone effects, potentially due to DHT effects on cell cycle progression (Greeve

et al 2004).

4.2.7 Isolation of Breast Cancer Stem-Like Cells from MCF-7 Breast Cancer Cells

Increasing evidence has indicated that resistance of breast cancer stem cells to

therapeutic agents (e.g chemotherapy) is due to overexpression of the ABC transporters,

in particular ABCG2 (Kim et al 2002, Ding et al 2010, Britton et al 2012). To

investigate DHT and cyclopamine regulation of ABCG2 protein expression and

intracellular localisation in breast cancer stem-like cells, subpopulations of cells that

accumulate low levels of the fluorescent ABC transporter substrate, Hoechst 33342 and

express high levels of CD44 and low levels of CD24 (Hoechst 33342lo/CD44hi/CD24lo)

were isolated from the MCF-7 breast cancer cell line by fluorescence-activated cell

sorting (FACS) (Section 3.1.4, 3.5). This subpopulation of cells is reported to function

as cancer stem-like cells and express markers previously characterised as cancer stem

cell markers (Engelmann et al 2008). In initial studies, the concentrations of Hoechst

33342 and antibodies for detection of CD44 and CD24 were optimised using flow

cytometry. For these experiments, MCF-7 cells were incubated with increasing

concentrations of Hoechst 33342 (0.5, 1, 2 or 5 µg/mL) for 60 minutes and Hoechst

33342 fluorescence was detected at two wavelengths, 450 nm (blue) and 650 nm (red)

(Section 3.5; Figure 4.20). In cells incubated with 0.5 µg/mL and 1 µg/mL Hoechst

33342, a Hoechst 33342lo population was not able to be detected as different

populations of cells were not clearly demarcated (Figure 4.20) In contrast, at higher

concentrations of Hoechst 33342 (2 µg/mL and 5 µg/mL), Hoechst 33342lo cells, which

appear as a subgroup of cells at the ‘side’ of Hoechst 33342 (red) vs Hoechst 33342

(blue) plots were evident (Figure 4.20). This was clearest in cells incubated with 5

µg/mL Hoechst 33342, which was used for subsequent studies (Figure 4.20).

To optimise CD44 and CD24 immunostaining, MCF-7 cells were incubated with 1:5

and 1:20 dilutions of allophycocyanin (APC)-conjugated CD44 antibodies (CD44-APC)

or 1:20 and 1:50 dilutions of Brilliant-Violet™ 421-labelled CD24 antibodies (CD24-

BV421) for 30 minutes. At the 1:20 dilution of CD44-APC, a marked overlap between

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135

fluorescence histograms of CD44-APC signals and background fluorescence of

unstained cells, was observed (Figure 4.21A). In contrast, in cells incubated with a 1:5

dilution of CD44-APC, a high proportion of CD44-APC signals did not overlap with

background signals and therefore this antibody dilution was used in subsequent studies

(Figure 4.21A). In cells stained with both 1:20 and 1:50 dilutions of the CD24-BV421

antibody, fluorescence histograms of CD24 did not overlap with background

fluorescence although at the higher concentration (1:20 dilution), a much larger

difference between CD24 and background fluorescence was observed compared to

results in cells incubated with 1:50 CD24-BV421 antibodies (Figure 4.21B). For

experimental studies, the 1:50 dilution of the CD24-BV421 antibody was chosen as this

concentration produced acceptable results. Unfortunately, following co-staining of

MCF-7 cells with 5 µg/mL Hoechst 33342 dye, 1:5 CD44 and 1:50 CD24 antibodies,

spillover of Hoechst 33342 background fluorescence into BV421 detection channels

was observed (Figure 4.21C). As these signals would interfere with identification of

CD24-BV421 fluorescence, a CD24 antibody labelled with a different fluorophore,

phycoerythrin (PE) was used. When MCF-7 cells were incubated with 5 µg/mL Hoechst

33342, 1:5 CD44-APC and 1:5 CD24-PE, there was no spillover of fluorescence or

background signals and therefore the CD24-PE antibody was used in conjunction with

Hoechst 33342 and CD44-APC for subsequent experiments (Figure 4.22).

To isolate Hoechst 33342lo/CD44hi/CD24lo breast cancer stem-like cells from the MCF-

7 breast cancer cell line, MCF-7 cells were cultured in medium containing 5 µg/mL

Hoechst 33342 for 60 minutes, trypsinised then co-stained with 1:5 CD44-APC and 1:5

CD24-PE antibodies for 30 minutes (Section 3.1.4). Breast cancer stem-like cells were

isolated from these cells using a BD Influx™ Cell Sorter (Section 3.5). The MCF-7

population was first gated in FSC vs SSC plots, then single MCF-7 cells were identified

in FSC-height (FSC-H) vs FSC-area (FSC-A) plots (Figure 4.22). By FACS, ~9% of the

single MCF-7 cells were Hoechst 33342lo and 6.4% of these cells expressed high levels

of CD44 and low levels of CD24 (CD44hi/CD24lo), indicating that the Hoechst

33342lo/CD44hi/CD24lo cells constituted ~0.45% of the MCF-7 cell population (Figure

4.22).

To confirm the stem cell-like characteristics of the isolated cells, Hoechst 33342

accumulation, and CD44 and CD24 expression were evaluated by flow cytometry

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136

following culture of the cells for 30 days. During this time period, stem cells and cancer

stem cells have been reported to differentiate into mixed populations including stem-

like cells and non stem-like cells, in this case repopulating the culture with a mixture of

cells similar to that of parental MCF-7 cells (Yin et al 2008). For these assays, the

breast cancer stem-like cells (Hoechst 33342lo/CD44hi/CD24lo) as well as the Hoechst

33342hi cells, which represent cells with lower levels of expression of ABC transporters

and non cancer stem-like cell characteristics, were isolated from parental MCF-7 cells

using FACS (Section 3.5), then cultured for 30 days. Following 30 days of culture of

the cells, Hoechst 33342lo cells constituted ~11.1% of the total cell population, a result

which was similar to parental MCF-7 cells (Figure 4.23A). However, in the Hoechst

33342lo cell population, 56.6% of the cells were CD44hi/CD24lo, which was

proportionally higher than in parental MCF-7 cells, potentially resulting from an initial

lag in cell proliferation which reduced the number of cell divisions in 30 days of culture

compared to published studies (Figure 4.23). Despite this, the breast cancer stem-like

cells were able to differentiate into non stem-like populations that were absent at day 0

when cells were isolated. These included Hoechst 33342hi cells which constituted 75.6%

of the total population, while in the Hoechst 33342lo subpopulation, 28.4% were

CD44hi/CD24hi, 12.4% were CD44lo/CD24lo and 2.6% of cells were CD44lo/CD24hi

(Figure 4.23). These results indicated that the isolated cells contained stem cell-like

properties as they were capable of giving rise to cells other than those which express the

characteristics of stem cells (CD44hi/CD24lo). In contrast to the breast cancer stem-like

cells, after 30 days of culture of the Hoechst 33342hi cells, only 1.2% of the cells were

Hoechst 33342lo whereas 85.1% of the population was Hoechst 33342hi (Figure 4.23).

None of the Hoechst 33342lo cells was CD44hi/CD24lo, indicating a lack of stem-like

cells within this population.

4.2.7.1 DHT and Cyclopamine Effects on ABCG2 and AR Protein Levels in Breast

Cancer Stem-Like Cells

Following isolation of breast cancer stem cell-like cells, cultures were treated for 8 days

with 10-8 M DHT and/or 2 µM cyclopamine and ABCG2 and AR protein levels were

evaluated by immunoblotting. Due to the low numbers of breast cancer stem-like cells

able to be isolated, mRNA analyses were not carried out for this study. In comparison to

parental MCF-7 cells, ABCG2 protein levels were elevated in the breast cancer stem-

like cells (Figure 4.24A), and following 8 days of 10-8 M DHT treatment, ABCG2

protein expression was decreased by ~37% compared to control breast cancer stem-like

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137

Figure 4.20: Optimisation of Hoechst 33342 concentration for flow cytometry. MCF-7 cells were incubated with 0.5 µg/mL, 1 µg/mL, 2 µg/mL or 5 µg/mL Hoechst 33342 for 60 minutes prior to measurement of Hoechst 33342 fluorescence at 450 nm (blue) and 650 nm (red). Representative results from three independent experiments are shown.

Hoechst 33342 (Red)

Hoe

chst

333

42 (B

lue)

0.5 µg/mL Hoechst 33342 1 µg/mL Hoechst 33342

Hoechst 33342 (Red)

Hoe

chst

333

42 (B

lue)

Hoechst 33342 (Red)

Hoe

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42 (B

lue)

2 µg/mL Hoechst 33342

Hoechst 33342 (Red)

Hoe

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42 (B

lue)

5 µg/mL Hoechst 33342

Hoechst 33342lo Hoechst 33342

lo

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A (i)

A (ii)

B (i)

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CD

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PC

CD24-BV21

Cou

nt

1:20 CD24-BV21

Negative Control CD24-BV421

Negative Control

CD24-BV421

CD24-BV421

CD

44-A

PC

CD44-APC

Cou

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1:20 CD44-APC Negative Control

CD44-APC

Negative Control

CD44-APC

CD24-BV421

CD

44-A

PC

CD44-APC

Cou

nt

1:5 CD44-APC

Negative Control CD44-APC

Negative Control CD44-APC

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B (ii)

(C)

Figure 4.21: Optimisation of CD44-APC and CD24-BV421 antibodies for flow cytometry. MCF-7 cells were stained with (A) APC-conjugated CD44 antibody (CD44-APC) at (i) 1:5 or (ii) 1:20 dilutions or with (B) BV421-conjugated CD24 antibody (CD24-BV421) at (i) 1:20 or (ii) 1:50 dilutions for 30 minutes. Negative controls, which were unstained cells were included to identify background fluorescence. (C) Expression profile of Hoechst 33342, CD44-APC and CD24-BV421 in MCF-7 cells stained with 5 µg/mL Hoechst 33342, 1:5 CD44-APC and 1:50 CD24-BV421.

CD24-BV421

CD

44-A

PC

CD24-BV21

Cou

nt

1:50 CD24-BV21

Hoechst 33342 (Red)

Hoe

chst

333

42 (B

lue)

CD24-BV421

CD

44-A

PC

Hoechst 33342 background



Hoechst 33342lo

Hoechst 33342hi

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(A)

Figure 4.22: Isolation of breast cancer stem-like cells (Hoechst 33342lo/CD44hi/CD24lo) from MCF-7 cells. MCF-7 cells incubated with 5 µg/mL Hoechst 33342 for 60 minutes were stained with 1:5 CD44-APC and 1:5 CD24-PE for 30 minutes. (A) Forward (FSC) and side scatter (SSC) plots were used to identify the MCF-7 cell population, from which (B) single MCF-7 cells were gated in FSC-H (height) vs FSC-A (area) plots. (C) Low Hoechst 33342-containing cells (Hoechst 33342lo) were identified by measuring Hoechst 33342 fluorescence at two wavelengths, 450 nm (blue) and 650 nm (red), and in this population of cells, cells expressing high levels of CD44 and low levels of CD24 (CD44hi/CD24lo) were isolated using a BD Influx™ Cell Sorter.

FSC

SSC

FSC-A

FSC

-H Single Cells

Hoechst 33342 (Red)

Hoe

chst

333

42 (B

lue)

Hoechst 33342lo

Hoechst 33342hi

CD24-PE

CD

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PC

Hoechst 33342lo

Cells

CD44hi/

CD24lo

(B)

(C) (D)

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(A)

(B)

Hoechst 33342lo

Hoechst 33342 (Red)

Hoe

chst

333

42 (B

lue)

CD24-PE

CD

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Cells

CD44hi/

CD24lo

Day 0

Hoechst 33342 (Red) Hoe

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Hoechst 33342hi

CD24-PE

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CD24lo

Hoechst 33342lo

Cells Day 30

Hoechst 33342 (Red)

Hoe

chst

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Hoechst 33342hi

Day 0

Hoechst 33342 (Red)

Hoe

chst

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Hoechst 33342lo

Hoechst 33342hi

CD24-PE

CD

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PC

Hoechst 33342lo

CD44hi/

CD24lo

Day 30

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Figure 4.23: Confirmation of stem cell properties in MCF-7 breast cancer stem-like cells (Hoechst 33342lo/CD44hi/CD24lo). Expression profile of Hoechst 33342, CD44-APC and CD24-PE in (A) Hoechst 33342lo/CD44hi/CD24lo MCF-7 cultures and in (B) Hoechst 33342hi MCF-7 cultures on the day of isolation (Day 0) and 30 days post isolation of cells (Day 30).

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cell cultures incubated with 0.1% (v/v) ethanol (Figure 4.24A). A similar DHT-induced

downregulation of ABCG2 levels (~28%) was also evident after 4 days of treatment,

results that were comparable to those detected in DHT-treated parental MCF-7 cells

(Figure 4.4, 4.24A). Co-treatment of the cultures with 10-8 M DHT and 2 µM

cyclopamine for 8 days downregulated ABCG2 protein levels by ~26% compared to the

vehicle control while treatment of MCF-7 stem-like cells with 2 µM cyclopamine

produced small decreases in ABCG2 protein of ~11.7% (Figure 4.24A).

Although AR protein was readily detectable in parental MCF-7 cells, in the breast

cancer stem-like cells, AR protein was barely detectable (Figure 4.24B). However,

following 10-8M DHT treatment of breast cancer stem-like cells for 4 days, AR protein

expression was elevated to ~160% that in parental MCF-7 cells, while after 8 days of

treatment, AR protein expression remained increased at levels that were comparable to

those in parental MCF-7 cells (Figure 4.24B). (AR was not able to be quantitated

against (AR) levels in untreated breast cancer stem-like cells due to the very low

expression of AR in this subpopulation (Figure 4.24B)). AR protein levels are also

reported to be induced in parental MCF-7 cells following DHT treatment, which is in

part due to increased AR protein stability (Greeve et al 2004). In breast cancer stem-like

cells treated for 8 days with 2 µM cyclopamine, AR protein levels remained

undetectable, while 10-8 M DHT and 2 µM cyclopamine co-treatment elevated AR

protein expression to levels ~40% that in parental MCF-7 cells (Figure 4.24B).

4.2.7.2 Intracellular Localisation of ABCG2 in DHT and Cyclopamine Treated

Breast Cancer Stem-Like Cells

DHT and cyclopamine effects on the intracellular localisation of ABCG2 in breast

cancer stem-like cells were evaluated by confocal microscopy using ABCG2 antibodies

and the filamentous actin (F-actin) marker, Phalloidin Red, methods for which had been

optimised previously (Section 4.2.4). ABCG2 staining was diffuse in the nucleus and

cytoplasm of cells and also accumulated in cell-to-cell junction complexes (yellow

arrows) and in round cytoplasmic vesicles (red arrows), similar to its localisation in

parental MCF-7 cells (Figure 4.7, 4.25). Although ABCG2 localisation to these

complexes and vesicles was not quantitated, the numbers of ABCG2-containing cell-to-

cell junction complexes and cytoplasmic vesicles were observed to be higher compared

to parental MCF-7 cells (Figure 4.7, 4.25). ABCG2 also localised to edges of large and

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round vesicles (blue arrow) which formed between adjacent breast cancer stem-like

cells and resembled the ABCG2-rich extracellular vesicles (EVs) observed previously in

MCF-7 cells selected for resistance to mitoxantrone (MCF-7/MX) (Figure 4.25) (Goler-

Baron and Assaraf 2011). However, these ABCG2-associated EV-like structures were

not frequently seen in the breast cancer stem-like cell population and were also absent in

parental MCF-7 cells (Figure 4.7, 4.25).

In the breast cancer stem-like cells, the ABCG2-associated cell-to-cell junction

complexes, cytoplasmic (aggresome-like) vesicles and EV-like structures co-localised

with F-actin (Figure 4.25). Treatment of the breast cancer stem-like cells with 10-8 M

DHT, 2 µM cyclopamine or the combination of 10-8 M DHT and 2 µM cyclopamine for

4 days did not alter the localisation or expression of ABCG2 in the EV-like structures

but DHT and DHT/cyclopamine treatments markedly decreased numbers of ABCG2-

containing cell-to-cell junction complexes and cytoplasmic vesicles (Figure 4.25). In

breast cancer stem-like cells treated with 2 µM cyclopamine only, ABCG2 localisation

to cell-to-cell membrane junctions also decreased but ABCG2 accumulation in

cytoplasmic vesicles was increased (Figure 4.25). Interestingly, the cytoplasmic vesicles

in cyclopamine-treated breast cancer stem-like cultures formed as clusters of smaller

vesicles compared to the larger and singular aggresome-like vesicles that had been

observed in control (vehicle-treated) cultures of breast cancer stem-like cells, in parental

MCF-7 cells and in cyclopamine-treated parental MCF-7 cells (Figure 4.25).

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(A)

(B)

Figure 4.24: DHT and cyclopamine regulation of ABCG2 and AR protein levels in breast cancer stem-like cells isolated from MCF-7 cultures. Breast cancer stem-like cells (Hoechst 33342lo/CD44hi/CD24lo) isolated from MCF-7 cultures were treated with 10-8

M DHT and/or 2 µM cyclopamine for 8 days prior to protein isolation for immunoblotting. (A) ABCG2 protein levels were increased in MCF-7 stem-like cells in comparison to parental (unsorted) MCF-7 cells and reduced by 4 and 8 days of DHT treatment and 8 days of DHT and cyclopamine treatments. (B) AR levels were barely detectable in MCF-7 stem-like cells but strongly induced in DHT or in DHT and cyclopamine treated cells. Experiments were repeated three times and representative immunoblots are shown.

ABCG2 (70 kDa)

β-actin (44 kDa)

MC

F-7

(Par

enta

l)

MCF-7 (Stem cells)

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-

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-

-

+

+

+

+

- DHT Cyclopamine

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BC

G2

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β-actin (44 kDa)

AR (110 kDa)

MC

F-7

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MCF-7 (Stem cells)

-

-

+

-

-

+

+

+

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- DHT Cyclopamine

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AR

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otei

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s

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10-8 M DHT + 2 µM

Cyclopamine

ABCG2 (green)

F-actin (red) ABCG2 + F-actin + Hoechst 33258

2 µM Cyclopamine

10-8 M DHT

Vehicle Control

(0.1% (v/v) ethanol)

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Figure 4.25: Effects of DHT and cyclopamine on the intracellular localisation of ABCG2 in breast cancer stem-like cells isolated from MCF-7 cultures. Breast cancer stem-like cells isolated from MCF-7 cells and seeded onto coverslips were cultured for 4 days in the presence of 10-8 M DHT and/or 2 µM cyclopamine, or 0.1% (v/v) ethanol (vehicle control) prior to immunostaining with ABCG2 primary antibody and Alexafluor® 488-conjugated anti-mouse secondary antibodies (green). Filamentous actin (F-actin, red) was imaged with Phalloidin Red and nuclei (blue) were stained with Hoechst 33258. Negative controls were cells stained with the secondary antibodies only. ABCG2 staining in cell-to-cell junction complexes and in round cytoplasmic vesicles are indicated by yellow and red arrows, respectively. An EV-like structure is indicated by a blue arrow in control cells. Experiments were performed three times and representative results are shown. Scale bar: 30 µM.

Negative Control

ABCG2 (green) Hoechst 33258 (blue) ABCG2 +

Hoechst 33258

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4.3 Discussion

Interaction between the AR and Hedgehog signalling pathways has been reported

previously and in those studies, cross-regulation of the expression of target genes was

observed following activation or inhibition of either pathway (Chen et al 2011a, Sirab et

al 2012b). For example, DHT downregulated the expression of Hedgehog target genes

(e.g. SHH, GLI1, PTCH1) in LNCaP and VCaP prostate cancer cells whilst inhibition of

the Hedgehog pathway was shown to downregulate the mRNA levels of DHT/AR-

mediated target genes (e.g. KLK2, KLK3) in LNCaP cells (Sirab et al 2012b).

Androgens, including DHT have anti-proliferative effects in breast cancer cells and

similarly, the Hedgehog pathway small molecule inhibitor, cyclopamine, has been

shown to inhibit the proliferation of breast cancer cell lines (Greeve et al 2004, Kubo et

al 2004, Zhang et al 2009). In this thesis study, the effects of DHT and cyclopamine

treatments on gene expression were initially evaluated in the ER+ve, PR+ve and AR+ve

breast cancer cell lines, MCF-7 and T-47D by screening the expression of 84 breast

cancer-associated genes using RT2 Profiler Human Breast Cancer PCR Arrays.

Key findings from analysis of the breast cancer PCR arrays included downregulation of

the expression of genes that encode cell cycle regulators (e.g. cyclin D1 (CCND1),

cyclin D2 (CCND2), CDKN1A, JUN, MYC, BCL2) or anti-apoptosis factors (e.g. BCL2,

MYC, JUN) as well as decreased expression of the multidrug resistance (MDR)

transporters, ABCB1 and ABCG2, and regulators of EMT. mRNA levels of cyclin D1

(CCND1), MYC, JUN and BCL2, proteins encoded by which induce cell cycle

progression in breast cancer cells, were downregulated in DHT/cyclopamine co-treated

MCF-7 and T-47D cells. In support of these findings, treatment of MCF-7 cells with

DHT or cyclopamine has been shown to decrease expression of cyclin D1 (Greeve et al

2004, Che et al 2013). Low mRNA expression of MYC, an AR target gene, has been

correlated with increased expression of AR in human breast tumour samples and it was

proposed that AR suppresses MYC expression, a result that is in agreement with DHT-

induced downregulation of MYC observed in the present study (Bieche et al 2001, Gao

et al 2013). Overexpression of JUN in MCF-7 cells has been identified to be a marker

of aggressiveness as it led to increased cell invasion, chemoresistance and loss of

responsiveness of cells to the anti-oestrogen, tamoxifen (Smith et al 1999). Therefore,

downregulation of JUN expression suggests that cellular processes facilitating tumour

progression in addition to cell proliferation are inhibited. GLI1 and AP-1 binding sites

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have been identified in the JUN promoter and downregulation of JUN may be mediated

via inhibition of Hedgehog/GLI signalling in the presence of cyclopamine in the breast

cancer cell cultures (Laner-Plamberger et al 2009). Previously, DHT was found to

decrease BCL2 mRNA and protein expression in MCF-7 cells as well as in the ER+ve,

PR+ve and AR+ve breast cancer cell line, ZR-75-1 (Lapointe et al 1999, Macedo et al

2006). This effect may not be direct as ARE sequences were not able to be identified in

the BCL2 promoter, however an indirect mechanism involving androgen-induced

regulation of the E2F1 transcription factor, which binds to E2F binding sites located in

the BCL2 promoter may mediate androgen effects on BCL2 levels (Huang et al 2004).

Androgens including DHT have been shown in previous studies to inhibit the

proliferation of ER+ve breast cancer cells (MCF-7, T-47D, ZR-75-1) but stimulate the

growth of cell lines which express low to undetectable levels of ER (MDA-MB-231,

MDA-MB-453) (Hackenberg et al 1991, Birrell et al 1995, Greeve et al 2004, Macedo

et al 2006, Ni et al 2011, Barton et al 2015). In this study, treatment of the ER+ve

MCF-7 and T-47D cells with 10-8M DHT inhibited cell proliferation, a result which is

in agreement with previous reports and is associated with the downregulation of

expression of cell cycle and anti-apoptosis genes (Greeve et al 2004, Macedo et al

2006). DHT has been reported to inhibit E2-induced MCF-7 and T-47D cell

proliferation and downregulate ERα transcriptional activity, suggesting that DHT-

induced inhibition of MCF-7 and T-47D cell proliferation by DHT in this study may be

in part mediated via antagonism of the E2/ERα pathway (Peters et al 2009, Need et al

2012).

The Hedgehog pathway inhibitor, cyclopamine is a steroidal alkaloid and teratogen

derived from the corn-lily Veratrum californicum. Cyclopamine specifically binds to

and inhibits SMO by altering its conformation, a similar mechanism to the regulation of

SMO by PTCH1 (Section 1.4.5) (Chen et al 2002). Previous studies have reported that

cyclopamine inhibits the proliferation of both ER+ve (e.g. MCF-7, T-47D, BT-474) and

ER-ve (e.g. SK-BR-3, MDA-MB-231) breast cancer cell lines (Kubo et al 2004,

Mukherjee et al 2006, Zhang et al 2009). This was associated with decreased nuclear

and cytoplasmic levels of GLI1, indicating inhibition of the canonical Hedgehog

signalling pathway. However, most studies have used high concentrations of

cyclopamine (10-20 µM), with MCF-7 and MDA-MB-231 cells reported to be

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unresponsive to cyclopamine concentrations below 20µM, and T-47D cells growth

inhibited only by 10 µM and 20 µM cyclopamine (Mukherjee et al 2006, Zhang et al

2009). At higher concentrations (10-20 µM), cyclopamine-induced growth inhibition

may result from non-specific or SMO-independent effects as the proliferation of both

SMO-expressing and SMO-nonexpressing breast cancer cells is reported to be inhibited

(Zhang et al 2009). In contrast, in the present study, inhibition of MCF-7 and T-47D

cell proliferation was observed at lower concentrations (2 µM) of cyclopamine,

indicating that cultures were more responsive to cyclopamine effects. This may be due

to clonal variation between isolates of the cell lines and differences in study design.

Importantly, treatment of the cells with 2 µM cyclopamine led to downregulation of

GLI1 mRNA levels after 24 h, a result identified in the PCR arrays (data not shown)

which indicates inhibition of Hedgehog signalling.

Co-treatment of MCF-7 and T-47D cells with DHT and cyclopamine also led to

inhibition of cell proliferation. In prostate cancer cells, growth of which is stimulated by

androgens, the combination of an AR inhibitor, pyrvinium pamoate and a Hedgehog

pathway inhibitor, either cyclopamine or LDE225 led to synergistic inhibition of cell

proliferation in vitro and in vivo (Gowda et al 2013). Although there were no marked

differences between the effects on MCF-7 and T-47D cell proliferation of DHT and

cyclopamine co-treatment or treatment with either agent alone, analysis of the RT2

Profiler Human Breast Cancer PCR Arrays indicated that DHT and cyclopamine co-

treatment resulted in regulation of a greater number of genes, most of which were

downregulated. At the present time, there are no published reports on the effects of

DHT and cyclopamine co-treatment on the proliferation of, or gene regulation in breast

cancer cells, and mechanisms underlying the predominant downregulation of gene

expression are currently unknown. Direct interactions between the AR and

Hedgehog/GLI transcription factors have been demonstrated in the prostate cancer cell

line LNCaP and based on these reports, AR-GLI1 interactions in breast cancer cells as

well as binding of the heterodimers to AREs or GLI binding sites resulting in regulation

of the expression of AR, Hedgehog or unique target genes may be investigated in future

studies (Chen et al 2010, Chen et al 2011a).

The AR and Hedgehog pathways modulate cancer cell proliferation and survival, and

are shown to contribute to the development of chemoresistance in multiple types of

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cancers via regulation of the ABC transporters (Cai et al 2007, Ho et al 2008, Singh et

al 2011, Chai et al 2013, Hsieh et al 2013). In the prostate cancer cell line, LNCaP,

DHT increased the mRNA and protein levels of ABCC4, with knockdown of expression

of the transporter by transfection of cells with siRNA-ABCC4 restoring the sensitivity

of LNCaP cells to methotrexate (Cai et al 2007, Ho et al 2008). Overexpression of the

AR in the BFTC 909 upper urinary tract urothelial carcinoma cell line elevated the

expression of ABCG2 and suppressed the cytotoxic effects of doxorubicin in the cells

(Hsieh et al 2013). In the present study, DHT and cyclopamine treatments

downregulated ABCB1 and ABCG2 mRNA expression in both MCF-7 and T-47D cells.

Additional investigation of ABCG2 expression in MCF-7 cells confirmed that DHT and

DHT/cyclopamine co-treatment of the cells downregulated the mRNA and protein

levels of ABCG2.

The expression of ABCB1 in MCF-7 and T-47D cells as well as ABCG2 in T-47D cells

were not further examined in this study due to low endogenous expression of these

transporters, which was evidenced by the high Ct values for ABCG2 in T-47D cells and

ABCB1 in both MCF-7 and T-47D cells. In support of these data, endogenous ABCB1

mRNA and protein expression has been reported as undetectable in previous studies of

MCF-7 cells, and low expression of the ABCG2 protein was also shown in western blot

analysis of ABCG2 in T-47D cells (Imai et al 2005, Calcagno et al 2008, He et al

2013). In future studies investigating ABCB1, experiments may be performed in

ABCB1-overexpressing cells such as following transient or stable expression of

ABCB1 in MCF-7 and T-47D cells. In addition to ABCB1 and ABCG2, at least 16

ABC transporters including ABCC4 and ABCB4 have been reported to be

overexpressed in drug resistant MCF-7 cells (MCF-7/AdVp3000) (Liu et al 2005). As

ABC transporters have overlapping and unique substrates that together influence drug

efflux and drug resistance, comprehensive characterisation of their regulation by

androgens and Hedgehog inhibitors in breast cancer cells will be important for

determining the usefulness of androgen and Hedgehog inhibitor treatments to delay or

prevent drug resistance.

In studies which identified regulation of ABCC4 by the AR, three consensus AREs

were identified 3-6 kb upstream of exon 1 of the ABCC4 sequence (Cai et al 2007).

However, chromatin immunoprecipitation (ChIP) assays did not detect interaction

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between the AR and these AREs in prostate cancer cell lines and it was proposed that

androgen effects may be mediated indirectly via intermediate factors known to regulate

ABCC4 expression such as the ETS variant 1 (ETV1) transcription factor, levels of

which were upregulated by DHT (Sampath et al 2002, Cai et al 2007). As identification

of ARE(s) in the ABCG2 promoter was not performed in this study or reported

previously, it is not known whether the DHT-induced suppression of ABCG2 mRNA

levels involves direct binding of ligand-activated AR to regulatory regions of the

ABCG2 gene. To determine whether DHT effects on ABCG2 expression in MCF-7 cells

were direct, putative AREs in the ABCG2 promoter as well as in the 3’-untranslated

region (UTR) of DNA sequences may be investigated in future studies.

Direct effects of oestrogens and progesterone, but not androgens, on the expression of

ABCG2 in breast cancer cells have been reported previously (Ee et al 2004a, Imai et al

2005, Yasuda et al 2006, Yasuda et al 2009). Oestrogen (ERE) and progesterone (PRE)

responsive elements were identified in the ABCG2 promoter, and oestrogen- or

progesterone-mediated modulation of ABCG2 mRNA and protein expression was

shown to involve ligand-induced binding of ER and PR to their respective DNA binding

sites in the ABCG2 promoter (Ee et al 2004b, Wang et al 2008b). As DHT antagonises

E2/ERα-induced MCF-7 and T-47D breast cancer cell proliferation and ERα target

genes in part by direct interaction between the AR and ERα and binding of the AR to an

ERE, it is possible that the downregulation of ABCG2 expression by DHT is mediated

via indirect mechanisms involving inhibition of the ERα signalling pathway (Panet-

Raymond et al 2000, Peters et al 2009, Need et al 2012).

The role of Hedgehog signalling in the overexpression of ABCG2 has been investigated

using diffuse large B-cell lymphoma (DLBCL) cells, identifying a GLI binding site

~408 bp upstream of the ABCG2 transcriptional start site (Singh et al 2011). Inhibition

of the Hedgehog pathway by the synthetic inhibitor, KAAD-cyclopamine decreased

ABCG2 mRNA levels in the DLBCL cell lines, SUDHL2, OCI-LY10, BJAB and

DOHH2, indicating that Hedgehog signalling in part regulates steady state ABCG2

levels (Singh et al 2011). However, in the present study, cyclopamine treatment on its

own had little to no effects on ABCG2 mRNA and protein levels in MCF-7 cells.

Although further studies will be required to characterise the cell type-specific effects of

Hedgehog signalling on the regulation of ABCG2 levels, these effects may be due to the

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differential expression of GLI/Hedgehog cofactors in different cell types (Kasper et al

2006). In contrast to findings in this thesis, KAAD-cyclopamine was recently reported

to downregulate ABCB1 and ABCG2 mRNA levels in MCF-7 cells (Das et al 2013).

The discordant results may have resulted from the higher concentration of KAAD-

cyclopamine (10 µM) used in that study (Das et al 2013). KAAD-cyclopamine has also

been reported to exhibit greater potency compared to natural cyclopamine, inhibiting

Hedgehog signalling activity to levels similar to that with cyclopamine but at lower

concentrations (Taipale et al 2000).

ABCG2 functions as a drug efflux transporter when bound to the plasma membrane of

cells (Robey et al 2007, Nakanishi 2012). Decreased ABCG2 localisation to the

membrane and retention of ABCG2 in the cell cytoplasm have been shown to impede

ABCG2 efflux activity and increase sensitivity of cells to cytotoxic drugs exported by

ABCG2 (Mizuarai et al 2004, Robey et al 2007, Nakanishi 2012, To and Tomlinson

2013). In the present study, DHT and cyclopamine treatments of MCF-7 cells decreased

ABCG2 levels in cell-to-cell junction complexes, with cyclopamine treatment alone

also shown to induce accumulation of ABCG2 into cytoplasmic vesicles. These findings

suggested that DHT and cyclopamine were inhibiting ABCG2 function and in support

of this hypothesis, DHT, cyclopamine and the combination of both agents were shown

to delay efflux of the ABCG2 substrate, mitoxantrone from MCF-7 cells, which resulted

in increased sensitivity of cells to mitoxantrone-induced cytotoxic effects.

The identity of the ABCG2-containing cytoplasmic vesicle is currently unclear.

However, these vesicles resembled aggresomes in which aggregates of proteins that

have been tagged for degradation are accumulated (Garcia-Mata et al 2002,

Wakabayashi et al 2007, Zaarur et al 2014). Previous studies have identified that

histone deacetylase 6 (HDAC6) forms bridges between ubiquitinated protein aggregates

and dynein motors, which transport the protein cargo along microtubules towards the

microtubule organising centre (MTOC) for development of aggresomes (Garcia-Mata et

al 2002, Kawaguchi et al 2003). Disruption of the microtubules prevents aggresome

formation (Garcia-Mata et al 1999, Kawaguchi et al 2003). Hence, to investigate

whether the ABCG2-containing cytoplasmic vesicles are aggresomes, experiments

using aggresome specific markers such as HDAC6 and treatment of MCF-7 cells with

nocodazole, an inhibitor of polymerisation of microtubules, may be performed (Garcia-

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Mata et al 1999, Kawaguchi et al 2003). In a recent study, ABCG2 protein in pancreatic

ductal adenocarcinoma (PDAC) cells was reported to localise in the membranes of large

and round autofluorescent compartments, which resembled the ABCG2-associated

cytoplasmic vesicles identified in MCF-7 cells (Miranda-Lorenzo et al 2014). The

autofluorescence was attributed to accumulation of the naturally fluorescent ABCG2

substrate, riboflavin into these compartments, formation of which was dependent on

ABCG2 expression and activity as autofluorescence was abolished by treatment of the

cells with the ABCG2 inhibitor, fumitremorgin C (FTC) (Miranda-Lorenzo et al 2014).

Only a minor proportion of the PDAC-derived cells expressed the autofluorescent

compartments, a feature that is similar to the frequency of ABCG2-containing vesicles

in MCF-7 cells, and the autofluorescent but not non-autofluorescent cells were shown to

form tumours in mice and possess stem cell-like characteristics by generating both

autofluorescent and non-autofluorescent cells in vitro (Miranda-Lorenzo et al 2014). As

such, the ABCG2-containing cytoplasmic vesicles may be a characteristic of cancer

stem cells, which is consistent with the higher numbers of ABCG2-containing vesicles

in the breast cancer stem-like cells observed in the present study.

Localisation of Lysotracker Red around ABCG2-containing cytoplasmic vesicles in

MCF-7 cells was similar to previous findings where lysosome clustering around

aggresomes was shown to be important for lysosomal degradation of proteins in the

aggresomes (Zaarur et al 2014). These findings therefore suggested that the ABCG2-

containing cytoplasmic vesicles may be degraded by the lysosomes. However, it was

difficult to strongly support this hypothesis by western blot analysis of chloroquine

effects on ABCG2 protein levels in DHT and cyclopamine treated MCF-7 cells as

results were not prominent and were difficult to reliably reproduce. To confirm these

results, other inhibitors of the lysosome (e.g. ammonium chloride, bafilomycin A1) may

be evaluated in future studies to investigate DHT and cyclopamine regulation of

ABCG2 expression. The lack of reproducibility of western blot analysis of lysosome-

mediated degradation of ABCG2 may also be attributed to activation of secondary

degradation pathways to compensate for loss of the lysosomal pathway or recycling of

ABCG2 between the cell membrane and cytoplasmic organelles/vesicles, which can

occur following de-ubiquitination of proteins (Studzian et al 2015). For example,

ubiquitin-specific processing protease Y (UBPY)/USP8, a de-ubiquitinating enzyme has

been shown to decrease levels of ubiquitinated EGFR and delay proteasomal

degradation of EGFR (Mizuno et al 2005).

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Diffuse staining of ABCG2 was detected in the cytoplasm and nucleus of MCF-7 cells,

with nuclear localisation of ABCG2 confirmed by subcellular fractionation studies.

Cytoplasmic and nuclear localisation of ABCG2 have been reported in drug resistant

MCF-7 cells (MCF-7/Advrp3000) but not in parental MCF-7 cells (Litman et al 2000).

Although nuclear localisation of ABCG2 has been documented in multiple cell types

including head and neck squamous cell carcinoma and glioblastoma multiforme cells,

functional studies of nuclear ABCG2 are limited (Chen et al 2006, Bhatia et al 2012).

Recently, ABCG2 was shown to exhibit transcription factor-like functions in the

nucleus of A549 human lung carcinoma cells and induced transcription of E-cadherin

through binding to the E-box of the CDH1 (E-cadherin) promoter (Liang et al 2015).

MCF-7 cells are AR+ve breast cancer cell lines and AR protein levels have been shown

to increase following DHT treatment (Greeve et al 2004, Chua 2011). Interestingly, in

this study, AR protein expression in breast cancer stem-like cells derived from the

MCF-7 breast cancer cell line was not able to be detected by western blotting, although

DHT treatment of these cells markedly induced expression of AR protein. This

suggested that the very low levels of AR expression in breast cancer stem-like cells

were below detection limits of the AR antibody. AR expression in breast cancer stem

cells has not been reported previously but low levels of the AR have been documented

in stem cells of benign and malignant prostate tissues (Fedoruk et al 2004, Huss et al

2005). Previously, oestrogens and progesterone have been reported to increase the

proportion of breast cancer stem cells, promoting the formation of breast tumours

(Vares et al 2013). In stem cells of luminal breast cancer cell lines (e.g. MCF-7 and T-

47D) as well as normal mammary gland stem or progenitor cells, expression of ER and

PR were low. Despite this, the breast cancer stem cells were capable of responding to

oestrogens and progesterone in a paracrine manner resulting from interactions with

ER+ve and PR+ve breast cancer cells in the cell population (Asselin-Labat et al 2010).

Hence, DHT-induced upregulation of AR protein levels in cultures of MCF-7-derived

breast cancer stem-like cells may similarly involve paracrine activation of AR signalling

in the breast cancer stem-like cells by rare AR+ve cells that may be present in the

cultures. This may be investigated by AR immunofluorescence or confocal microscopy

of MCF-7 stem cell-like cells.

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ABC transporters are implicated in the resistance of cancer stem cells to therapeutic

drugs, which potentially leads to tumour relapse and progression (Lou and Dean 2007,

Robey et al 2007). In the present study, DHT and DHT/cyclopamine treatment of breast

cancer stem-like cells markedly downregulated ABCG2 protein levels and ABCG2

localisation in cell-to-cell junction complexes and cytoplasmic vesicles. Cyclopamine

treatment of the breast cancer stem-like cells also stimulated the accumulation of

ABCG2 in cytoplasmic vesicles and interestingly, these vesicles were observed as

clusters of small vesicles unlike the larger and single ABCG2-containing vesicles seen

in parental MCF-7 cells. As it is possible that these smaller vesicles fuse to form large

vesicles, real time fluorescence microscopy may be performed to investigate formation

of ABCG2 cytoplasmic vesicles in the breast cancer stem-like cells. Based on results

obtained using parental MCF-7 cells, DHT- and/or cyclopamine-induced decreases in

ABCG2 protein expression and localisation in cell-to-cell junction complexes suggest

that the treatments also inhibit ABCG2 efflux function in the breast cancer stem-like

cells. To investigate this hypothesis, flow cytometry and MTS viability assays may

similarly be performed to determine DHT and cyclopamine regulated efflux of ABCG2

substrates and sensitivity of the breast cancer stem-like cells to chemotherapeutic

agents.

In breast cancer stem-like cell cultures, a small population of the cells also expressed

round ABCG2-associated vesicles between adjacent cells. These vesicles resembled

extracellular vesicles (EVs) previously documented in MCF-7 cells selected for

resistance to mitoxantrone (MCF-7/MX) which express high levels of ABCG2 (Ifergan

et al 2005, Goler-Baron and Assaraf 2011). Therefore, it is possible that the elevated

levels of ABCG2 protein in the MCF-7 derived breast cancer stem-like cells induced

formation of the EV-like structures. ABCG2-associated EVs were also reported to

sequester a number of ABCG2 substrates including mitoxantrone, topotecan and

methotrexate, resulting in drug resistance (Ifergan et al 2005, Goler-Baron and Assaraf

2011). Immunofluorescence or confocal microscopy may be performed to determine

whether ABCG2 substrates are similarly sequestered into the EV-like structures in the

breast cancer stem-like cells. Although DHT and cyclopamine treatments did not

markedly alter ABCG2 levels in the EV-like structures, DHT and cyclopamine effects

on drug sequestration in the EV-like structures may also be investigated.

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Initial findings from this thesis demonstrated that DHT and cyclopamine treatments of

MCF-7 and T-47D cells downregulated the expression of genes that encode cell cycle

regulators, anti-apoptosis factors, ABC drug transporters and EMT-associated factors.

Further investigation of DHT- and cyclopamine-induced regulation of ABCG2

identified decreased ABCG2 protein expression and reduced localisation of ABCG2 in

cell-to-cell junction complexes in both MCF-7 cells and breast cancer stem-like cells

isolated from MCF-7 cultures. In MCF-7 cells, reduced ABCG2 expression at the

plasma membrane was correlated with increased intracellular accumulation of the

ABCG2 substrate, mitoxantrone and increased sensitivity of MCF-7 cells to the

cytotoxic effects of mitoxantrone. Based on preliminary experiments that screened

regulation of gene expression in DHT and cyclopamine treated MCF-7 cells (Section

4.2.1), subsequent studies investigated DHT and cyclopamine effects on EMT.

Chapter 5

DHT AND CYCLOPAMINE REGULATION OF

EMT IN MCF-7 AND T-47D CELLS

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5.1 Introduction

Metastatic disease is a major cause of breast cancer-associated death and although

treatment of early stage breast tumours is initially successful, ~30% of patients develop

distant metastases while 4-10% of patients present with metastatic disease (Cardoso et

al 2012, Purushotham et al 2014). EMT is an important physiological programme

which has been shown to facilitate cancer cell migration, invasion and metastasis via the

co-ordinated regulation of expression of genes that encode regulators or components of

cell-to-cell adhesion complexes, cell-to-ECM interactions, secretion and deposition of

ECM components, re-organisation of the ECM and actin cytoskeleton, migration,

production of proteases (e.g. MMP) and invasion. The EMT process is driven by

activation of major pro-EMT signalling pathways, including the TGFβ, WNT and

NOTCH pathways (Section 1.7), while a number of modulators of the expression and/or

activity of central EMT or EMT-associated processes influence initiation or progression

of EMT, for example, steroid hormones and microRNAs (miRNAs) (Wu and Zhou

2008).

Oestrogens and ERα stimulate EMT in ERα-expressing breast cancer cells, and

treatment of MCF-7 and T-47D cells with E2 has been reported to decrease expression

of E-cadherin and upregulate vimentin levels, indicating induction of an EMT

programme (Jimenez-Salazar et al 2014, Sun et al 2014). (Jimenez-Salazar et al 2014,

Sun et al 2014). These effects were reversed by fulvestrant, an ER antagonist,

supporting involvement of E2/ER signalling in the promotion of EMT (Jimenez-Salazar

et al 2014). Loss of E-cadherin expression has been associated with E2-mediated re-

organisation of the actin cytoskeleton and formation of lamellipodial structures which

facilitate cell migration (DePasquale 1999). MCF-7 and T-47D cells undergo

transformation to motile mesenchymal-like or spindle-shaped cells following treatment

with E2, which also downregulates expression of the epithelial marker, occludin and

induces nuclear localisation of the tight junction proteins, zona occludens 1 (ZO-1) and

ZO-1-associated nucleic acid binding (ZONAB), thereby disrupting tight junctions and

facilitating cell migration (Jimenez-Salazar et al 2014, Sun et al 2014). E2/ER-induced

EMT was also found to involve GLI1 activation that was independent of the canonical

Hedgehog signalling pathway as the small molecule Hedgehog pathway inhibitor,

cyclopamine did not inhibit E2-induced activation of GLI1 (Sun et al 2014).

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In more aggressive and metastatic ER-ve breast tumours, the absence of ERα expression

has been proposed to lead to activation of EMT (Al Saleh et al 2011, Iseri et al 2011).

Although oestrogens and ERα promote the proliferation, migration and invasion of

ER+ve breast cancer cells, ERα maintains a more epithelial phenotype of ER+ve breast

cancers. Metastasis tumour antigen 3 (MTA3), a component of the transcriptional

repressor complex, Mi2/NuRD, is transcriptionally activated by E2/ERα signalling and

downregulates expression of the EMT-inducing transcription factor, SNAI1, inhibiting

EMT (Fujita et al 2003). In that study, it was hypothesised that low expression of

MTA3 in ER-ve breast cancers may be a mechanism by which EMT and tumour

metastasis are promoted in these cancers (Fujita et al 2003). The role of E2/ERα

signalling in promoting proliferation and migration but maintaining an epithelial

phenotype of ER+ve breast cancers as opposed to the activation of EMT in ER-ve

breast tumours therefore suggests that EMT is differentially regulated by E2/ERα

signalling in breast tumours according to the level of ERα expression.

Progesterone and PR signalling inhibit or reverse EMT in several types of malignancies

including breast and endometrial cancers (Zuo et al 2010, van der Horst et al 2012). In

PR-ve breast cancer, in which loss of PR expression was postulated to facilitate EMT

and tumour metastasis, progesterone treatment or re-activation of PR signalling reversed

EMT (Zuo et al 2010). In the basal-like breast cancer cell line, MDA-MD-468 (ER-

ve/PR-ve/HER2-ve), progesterone was shown to upregulate expression of epithelial

markers, including occludin and E-cadherin, and downregulate SNAI1 protein

expression, indicating reversal of EMT (Zuo et al 2010). MDA-MB-468 cells lack

expression of cytoplasmic and nuclear PR, and this study provided evidence that

progesterone effects on EMT were mediated via non-genomic PR signalling involving

membrane-associated PRα (mPRα), which is capable of activating secondary pathways

such as the MAPK or ERK1/2 pathways (Zhu et al 2003, Zuo et al 2010). In

endometrial cancer, canonical PR signalling is involved in mediating progesterone

effects on EMT. In the Ishikawa (IK) endometrial cancer cell line transfected with PRB,

treatment with progesterone or the synthetic progestin, medroxyprogesterone acetate

(MPA) reduced cell migration, vimentin expression and expression of IL6, TGFβ and

WNT signalling intermediates, indicating reversal of EMT (van der Horst et al 2012).

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Due to the significance of the androgen/AR axis in prostate carcinogenesis and tumour

growth, studies on androgen/AR regulation of EMT have been focussed on prostate

cancer and progression to castrate-resistant prostate tumours (Wang et al 2008a, Zhu

and Kyprianou 2010). DHT treatment of the LNCaP prostate cancer cell line has been

shown to downregulate E-cadherin levels and in the low AR+ve prostate cancer cell

line, PC-3, in which AR levels are stimulated by DHT, E-cadherin levels also decreased

and N-cadherin expression was upregulated following DHT treatment, indicating

activation of EMT (Zhu and Kyprianou 2010). Prostate tumours are commonly treated

with androgen ablation therapies, but development of androgen-independent (castrate-

resistant) tumours frequently occurs and is associated with tumour progression and

metastasis. This is also reported to be correlated with activation of EMT (Jennbacken et

al 2010, Zhu and Kyprianou 2010, Sun et al 2012). For example, N-cadherin levels are

higher in androgen-independent LNCaP-19 prostate tumours grown as xenografts in

mice compared to androgen-dependent LNCaP tumours (Jennbacken et al 2010).

Similarly, E-cadherin levels were decreased but expression of the EMT-inducing

transcription factors, ZEB1, ZEB2 and TWIST1 was increased in LuCaP35 prostate

tumours growing in castrated mice in comparison to prostate tumours growing in intact

mice (Sun et al 2012).

In breast cancer, androgens have been shown to promote EMT in both ER-ve and

ER+ve breast cancer cells. The molecular apocrine breast cancers lack expression of ER

and PR but express the AR, while a proportion of ER-ve/PR-ve/HER2-ve triple-

negative breast cancers (TNBC) are also AR+ve (Section 1.4.4.3) (Moinfar et al 2003,

Safarpour et al 2014). In in vitro models of ER-ve/PR-ve breast tumours, such as the

AR+ve MDA-MB-453 cell line, treatment with the AR inhibitor, enzalutamide inhibited

cell proliferation and knockdown of AR expression similarly decreased cell

proliferation as well as inhibiting anchorage-independent growth of cells, cell migration

and cell invasion (Cochrane et al 2014, Barton et al 2015). The TNBC cell line, MDA-

MB-231 expresses very low levels of AR but AR nuclear localisation was inducible

following DHT treatment (Barton et al 2015). DHT was shown to stimulate ZEB1

expression as well as migration of MDA-MB-231 cells and these effects were reversed

by the anti-androgen, bicalutamide, indicating that androgens and the AR stimulate

EMT in ER-ve/PR-ve breast cancers (Graham et al 2010). In the ER+ve, PR+ve, and

AR+ve breast cancer cell lines, MCF-7 and T-47D, DHT but not the synthetic

androgen, R1881 has been shown to stimulate cell migration and to also reduce E-

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cadherin mRNA expression (Liu et al 2008, Zhu and Kyprianou 2010). Furthermore,

DHT was reported to induce AR binding to regulatory sequences in the E-cadherin

promoter, indicating direct regulation of E-cadherin expression (Liu et al 2008).

In addition to the steroid hormones, miRNAs, cytokines (e.g. tumour necrosis factor

alpha (TNFα)), growth factors (e.g. HGF, EGF) and their associated pathways, and

Hedgehog, WNT and NOTCH signalling also modulate EMT by altering the expression

of EMT regulators as well as mediators of cell migration and invasion (Lo et al 2007,

Gregory et al 2008, Fiaschi et al 2009, Li et al 2012). miRNAs are non-coding RNAs

that regulate gene expression at the post-transcriptional level by inhibiting protein

translation or inducing mRNA degradation (Wang and Zhou 2013). Both miRNA-

mediated stimulatory and inhibitory effects on breast cancer metastasis have been

reported, with members of the miR-200 family (miR-200a, miR-200b, miR-200c, miR-

141 and miR-429) and miR-205 antagonising EMT (Gregory et al 2008, Kong et al

2008, Korpal et al 2008). In support of this, expression of the miR-200 family members

and miR-205 were lower in normal murine mammary gland (NMuMG) cells treated

with TGF-β1 which induced EMT by downregulating E-cadherin expression,

upregulating levels of ZEB1 and N-cadherin, and promoting cell migration (Gregory et

al 2008, Korpal et al 2008). In contrast, overexpression of miR-200a, miR-200b and

miR-429 in TGF-β1-treated NMuMG and mesenchymal-like 4TO7 mammary

carcinoma cells reversed TGF-β1-induced EMT, indicating the inhibitory effects of

miR-200 family members on EMT (Gregory et al 2008, Korpal et al 2008).

Other miRNAs which facilitate EMT and EMT-associated cell migration and invasion

include miR-155, miR-9 and miR-10b (Ma et al 2007, Gregory et al 2008, Kong et al

2008). Expression of miR-155 is elevated in NMuMG cells following TGF-β1

treatment, whereas knockdown of miR-155 expression in TGF-β1-treated NMuMG

cells reversed TGF-β1-induced effects on EMT such as the downregulation of E-

cadherin levels and disruption of E-cadherin-associated tight junctions (Kong et al

2008). In the SUM-149 breast cancer cell line, overexpression of miR-10b increased in

vitro cell invasion and inhibited the translation of HOXD10 mRNA, resulting in

increased expression of regulators of cell migration and extracellular matrix remodelling

(e.g. RHOC, ITGA3, MMP14, urokinase-type plasminogen activator receptor (uPAR)),

thereby promoting an EMT programme (Ma et al 2007). Supporting this mechanism,

Chapter 5

162

transplantation of SUM-149 cells transfected with miR-10b into the mammary fat pad

of mice led to increased tumour invasion (Ma et al 2007).

TNF-α is a cytokine that has important roles in the regulation of inflammation and cell

homeostasis, and is also involved in tumour progression (Balkwill 2009). TNFα/TNFα

receptor 1 (TNFR1)-mediated activation of TNF receptor-associated factor (TRAF2)

recruits inhibitor of kappa B (IκB) kinase (IKK) to phosphorylate IκB, preventing its

binding and sequestration of the NFκB transcription factor (Wu and Zhou 2010). As a

result, release of NFκB leads to its nuclear localisation, where it binds to consensus

sequences (κB sites) to transcriptionally activate genes (Wang and Zhou 2013). Several

experimental studies have provided evidence that TNF-α is able to induce EMT in

breast cancer cells via activation of NFκB signalling. Treatment of the nonmalignant

breast epithelial cell line, MCF10A and the breast cancer cell line, BT-549 with TNF-α

resulted in transcriptional upregulation of TWIST1 via p56, a downstream target of

NFκB signalling (Li et al 2012). TWIST1 was also required for TNFα-induced EMT as

knockdown of TWIST1 expression in MCF10A cells led to decreased expression of N-

cadherin, fibronectin, TWIST1 and upregulation of E-cadherin, indicating inhibition of

EMT (Li et al 2012).

Growth factors such as hepatocyte growth factor (HGF), epidermal growth factor (EGF)

and fibroblast growth factors (FGF) regulate cell survival, proliferation, migration and

invasion following interaction with their cognate receptor tyrosine kinases (RTKs) and

activation of RAS signalling which transduces signals from RTKs (Wang and Zhou

2013). For example, EGF and transforming growth factor α (TGFα) induced a more

mesenchymal-like phenotype in the MDA-MB-468 breast cancer cell line, which was

associated with elevated expression of TWIST1 mRNA and protein, an important EMT

regulator (Lo et al 2007). In addition, activation of MAPK signalling in HEK293 and

MCF10A cells by transfection of RAS or treatment with TGF-β1 stimulated

phosphorylation of TWIST1 at serine 68 (S68), which is known to stabilise and protect

TWIST1 from ubiquitination and degradation (Hong et al 2011). This results in

increased expression of TWIST1, promoting TWIST1-induced EMT, which was

associated with downregulation of the expression of epithelial markers, E-cadherin, β-

catenin and γ-catenin, increased expression of vimentin, and increased cell invasion

(Hong et al 2011).

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163

Aberrant activation of the Hedgehog signalling pathway is a major cause of cancer cell

proliferation, survival, migration and invasion that may be in part mediated via EMT.

Overexpression of GLI1 in immortalised human pancreatic ductal epithelial cells

promoted invasion and markedly downregulated E-cadherin expression, while

inhibition of Hedgehog pathway signalling in the E3LZ10.7 pancreatic cancer cell line

decreased SNAI1 but upregulated E-cadherin mRNA levels, which are indicative of

inhibition of EMT (Feldmann et al 2007). In the mouse mammary gland, ectopic

expression of Gli1, which led to formation of hyperplastic lesions and breast tumour

development, also induced EMT-like characteristics (Fiaschi et al 2009). In that model,

levels of E-cadherin, which was expressed on baso-lateral surfaces of alveolar and

ductal epithelial cells in the mammary glands of wild-type mice, were markedly

downregulated in hyperplastic regions or ductal tumours of Gli1-overexpressing mice

where a large proportion of cells expressed SNAI1 (Fiaschi et al 2009). Paracrine

Hedgehog signalling involving tumour and stromal cell interactions is also important in

inducing stroma-mediated tumour growth and metastasis of breast cancers and other

cancers (Section 1.4.5.1). Transplantation of GLI2-transfected MDA-MB-231 cells into

mice has been shown to induce formation of osteolytic bone metastases in the femora or

tibiae of mice (Sterling et al 2006, Johnson et al 2011). In other cancers such as

pancreatic cancer, formation of liver metastases, which was inhibited by the Hedgehog

pathway antagonist, AZD8542, was observed in mice injected with both the BxPC3

pancreatic cancer cells and pancreatic cancer associated fibroblasts but not in mice

injected with BxPC3 cells only, indicating the involvement of paracrine Hedgehog

signalling in the metastasis of pancreatic tumours to the liver (Hwang et al 2012).

In this study, analysis of results from RT2 Profiler Human Breast Cancer PCR Arrays

identified downregulation of expression of genes associated with EMT in MCF-7 and

T-47D cells treated with DHT, cyclopamine or co-treated with DHT and cyclopamine

(Section 4.2.1). These findings were further investigated using RT2 Profiler EMT PCR

Arrays, which screened expression of 84 EMT-associated genes. As the EMT process

alters migration and invasion of cancer cells, the effects of DHT, cyclopamine and

DHT/cyclopamine treatments on the migration and invasion of MCF-7 cells were

evaluated to support bioinformatics predictions based on results of the EMT PCR

Arrays.

Chapter 5

164

5.2 Results

Analysis of results from RT2 Profiler Human Breast Cancer PCR Arrays (Section 4.2.1)

indicated that expression of the EMT regulators, TGFB1, SRC and NOTCH1, and the

EMT transcription factors, TWIST1 and SNAI2 were downregulated following 24 h of

treatment of MCF-7 and T-47D cells with 10-8 M DHT and/or 2 µM cyclopamine. The

decreased expression of these genes, which encode promotors of EMT suggested that

DHT and cyclopamine may reverse EMT and potentially drive an MET-like process,

inhibiting cell migration, invasion and cancer metastasis (Yilmaz and Christofori 2009).

In this study, DHT and cyclopamine regulation of EMT was further investigated using

RT2 Profiler Human EMT PCR Arrays which screened the expression of 84 EMT-

associated genes (Figure 3.1, Appendix 2). These analyses were again performed

following 24 h of 10-8 M DHT and/or 2 µM cyclopamine treatments of MCF-7 and T-

47D cells.

5.2.1 DHT and Cyclopamine Regulation of EMT-Associated Genes in Breast

Cancer Cells

Prior to studies using the RT2 Profiler Human EMT Arrays, androgen receptor (AR)

qPCR was performed to verify cDNA quality and to confirm the previously determined

effects of DHT and cyclopamine treatments on AR gene expression in MCF-7 and T-

47D cells. For this study, efficiency curves for AR and the housekeeping gene, GAPDH,

were initially constructed by amplification of the genes of interest in serial dilutions of

cDNA derived from MCF-7 and T-47D cells (Section 3.8.7). Efficiencies for AR and

GAPDH qPCR were between 95 and 101% in both the MCF-7 and T-47D cells (AR:

100.6% and 96.6% in MCF-7 and T-47D, respectively, and GAPDH: 95.8% and

101.4% in MCF-7 and T-47D cells, respectively) with correlation coefficient values

(R2) of the linear curves close to 1 (0.97-0.99) (Figure 5.1). Similar to results obtained

during my Honours project and in previous studies carried out in the laboratory, AR

mRNA levels were downregulated following DHT treatment and DHT/cyclopamine co-

treatment, while cyclopamine had little effects on AR levels (Figure 5.2).

To evaluate DHT and cyclopamine induced changes in the expression of genes

encoding regulators or effectors of EMT, RNA isolated from MCF-7 and T-47D cells

which had been treated for 24 h with 10-8 M DHT, 2 µM cyclopamine or a combination

of 10-8 M DHT and 2 µM cyclopamine (Section 3.8.1) was reverse transcribed (Section

Chapter 5

165

3.8.2.2) and added with RT2 SYBR Green Master Mix to 384 array plates that contained

primers for 84 EMT-associated genes (Section 3.8.8). qPCR was performed using a

Roche Light Cycler® 480 with threshold cycle (Ct) values derived from amplification

curves identifying 10 genes in both MCF-7 and T-47D cells which had Ct values of 0 or

40 cycles, indicating low or undetectable expression of these genes (Appendix 3, 4, 5,

Figure 5.3, 5.4). These included genes associated with cell invasion in MCF-7 cells such

as the ECM component, collagen 1 alpha 2 (COL1A2) as well as the matrix

metalloproteinases, MMP2 and MMP3, which degrade the ECM to facilitate cell

migration and invasion into the ECM. MMP2 gene expression was also undetectable in

T-47D cells, which may be due to the non-invasive characteristics of the MCF-7 and T-

47D cell lines. A study by Nawrocki Raby et al has similarly reported undetectable

levels of MMP2 mRNA in MCF-7 and T-47D cells (Nawrocki Raby et al 2001).

PDGFRB levels were also low in T-47D cells, in addition to SNAI2, bone

morphogenetic 2 (BMP2), forkhead box protein C2 (FOXC2) and caveolin 2 (CAV2)

(Figure 5.3 and 5.4).

Ct values of genes expressed in the cell lines were deposited into the SABiosciences

web-based data analysis programme to normalise gene expression to an average of the 5

housekeeping genes, ACTB, B2M, GAPDH, HPRT1 and RPLP0, and to calculate their

expression relative to control cultures treated with 0.1% (v/v) ethanol (vehicle) (Section

3.8.8, Appendix 4, 5). By setting the fold regulation threshold to 1.5-fold, a total of 31

genes were either up- or downregulated in MCF-7 cells cultured with any of the

treatments, while 56 genes were differentially expressed in DHT and/or cyclopamine

treated T-47D cells, with the affected genes predominantly downregulated (Figure 5.3,

5.4). In MCF-7 cells, DHT upregulated expression of 12 genes and decreased

expression of 11 genes, cyclopamine upregulated expression of 8 and downregulated

expression of 7, while DHT and cyclopamine co-treatment upregulated expression of 11

and downregulated expression of 9 genes (Figure 5.3). In T-47D cells, DHT upregulated

expression of 3 genes and downregulated expression of 34 genes, cyclopamine

upregulated expression of 2 and downregulated expression of 39, while DHT and

cyclopamine co-treatment upregulated expression of 4 and downregulated expression of

35 genes (Figure 5.4).

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166

Expression of the EMT or mesenchymal markers, SNAI1, TWIST1 and vimentin (VIM)

were downregulated in T-47D cells treated with DHT and/or cyclopamine (Figure 5.4).

The N-cadherin gene, CDH2, which is upregulated during EMT, was also

downregulated following DHT treatment of T-47D cells. These results were in

agreement with findings from the Human Breast Cancer PCR Array which showed that

the treatments downregulated expression of mesenchymal markers, indicating inhibition

of EMT (Section 4.2.1). In MCF-7 cells, expression of SNAI1 was reduced in

DHT/cyclopamine co-treated MCF-7 cells, however SNAI2 and TWIST1 were

upregulated by DHT and the combination of DHT and cyclopamine treatments (Figure

5.3). SNAI2 and TWIST1 have been characterised previously as AR target genes, and

candidate AREs have been identified in the promoter of the SNAI2 and TWIST1 genes

(Bolton et al 2007, Eide et al 2013). Levels of the epithelial marker, cytokeratin 19

(KRT19), which are reported to be decreased in breast tumours were upregulated in

DHT-treated MCF-7 cells and in DHT and/or cyclopamine treated T-47D cultures

(Figure 5.3, 5.4) (Fuchs et al 2002). These results indicate inhibition or reversal of

EMT.

To investigate the EMT-associated pathways or biological processes that were

potentially enriched, markedly regulated genes (≥1.5-fold) were analysed using the

REACTOME bioinformatics programme (Croft et al 2014). This programme maps the

regulated genes to an existing pathway database and predicts involvement of pathways

according to p-values or significance (ie. low or significant p-values indicate that the

association between genes of interest and pathways is not occurring randomly).

Analysis of data using REACTOME indicated that a similar set of pathways was

regulated in both MCF-7 and T-47D cells and that there were no marked differences in

the types of pathways regulated by DHT, cyclopamine and the combination of DHT and

cyclopamine (Table 5.1, 5.2). In both the MCF-7 and T-47D cells, the most significant

pathway/biological process which had the lowest p-value was extracellular matrix

(ECM) remodelling or organisation (Table 5.1, 5.2). Other pathways regulated in both

the cell lines by DHT and/or cyclopamine included the growth and developmental

pathway, WNT. DHT treatment alone also regulated genes associated with TGFβ

signalling in MCF-7 and T-47D cells, and in MCF-7 cells, cyclopamine and

DHT/cyclopamine co-treatment modulated cell-to-cell communication and BMP

signalling, respectively (Table 5.1, 5.2).

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167

(A)

Efficiency (E): 10-1/slope = 10(-1/-3.3079) = 2.006 %E = (E-1) × 100% = (2.006-1) × 100% = 100.6%

(B)


y = -3.3079x + 24.807 R² = 0.9871

0

5

10

15

20

25

0 0.5 1 1.5 2 2.5

Ave

rage

Ct

log cDNA

y = -3.4271x + 19.165 R² = 0.9731

0

2

4

6

8

10

12

14

16

18

0 0.5 1 1.5 2 2.5

Ave

rage

Ct

log cDNA

Chapter 5

168

(C)


(D)


Figure 5.1: Efficiency curves for AR and GAPDH qPCR in (A), (B) MCF-7 and (C), (D) T-47D cells. RNA extracted from MCF-7 or T-47D cells was reverse transcribed and 1:2, 1:10 and 1:20 dilutions of the (100ng) cDNA was prepared for (A), (C) AR and (B), (D) GAPDH qPCR. Experiments were repeated three times and representative results are shown.

y = -3.4047x + 25.52 R² = 0.9984

0

5

10

15

20

25

0 0.5 1 1.5 2 2.5

Ave

rage

Ct

log cDNA

y = -3.2893x + 20.62 R² = 0.9805

02468

101214161820

0 0.5 1 1.5 2 2.5

Ave

rage

Ct

log cDNA

Chapter 5

169

(A)

(B)

Figure 5.2: DHT and cyclopamine regulation of AR mRNA levels. Following treatment of (A) MCF-7 and (B) T-47D cells with 10-8 M DHT and/or 2 μM cyclopamine or 0.1% (v/v) ethanol (vehicle control) for 24 h, RNA was isolated and AR mRNA expression was evaluated by RT-qPCR. AR levels were normalised to corresponding GAPDH levels. Duplicate samples were prepared in each experiment and results are expressed as mean ± S.E.M. of normalised ABCG2 mRNA levels from three independent experiments. Statistical significance relative to controls was calculated using the Mann-Whitney U test, *p<0.05.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Control DHT Cyclopamine DHT +Cyclopamine

Nor

mal

ised

AR

mR

NA

Lev

els

Treatment (24hrs)

*

Control 10-8 M DHT 2 µM Cyclopamine

10-8 M DHT + 2 µM

Cyclopamine

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Control DHT Cyclopamine DHT +Cyclopamine

Nor

mal

ised

AR

mR

NA

Lev

els

Treatment (24hrs)

*

*

Control 10-8 M DHT 2 µM Cyclopamine

10-8 M DHT + 2 µM

Cyclopamine

Chapter 5

170

(A)

(B)

AHNAK

AKT1

BMP1

BMP2 -3.36

BMP7 -1.58

CALD1 -1.70

CAMK2N1

-13682.08

CAV2

CDH1

CDH2

COL1A2

COL3A1 5.86

COL5A2

CTNNB1

DSC2

DSP 2.95

EGFR

ERBB3

ESR1

F11R

FGFBP1

FN1

FOXC2

FZD7 2.34

GNG11

GSC

GSK3B

IGFBP4

IL1RN

ILK

ITGA5 -2.33

ITGAV

ITGB1

JAG1

KRT14

KRT19 1.59

KRT7 -1.67

MAP1B 2.38

MMP2

MMP3

MMP9 2.22

MSN

MST1R

NODAL

NOTCH1

NUDT13

OCLN

PDGFRB

PLEK2

PPPDE2

PTK2

PTP4A1 1.58

RAC1

RGS2 -1.62

SERPINE1

1.65

SIP1

SMAD2

SNAI1

SNAI2 8.40

SNAI3 -1.67

SOX10

SPARC -1.97

SPP1 -1.47

STAT3

STEAP1

TCF3

TCF4

TFPI2 2.48

TGFB1

TGFB2

TGFB3

TIMP1

TMEFF1

TMEM132A

TSPAN13

TWIST1 1.57

VCAN -1.59

VIM

VPS13A

WNT11

WNT5A

WNT5B 2.20

ZEB1

ZEB2

AHNAK

AKT1

BMP1

BMP2

BMP7

CALD1 -1.94

CAMK2N1

CAV2

CDH1

CDH2

COL1A2

COL3A1 3.42

COL5A2

CTNNB1

DSC2

DSP 2.72

EGFR

ERBB3

ESR1

F11R -1.52

FGFBP1

FN1

FOXC2

FZD7 2.61

GNG11

GSC

GSK3B

IGFBP4

IL1RN

ILK

ITGA5

ITGAV

ITGB1

JAG1

KRT14

KRT19

KRT7 -2.24

MAP1B

MMP2

MMP3

MMP9 2.67

MSN

MST1R

NODAL -2.61

NOTCH1

NUDT13

OCLN

PDGFRB

PLEK2

PPPDE2

PTK2

PTP4A1 1.48

RAC1

RGS2

SERPINE1

1.51

SIP1

SMAD2

SNAI1

SNAI2

SNAI3 -2.24

SOX10

SPARC

SPP1 -1.50

STAT3

STEAP1 1.82

TCF3

TCF4

TFPI2

TGFB1

TGFB2

TGFB3

TIMP1

TMEFF1

TMEM132A

TSPAN13

TWIST1

VCAN -1.54

VIM

VPS13A

WNT11

WNT5A

WNT5B 1.59

ZEB1

ZEB2

Chapter 5

171

(C)

Figure 5.3: DHT and cyclopamine regulation of EMT-associated genes in MCF-7 cells. Genes which were up- or downregulated by ≥1.5-fold in MCF-7 cells treated with (A) 10-8 M DHT, (B) 2 µM cyclopamine and (C) 10-8 M DHT and 2 µM cyclopamine are shown in the EMT PCR array layout with red signals indicating upregulation and green signals indicating downregulation of gene expression. Grey signals are genes which had very low expression or were undetectable in the cells.

AHNAK

AKT1

BMP1

BMP2 -2.51

BMP7

CALD1 -6.30

CAMK2N1

CAV2

CDH1

CDH2

COL1A2

COL3A1 5.29

COL5A2

CTNNB1 -1.62

DSC2 -1.81

DSP 2.87

EGFR

ERBB3

ESR1

F11R

FGFBP1

FN1

FOXC2

FZD7 1.95

GNG11

GSC -1.53

GSK3B

IGFBP4

IL1RN

ILK

ITGA5 -1.82

ITGAV

ITGB1

JAG1

KRT14

KRT19

KRT7

MAP1B 2.35

MMP2

MMP3

MMP9 2.84

MSN

MST1R

NODAL

NOTCH1

NUDT13

OCLN

PDGFRB

PLEK2

PPPDE2

PTK2

PTP4A1 1.53

RAC1

RGS2 2.43

SERPINE1

SIP1

SMAD2

SNAI1 -1.71

SNAI2 5.79

SNAI3

SOX10

SPARC

SPP1

STAT3

STEAP1

TCF3

TCF4

TFPI2 2.12

TGFB1

TGFB2

TGFB3

TIMP1

TMEFF1

TMEM132A

TSPAN13

TWIST1 2.00

VCAN -1.48

VIM

VPS13A

WNT11

WNT5A 1.90

WNT5B 2.06

ZEB1

ZEB2 -1.97

Chapter 5

172

(A)

(B)

AHNAK

AKT1

BMP1

BMP2

BMP7 -2.33

CALD1

CAMK2N1

-4.15

CAV2

CDH1

CDH2 -2.55

COL1A2

COL3A1

COL5A2 -1.72

CTNNB1 -1.54

DSC2 -1.59

DSP -2.30

EGFR

ERBB3 -1.48

ESR1 -1.86

F11R

FGFBP1 -1.47

FN1 -1.67

FOXC2

FZD7 -1.79

GNG11

GSC

GSK3B

IGFBP4 -1.84

IL1RN -2.83

ILK

ITGA5 -5.18

ITGAV

ITGB1

JAG1

KRT14

KRT19 2.77

KRT7 2.07

MAP1B

MMP2

MMP3

MMP9 -2.68

MSN

MST1R -1.71

NODAL -1.54

NOTCH1 -1.69

NUDT13

OCLN -1.73

PDGFRB

PLEK2 -2.61

PPPDE2

PTK2 -1.50

PTP4A1

RAC1

RGS2

SERPINE1

-8.18

SIP1

SMAD2 -1.52

SNAI1 -3.14

SNAI2

SNAI3

SOX10 -4.35

SPARC

SPP1

STAT3

STEAP1 4.72

TCF3

TCF4

TFPI2 -2.91

TGFB1 -4.12

TGFB2

TGFB3 -4.38

TIMP1 -2.22

TMEFF1

TMEM132A

TSPAN13

TWIST1 -2.48

VCAN -4.15

VIM -1.67

VPS13A

WNT11

WNT5A

WNT5B -2.00

ZEB1

ZEB2

AHNAK -1.80

AKT1 -1.60

BMP1 -1.55

BMP2

BMP7

CALD1

CAMK2N1

CAV2

CDH1 -1.48

CDH2

COL1A2 -2.33

COL3A1

COL5A2

CTNNB1 -1.94

DSC2 -1.62

DSP -1.59

EGFR

ERBB3 -1.51

ESR1 -1.46

F11R -1.54

FGFBP1 -2.48

FN1 -1.73

FOXC2

FZD7 -2.11

GNG11

GSC

GSK3B

IGFBP4 -1.94

IL1RN

ILK

ITGA5 -1.79

ITGAV -1.48

ITGB1 -1.47

JAG1 -1.51

KRT14

KRT19 1.80

KRT7 2

MAP1B -2.50

MMP2

MMP3

MMP9 -1.88

MSN

MST1R -1.96

NODAL

NOTCH1 -1.49

NUDT13 -1.58

OCLN -2.83

PDGFRB

PLEK2 -1.78

PPPDE2

PTK2 -1.49

PTP4A1

RAC1

RGS2

SERPINE1

-16.22

SIP1

SMAD2 -1.47

SNAI1 -1.75

SNAI2

SNAI3 -1.73

SOX10 -3.89

SPARC -1.84

SPP1

STAT3

STEAP1

TCF3

TCF4

TFPI2

TGFB1 -2.62

TGFB2

TGFB3

TIMP1 -1.85

TMEFF1

TMEM132A

-1.75

TSPAN13

TWIST1

VCAN

VIM -1.83

VPS13A

WNT11

WNT5A

WNT5B -1.47

ZEB1

ZEB2 -3.51

Chapter 5

173

(C)

Figure 5.4: DHT and cyclopamine regulation of EMT-associated genes in T-47D cells. Genes which were up- or downregulated by ≥1.5-fold in T-47D cells treated with (A) 10-8 M DHT, (B) 2 µM cyclopamine and (C) 10-8 M DHT and 2 µM cyclopamine are shown in the EMT PCR array layout with red signals indicating upregulation and green signals indicating downregulation of gene expression. Grey signals are genes which had very low expression or were undetectable in the cells.

AHNAK

AKT1 -2.31

BMP1

BMP2

BMP7 -2.20

CALD1

CAMK2N1

CAV2

CDH1

CDH2 1.76

COL1A2 -1.50

COL3A1

COL5A2 -1.56

CTNNB1 -1.96

DSC2 -1.71

DSP -2.11

EGFR

ERBB3

ESR1 -1.49

F11R

FGFBP1 -2.22

FN1 -1.68

FOXC2

FZD7 -2.13

GNG11

GSC

GSK3B

IGFBP4 -1.76

IL1RN -4.95

ILK

ITGA5 -2.82

ITGAV

ITGB1 -1.50

JAG1

KRT14

KRT19 3.10

KRT7 2.09

MAP1B

MMP2

MMP3

MMP9 -2.41

MSN

MST1R -1.84

NODAL -1.77

NOTCH1 -1.64

NUDT13

OCLN -1.62

PDGFRB

PLEK2 -2.51

PPPDE2

PTK2

PTP4A1

RAC1

RGS2 -1.92

SERPINE1

-2.02

SIP1

SMAD2

SNAI1 -3.45

SNAI2

SNAI3 -1.62

SOX10 -1.66

SPARC -1.69

SPP1

STAT3

STEAP1 5.40

TCF3

TCF4 -1.59

TFPI2

TGFB1 -3.13

TGFB2

TGFB3 -1.74

TIMP1 -2.14

TMEFF1

TMEM132A

TSPAN13

TWIST1 -2.00

VCAN -2.88

VIM -2.01

VPS13A

WNT11 -1.54

WNT5A

WNT5B

ZEB1

ZEB2

Chapter 5

174

Table 5.1: Pathway enrichment associated with DHT and cyclopamine regulated genes in MCF-7 cells.

Treatment Pathway, p-value

10-8 M DHT

1) Extracellular Matrix (ECM) Organisation (1.84×10-7) ECM Proteoglycans (4.3×10-5) Integrin Cell Surface Interactions (1.66×10-2) Degradation of ECM (3.13×10-2) Fibronectin Matrix Formation (1.6×10-2) Collagen Formation (2.16×10-2) Elastic Fibre Formation (1.61×10-4)

2) WNT Pathway (6.09×10-3)

3) TGFβ Pathway (1.55×10-2)

2 µM Cyclopamine

1) Extracellular Matrix (ECM) Organisation (1.21×10-3) ECM Proteoglycans (8.11×10-3) Integrin Cell Surface Interactions (1.03×10-2) Collagen Formation (1.05×10-2) Degradation of ECM (1.9×10-2)

2) WNT Pathway (1.64×10-3)

3) Cell-Cell Communication (2.57×10-2)

10-8 M DHT + 2 µM

Cyclopamine

1) Extracellular Matrix (ECM) Organisation (3.81×10-4) Elastic Fibre Formation (4.6×10-3) ECM Proteoglycans (1.27×10-2) Integrin Cell Surface Interactions (1.52×10-2) Fibronectin Matrix Formation (1.53×10-2) Collagen Formation (1.99×10-2) Degradation of ECM (2.88×10-2)

2) WNT Pathway (5.16×10-3)

3) BMP Pathway (5.36×10-2)

Genes regulated by ≥1.5-fold were analysed using the REACTOME open-source bioinformatics programme and database, which maps genes to pathways or functional processes. Using this programme, p-values represent the probability of non-random association of the genes of interest overlapping with the pathways. Therefore, the lower the p-value, the less likely that this overlap occurred by chance. Pathways with the lowest p-values are listed as top pathways enriched in the genes. Top three pathways are shown.

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Table 5.2: Pathway enrichment associated with DHT and cyclopamine regulated genes in T-47D cells.

Treatment Pathway, p-value

10-8 M DHT

1) Extracellular Matrix (ECM) Organisation (4.39×10-9) Elastic Fibre Formation (2.03×10-7) ECM Proteoglycans (2.26×10-7) Integrin Cell Surface Interactions (1.05×10-4) Non-integrin Membrane-ECM Interaction (3.44×10-4) Degradation of ECM (5.01×10-4) Fibronectin Matrix Formation (8.29×10-4) Collagen Formation (1.66×10-2)


3) WNT Pathway (3.11×10-2)

2 µM Cyclopamine

1) Extracellular Matrix (ECM) Organisation (3.87×10-10) ECM Proteoglycans (4.15×10-10) Elastic Fibre Formation (5.4×10-6) Integrin Cell Surface Interactions (7.34×10-6) Fibronectin Matrix Formation (8.29×10-6) Non-integrin Membrane-ECM Interaction (2.08×10-5) Degradation of ECM (5×10-5) Collagen Formation (2.05×10-3)


3) WNT Pathway (3.11×10-2)

10-8 M DHT + 2 µM

Cyclopamine

1) Extracellular Matrix (ECM) Organisation (5.6×10-9) ECM Proteoglycans (4.93×10-10) Elastic Fibre Formation (2.27×10-7) Fibronectin Matrix Formation (8.76×10-6) Non-integrin Membrane-ECM Interaction (2.28×10-5) Integrin Cell Surface Interactions (1.15×10-4) Degradation of ECM (5.46×10-4) Collagen Formation (1.74×10-2)


3) WNT Pathway (8.88×10-3)

Genes regulated by ≥1.5-fold were analysed using the REACTOME open-source bioinformatics programme and database, which maps genes to pathways or functional processes. Using this programme, p-values represent the probability of non-random association of the genes of interest overlapping with the pathways. Therefore, the lower the p-value, the less likely that this overlap occurred by chance. Pathways with the lowest p-values are listed as top pathways enriched in the genes. Top three pathways are shown.

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5.2.1.1 Effects of DHT and Cyclopamine on ECM Remodelling

During EMT, the ECM remodels following increased deposition and cross-linking of

fibrillar collagens in the ECM, and increased cell-to-ECM interactions/adhesions such

as the binding of cell surface receptors (e.g. integrins) to ECM components (e.g.

collagen, fibronectin, vitronectin) (Bonnans et al 2014). This facilitates cell migration

and invasion. Degradation of ECM components by enzymes, including matrix

metalloproteinases (MMPs) also facilitates cell movement and invasion into the ECM

via cleavage of ECM components to create tracks for migration (Bigg et al 2007, Wolf

et al 2013). In MCF-7 cells, DHT downregulated the mRNA levels of ECM

components, SPARC and versican (VCAN), although DHT treatment or

DHT/cyclopamine co-treatment also upregulated expression of collagen 3 alpha 1

(COL3A1) (Figure 5.5). In contrast to MCF-7 cells, DHT and cyclopamine treatments

predominantly downregulated expression of genes encoding ECM components in T-

47D cells, including the collagens, COL5A2, fibronectin (FN1) and SPARC, indicating

inhibition of cell-ECM interactions. SERPINE1 encodes plasminogen activator inhibitor

1 (PAI-1), and its increased expression is associated with EMT (Zavadil et al 2004,

Labelle et al 2011). Although SERPINE1 mRNA levels were upregulated by 1.5 and 1.6

fold in MCF-7 cells treated individually with DHT or cyclopamine, respectively, the

combination of DHT and cyclopamine treatments led to a smaller upregulation of

SERPINE1 levels. In contrast, SERPINE1 expression was markedly downregulated in

DHT and/or cyclopamine treated T-47D cells (Figure 5.5).

Formation of integrin- and fibronectin-mediated cell-to-ECM interactions on the cell

surface allows connection between cells and the ECM to induce re-organisation of the

intracellular actin cytoskeleton and initiation of cell movement (Bonnans et al 2014).

mRNA levels of integrin alpha 5 (ITGA5) were suppressed following DHT and

cyclopamine treatments in both MCF-7 and T-47D cells (Figure 5.5). According to the

KEGG database, interactions between the ECM components (e.g. collagens,

fibronectin) and integrins lead to remodelling of the actin cytoskeleton, formation of

cell edge protrusions (filopodia and lamellipodia) and cell motility. As such,

downregulation of expression of the ECM components and ITGA5 would impede

movement of MCF-7 and T-47D cells (Figure 5.6, 5.7). In T-47D cells, expression of

integrin beta 1 (ITGB1) was also downregulated which suggests that binding of

fibronectin to integrins in the cells is suppressed. Proteins encoded by ITGA5 and

ITGB1 along with the collagens and TGFB1, which were markedly downregulated

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following DHT and cyclopamine treatments of T-47D cells are also involved in non-

integrin membrane-ECM interactions. Expression of the bone morphogenetic proteins

(BMPs) encoded by BMP1, BMP2 or BMP7 was decreased following DHT and

cyclopamine treatments of MCF-7 and T-47D cells (Figure 5.5). BMPs are extracellular

growth factor proteins belonging to the TGFβ superfamily that can be sequestered in

elastic fibres in the ECM, blocking BMP from reaching its cellular receptors for

activation of BMP-mediated signalling which regulates cell proliferation, differentiation

and migration (Alarmo and Kallioniemi 2010). BMP-1 has been reported to interact

with fibronectin in the ECM and induce cross-linking of collagens, facilitating cell

migration and invasion (Maruhashi et al 2010). In breast cancer cell lines, MCF-7 and

MDA-MB-231, overexpression of BMP2 and BMP7 have also been shown to increase

the migration and invasion of cells (Clement et al 2005, Alarmo et al 2009). Therefore,

downregulation of expression of the BMP genes may indicate inhibition of cell motility

and invasiveness.

Expression of regulators of ECM degradation was also modulated by DHT and

cyclopamine treatments. MMP9 expression was upregulated by 2 to 3 fold following

treatment of MCF-7 cells with DHT, cyclopamine or the combination of DHT and

cyclopamine (Figure 5.3, 5.5). In contrast, in T-47D cells, expression of both MMP9

and tissue inhibitor of metalloproteinases, TIMP1 were markedly downregulated

following DHT and/or cyclopamine treatments (Figure 5.3, 5.5). TIMP1 exhibits dual

EMT-associated functions, inhibiting the proteolytic effects of MMPs and ECM

degradation, but also able to promote EMT via inducing the expression of TWIST1

(D'Angelo et al 2014).

5.2.1.2 DHT and Cyclopamine Regulation of the WNT and TGFβ Pathways

Overexpression of intermediates of pro-EMT signalling pathways such as WNT and

TGFβ increases expression of EMT transcription factors (e.g. SNAI1, TWIST1) and

molecules which lead to re-organisation of the actin cytoskeleton, cell-to-ECM

interactions, migration and invasion (Talbot et al 2012). Genes associated with WNT

signalling (WNT5B, FZD7, CTNNB1, TCF4) were differentially expressed in MCF-7

and T-47D cells following DHT and cyclopamine treatments. In MCF-7 cells, WNT5A

and WNT5B, which encode the non-canonical WNT5A and WNT5B ligands,

respectively, in the planar cell polarity (PCP) pathway, and the Frizzled receptor, FZD7

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were markedly upregulated by DHT and/or cyclopamine, suggesting that actin

cytoskeleton remodelling is activated (Figure 5.3, 5.5, 5.6). Despite this, β-catenin

(CTNNB1), a downstream effector of the canonical WNT signalling pathway which

facilitates TCF/LEF-mediated activation of the transcription of WNT target genes, was

found to be markedly downregulated following co-treatment with DHT and

cyclopamine (Figure 5.3, 5.5, 5.6). Decreased expression of CTNNB1 indicates

inhibition of canonical WNT signalling and potentially inhibition of WNT-induced

EMT as WNT/β-catenin target genes include the EMT transcription factors, TWIST1

and SLUG (Borchers et al 2001, Vallin et al 2001). In T-47D cells, DHT and

cyclopamine treatments markedly reduced expression of the WNT-associated genes,

WNT5B, FZD7, CTNNB1 as well as TCF4, which is a major effector of canonical WNT

signalling (Faro et al 2009). These results indicate that the treatments inhibit both

canonical and non-canonical WNT pathways in T-47D cells via downregulation of

WNT/β-catenin effectors and WNT5B and FZD7 in the PCP pathway (Figure 5.4, 5.5,

5.7).

Regulators of the TGFβ signalling pathway were also downregulated in T-47D cells

treated with DHT and/or cyclopamine (Figure 5.4 and 5.7). As TGFβ signalling induces

EMT and EMT-associated cell migration and invasion in cancer cells via upregulation

of EMT transcription factors, reduced expression of TGFB1 which encodes the TGF-β1

ligand and the pathway effector and transcription factor, SMAD2, indicate that the

transcriptional regulatory activity of the pathway was reduced (Xu et al 2009). In

support of this result, expression of SERPINE1, which has been shown to be a target of

TGFβ signalling, was also downregulated (Figure 5.4, 5.5) (Zavadil et al 2004, Labelle

et al 2011).

5.2.1.3 Classification of DHT and Cyclopamine-Specific Pathways

To identify pathways that are specific to DHT or cyclopamine treatments, three-wheeled

Venn diagrams were constructed (Figure 5.8). In MCF-7 and T-47D cells, treatments

with DHT, cyclopamine and the combination of DHT and cyclopamine regulated

expression of genes involved in EMT-associated processes or components including the

ECM proteoglycans (SPARC, COL3A1, COL1A2, VCAN, COL5A2), integrin cell

surface interactions (ITGA5, COL3A1, ITGB1, COL1A2, COL5A2), degradation of the

ECM (MMP9) and WNT signalling pathway (CTNNB1, AKT1, TCF4, FZD7) (Figure

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(A)

WNT Pathway

Programmed Cell Death

TGFβ Pathway

Non-Integrin Membrane-ECM

Interaction

Elastic Fibre Formation

Fibronectin Matrix Formation

Degradation of ECM

Integrin Cell Surface Interaction

ECM Proteoglycans

Collagen Formation

Extracellular Matrix (ECM) Organisation

COL1A2

TGFB3 VCAN SERPINE1 FN1

SPARC

ITGB1

TGFB1 COL1A2 COL5A2 ITGA5

COL5A2

F11R

ITGB1 FN1

FN1 BMP1 COL1A2

COL5A2

TIMP1 MMP9

ITGB1 FN1 ITGA5

TGFB1

ITGB1 FN1

ITGA5 BMP7 TGFB3

BMP1

MMP9 COL5A2

COL1A2

ITGB1 FN1

COL1A2 TGFB1 COL5A2

OCLN

DSP PTK2 CTNNB1 VIM

AKT1

SMAD2

F11R SERPINE1 WNT5B TCF4

TGFB1

AKT1

FZD7 CTNNB1

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(B)

Figure 5.5: Classification of DHT and cyclopamine regulated EMT-associated genes in MCF-7 and T-47D cells. Heatmaps indicate genes regulated by ≥1.5-fold and classified into pathways or processes using the REACTOME bioinformatics programme in (A) T-47D and (B) MCF-7 cells.

Magnitude of log2 (Fold Change)

0 -2.432 2.432

COL3A1

SPARC VCAN COL3A1 ITGA5

SERPINE1

COL3A1

ITGA5 ITGA5 BMP2 BMP7

MMP9

SERPINE1

FZD7 CTNNB1

Extracellular Matrix (ECM) Organisation

WNT Pathway

Programmed Cell Death

DSP CTNNB1 WNT5B

TGFβ Pathway


Fibronectin Matrix Formation Degradation of ECM

Integrin Cell Surface Interaction

ECM Proteoglycans

WNT5A

(A)

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183

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184

Chapter 5

185

(A)

(B)

Figure 5.8: Pathways associated with genes regulated by ≥1.5-fold following DHT and cyclopamine treatments of (A) MCF-7 and (B) T-47D cells.

DHT Cyclopamine

DHT + Cyclopamine

TGFβ Pathway

Integrin Cell

Surface Interaction


ECM Proteoglycans

Degradation of ECM

WNT Pathway

MCF-7

DHT Cyclopamine

DHT + Cyclopamine

Collagen Formation

WNT Pathway

TGFβ Pathway

T-47D

ECM Proteoglycans

Integrin Cell Surface

Interaction

Degradation of ECM

Fibronectin Matrix

Formation Elastic Fibre Formation

Fibronectin Matrix

Formation

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5.5, 5.8). Additionally, in T-47D cells, DHT and/or cyclopamine treatments also

regulated genes which encode components of TGFβ signalling (TGFB1, SERPINE1,

F11R) and formation of the fibronectin matrix (ITGA5, ITGB1, FN1) and elastic fibres

(BMP7, TGFB3, TGFB1, ITGA5, ITGB1). DHT-treated and DHT and cyclopamine co-

treated MCF-7 cultures exhibited downregulated expression of genes associated with

fibronectin matrix (ITGA5) and elastic fibre (BMP2) formation, while collagen

formation (MMP9, COL5A2) was regulated in T-47D cells (Figure 5.5, 5.8).

5.2.2 DHT and Cyclopamine Effects on MCF-7 Cell Migration and Invasion

Results from analysis of the EMT PCR Arrays indicated that DHT and cyclopamine

may inhibit or mediate the reversal of EMT in breast cancer cells as the treatments

predominantly downregulated expression of genes which encode intermediates of the

pro-EMT, WNT and TGFβ signalling pathways, factors mediating interaction between

cells and the ECM and EMT mesenchymal markers. Further investigation of the EMT

PCR Array findings by validation of mRNA and protein expression of the DHT and

cyclopamine regulated genes was not able to be carried out due to time constraints but

may be performed in future studies. As cancer-associated EMT promotes cell migration

and invasion, inhibition of these processes would support findings from the PCR arrays

that EMT is being inhibited or reversed. Therefore, to investigate DHT and cyclopamine

regulation of cell migration and invasion, in vitro scratch wound healing assays were

performed to evaluate cell migration, and BioCoat™ Matrigel™ Invasion Chamber and

3D Matrigel™ colony formation assays were used to investigate cell invasion.

The migration of DHT and/or cyclopamine treated MCF-7 cells into a wound area

created by scratching confluent monolayer cultures was determined by measuring the

percentage of wound closure after 72 h. Prior to the generation of the ‘wound’, cells

were pre-treated with 10-8 M DHT and/or 2 µM cyclopamine for 4 days (Section

3.1.5.6). In control (0.1% (v/v) ethanol)-treated MCF-7 cultures, 75±5.19% of the

wounds were repopulated with cells at 72 h (Figure 5.9). In contrast, in cyclopamine-

treated cells, wound closure was decreased to 57.7±1.02% at 72 h, while in DHT-treated

and DHT/cyclopamine co-treated cells, wound closure of only 29.0±1.48% and

36.3±1.86%, respectively, was evident at 72 h (Figure 5.9). The decreased wound

closure in the treated cells was evident at 24 h post wound generation and persisted for

the duration of the treatment periods (Figure 5.9).

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To investigate DHT and cyclopamine effects on MCF-7 cell invasion, BioCoat™

Matrigel™ Invasion Chamber assays were initially used. For these assays, MCF-7 cells

were seeded into the upper chamber of BioCoat™ Matrigel™ Invasion Chambers and the

numbers of cells that had migrated into the lower chamber by invasion and migration

through the Matrigel™ layer were calculated (Section 3.1.5.7). When MCF-7 cells were

initially seeded at 5×104 cells per well as reported previously (Girnita et al 2012, Park et

al 2013), only ~20 cells had invaded into the lower chamber at 24 h (data not shown).

The seeding densities of MCF-7 cells were therefore increased (1×105 and 2×105 cells

per chamber) and cultures were incubated for longer periods (up to 48 h), however the

numbers of cells invading into the lower chamber remained at 20-39 cells (data not

shown). As the low numbers of cells invading through the Matrigel™ would not permit

detection of inhibition of invasion by the treatments, use of this method was ceased.

In order to investigate cell invasion, an alternative Matrigel™-based method, the 3D

Matrigel™ colony formation assay was performed. This assay has been used previously

to study the morphologies of normal and malignant epithelial cells in three-dimensional

cultures and to investigate the extent of cancer cell invasion into Matrigel™ (Debnath et

al 2003, Lee et al 2007, Quail et al 2012). For this assay, MCF-7 cells were cultured in

Matrigel™ containing 10-8M DHT, 2µM cyclopamine or the combination of 10-8M DHT

and 2 µM cyclopamine for 10 days (Section 3.1.5.8). Images of colonies formed in the

Matrigel™ were quantitated using Image J to estimate colony size (pixels), which

represents the ability of colonies to invade into the surrounding Matrigel™. In

comparison to control (0.1% (v/v) ethanol)-treated MCF-7 cultures (100%),

cyclopamine treatment of MCF-7 cells decreased the median colony size to

87.2±11.81% (which did not reach significance), and following DHT and the

combination of DHT and cyclopamine treatments, the median colony sizes were

significantly decreased to 58.1±1.46% and 62.9±5.21% of controls, respectively (Figure

5.10). Formation of smaller colonies in DHT and/or cyclopamine treated cultures

indicated inhibition of invasion of MCF-7 colonies into Matrigel™.

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188

Figure 5.9: DHT and cyclopamine effects on MCF-7 cell migration. MCF-7 cells were pre-treated for 4 days with 10-8 M DHT, 2 µM cyclopamine or the combination of 10-8

M DHT and 2 µM cyclopamine prior to generation of wound areas between the confluent cells. Images of the wound areas were captured every 24 h post scratching of the cell monolayer and the percentages of wound closure relative to values at time 0 were calculated using TScratch 1.0. Experiments were repeated three times and representative results (mean ± S.E.M.) are shown. Statistical significance relative to vehicle controls (0.1% (v/v) EtOH) was calculated using the Mann-Whitney U test, *p<0.05.

0

10

20

30

40

50

60

70

80

90

0 24 48 72

Wou

nd c

losu

re (%

)

Time (hours)

Ethanol control

DHT

Cyclopamine

DHT + Cyclopamine

0h

24h

48h

72h

Control 10-8 M DHT

10-8 M DHT + 2 µM

Cyclopamine 2 µM

Cyclopamine

*

*

*

Vehicle (0.1% (v/v) EtOH) DHT Cyclopamine

DHT + Cyclopamine

Chapter 5

189

0 10000 20000 30000 40000 500000

10

20

Colony size (pixels)

Col

onie

s

0 10000 20000 30000 40000 500000

10

20


Col

onie

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0 10000 20000 30000 40000 500000

10

20


Col

onie

s

0 10000 20000 30000 40000 500000

10

20


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onie

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(A)

Control 10-8 M DHT

2 µM Cyclopamine 10-8 M DHT +

2 µM Cyclopamine

Chapter 5

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0

20

40

60

80

100

120

Med

ian

Num

ber

of P

ixel

s (%

)

Treatment

(B)

Figure 5.10: DHT and cyclopamine regulation of MCF-7 cell invasion. MCF-7 cells were cultured for 10 days in Matrigel containing 10-8 M DHT and/or 2 μM cyclopamine. (A) Number of colonies and colony size (pixels) were quantitated using Image J, with representative images (day 10) shown. (B) Median colony size (pixels) is depicted for each of the treatment groups. Experiments, performed in triplicate wells, were repeated three times. Representative results of the average of median pixels ± S.E.M. from the triplicate wells are shown. Statistical significance was calculated relative to results from vehicle (0.1% (v/v) ethanol) treated cultures by Mann-Whitney U test, *p<0.05.

Control (0.1% (v/v)

EtOH)

10-8 M DHT

2 µM Cyclopamine

10-8 M DHT + 2 µM

Cyclopamine

* *

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191

5.3 Discussion

The transition from an epithelial to a mesenchymal phenotype of cancer cells (EMT) is

associated with tumour invasion and metastasis. Hallmarks of EMT include elevated

expression of the mesenchymal markers, vimentin and N-cadherin, increased levels of

transcription factors, SNAI1, SLUG, TWIST1, and a concomitant decrease in

expression of epithelial markers such as the cytokeratins. The EMT programme is

induced by a number of signalling pathways, notably the TGFβ, WNT and NOTCH

pathways, and involves a series of events that promote cell migration and invasion,

including dissociation of cell-to-cell adhesion, formation of focal adhesions or cell-to-

ECM adhesions mediated by integrins, collagens and fibronectin, and proteolytic

cleavage of the ECM (Yilmaz and Christofori 2009, Tsai and Yang 2013). In this study,

preliminary findings from investigation of DHT- and cyclopamine-induced regulation

of expression of breast cancer-associated genes in MCF-7 and T-47D cells using RT2

Profiler Human Breast Cancer PCR Arrays (Section 4.2.1) indicated that the treatments

reduced expression of TGFβ1, SRC, NOTCH1 and TWIST1, suggesting inhibition or

reversal of EMT.

A more specific examination of DHT and cyclopamine effects on EMT using Human

EMT PCR Arrays identified that in addition to downregulation of the expression of

mesenchymal markers and upregulation of epithelial marker expression, genes whose

encoded products mediate other EMT-associated processes and pathways were also

downregulated. These processes included remodelling of the ECM (VCAN, SPARC,

collagens, integrins (ITGA5 and ITGB1)), ECM degradation (MMP9), TGFβ signalling

(TGFB1, SMAD2, SERPINE1), and WNT signalling (FZD7, WNT5B). Similar findings

have been reported in previous studies using cell lines of other cancer types. For

example, in the LNCaP prostate cancer cell line, high-throughput screening of androgen

regulated genes also identified a number of EMT-associated genes regulated by the

synthetic androgen, R1881. These genes encoded proteins involved in cell-to-cell or

cell-to-ECM interactions (e.g. integrin alpha V (ITGAV), laminin α4, fibronectin (FN1),

occludin), TGFβ signalling (SERPINE1) and WNT signalling (FZD3) (DePrimo et al

2002). Treatment of ovarian cancer cells with 3-keto-N-(aminoethyl-aminocaproyl-

dihydrocinnamoyl)-cyclopamine also downregulated levels of mRNAs encoding

membrane type 1 matrix metalloproteinase (MT1-MMP) and β1 integrin, both of which

induce remodelling of the ECM during EMT (Liao et al 2009).

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Pathway enrichment analysis of the EMT arrays identified that DHT and/or

cyclopamine treatments reduced expression of genes associated with the TGFβ

signalling pathway; TGFB1, SMAD2 and SERPINE1 in T-47D cells. As SERPINE1 is a

TGFβ signalling-induced target gene, the PCR array results indicated that DHT and

cyclopamine inhibited TGFβ-mediated gene transcription (Xu and Kapoun 2009).

SERPINE1 has also been shown to be upregulated in cancer-associated EMT, and

therefore its downregulation suggests reversal of EMT (Zavadil et al 2001, Xu and

Kapoun 2009, Labelle et al 2011). Of interest, reciprocal regulation of the AR or

Hedgehog signalling pathways and the TGFβ pathway has been reported in a number of

cancer cell lines (Kang et al 2001, Steinway et al 2014). Direct interaction between

SMAD3 and the AR were demonstrated in the SW480.7 colon carcinoma cell line and

overexpression of both SMAD3 and AR in the cells enhanced AR-mediated

transactivation, thereby suggesting that SMAD3 could function as a co-activator of AR

transcriptional activity (Kang et al 2001). TGF-β1 treatment of the human

hepatocellular carcinoma cell line, PLC/PRF/5, which stimulated EMT by increasing

expression of N-cadherin and decreasing expression of E-cadherin, also upregulated

GLI2 mRNA and protein expression, suggesting that the Hedgehog pathway may be

involved in mediating TGFβ-induced EMT in hepatocellular carcinoma (Steinway et al

2014). In addition to findings from the present study showing DHT and cyclopamine

induced downregulation of the expression of genes associated with the TGFβ pathway,

it is possible that decreased TGFβ pathway activity reciprocally regulates AR and

Hedgehog signalling, with these interactions potentially important in the manifestation

or modulation of EMT.

Elevated expression of WNT ligands, FZD receptors and the TCF/LEF transcription

factors, and increased nuclear levels of β-catenin in the canonical WNT/β-catenin

signalling pathway are associated with progression of EMT (Wu et al 2012a,

MacMillan et al 2014). DHT and cyclopamine treatments downregulated mRNA levels

of the β-catenin gene, CTNNB1, in MCF-7 cells, and CTNNB1, TCF4, WNT5B and

FZD7 in T-47D cells, with co-treatment of the cells with DHT and cyclopamine

enhancing DHT- or cyclopamine-induced downregulation of CTNNB1 in MCF-7 cells

and TCF4 in T-47D cells. These results indicated inhibition of canonical WNT

signalling, and supporting this hypothesis, AKT1, a target gene of WNT signalling, was

shown in the EMT arrays to be repressed in DHT and cyclopamine co-treated T-47D

cells (Wang et al 2011b). An interesting finding from the EMT PCR arrays was that

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WNT5B levels were downregulated in T-47D cells, which was consistent with decreased

WNT signalling and inhibition of EMT, but WNT5A and WNT5B levels were

upregulated in DHT and/or cyclopamine treated MCF-7 cells. E2 treatment of T-47D

cells has been shown to increase WNT5B mRNA levels (Saitoh and Katoh 2002), while

treatment of MCF-7 cells with recombinant WNT5B was reported to increase cell

invasion, a result that is consistent with both induction of WNT signalling and

promotion of EMT. Regulation of WNT5A and WNT5B mRNA and protein levels by

DHT and cyclopamine treatments should be validated in future studies incorporating

longer timepoints and utilising anti-androgens and Hedgehog pathway ligands to

confirm results in MCF-7, T-47D and other breast cancer cell lines. Although

upregulated WNT5A and WNT5B expression in MCF-7 cells suggests induction of WNT

signalling, which would promote EMT, the marked downregulation of CTNNB1 that

encodes the WNT signalling effector β-catenin indicates decreased WNT signalling and

therefore, inhibition of EMT, a hypothesis that is more consistent with results of

migration and invasion assays.

Interactions between integrin heterodimers (αvβ3, α6β1, α6β4, α5β1 and α1β1) and

components of the ECM (e.g. collagens, laminin, fibronectin) facilitate cell migration

(Bonnans et al 2014). In MCF-7 cells, elevated expression of α5β1 integrin has been

associated with increased cell invasion (Morozevich et al 2009). In the present study,

DHT and cyclopamine treatments of MCF-7 cells downregulated expression of ITGA5,

which encodes α5 integrin while in T-47D cells, ITGA5 and ITGB1, which encodes β1

integrin were downregulated. α5 integrin is a major partner of the β1 integrin subunit

(Goel et al 2010). Therefore, downregulation of α5 and/or β1 integrin suggests

inhibition of the formation of α5β1 integrins and suppression of cell migration and

invasion. Fibronectin in the ECM is a ligand which binds to α5β1 integrins to induce

cell migration (Jia et al 2004). In the EMT PCR array, the gene encoding fibronectin,

FNI, was also downregulated in T-47D cells following DHT and cyclopamine

treatments, further supporting inhibition of integrin α5β1-fibronectin interaction and cell

invasion mediated by integrin α5β1 heterodimers. Hormones other than androgens have

been shown to modulate expression of integrins, for example, E2 induces elevation of

integrin α5, α6 and β1 mRNA levels in endothelial cells (Cid et al 1999). The E2-

stimulated increase in ITGA5 expression in MCF-7 cells has been shown to be mediated

via formation of ERα/Sp1 complexes which bind to an Sp1 binding site located in the

ITGA5 promoter (Sisci et al 2010). Since androgens inhibit oestrogen/ER-mediated

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effects, it is possible that DHT-induced downregulation of α5 and β1 integrins observed

in this study may be mediated in part via inhibition of ER signalling (Peters et al 2009,

Need et al 2012).

Genes encoding type I and V collagens, COL1A2 and COL5A2, respectively, were

markedly downregulated in T-47D cells treated with DHT and/or cyclopamine whereas

in MCF-7 cells, the type III collagen, COL3A1 was upregulated. Collagens interact with

receptors on the cell surface (e.g. integrins) to initiate cell migration, and elevated

synthesis and deposition of collagens in the ECM induce cross-linking of the ECM

which contributes to cell invasion (Provenzano et al 2006). In vivo, deposition of type I

and III collagen bundles was shown to be localised at the invasive front of infiltrating

breast ductal carcinomas, indicating the role of collagens in facilitating tumour invasion

(Kauppila et al 1998). Therefore, downregulation of COL5A2 and COL1A2 in T-47D

cells suggests reversal of cell invasiveness. In contrast, levels of COL3A1 were

upregulated following DHT treatment of MCF-7 cells, a similar finding to previously

reported upregulation of Col3a1 in DHT-treated murine skeletal muscle tissue

(Svensson et al 2010). Matrix metalloproteinases (MMPs) contribute to cell invasion

but are also capable of controlling the aberrant overproduction of collagens by cleaving

and inactivating collagens as well as other ECM components. For example, MMP2 and

MMP9 have been shown to cleave type I and III collagens (Bigg et al 2007). In MCF-7

cells, MMP9 expression was markedly upregulated following DHT and/or cyclopamine

treatments, and it is possible that DHT-induced increases in COL3A1 expression may be

counteracted by secretion of MMP9 enzymes.

Upregulation of mesenchymal markers and downregulation of epithelial markers are

characteristics of EMT. DHT and/or cyclopamine treatments of MCF-7 and T-47D cells

markedly downregulated expression of the EMT-inducing transcription factor, SNAI1 in

MCF-7 and T-47D cells as well as the EMT mesenchymal markers, VIM and N-

cadherin (CDH2) in T-47D cells. The epithelial marker, cytokeratin-19 (KRT19) was

also upregulated in both cell lines in response to DHT and cyclopamine treatments.

These results are in agreement with an earlier study which showed that ectopic

expression of GLI1 in mammary gland of mouse models, which led to formation of

breast tumours, was associated with EMT progression, with expression of E-cadherin

downregulated and SNAI1 upregulated in the tumours (Fiaschi et al 2009). However,

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others have reported that DHT stimulates EMT in MCF-7 and T-47D cells by

transcriptionally downregulating the expression of E-cadherin, results that are

contradictory to those observed in this thesis study (Liu et al 2008, Zhu and Kyprianou

2010). Androgens have been reported previously to exhibit divergent effects in

individual breast cancer cell lines, in particular the MCF-7 cell line, in which androgens

are documented to be either inhibitory or to stimulate proliferation (Birrell et al 1995,

Szelei et al 1997, Greeve et al 2004, Macedo et al 2006, Cops et al 2008). While

differences in the androgen responsiveness of breast cancer cell lines may in part be due

variation between isolates of the cell lines and use of cell lines that have undergone

extensive passaging, potentially altering the ratio of AR to ER expression in the cells,

reasons for these well-documented discrepancies are generally unknown. However, the

previously successful treatment of breast cancers with androgens (Section 1.4.4.4) and

the fact that MCF-7 cells have been classified as luminal A (Section 1.2.1) are

consistent with an inhibition of EMT following DHT treatment.

Although comprehensive validation and investigation of the EMT PCR Array results are

important future directions of this work, downregulation of the expression of EMT-

associated genes following DHT and/or cyclopamine treatments of MCF-7 and T-47D

cells suggested that the treatments reverse EMT. The abilities of cancer cells to migrate

and invade into the surrounding tumour microenvironment are promoted by EMT,

therefore DHT and cyclopamine treatments were hypothesised to inhibit the migration

and invasion of breast cancer cells. In support of this hypothesis, inhibition of MCF-7

cell migration following DHT, cyclopamine and DHT/cyclopamine treatments was

shown using wound healing assays in the present study. In contrast to these results,

others have reported stimulation of MCF-7 cell migration by DHT, which was

associated with DHT-induced activation of EMT (Liu et al 2008, Zhu and Kyprianou

2010). Androgens, DHT and R1881, have been shown to increase LNCaP prostate

cancer cell migration and to also downregulate expression of E-cadherin and re-organise

the actin cytoskeleton, which are indicative of an induction of EMT (Liao et al 2003,

Zhu and Kyprianou 2010). Inhibition of MCF-7 cell migration following cyclopamine

treatment is in agreement with previous studies where knockdown of GLI1 in MCF-7

cells was shown to abrogate cell migration (Sun et al 2014). However, in a study by

Sabol et al, cyclopamine-mediated downregulation of MCF-7 cell migration, which was

investigated using wound healing assays, was not significant, possibly because wound

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closure was measured at 26 h while in this study, cyclopamine was found to markedly

inhibit MCF-7 cell migration at later timepoints (up to 72 h) (Sabol et al 2014).

DHT and DHT/cyclopamine treatments were also shown to inhibit MCF-7 cell invasion

using 3D Matrigel™ colony formation assays. Initial studies of MCF-7 cell invasion

were unsuccessful using the BioCoat™ Matrigel™ Invasion Chambers likely due to the

poor invasive abilities of MCF-7 cells (McSherry et al 2011). In other studies where

MCF-7 cell invasion was investigated, BioCoat™ Matrigel™ Invasion Chambers were

similarly not used, while in most studies which reported usage of these chambers,

stimulation of MCF-7 cell invasion was being evaluated (Wicki et al 2006, Rosman et

al 2008, Walsh et al 2010, McSherry et al 2011, Yang and Kim 2014). As the invasion

chamber assays were unsuitable in this study, an alternative 3D Matrigel™ colony

formation assay, which has been used to investigate cancer cell invasion, was performed

(Debnath et al 2003, Lee et al 2007, Quail et al 2012). Androgen regulation of MCF-7

cell invasion has not been investigated previously, however in the prostate cancer cell

lines, LNCaP and MDA PCa 2b, DHT treatment or overexpression of the AR has been

shown to increase cell invasion (Hara et al 2008, Li et al 2009, Zhu and Kyprianou

2010). In this study, cyclopamine treatment alone did not significantly alter MCF-7 cell

invasion into Matrigel™, a result that is in contrast to previous reports which found

inhibition of MCF-7 cell invasion following knockdown of GLI1 or treatment with

cyclopamine (Che et al 2013, Sun et al 2014). However, in those studies, cell invasion

was investigated using BioCoat™ Matrigel™ Invasion Chambers and the MCF-7 cells

were more invasive compared to MCF-7 cells used in this study (Che et al 2013, Sun et

al 2014). Furthermore, the cultures were treated with 10-20 fold higher doses of

cyclopamine compared to the present study and higher concentrations of cyclopamine

have been documented previously to exhibit effects that are not specific to inhibition of

SMO (Zhang et al 2009, Che et al 2013). For the more metastatic breast cancer cell

lines, MDA-MB-231 and SKBR3, cyclopamine has been reported to inhibit cell

invasion and for other cancer cell lines such as the SW480 colorectal cancer cells,

cyclopamine also repressed cell invasion in association with decreased mRNA levels of

SLUG, SNAI1 and TWIST1 and increased E-cadherin levels, indicating inhibition or

reversal of EMT (Kameda et al 2009, Qualtrough et al 2015).

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In summary, DHT and cyclopamine treatments of MCF-7 and T-47D cells were found

to decrease the expression of a number of genes encoding regulators and mediators of

EMT. These included TGFβ and WNT signalling pathway intermediates, mediators of

cell-to-ECM interactions and EMT core transcription factors. In combination with the

upregulation of epithelial and downregulation of mesenchymal marker expression, this

pattern of gene expression indicated a reversal or inhibition of EMT, a hypothesis

supported by the reduced migration and invasion of DHT and cyclopamine treated

MCF-7 cells. Overall, results of this thesis study have shown that DHT and

cyclopamine treatments of breast cancer cells inhibit cellular processes that promote

progression of tumours, development of drug resistance and progression of EMT. The

findings support further investigation to determine whether targeting of the AR and

Hedgehog signalling pathways improves the efficacy of current breast cancer treatment

regimens and increases progression-free and overall survival.

Chapter 6

General Discussion

Chapter 6: General Discussion

198

6.1 General Discussion

Breast cancer associated mortality is most frequently due to re-initiation of tumour

growth and development of metastatic tumours despite initial success of disease

treatments. Tumour growth and metastasis result from the dysregulation of a number of

pathways including cell proliferation, apoptosis, drug resistance, EMT, cell migration,

cell invasion and initiation of tumour-associated angiogenesis. As such, combinations of

drugs that together inhibit these critical processes are likely to improve therapeutic

outcomes including progression-free and overall survival of breast cancer patients.

Underpinning the development and application of these treatment strategies is the

characterisation of pathways and associated mechanisms regulated by both current and

novel therapies, enabling selection of the most effective combinations of drugs for the

treatment of different breast cancer subtypes and individual tumours.

The uncontrolled growth of breast tumours resulting from aberrant regulation of the cell

cycle can be targeted by existing breast cancer therapies including chemotherapeutic

drugs and drug combinations (anthracyclines, taxanes, cyclophosphamide /

methotrexate / fluorouracil (CMF)), endocrine therapies (tamoxifen, fulvestrant,

aromatase inhibitors) and the anti-HER2 monoclonal antibody, trastuzumab, with

effects including induction of cell cycle arrest in G1/S or G2/M and cell cycle exit in

susceptible tumours (Le et al 2003, Pohl et al 2003, Dalvai and Bystricky 2010, Hallett

et al 2015). The ability of cells to proceed from G1 to M phase of the cell cycle is

modulated by appropriate expression of positive (e.g. cyclin D, cyclin E, cyclin-

dependent kinases (CDKs)) and negative regulators (CDK inhibitors, p21Cip1/Waf1,

p27Kip1), which when dysregulated, may stimulate cell growth (Deshpande et al 2005,

Wang et al 2009a). As these factors modulate distinct stages of the cell cycle, profiling

of their expression in breast tumours may be used as a predictive marker for responses

to established or novel breast cancer treatments (Kurebayashi et al 2011, Magbanua et

al 2015).

Chemotherapeutic agents, for example CMF (cyclophosphamide / methotrexate /

fluorouracil) that inhibit the proliferation of rapidly dividing cells by intercalating DNA,

impede the progression of cells from G1 to S phase, where DNA synthesis occurs (Pohl

et al 2003, Kurebayashi et al 2011). Expression of p27Kip1 may serve as a predictive

marker of response as breast tumours with low p27Kip1 expression respond poorly to


199

CMF (Han et al 1999). The ER antagonist, tamoxifen, and the pure anti-oestrogen,

fulvestrant increase the proportion of MCF-7 cells in the G0/G1 phase of the cell cycle,

reflecting the mechanism of action of these treatments which is to repress ERα-

mediated expression of target genes, several of which are cell cycle regulators

(Lykkesfeldt et al 1984, Dalvai and Bystricky 2010). For example, inhibition of cell

proliferation induced by tamoxifen and fulvestrant are associated with downregulation

of E2/ER-mediated transcription of cyclin D1, c-Myc and cyclin E leading to the

accumulation of cells in the G1 phase of the cell cycle. This is associated with reduced

phosphorylation of retinoblastoma protein (Rb), elevated expression of p21Cip1/Waf1 and

p27Kip1, and reduced formation and activity of cyclin-CDK complexes (e.g. cyclin D1-

CDK4, cyclin E-CDK2) (Watts et al 1995, Cariou et al 2000, Dalvai and Bystricky

2010). Similar to tamoxifen, other SERMs such as raloxifene inhibit MCF-7 cell

proliferation by preventing transition of cells from G1 to S phase (Fryar et al 2006,

Shibata et al 2010).

The aromatase inhibitors, anastrazole and letrozole have also been shown to induce cell

cycle arrest in G0/G1 phase in MCF-7 cells (Itoh et al 2005). Recently, a newer group of

aromatase inhibitors (3β-hydroxyandrost-4-en-17-one, 5α-androst-2-en-17-one, androst-

4-en-17-one, 4α,5α-epoxyandrostan-17-one), which are chemically modified forms of

androstenedione, a substrate of aromatase, were identified to similarly inhibit cell cycle

progression, supporting the application of these agents for the treatment of human breast

tumours (Amaral et al 2013). In the study by Amaral et al, 3β-hydroxyandrost-4-en-17-

one and 5α-androst-2-en-17-one were shown to inhibit cell cycle progression from G1

to S phase, while androst-4-en-17-one and 4α,5α-epoxyandrostan-17-one increased the

number of cells in G2 phase, indicating that the aromatase inhibitors alter the cell cycle

via different mechanisms (Amaral et al 2013). Androgens have also been reported to

alter the expression of cell cycle regulators and induce accumulation of cells in G1

phase, with DHT treatment of MCF-7 cells decreasing expression of CDK2 and CDK4

but upregulating levels of the cell cycle inhibitor and AR target, p27Kip1 (Greeve et al

2004). In the present study, PCR array analysis of breast cancer-associated genes

indicated that DHT downregulated expression of cyclin D1, c-MYC as well as c-JUN,

which promote cell cycle progression.


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The expression of cell cycle regulators is modified by activation of signalling pathways

(e.g. MAPK, ERK, PI3K) following ligand binding to cell surface receptors (e.g. EGF,

IGF-1, TGFβ, Hedgehog, WNT), frequently promoting proliferation. For this reason,

inhibition of signalling pathways may be used to reduce proliferation, for example,

inhibition of PI3K signalling by the small molecule inhibitor, LY294002 downregulates

expression of cyclinD1/D3 and CDK4 in MCF-7 cells, impeding cell cycle progression

(Wang et al 2014). In the present and in previous studies (Che et al 2013), inhibition of

the Hedgehog signalling pathway by cyclopamine was shown to downregulate cyclin

D1 mRNA levels, which was correlated with MCF-7 cell cycle arrest in G1 phase and

inhibition of cell proliferation (Che et al 2013).

In line with the well-characterised abnormal expression of cell cycle regulators that are

evident in cancers, specific inhibitors of cell cycle regulators have been developed as

novel treatment strategies. For example, PD0332991 (palbociclib), an inhibitor of

CDK4 and CDK6 (CDK4/6), inhibits the proliferation of breast cancer cell lines,

including MCF-7 and the HER2-overexpressing SUM-190 and MDA-MB-361 cell lines

(Finn et al 2009). Due to its effects on CDK4/6 function, PD0332991 arrests the cell

cycle in G1 phase and reduces phosphorylation of Rb (Finn et al 2009). Three CDK4/6

inhibitors, palbociclib, abemaciclib, and LEE011 have entered clinical trials for solid

tumours including locally advanced and metastatic breast cancer, and results indicated

that the drugs were safe and prolonged progression-free survival of patients when

administered in combination with endocrine therapies (Bardia et al 2014, Patnaik et al

2014, Asghar et al 2015, Finn et al 2015). Supporting this novel strategy of direct

targeting of cell cycle progression, palbociclib was granted accelerated approval in

February 2015 for use in combination with the aromatase inhibitor, letrozole in

postmenopausal women with ER+ve/HER2-ve breast cancers (Finn et al 2015, Mayer

2015).

Cancer treatments that induce apoptosis frequently do so by regulation of the expression

of anti-apoptotic (e.g. BCL2) and pro-apoptotic (e.g. p53) regulators (Arun et al 2003,

Buchholz et al 2003). Mutation or altered expression of these regulators, which leads to

disruption of the balance between cell proliferation and apoptotic cell death,

contributing to tumour growth, similarly indicates low responsiveness of tumour cells to

a variety of therapies (Tabuchi et al 2009, AbuHammad and Zihlif 2013). Consistent


201

with this hypothesis, BCL2 was markedly upregulated in MCF-7 cells selected for

resistance to doxorubicin, suggesting that elevated expression of BCL2 supports cell

growth in drug-resistant breast cancer cells (AbuHammad and Zihlif 2013). Tamoxifen,

fulvestrant and androgens such as DHT in the present study downregulate BCL2 and c-

MYC, and upregulate p53 mRNA levels in MCF-7, T-47D and ZR-75-1 cells,

supporting the inhibitory effects of these agents in breast cancer cells (Lapointe et al

1999, Zhang et al 1999, Thiantanawat et al 2003). Treatment of primary breast tumours

with the chemotherapeutic agents, docetaxel and doxorubicin also reduce expression of

BCL2 (Buchholz et al 2003), and natural compounds such as curcumin, a polyphenolic

compound found in the spice turmeric, which has been proposed as a cancer treatment,

elevated the ratio of the pro-apoptotic gene, BAX to anti-apoptosis (pro-survival) gene,

BCL2 in MCF-7 cells (Masuelli et al 2013).

Although current and novel therapies effectively inhibit proliferation and induce

apoptosis in breast cancer cells via regulation of expression of genes that encode

mediators of these processes, development of treatment resistance occurs frequently,

leading to regrowth of the tumours (Holohan et al 2013). Therapies given in

combination to patients have been shown to prolong resistance-free survival. For

example, treatment with the chemotherapeutic agents, doxorubicin, docetaxel and

cyclophosphamide as a combination decreased the occurrence of drug resistance in

patients with node-positive and early breast cancers (Mackey et al 2013). Similarly,

combinations of chemotherapy and trastuzumab (e.g. docetaxel / carboplatin /

trastuzumab) in HER2-overexpressing breast cancers increased time to disease

progression and improved patient survival (Valero et al 2011). In support of these

findings, trastuzumab, when combined with doxorubicin, epirubicin and paclitaxel was

found to exhibit additive inhibitory effects on in vitro and in vivo growth of the HER2-

overexpressing breast cancer cell lines, SK-BR-3 and MDA-MD-361 (Pegram et al

2004). Fulvestrant was also shown to increase the sensitivity of ER+ve MCF-7 and ZR-

75-1 cells to cytotoxic agents, taxanes (paclitaxel, docetaxel), doxorubicin, vinorelbine

and fluorouracil when fulvestrant was given in combination with the cytotoxic agents

(Ikeda et al 2011).

While treatment of breast cancer patients with multiple therapeutic drugs has been

successful in delaying development of drug resistance, patients may be given drugs that


202

are unnecessary, or which result in side effects and toxicity that necessitate dose

reduction or early cessation of treatment, potentially accelerating disease progression.

Characterisation of the mechanisms underlying treatment resistance may improve the

selection of therapies or combinations of therapies that maximise the duration of

responses but minimise long-term impact on quality of life. Factors which have been

shown to engender drug resistance in cancers include disruption of mechanisms

associated with breakdown or metabolism of drugs, alteration of drug detoxification,

mutation or loss of expression of drug targets, aberrant activation of secondary

pathways and increased drug efflux (Housman et al 2014).

Targeted therapies and anti-cancer drugs are metabolised by enzymes such as the

cytochrome P450 (CYP) enzymes which, depending on the drug, either produce the

toxic or more toxic form of the drug, or alternatively detoxify it. For example, CYP2D6

metabolises tamoxifen to the active metabolites, 4-hydroxytamoxifen and endoxifen.

CYP2D6 is highly polymorphic and a number of CYP2D6 allelic variants (e.g.

CYP2D6*10, CYP2D6*9, CYP2D6*10, CYP2D6*17, CYP2D6*29, CYP2D6*36,

CYP2D6*37, CYP2D6*41) have been associated with reduced function of CYP2D6

(Marez et al 1997, Sachse et al 1997, Borges et al 2006). In women who express the

CYP2D6*10 variant, serum levels of 4-hydroxytamoxifen were found to be lower and

disease-free survival rates were also poorer following tamoxifen treatment, compared to

women expressing more highly active CYP2D6 alleles (Xu et al 2008). Another CYP

enzyme, CYP3A4 detoxifies docetaxel and elevated expression of CYP3A4 in recurrent

breast tumours has been associated with poorer responses of the tumours to docetaxel

(Sakurai et al 2011). Hence, profiling of the expression of drug metabolising enzymes

may predict tumour responsiveness to therapy and allow for more appropriate treatment

selection. Inhibitors of CYP3A4 (e.g. ritonavir) in combination with chemotherapy have

been evaluated in human breast tumours but side effects associated with the drug

combinations suggest the need for development of alternative drugs to target this CYP

enzyme (Swiecicki et al 2013).

A number of drugs bind specifically to their cellular targets (e.g. oncoproteins, hormone

receptors) to exhibit their effects, but mutations or altered conformation of these drug

targets reduce binding or binding affinity and constitute a major mechanism of drug

resistance. In breast cancer, mutations, for example, in the oestrogen receptor gene,


203

ESR1, and HER2, have been reported to reduce binding affinities or prevent binding of

anti-oestrogens to ERα and anti-HER2 monoclonal antibodies to HER2, resulting in

resistance to the targeted therapies (Anido et al 2006, Mitra et al 2009, Merenbakh-

Lamin et al 2013, Rexer et al 2013, Robinson et al 2013, Jeselsohn et al 2014). For

example, in HER2-overexpressing breast tumours, p95HER2, a truncated form of HER2

which lacks the binding region for trastuzumab, confers resistance of tumours to

trastuzumab (Anido et al 2006). Other examples of mutations affecting binding of

therapeutic drugs similarly contribute to drug resistance. The EGFRT790M mutation in

the EGFR kinase domain in lung adenocarcinomas decreases binding of the EGFR

tyrosine kinase inhibitors, gefitinib and erlotinib, resulting in drug resistance, while

secondary mutations in the BCR-ABL fusion gene (e.g. BCR-ABLT315I) induce

conformational changes in BCR-ABL and prevent binding of imatinib, an Abelson

tyrosine kinase inhibitor, leading to imatinib resistance (Shah et al 2002, Pao et al

2005). To overcome this form of resistance, novel therapeutic drugs targeting

EGFRT790M and BCR-ABLT315I mutations have been developed (Noronha et al 2008,

Sequist et al 2015), and pre-clinical and clinical studies have also shown that binding of

lapatinib to p95HER2 reduced tumour growth and improved overall survival of patients

with p95HER2 expressing tumours (Scaltriti et al 2007, Hutchinson 2010, Scaltriti et al

2010).

Anti-oestrogens including tamoxifen are often successful in the treatment of ERα-

expressing breast tumours but drug resistance can occur, with a proportion of the

tamoxifen-resistant tumours (~17%) shown to have become ERα-ve (Johnston et al

1995, Gutierrez et al 2005). One mechanism by which ERα expression may be

downregulated is by epigenetic modification (e.g. DNA methylation, histone

deacetylation) of the ERα gene, ESR1. DNA methylation induces re-organisation of the

chromatin structure which reduces binding of transcriptional regulators and hence

represses gene transcription (Bird 2002, Leu et al 2004). In breast cancer,

hypermethylation of a CpG island encompassing the ESR1 promoter, which decreases

ERα expression, has been demonstrated in ERα-ve but not in ERα+ve breast tumours

(Kim et al 2004). Inhibition of DNA methyltransferase, an enzyme which catalyses

DNA methylation, by 5’-aza-2’-deoxycytidine (deoxyC) was reported to re-activate

ERα expression in ER-ve breast cancer cells, MDA-MB-231, and similarly, inhibition

of histone deacetylases increased ERα expression in MDA-MB-231 cells and enhanced

their sensitivity to 4-hydroxytamoxifen (Sharma et al 2005, Zhou et al 2007).


204

Supporting the findings of these experimental studies, a clinical trial evaluating a

combination of tamoxifen and the histone deacetylase inhibitor, vorinostat in tamoxifen-

resistant breast tumours reported that vorinostat increased the responses of tumours to

tamoxifen (Munster et al 2011).

An alternative mechanism that promotes drug resistance in breast cancers is aberrant

activation and expression of intermediates of secondary pathways that stimulate tumour

growth. For example, the EGFR/HER2 pathway has been implicated in resistance of

ER+ve breast tumours to anti-oestrogens (Shou et al 2004, Massarweh et al 2008).

EGFR and HER2 protein expression as well as levels of phosphorylated (activated)

p42/p44 and p38 MAPKs, which are downstream intermediates of EGFR/HER2

signalling, were shown to be upregulated in tamoxifen-resistant MCF-7 xenograft

(murine) models. Treatment of the mice with gefitinib, a TKI which inhibits EGFR, in

combination with tamoxifen delayed the time to tamoxifen resistance, supporting

involvement of this secondary signalling mechanism (Massarweh et al 2008).

Development of resistance to trastuzumab has been associated with hyperactivation of

PI3K/AKT signalling and elevated expression of IGF1R (Berns et al 2007, Dieras et al

2007, Browne et al 2011). Increased PI3K/AKT signalling which is indicated by loss of

PTEN expression was observed in the trastuzumab-resistant BT-474 breast cancer cell

line (Berns et al 2007). Additionally, expression of IGF1R was elevated in SKBR3 cells

that were selected for resistance to trastuzumab, with inhibition of IGF1R by siRNA in

combination with trastuzumab shown to reduce cell proliferation. As IGF1R-siRNA and

trastuzumab individually had little effects on cell proliferation, these findings indicated

that inhibition of IGF1R enhanced the responsiveness of trastuzumab-resistant SKBR3

cells to trastuzumab (Browne et al 2011). Overall, blocking of multiple signalling

pathways can potentially delay development of resistance, however use of inhibitors of

multiple pathways is also likely to increase side effects and this needs to be balanced

with benefits associated with the treatments such as improvement in disease-free and

overall survival.

Drug resistance is also caused by overexpression of the ABC drug efflux transporters

which are capable of exporting a variety of drugs especially chemotherapeutic agents.

Overexpression of ABCB1 and ABCG2 was initially identified in cancer cell lines

including MCF-7 cells which had been selected for resistance to doxorubicin and


205

mitoxantrone, implicating the ABC transporters in the development of drug resistance

(Roninson et al 1986, Doyle et al 1998, Miyake et al 1999). As such, downregulation of

the expression and function of these transporters would be expected to delay or prevent

ABC transporter-mediated resistance of tumours. In support of this hypothesis,

treatment of doxorubicin-resistant and ABCB1-overexpressing MCF-7 cells (MCF-

7/Adr) with the ABCB1 inhibitor, verapamil increased the sensitivity of cells to the

cytotoxic effects of doxorubicin (Mealey et al 2002). The proliferation of ABCG2-

transfected MCF-7 cells, which were resistant to mitoxantrone cytotoxicity, was

decreased following co-treatment of the cells with the ABCG2 inhibitor, fumitremorgin

C (FTC), indicating that FTC reversed ABCG2-mediated resistance of MCF-7 cells to

mitoxantrone (Rabindran et al 2000). A number of ABC transporter inhibitors (e.g.

Zosuquidar, Elacridar, Tariquidar) have been developed but in clinical studies of

cancers including breast cancer, small cell lung cancer and acute myeloid leukaemia

(AML), these agents did not improve responses of cancers to chemotherapy (e.g.

doxorubicin, vincristine, topotecan) or increase overall survival despite successes of

these agents in enhancing the sensitivity of cancer cells and tumours to

chemotherapeutic agents in pre-clinical and early clinical studies (Mistry et al 2001,

Kruijtzer et al 2002, Gerrard et al 2004, Pusztai et al 2005, Kuppens et al 2007,

Morschhauser et al 2007, Saeki et al 2007, Cripe et al 2010). Of note, the ABC

transporter inhibitors evaluated in clinical trials were predominantly inhibitors of

ABCB1 and only a few of these such as elacridar were shown to cross-react with

ABCG2 (Kruijtzer et al 2002).

A growing number of studies have identified that inhibitors of signalling pathways (e.g.

PI3K/AKT, MAPK/ERK (MEK), Hedgehog, WNT), clinically available targeted drugs

(e.g. tyrosine kinase inhibitors) and natural compounds (e.g. vitamin D3, curcumin) are

capable of downregulating ABC transporter expression and/or function and may

therefore be evaluated as treatments to reverse ABC transporter-mediated drug

resistance in breast tumours (Chearwae et al 2006, Katayama et al 2007, Dai et al 2008,

Chikazawa et al 2010, Goler-Baron et al 2012, Wei et al 2012). For example, the PI3K

inhibitor, LY294002 did not alter ABCG2 protein levels but increased the sensitivity of

mitoxantrone-resistant MCF-7 cells (MCF-7/MX) to the ABCG2 substrates,

mitoxantrone and topotecan, which may be attributed to inhibition of ABCG2 efflux

activity (Goler-Baron et al 2012). Treatment of ABCB1-transfected MCF-7 and MDA-

MB-231 cells, which were resistant to paclitaxel, with the MEK inhibitor, U0126,


206

downregulated ABCB1 expression and elevated paclitaxel cytotoxic effects in the cells

(Katayama et al 2007). In this study, the androgen ligand, DHT downregulated ABCG2

mRNA and protein expression in MCF-7 cells and this was associated with increased

sensitivity to mitoxantrone, and although the Hedgehog signalling inhibitor,

cyclopamine did not alter ABCG2 expression, the decreased ABCG2 localisation to

membrane-associated complexes induced in cyclopamine-treated MCF-7 cells was

associated with increased sensitivity of the cells to mitoxantrone, presumably via

inhibition of ABCG2 efflux function.

In cell lines, resistance to therapeutic agents is frequently associated with

overexpression of ABC transporters however in human breast tumours, ABC

transporters are not markedly overexpressed although their expression is generally

correlated with poorer responses to chemotherapy (Kanzaki et al 2001, Faneyte et al

2002, Burger et al 2003, Yuan et al 2008). Recent research has identified that ABC

transporters, in particular ABCG2 are overexpressed in breast cancer stem cells and in

cancer stem cells of other tumour types (Kim et al 2002, Engelmann et al 2008, Zhang

et al 2013a, Guzel et al 2014). Overexpression of ABC transporters in cancer stem cells

protects the stem cells from exogenous and endogenous toxic influences as solid

tumours frequently contain regions of necrosis and apoptosis, with an inefficient blood

supply to remove metabolic toxins and toxins produced by dead and dying cells (Dean

et al 2005). The high levels of ABC transporter expression also confer resistance of

stem cells to therapeutic drugs, allowing the cancer stem cells to “differentiate” into

cancer cells and initiate tumour relapse (Kim et al 2002, Ding et al 2010, Jiang et al

2012). Therefore, therapeutic strategies to deplete or eliminate the cancer stem cell

population or to reduce its chemoresistance are important for prolonging recurrence-free

and thus overall survival. In previous studies, inhibition of pathways associated with

stem cell development including the Hedgehog, WNT and NOTCH pathways has been

shown to decrease the proliferation of cancer stem-like cells and to curb in vitro and in

vivo tumorigenesis associated with these cells (Bar et al 2007, Chikazawa et al 2010,

McAuliffe et al 2012). Inhibitors of NOTCH and WNT signalling are also being

investigated in clinical trials for breast cancer and for other solid tumours

(ClinicalTrials.gov Identifier: NCT01616758, NCT01345201). In the present study,

DHT was found to downregulate ABCG2 expression and membrane-associated

localisation of ABCG2 in breast cancer stem-like cells isolated from the MCF-7 breast

cancer cell line which, based on results from parental MCF-7 cells, may increase the


207

sensitivity of the stem-like cells to mitoxantrone. Although cyclopamine did not

markedly alter total ABCG2 protein levels, the treatment reduced ABCG2 levels in

membrane-associated complexes in breast cancer stem-like cells, indicating that

inhibition of the Hedgehog pathway may also affect sensitivity to chemotherapeutic

agents by modulating ABCG2 localisation. Thus, potential beneficial effects of adjunct

treatments with androgens or Hedgehog signalling inhibitors may be in part mediated

by their downregulation of ABC transporter efflux activity and consequent increase in

chemosensitivity of both breast cancer cells and breast cancer stem cells.

Tumour metastasis is a major cause of breast cancer-related death. Patients with

metastatic breast tumours are treated with chemotherapy, hormonal therapies or anti-

HER2 monoclonal antibodies depending on the breast cancer subtype and the general

health of the patient, however, the disease commonly relapses. As combination

therapies have been shown to improve treatment efficacy, adjunct or additional

therapies that extend the progression-free survival of patients with advanced breast

cancer are constantly evaluated. A number of inhibitors of signalling pathways such as

the PI3K/AKT/mTOR and IGF pathways are currently in or have recently been

investigated in clinical trials for metastatic breast cancer (Robertson et al 2013, Qiao et

al 2014, Gonzalez-Angulo et al 2015). However, growth factor inhibitors are often

associated with treatment resistance and worse treatment outcome due to activation of

other growth factor family members to sustain tumour growth (Haluska et al 2007, Lo

et al 2007, Robertson et al 2013). For example, treatment of metastatic breast cancer

patients with the anti-IGF1R monoclonal antibody, ganitumab, in combination with the

anti-oestrogen, fulvestrant or the aromatase inhibitor, exemestane, in a phase II clinical

trial, was shown to result in shorter progression-free survival compared to patients

treated with the hormonal therapy alone (Robertson et al 2013). It has been proposed

that inhibition of IGF1R may induce expression of growth hormone and IGF1 to

support the continued growth of breast tumours (Haluska et al 2007).

EMT is a developmental programme which induces the transition of epithelial-like cells

into mesenchymal-like cells that have enhanced abilities to migrate and invade. During

tumour progression to metastasis, EMT is commonly induced, allowing tumour

dissemination from the original tumour site to a new site or organ, where MET, the

reverse process of EMT, is activated to allow growth of the metastatic tumour deposit.


208

The processes involved in EMT that modify the tumour cells and their surrounding

stroma are regulated by signalling pathways (e.g. TGFβ, WNT, NOTCH). Therefore,

inhibition of EMT-associated signalling pathways and processes may delay the

development of metastatic tumours and improve progression-free and overall survival, a

treatment strategy that is being assessed in experimental models and early clinical trials.

For example, in a mouse model of breast cancer bone metastasis, the anti-TGF-β1

antibody, ID11 decreased tumour burden in bone and reduced the number of osteolytic

lesions (Biswas et al 2011). Withaferin A (WFA), an extract from the plant Withania

somnifera inhibited MDA-MB-231 breast cancer cell migration and invasion by

inducing depolymerisation of the EMT marker and cytoskeletal element, vimentin

(Thaiparambil et al 2011). Intetumumab, an anti-αV integrin monoclonal antibody was

reported to decrease the formation of brain metastases in mice transplanted with

metastatic breast cancer cells, 231BR-HER2 (Wu et al 2012b). Phase I and II clinical

trials for intetumumab have been carried out for advanced solid tumours including

breast and prostate cancers and melanoma, with the agent shown to be safe, without

major cytotoxicity and to improve overall patient survival when combined with

chemotherapy (Mullamitha et al 2007, Chu et al 2011, O'Day et al 2011). Results from

this thesis indicated that DHT and cyclopamine treatments repressed EMT as genes

which encode mediators of EMT-inducing signalling pathways (TGFβ, WNT) and ECM

components were markedly downregulated, with these findings supported by the

suppression of migration and invasion of MCF-7 cells. The inhibition of multiple facets

of the EMT programme by DHT and cyclopamine provide evidence for further

development of androgens and Hedgehog signalling inhibitors as adjunct therapies that

impede breast tumour progression to metastatic disease.

Angiogenesis is another process essential for tumour progression as it promotes

development and assembly of the blood vasculature, a critical source of nutrients

required for tumour growth (Kerbel 2008). Regulators of angiogenesis include vascular

endothelial growth factors (VEGF), fibroblast growth factors (FGF), platelet derived

growth factors (PDGF) and their receptors, and intermediates of signalling cascades

(e.g. Delta/Notch) (Hicklin and Ellis 2005, Lieu et al 2011, Heldin 2013, Zhou et al

2013). Combinations of anti-angiogenesis agents such as the humanised monoclonal

antibody targeting VEGF-A, bevacizumab, or small molecule inhibitors of VEGFR and

PDGFR, sorafenib and sunitinib, with anti-oestrogens, trastuzumab or chemotherapy

have been shown in pre-clinical studies to delay tumour progression (Qu et al 2008,


209

Coxon et al 2009). For example, overexpression of VEGF in MCF-7 cells was

associated with development of resistance to tamoxifen and formation of lung

metastases in mouse xenograft models, indicating the importance of tumour-associated

angiogenesis in disease progression (Qu et al 2008). When mice transplanted with

MCF-7 cells were treated with a combination of tamoxifen and motesanib, a muti-

targeted inhibitor of VEGFR1, VEGFR2, VEGFR3, PDGFR and c-KIT, inhibition of

tumour growth was enhanced compared to either treatment alone (Coxon et al 2009).

These studies support inclusion of agents which inhibit angiogenesis pathways to

treatment of breast cancer in order to delay tumour progression. In this study, DHT and

cyclopamine downregulated expression of the angiogenesis-inducing regulators, JUN,

NOTCH1 and inhibitor of DNA binding 1 (ID1), and the effects of these treatments on

tumour-associated angiogenesis may be evaluated in future studies using MCF-7

xenografts grown in immunosuppressed mice.

Several clinical trials have assessed combinations of angiogenesis inhibitors with

established breast cancer therapies. For example, a phase III study of bevacizumab and

letrozole in ER+ve advanced breast cancer showed that the combination of these agents

increased progression-free survival of patients (Dickler et al 2015). An ongoing study is

similarly evaluating bevacizumab and letrozole or fulvestrant in locally recurrent or

metastatic ERve/PR+ve/HER2-ve breast cancers (Martín et al 2013). Several previous

clinical trials investigating the combination of bevacizumab with chemotherapy and/or

trastuzumab produced disappointing results with small effects on progression-free

survival and no improvement in overall survival (Miller et al 2007, Miles et al 2010,

Robert et al 2011, Smith et al 2011, Brufsky et al 2012). However, the combination of

bevacizumab, trastuzumab and docetaxel in HER2-overexpressing breast cancers was

found to increase progression-free survival of patients with tumours expressing VEGF-

A, suggesting that only a proportion of breast cancer patients would benefit from

treatment regimens that include bevacizumab (Gianni et al 2013). Similarly, in

experimental studies, VEGF-overexpressing MCF-7 xenografts were found to be more

sensitive to the effects of bevacizumab compared to xenografts of parental MCF-7 cells

(Gokmen-Polar et al 2014). These findings indicate that use of biomarkers, for example

VEGF expression may be required to select patients whose breast tumours would

respond most favourably to bevacizumab-containing treatment combinations.


210

Tumour progression is regulated by a number of processes, including cell proliferation,

suppression of apoptosis, drug resistance, cell migration/invasion, EMT and

angiogenesis, and therefore optimal treatment would involve a combination of

therapeutic drugs that target as many of these pathways as possible to improve

progression-free and overall survival of patients. To enhance the efficacy of treatment

regimens, the aim for cancer management is the development and refinement of

personalised therapy, whereby treatment combinations are tailored to individual patients

and their tumours. Although this goal has not yet been achieved, considerable

improvements have been made in our understanding of mechanisms associated with

tumour progression. These have led to the development of a number of novel agents that

have been or are being evaluated in pre-clinical and clinical trials as well as

identification of previously uncharacterised effects mediated by current therapeutic

agents that pre-empt modification of their clinical use. Implementation of personalised

cancer therapies by definition requires the establishment of biomarkers that predict

sensitivity or resistance to individual and combinations of treatments as well as disease

prognosis. Underpinning these advances in the clinical application of novel therapies is

a comprehensive knowledge of the mechanisms of action of current and novel agents to

devise the appropriate application of the drugs and drug combinations for different

stages and subtypes of breast tumours. Results of this thesis describing the effects of

androgens and Hedgehog signalling inhibitors on pathways that contribute to breast

cancer progression add to this knowledge, thereby indicating how these agents can

contribute to treatment regimens already established or under development.

Implementation of androgens and/or Hedgehog signalling inhibitors in breast cancer

management will require additional in vitro and in vivo studies that similarly evaluate

members of these classes of pharmaceutical agents that are able to be administered to

humans as well as biomarkers of treatment sensitivity or resistance.

6.2 Future Directions

In this study, AR- and Hedgehog pathway-mediated regulation of breast cancer-

associated genes, including genes encoding the ABCG2 drug efflux transporter and

EMT regulators were evaluated by treatment of MCF-7 and T-47D cells with the

androgen, 5α-dihydrotestosterone (DHT) and the small molecule Hedgehog pathway

inhibitor, cyclopamine. More extensive analysis of ABCG2 and EMT showed that DHT


211

and cyclopamine treatments downregulated ABCG2 expression and efflux activity as

well as suppressing the expression of EMT-associated genes and inhibiting cell

migration and invasion. As DHT and cyclopamine are not suitable for clinical use, in

future studies, additional androgens and Hedgehog signalling inhibitors, especially

those that are pharmacologically applicable such as the selective androgen receptor

modulator (SARM), enobosarm and the Hedgehog/SMO inhibitor, vismodegib or GDC-

0449 may be tested in vitro (Gao and Dalton 2007, Dalton et al 2011, LoRusso et al

2011, Sandhiya et al 2013, Overmoyer et al 2014).

PCR arrays or cDNA microarrays may be used initially to screen for genes and cellular

processes potentially regulated by the agents, with dose responses and additional

timepoints providing a more comprehensive analysis of regulation of gene expression

following treatment of breast cancer cells. Additional cell lines representing other breast

cancer cell types (e.g. molecular apocrine, triple-negative breast cancer (TNBC)) may

be screened to indicate the subtypes of breast cancer potentially sensitive or resistant to

these treatment strategies (Perou et al 1999, Sorlie et al 2001, Sorlie et al 2003, Farmer

et al 2005, Prat et al 2010, Ciriello et al 2013). Importantly, comparison with DHT and

cyclopamine regulated genes identified in the present study will help to identify genes

that are commonly regulated by the androgen/AR and Hedgehog signalling pathways as

opposed to genes regulated by specific androgens or Hedgehog signalling inhibitors

whose effectiveness may be more dependent on co-factor and other gene expression in

individual tumours. Results from the microarrays would also allow identification of

biomarkers of tumour responses which are relevant for downstream clinical application

of these treatments. As targeted agents have frequently been shown to exhibit greater

efficacy when administered with other classes of drugs, androgens and Hedgehog

signalling inhibitors would also be evaluated in combination with chemotherapy or

endocrine therapies, for example, anti-oestrogens (e.g. tamoxifen, fulvestrant) and

aromatase inhibitors (e.g. anastrazole, letrozole) to detect potential additive, synergistic

or antagonistic effects associated with these drug combinations (Albain et al 2009,

Andersson et al 2011, Bedognetti et al 2011, Ramaswamy et al 2012, Chai et al 2013,

Sabol et al 2014).

Regulation of expression, intracellular localisation and efflux activity of drug

transporters, including ABCG2, ABCB1 and ABCC1 following short and long-term


212

treatment of breast cancer cell lines with novel androgens and Hedgehog signalling

inhibitors should be evaluated to determine whether the agents are potential substrates

of one or more of the transporters and whether, similar to DHT and cyclopamine, they

downregulate the levels of active transporter function in breast cancer cells, increasing

the efficacy of chemotherapeutic or other targeted agents. Considering the importance

of breast cancer stem cells in tumour relapse and the development of drug resistant

disease, the specific responses of breast cancer stem cells isolated from breast cancer

cell lines to androgens and Hedgehog signalling inhibitors should be evaluated

(Visvader and Lindeman 2008, Han et al 2013). For such studies, stem-like cells may be

isolated from the breast cancer cell lines using similar methods to those employed in

this thesis (Hoechst 33342lo/CD44hi/CD24lo) (Kim et al 2002, Patrawala et al 2005,

Engelmann et al 2008, Yin et al 2008). In addition to characterisation of the levels and

localisation of the ABC transporters in the treated cells, the effects of androgen and

Hedgehog signalling inhibitor treatments on proliferation, sensitivity to

chemotherapeutic agents and the ability of stem cells to form tumours (xenografts) (see

below) in mice will indicate potential therapeutic advantages in the implementation of

this treatment regimen for breast cancer management (Al-Hajj et al 2003, Patrawala et

al 2005, Yin et al 2008).

In this study, investigation of the expression of EMT-associated genes using RT2

Profiler Human EMT PCR Arrays revealed that DHT and cyclopamine predominantly

downregulated expression of genes which encode components or intermediates of

EMT-inducing processes (cell-to-ECM interaction, degradation of the ECM) and

signalling pathways (TGFβ, WNT). The same methods may be used to investigate

whether other androgens and Hedgehog signalling inhibitors similarly regulate the EMT

programme. Following validation of these results by RT-qPCR and western blotting,

effects of the treatments on cell migration and invasion, hallmarks of cancer cells that

have undergone EMT, should be evaluated. To determine potential reversal of EMT by

androgen and Hedgehog signalling inhibitor treatments of breast cancer cells, EMT may

be stimulated in epithelial-like breast cancer cell lines (MCF-7 and T-47D) by culture

with TGF-β1 or overexpression of WNT ligands (Yook et al 2005, Lv et al 2013). The

effects of co-treatment with androgens or Hedgehog signalling inhibitors on expression

of EMT or TGFβ/WNT signalling associated genes, epithelial/mesenchymal

morphology, and cell migration and invasion would indicate whether these agents

would be effective in more aggressive breast cancers in which EMT is being driven by


213

abnormal regulation of pro-EMT signalling. Expression of the intermediates of TGFβ

and WNT pathways may also be evaluated following androgen and Hedgehog

signalling inhibitor treatments to determine the mechanisms by which the treatments

regulate TGFβ or WNT-induced EMT.

Development of androgens and Hedgehog signalling inhibitors as adjunct therapies for

breast cancer is an important future direction of this research, and to generate pre-

clinical data, these agents will need to be evaluated in animal models (e.g. mice) in

which the tumour microenvironment more closely reflects that in humans. Mouse

xenograft models may be established by transplantation of breast cancer cell lines into

the mammary glands of mice to generate tumours in which to investigate responses to

androgens and/or Hedgehog signalling inhibitors. For these studies, tumour-bearing

mice would be administered with the treatments at doses which have been used in

clinical trials for breast cancer or other malignancies (Wang et al 2005, Masuelli et al

2013, Sandhiya et al 2013, Overmoyer et al 2014). The mouse models would also be

able to be used to determine effects of androgens and/or Hedgehog signalling inhibition

in combination with chemotherapy or targeted therapies (tamoxifen, aromatase

inhibitors, trastuzumab), with endpoints of tumour growth measured by tumour size and

weight, and immunohistochemical analysis of marker expression (e.g.

ER/PR/AR/HER2, EMT intermediates, proliferation markers). These results will

indicate the subtypes of breast tumours that would benefit from androgens and

Hedgehog signalling inhibitor treatments.

As results from this study indicate that androgens and Hedgehog signalling inhibitors

may inhibit the development of drug resistance and metastasis, tumour responses to

chemotherapeutic agents and formation of metastatic lesions in vivo may be evaluated

following treatment of host animals (e.g. mice) with combinations of chemotherapeutic

agents, androgens and Hedgehog signalling inhibitors. In vivo models of drug resistant

cancers have been generated in previous studies, for example, by transplanting

mitoxantrone-resistant breast cancer cell lines into mice (Kasibhatla et al 2007, Ma et al

2013). These models may be used to investigate whether co-treatment of the mice with

androgens or Hedgehog signalling inhibitors enhances tumour responsiveness to

chemotherapeutic agents (ie. diminishes chemoresistance). Evaluation of the expression

of the ABC transporters including ABCG2 in the tumours (xenografts) may also be


214

performed to identify whether androgens and Hedgehog signalling inhibitors similarly

regulate ABC transporter expression and localisation in vivo as observed in breast

cancer cell lines in this study. Formation of metastatic tumours in vivo may also be

investigated following treatment of mice transplanted with breast cancer cell lines with

androgens and Hedgehog signalling inhibitors. As MCF-7 and T-47D cells rarely

develop metastases in vivo, EMT may be induced by treatment with TGF-β1 or

overexpression of N-cadherin or WNT ligands prior to transplantation into mice and

time to development of metastatic lesions may be compared between treatment groups

(Hazan et al 2000, Yook et al 2005, Lv et al 2013).

Evaluation of the efficacy of androgens and Hedgehog signalling inhibitors may

subsequently be performed in clinical trials if findings from in vitro and in vivo studies

support the administration of these agents to breast cancer patients. Based on results

from in vitro and in vivo studies, participants would be selected according to disease

stage, breast cancer subtype and expression of tumour biomarkers (e.g. AR, ER, HER2,

GLI1/2) to indicate likely responsiveness to androgens and Hedgehog signalling

inhibitors. Following experimental evidence from this thesis, from previous studies, and

from previous clinical use of these agents, therapeutic efficacy of combining androgens

and/or Hedgehog signalling inhibitors with chemotherapy or targeted therapies will be

determined to identify improvement in progression-free survival and overall survival.

Side effects and toxicity associated with these drug combinations will also be recorded

to determine the tolerability and safety of the drugs for routine human usage.

Conclusion

This thesis study has demonstrated that DHT and cyclopamine treatments of breast

cancer cells antagonise ABCG2-mediated drug efflux and EMT, processes that drive

chemoresistance and tumour metastasis. The findings support development of

androgens and Hedgehog signalling inhibitors as adjunct therapies for susceptible breast

tumours, a treatment strategy that will potentially delay disease progression and prolong

overall survival.

References

215

Abe, K. and Takeichi, M. (2008). "EPLIN mediates linkage of the cadherin catenin complex to F-actin and stabilizes the circumferential actin belt." Proc Natl Acad Sci U S A 105(1): 13-19.

AbuHammad, S. and Zihlif, M. (2013). "Gene expression alterations in doxorubicin resistant MCF7 breast cancer cell line." Genomics 101(4): 213-220.

AIHW (2014). Cancer in Australia: an overview 2014. AIHW. Canberra.

Aka, J.A. and Lin, S.X. (2012). "Comparison of functional proteomic analyses of human breast cancer cell lines T47D and MCF7." PLoS One 7(2): e31532.

Akamatsu, M., Aota, S., Suwa, A., Ueda, K., Amachi, T., Yamada, K.M., Akiyama, S.K. and Kioka, N. (1999). "Vinexin forms a signaling complex with Sos and modulates epidermal growth factor-induced c-Jun N-terminal kinase/stress-activated protein kinase activities." J Biol Chem 274(50): 35933-35937.

Al-Hajj, M., Wicha, M.S., Benito-Hernandez, A., Morrison, S.J. and Clarke, M.F. (2003). "Prospective identification of tumorigenic breast cancer cells." Proc Natl Acad Sci U S A 100(7): 3983-3988.

Al Saleh, S., Al Mulla, F. and Luqmani, Y.A. (2011). "Estrogen receptor silencing induces epithelial to mesenchymal transition in human breast cancer cells." PLoS One 6(6): e20610.

Alarmo, E.L. and Kallioniemi, A. (2010). "Bone morphogenetic proteins in breast cancer: dual role in tumourigenesis?" Endocr Relat Cancer 17(2): R123-139.

Alarmo, E.L., Parssinen, J., Ketolainen, J.M., Savinainen, K., Karhu, R. and Kallioniemi, A. (2009). "BMP7 influences proliferation, migration, and invasion of breast cancer cells." Cancer Lett 275(1): 35-43.

Albain, K.S., Barlow, W.E., Ravdin, P.M., Farrar, W.B., Burton, G.V., Ketchel, S.J., Cobau, C.D., Levine, E.G., Ingle, J.N., Pritchard, K.I., Lichter, A.S., Schneider, D.J., Abeloff, M.D., Henderson, I.C., Muss, H.B., Green, S.J., Lew, D., Livingston, R.B., Martino, S. and Osborne, C.K. (2009). "Adjuvant chemotherapy and timing of tamoxifen in postmenopausal patients with endocrine-responsive, node-positive breast cancer: a phase 3, open-label, randomised controlled trial." Lancet 374(9707): 2055-2063.

Alberts, B., Johnson, A.J., Lewis, J., Raff, M., Roberts, K. and Walter, P. (2002). Transport from the trans golgi network to lysosomes. Molecular Biology of the Cell (4th edition). New York, Garland Science.

Ali, S. and Coombes, R.C. (2002). "Endocrine-responsive breast cancer and strategies for combating resistance." Nat Rev Cancer 2(2): 101-112.

Allan, J.A., Docherty, A.J., Barker, P.J., Huskisson, N.S., Reynolds, J.J. and Murphy, G. (1995). "Binding of gelatinases A and B to type-I collagen and other matrix components." Biochem J 309 ( Pt 1): 299-306.

Allan, J.A., Hembry, R.M., Angal, S., Reynolds, J.J. and Murphy, G. (1991). "Binding of latent and high Mr active forms of stromelysin to collagen is mediated by the C-terminal domain." J Cell Sci 99 ( Pt 4): 789-795.

Allen, J.D., van Loevezijn, A., Lakhai, J.M., van der Valk, M., van Tellingen, O., Reid, G., Schellens, J.H., Koomen, G.J. and Schinkel, A.H. (2002). "Potent and specific inhibition of the breast cancer resistance protein multidrug transporter in vitro and in mouse intestine by a novel analogue of fumitremorgin C." Mol Cancer Ther 1(6): 417-425.

References

216

Allikmets, R., Schriml, L.M., Hutchinson, A., Romano-Spica, V. and Dean, M. (1998). "A human placenta-specific ATP-binding cassette gene (ABCP) on chromosome 4q22 that is involved in multidrug resistance." Cancer Res 58(23): 5337-5339.

Allred, D.C., Carlson, R.W., Berry, D.A., Burstein, H.J., Edge, S.B., Goldstein, L.J., Gown, A., Hammond, M.E., Iglehart, J.D., Moench, S., Pierce, L.J., Ravdin, P., Schnitt, S.J. and Wolff, A.C. (2009). "NCCN Task Force Report: Estrogen receptor and progesterone receptor testing in breast cancer by immunohistochemistry." J Natl Compr Canc Netw 7 Suppl 6: S1-S21; quiz S22-23.

Amaral, C., Varela, C., Borges, M., Tavares da Silva, E., Roleira, F.M., Correia-da-Silva, G. and Teixeira, N. (2013). "Steroidal aromatase inhibitors inhibit growth of hormone-dependent breast cancer cells by inducing cell cycle arrest and apoptosis." Apoptosis 18(11): 1426-1436.

Ambudkar, S.V., Kim, I.W., Xia, D. and Sauna, Z.E. (2006). "The A-loop, a novel conserved aromatic acid subdomain upstream of the Walker A motif in ABC transporters, is critical for ATP binding." FEBS Lett 580(4): 1049-1055.

Andersson, M., Lidbrink, E., Bjerre, K., Wist, E., Enevoldsen, K., Jensen, A.B., Karlsson, P., Tange, U.B., Sorensen, P.G., Moller, S., Bergh, J. and Langkjer, S.T. (2011). "Phase III randomized study comparing docetaxel plus trastuzumab with vinorelbine plus trastuzumab as first-line therapy of metastatic or locally advanced human epidermal growth factor receptor 2-positive breast cancer: the HERNATA study." J Clin Oncol 29(3): 264-271.

Ando, S., De Amicis, F., Rago, V., Carpino, A., Maggiolini, M., Panno, M.L. and Lanzino, M. (2002). "Breast cancer: from estrogen to androgen receptor." Mol Cell Endocrinol 193(1-2): 121-128.

Anido, J., Scaltriti, M., Bech Serra, J.J., Santiago Josefat, B., Todo, F.R., Baselga, J. and Arribas, J. (2006). "Biosynthesis of tumorigenic HER2 C-terminal fragments by alternative initiation of translation." EMBO J 25(13): 3234-3244.

Apostolou, P. and Fostira, F. (2013). "Hereditary breast cancer: the era of new susceptibility genes." Biomed Res Int 2013: 747318.

Applanat, M.P., Buteau-Lozano, H., Herve, M.A. and Corpet, A. (2008). "Vascular endothelial growth factor is a target gene for estrogen receptor and contributes to breast cancer progression." Adv Exp Med Biol 617: 437-444.

Arimori, K., Kuroki, N., Hidaka, M., Iwakiri, T., Yamsaki, K., Okumura, M., Ono, H., Takamura, N., Kikuchi, M. and Nakano, M. (2003). "Effect of P-glycoprotein modulator, cyclosporin A, on the gastrointestinal excretion of irinotecan and its metabolite SN-38 in rats." Pharm Res 20(6): 910-917.

Aroeira, L.S., Aguilera, A., Sanchez-Tomero, J.A., Bajo, M.A., del Peso, G., Jimenez-Heffernan, J.A., Selgas, R. and Lopez-Cabrera, M. (2007). "Epithelial to mesenchymal transition and peritoneal membrane failure in peritoneal dialysis patients: pathologic significance and potential therapeutic interventions." J Am Soc Nephrol 18(7): 2004-2013.

Arun, B., Kilic, G., Yen, C., Foster, B., Yardley, D., Gaynor, R. and Ashfaq, R. (2003). "Correlation of Bcl-2 and p53 expression in primary breast tumors and corresponding metastatic lymph nodes." Cancer 98(12): 2554-2559.

References

217

Asghar, U., Witkiewicz, A.K., Turner, N.C. and Knudsen, E.S. (2015). "The history and future of targeting cyclin-dependent kinases in cancer therapy." Nat Rev Drug Discov 14(2): 130-146.

Askew, E.B., Gampe, R.T., Jr., Stanley, T.B., Faggart, J.L. and Wilson, E.M. (2007). "Modulation of androgen receptor activation function 2 by testosterone and dihydrotestosterone." J Biol Chem 282(35): 25801-25816.

Asselin-Labat, M.L., Vaillant, F., Sheridan, J.M., Pal, B., Wu, D., Simpson, E.R., Yasuda, H., Smyth, G.K., Martin, T.J., Lindeman, G.J. and Visvader, J.E. (2010). "Control of mammary stem cell function by steroid hormone signalling." Nature 465(7299): 798-802.

Bailey-Dell, K.J., Hassel, B., Doyle, L.A. and Ross, D.D. (2001). "Promoter characterization and genomic organization of the human breast cancer resistance protein (ATP-binding cassette transporter G2) gene." Biochim Biophys Acta 1520(3): 234-241.

Balkwill, F. (2009). "Tumour necrosis factor and cancer." Nat Rev Cancer 9(5): 361-371.

Bar, E.E., Chaudhry, A., Lin, A., Fan, X., Schreck, K., Matsui, W., Piccirillo, S., Vescovi, A.L., DiMeco, F., Olivi, A. and Eberhart, C.G. (2007). "Cyclopamine-mediated hedgehog pathway inhibition depletes stem-like cancer cells in glioblastoma." Stem Cells 25(10): 2524-2533.

Barbieri, R.L. (2014). "The endocrinology of the menstrual cycle." Methods Mol Biol 1154: 145-169.

Bardia, A., Modi, S., Gregor, M., Kittaneh, M., Marino, A.J., Matano, A., Bhansali, S., Hewes, B. and Cortes, J. (2014). "Phase Ib/II study of LEE011, everolimus, and exemestane in postmenopausal women with ER+/HER2-metastatic breast cancer". Paper presented at 2014 American Society of Clinical Oncology Annual Meeting.

Bardou, V.J., Arpino, G., Elledge, R.M., Osborne, C.K. and Clark, G.M. (2003). "Progesterone receptor status significantly improves outcome prediction over estrogen receptor status alone for adjuvant endocrine therapy in two large breast cancer databases." J Clin Oncol 21(10): 1973-1979.

Barton, V.N., D'Amato, N.C., Gordon, M.A., Lind, H.T., Spoelstra, N.S., Babbs, B.L., Heinz, R.E., Elias, A., Jedlicka, P., Jacobsen, B.M. and Richer, J.K. (2015). "Multiple molecular subtypes of triple-negative breast cancer critically rely on androgen receptor and respond to enzalutamide in vivo." Mol Cancer Ther 14(3): 769-778.

Batlle, E., Sancho, E., Franci, C., Dominguez, D., Monfar, M., Baulida, J. and Garcia De Herreros, A. (2000). "The transcription factor snail is a repressor of E-cadherin gene expression in epithelial tumour cells." Nat Cell Biol 2(2): 84-89.

Bedognetti, D., Sertoli, M.R., Pronzato, P., Del Mastro, L., Venturini, M., Taveggia, P., Zanardi, E., Siffredi, G., Pastorino, S., Queirolo, P., Gardin, G., Wang, E., Monzeglio, C., Boccardo, F. and Bruzzi, P. (2011). "Concurrent vs sequential adjuvant chemotherapy and hormone therapy in breast cancer: a multicenter randomized phase III trial." J Natl Cancer Inst 103(20): 1529-1539.

Benhaj, K., Akcali, K.C. and Ozturk, M. (2006). "Redundant expression of canonical Wnt ligands in human breast cancer cell lines." Oncol Rep 15(3): 701-707.

Bennett, N.C., Gardiner, R.A., Hooper, J.D., Johnson, D.W. and Gobe, G.C. (2010). "Molecular cell biology of androgen receptor signalling." Int J Biochem Cell Biol 42(6): 813-827.

References

218

Berns, K., Horlings, H.M., Hennessy, B.T., Madiredjo, M., Hijmans, E.M., Beelen, K., Linn, S.C., Gonzalez-Angulo, A.M., Stemke-Hale, K., Hauptmann, M., Beijersbergen, R.L., Mills, G.B., van de Vijver, M.J. and Bernards, R. (2007). "A functional genetic approach identifies the PI3K pathway as a major determinant of trastuzumab resistance in breast cancer." Cancer Cell 12(4): 395-402.

Bhatia, P., Bernier, M., Sanghvi, M., Moaddel, R., Schwarting, R., Ramamoorthy, A. and Wainer, I.W. (2012). "Breast cancer resistance protein (BCRP/ABCG2) localises to the nucleus in glioblastoma multiforme cells." Xenobiotica 42(8): 748-755.

Bieche, I., Parfait, B., Tozlu, S., Lidereau, R. and Vidaud, M. (2001). "Quantitation of androgen receptor gene expression in sporadic breast tumors by real-time RT-PCR: evidence that MYC is an AR-regulated gene." Carcinogenesis 22(9): 1521-1526.

Bigg, H.F., Rowan, A.D., Barker, M.D. and Cawston, T.E. (2007). "Activity of matrix metalloproteinase-9 against native collagen types I and III." FEBS J 274(5): 1246-1255.

Bird, A. (2002). "DNA methylation patterns and epigenetic memory." Genes Dev 16(1): 6-21.

Birrell, S.N., Bentel, J.M., Hickey, T.E., Ricciardelli, C., Weger, M.A., Horsfall, D.J. and Tilley, W.D. (1995). "Androgens induce divergent proliferative responses in human breast cancer cell lines." J Steroid Biochem Mol Biol 52(5): 459-467.

Biswas, S., Nyman, J.S., Alvarez, J., Chakrabarti, A., Ayres, A., Sterling, J., Edwards, J., Rana, T., Johnson, R., Perrien, D.S., Lonning, S., Shyr, Y., Matrisian, L.M. and Mundy, G.R. (2011). "Anti-transforming growth factor ss antibody treatment rescues bone loss and prevents breast cancer metastasis to bone." PLoS One 6(11): e27090.

Blackwell, K.L., Burstein, H.J., Storniolo, A.M., Rugo, H.S., Sledge, G., Aktan, G., Ellis, C., Florance, A., Vukelja, S., Bischoff, J., Baselga, J. and O'Shaughnessy, J. (2012). "Overall survival benefit with lapatinib in combination with trastuzumab for patients with human epidermal growth factor receptor 2-positive metastatic breast cancer: final results from the EGF104900 Study." J Clin Oncol 30(21): 2585-2592.

Bodicoat, D.H., Schoemaker, M.J., Jones, M.E., McFadden, E., Griffin, J., Ashworth, A. and Swerdlow, A.J. (2014). "Timing of pubertal stages and breast cancer risk: the Breakthrough Generations Study." Breast Cancer Res 16(1): R18.

Bolos, V., Mira, E., Martinez-Poveda, B., Luxan, G., Canamero, M., Martinez, A.C., Manes, S. and de la Pompa, J.L. (2013). "Notch activation stimulates migration of breast cancer cells and promotes tumor growth." Breast Cancer Res 15(4): R54.

Bolton, E.C., So, A.Y., Chaivorapol, C., Haqq, C.M., Li, H. and Yamamoto, K.R. (2007). "Cell- and gene-specific regulation of primary target genes by the androgen receptor." Genes Dev 21(16): 2005-2017.

Bombonati, A. and Sgroi, D.C. (2011). "The molecular pathology of breast cancer progression." J Pathol 223(2): 307-317.

Bonifas, J.M., Pennypacker, S., Chuang, P.T., McMahon, A.P., Williams, M., Rosenthal, A., De Sauvage, F.J. and Epstein, E.H., Jr. (2001). "Activation of expression of hedgehog target genes in basal cell carcinomas." J Invest Dermatol 116(5): 739-742.

Bonnans, C., Chou, J. and Werb, Z. (2014). "Remodelling the extracellular matrix in development and disease." Nat Rev Mol Cell Biol 15(12): 786-801.

References

219

Borchers, A., David, R. and Wedlich, D. (2001). "Xenopus cadherin-11 restrains cranial neural crest migration and influences neural crest specification." Development 128(16): 3049-3060.

Borges, S., Desta, Z., Li, L., Skaar, T.C., Ward, B.A., Nguyen, A., Jin, Y., Storniolo, A.M., Nikoloff, D.M., Wu, L., Hillman, G., Hayes, D.F., Stearns, V. and Flockhart, D.A. (2006). "Quantitative effect of CYP2D6 genotype and inhibitors on tamoxifen metabolism: implication for optimization of breast cancer treatment." Clin Pharmacol Ther 80(1): 61-74.

Bradbury, A.R. and Olopade, O.I. (2007). "Genetic susceptibility to breast cancer." Rev Endocr Metab Disord 8(3): 255-267.

Britton, K.M., Eyre, R., Harvey, I.J., Stemke-Hale, K., Browell, D., Lennard, T.W. and Meeson, A.P. (2012). "Breast cancer, side population cells and ABCG2 expression." Cancer Lett 323(1): 97-105.

Browne, B.C., Crown, J., Venkatesan, N., Duffy, M.J., Clynes, M., Slamon, D. and O'Donovan, N. (2011). "Inhibition of IGF1R activity enhances response to trastuzumab in HER-2-positive breast cancer cells." Ann Oncol 22(1): 68-73.

Brufsky, A., Valero, V., Tiangco, B., Dakhil, S., Brize, A., Rugo, H.S., Rivera, R., Duenne, A., Bousfoul, N. and Yardley, D.A. (2012). "Second-line bevacizumab-containing therapy in patients with triple-negative breast cancer: subgroup analysis of the RIBBON-2 trial." Breast Cancer Res Treat 133(3): 1067-1075.

Buchholz, T.A., Davis, D.W., McConkey, D.J., Symmans, W.F., Valero, V., Jhingran, A., Tucker, S.L., Pusztai, L., Cristofanilli, M., Esteva, F.J., Hortobagyi, G.N. and Sahin, A.A. (2003). "Chemotherapy-induced apoptosis and Bcl-2 levels correlate with breast cancer response to chemotherapy." Cancer J 9(1): 33-41.

Burger, H., Foekens, J.A., Look, M.P., Meijer-van Gelder, M.E., Klijn, J.G., Wiemer, E.A., Stoter, G. and Nooter, K. (2003). "RNA expression of breast cancer resistance protein, lung resistance-related protein, multidrug resistance-associated proteins 1 and 2, and multidrug resistance gene 1 in breast cancer: correlation with chemotherapeutic response." Clin Cancer Res 9(2): 827-836.

Burger, H., van Tol, H., Boersma, A.W., Brok, M., Wiemer, E.A., Stoter, G. and Nooter, K. (2004). "Imatinib mesylate (STI571) is a substrate for the breast cancer resistance protein (BCRP)/ABCG2 drug pump." Blood 104(9): 2940-2942.

Burger, H.G. (2002). "Androgen production in women." Fertil Steril 77 Suppl 4: S3-5.

Burstein, H.J., Temin, S., Anderson, H., Buchholz, T.A., Davidson, N.E., Gelmon, K.E., Giordano, S.H., Hudis, C.A., Rowden, D., Solky, A.J., Stearns, V., Winer, E.P. and Griggs, J.J. (2014). "Adjuvant endocrine therapy for women with hormone receptor-positive breast cancer: american society of clinical oncology clinical practice guideline focused update." J Clin Oncol 32(21): 2255-2269.

Cabodi, S., Moro, L., Baj, G., Smeriglio, M., Di Stefano, P., Gippone, S., Surico, N., Silengo, L., Turco, E., Tarone, G. and Defilippi, P. (2004). "p130Cas interacts with estrogen receptor alpha and modulates non-genomic estrogen signaling in breast cancer cells." J Cell Sci 117(Pt 8): 1603-1611.

Cai, C., Omwancha, J., Hsieh, C.L. and Shemshedini, L. (2007). "Androgen induces expression of the multidrug resistance protein gene MRP4 in prostate cancer cells." Prostate Cancer Prostatic Dis 10(1): 39-45.

References

220

Calcagno, A.M., Fostel, J.M., To, K.K., Salcido, C.D., Martin, S.E., Chewning, K.J., Wu, C.P., Varticovski, L., Bates, S.E., Caplen, N.J. and Ambudkar, S.V. (2008). "Single-step doxorubicin-selected cancer cells overexpress the ABCG2 drug transporter through epigenetic changes." Br J Cancer 98(9): 1515-1524.

Calcagno, A.M., Salcido, C.D., Gillet, J.P., Wu, C.P., Fostel, J.M., Mumau, M.D., Gottesman, M.M., Varticovski, L. and Ambudkar, S.V. (2010). "Prolonged drug selection of breast cancer cells and enrichment of cancer stem cell characteristics." J Natl Cancer Inst 102(21): 1637-1652.

Cardoso, F., Harbeck, N., Fallowfield, L., Kyriakides, S. and Senkus, E. (2012). "Locally recurrent or metastatic breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up." Ann Oncol 23 Suppl 7: vii11-19.

Cardozo, C.P., Michaud, C., Ost, M.C., Fliss, A.E., Yang, E., Patterson, C., Hall, S.J. and Caplan, A.J. (2003). "C-terminal Hsp-interacting protein slows androgen receptor synthesis and reduces its rate of degradation." Arch Biochem Biophys 410(1): 134-140.

Carey, L.A., Rugo, H.S., Marcom, P.K., Mayer, E.L., Esteva, F.J., Ma, C.X., Liu, M.C., Storniolo, A.M., Rimawi, M.F., Forero-Torres, A., Wolff, A.C., Hobday, T.J., Ivanova, A., Chiu, W.K., Ferraro, M., Burrows, E., Bernard, P.S., Hoadley, K.A., Perou, C.M. and Winer, E.P. (2012). "TBCRC 001: randomized phase II study of cetuximab in combination with carboplatin in stage IV triple-negative breast cancer." J Clin Oncol 30(21): 2615-2623.

Cariou, S., Donovan, J.C., Flanagan, W.M., Milic, A., Bhattacharya, N. and Slingerland, J.M. (2000). "Down-regulation of p21WAF1/CIP1 or p27Kip1 abrogates antiestrogen-mediated cell cycle arrest in human breast cancer cells." Proc Natl Acad Sci U S A 97(16): 9042-9046.

Ceckova, M., Libra, A., Pavek, P., Nachtigal, P., Brabec, M., Fuchs, R. and Staud, F. (2006). "Expression and functional activity of breast cancer resistance protein (BCRP, ABCG2) transporter in the human choriocarcinoma cell line BeWo." Clin Exp Pharmacol Physiol 33(1-2): 58-65.

Chai, F., Zhou, J., Chen, C., Xie, S., Chen, X., Su, P. and Shi, J. (2013). "The Hedgehog inhibitor cyclopamine antagonizes chemoresistance of breast cancer cells." Onco Targets Ther 6: 1643-1647.

Chang, E.C., Frasor, J., Komm, B. and Katzenellenbogen, B.S. (2006). "Impact of estrogen receptor beta on gene networks regulated by estrogen receptor alpha in breast cancer cells." Endocrinology 147(10): 4831-4842.

Che, J., Zhang, F.Z., Zhao, C.Q., Hu, X.D. and Fan, S.J. (2013). "Cyclopamine is a novel Hedgehog signaling inhibitor with significant anti-proliferative, anti-invasive and anti-estrogenic potency in human breast cancer cells." Oncol Lett 5(4): 1417-1421.

Chearwae, W., Shukla, S., Limtrakul, P. and Ambudkar, S.V. (2006). "Modulation of the function of the multidrug resistance-linked ATP-binding cassette transporter ABCG2 by the cancer chemopreventive agent curcumin." Mol Cancer Ther 5(8): 1995-2006.

Chen, G., Goto, Y., Sakamoto, R., Tanaka, K., Matsubara, E., Nakamura, M., Zheng, H., Lu, J., Takayanagi, R. and Nomura, M. (2011a). "GLI1, a crucial mediator of sonic hedgehog signaling in prostate cancer, functions as a negative modulator for androgen receptor." Biochem Biophys Res Commun 404(3): 809-815.

References

221

Chen, J.K., Taipale, J., Cooper, M.K. and Beachy, P.A. (2002). "Inhibition of Hedgehog signaling by direct binding of cyclopamine to Smoothened." Genes Dev 16(21): 2743-2748.

Chen, J.S., Pardo, F.S., Wang-Rodriguez, J., Chu, T.S., Lopez, J.P., Aguilera, J., Altuna, X., Weisman, R.A. and Ongkeko, W.M. (2006). "EGFR regulates the side population in head and neck squamous cell carcinoma." Laryngoscope 116(3): 401-406.

Chen, M., Feuerstein, M.A., Levina, E., Baghel, P.S., Carkner, R.D., Tanner, M.J., Shtutman, M., Vacherot, F., Terry, S., de la Taille, A. and Buttyan, R. (2010). "Hedgehog/Gli supports androgen signaling in androgen deprived and androgen independent prostate cancer cells." Mol Cancer 9: 89.

Chen, M., Tanner, M., Levine, A.C., Levina, E., Ohouo, P. and Buttyan, R. (2009). "Androgenic regulation of hedgehog signaling pathway components in prostate cancer cells." Cell Cycle 8(1): 149-157.

Chen, S. and Parmigiani, G. (2007). "Meta-analysis of BRCA1 and BRCA2 penetrance." J Clin Oncol 25(11): 1329-1333.

Chen, S.J., Artlett, C.M., Jimenez, S.A. and Varga, J. (1998). "Modulation of human alpha1(I) procollagen gene activity by interaction with Sp1 and Sp3 transcription factors in vitro." Gene 215(1): 101-110.

Chen, W.Y., Rosner, B., Hankinson, S.E., Colditz, G.A. and Willett, W.C. (2011b). "Moderate alcohol consumption during adult life, drinking patterns, and breast cancer risk." JAMA 306(17): 1884-1890.

Chen, X., Weisberg, E., Fridmacher, V., Watanabe, M., Naco, G. and Whitman, M. (1997). "Smad4 and FAST-1 in the assembly of activin-responsive factor." Nature 389(6646): 85-89.

Chikazawa, N., Tanaka, H., Tasaka, T., Nakamura, M., Tanaka, M., Onishi, H. and Katano, M. (2010). "Inhibition of Wnt signaling pathway decreases chemotherapy-resistant side-population colon cancer cells." Anticancer Res 30(6): 2041-2048.

Chlebowski, R.T., Anderson, G.L., Gass, M., Lane, D.S., Aragaki, A.K., Kuller, L.H., Manson, J.E., Stefanick, M.L., Ockene, J., Sarto, G.E., Johnson, K.C., Wactawski-Wende, J., Ravdin, P.M., Schenken, R., Hendrix, S.L., Rajkovic, A., Rohan, T.E., Yasmeen, S. and Prentice, R.L. (2010). "Estrogen plus progestin and breast cancer incidence and mortality in postmenopausal women." JAMA 304(15): 1684-1692.

Cho, H.S., Mason, K., Ramyar, K.X., Stanley, A.M., Gabelli, S.B., Denney, D.W., Jr. and Leahy, D.J. (2003). "Structure of the extracellular region of HER2 alone and in complex with the Herceptin Fab." Nature 421(6924): 756-760.

Chu, F.M., Picus, J., Fracasso, P.M., Dreicer, R., Lang, Z. and Foster, B. (2011). "A phase 1, multicenter, open-label study of the safety of two dose levels of a human monoclonal antibody to human alpha(v) integrins, intetumumab, in combination with docetaxel and prednisone in patients with castrate-resistant metastatic prostate cancer." Invest New Drugs 29(4): 674-679.

Chua, V.Y.L. (2011). "Hedgehog signalling in breast cancer cells". Western Australia, Australia, Murdoch University.

Chung, C.H., Lin, K.T., Chang, C.H., Peng, H.C. and Huang, T.F. (2009). "The integrin alpha2beta1 agonist, aggretin, promotes proliferation and migration of VSMC through NF-kB translocation and PDGF production." Br J Pharmacol 156(5): 846-856.

References

222

Cid, M.C., Esparza, J., Schnaper, H.W., Juan, M., Yague, J., Grant, D.S., Urbano-Marquez, A., Hoffman, G.S. and Kleinman, H.K. (1999). "Estradiol enhances endothelial cell interactions with extracellular matrix proteins via an increase in integrin expression and function." Angiogenesis 3(3): 271-280.

Ciriello, G., Sinha, R., Hoadley, K.A., Jacobsen, A.S., Reva, B., Perou, C.M., Sander, C. and Schultz, N. (2013). "The molecular diversity of Luminal A breast tumors." Breast Cancer Res Treat 141(3): 409-420.

Clement, J.H., Raida, M., Sanger, J., Bicknell, R., Liu, J., Naumann, A., Geyer, A., Waldau, A., Hortschansky, P., Schmidt, A., Hoffken, K., Wolft, S. and Harris, A.L. (2005). "Bone morphogenetic protein 2 (BMP-2) induces in vitro invasion and in vivo hormone independent growth of breast carcinoma cells." Int J Oncol 27(2): 401-407.

Cochrane, D.R., Bernales, S., Jacobsen, B.M., Cittelly, D.M., Howe, E.N., D'Amato, N.C., Spoelstra, N.S., Edgerton, S.M., Jean, A., Guerrero, J., Gomez, F., Medicherla, S., Alfaro, I.E., McCullagh, E., Jedlicka, P., Torkko, K.C., Thor, A.D., Elias, A.D., Protter, A.A. and Richer, J.K. (2014). "Role of the androgen receptor in breast cancer and preclinical analysis of enzalutamide." Breast Cancer Res 16(1): R7.

Cohen, M.M., Jr. (2010). "Hedgehog signaling update." Am J Med Genet A 152A(8): 1875-1914.

Cole, S.P., Bhardwaj, G., Gerlach, J.H., Mackie, J.E., Grant, C.E., Almquist, K.C., Stewart, A.J., Kurz, E.U., Duncan, A.M. and Deeley, R.G. (1992). "Overexpression of a transporter gene in a multidrug-resistant human lung cancer cell line." Science 258(5088): 1650-1654.

Cooray, H.C., Blackmore, C.G., Maskell, L. and Barrand, M.A. (2002). "Localisation of breast cancer resistance protein in microvessel endothelium of human brain." Neuroreport 13(16): 2059-2063.

Cops, E.J., Bianco-Miotto, T., Moore, N.L., Clarke, C.L., Birrell, S.N., Butler, L.M. and Tilley, W.D. (2008). "Antiproliferative actions of the synthetic androgen, mibolerone, in breast cancer cells are mediated by both androgen and progesterone receptors." J Steroid Biochem Mol Biol 110(3-5): 236-243.

Coxon, A., Bush, T., Saffran, D., Kaufman, S., Belmontes, B., Rex, K., Hughes, P., Caenepeel, S., Rottman, J.B., Tasker, A., Patel, V., Kendall, R., Radinsky, R. and Polverino, A. (2009). "Broad antitumor activity in breast cancer xenografts by motesanib, a highly selective, oral inhibitor of vascular endothelial growth factor, platelet-derived growth factor, and Kit receptors." Clin Cancer Res 15(1): 110-118.

Cripe, L.D., Uno, H., Paietta, E.M., Litzow, M.R., Ketterling, R.P., Bennett, J.M., Rowe, J.M., Lazarus, H.M., Luger, S. and Tallman, M.S. (2010). "Zosuquidar, a novel modulator of P-glycoprotein, does not improve the outcome of older patients with newly diagnosed acute myeloid leukemia: a randomized, placebo-controlled trial of the Eastern Cooperative Oncology Group 3999." Blood 116(20): 4077-4085.

Croft, D., Mundo, A.F., Haw, R., Milacic, M., Weiser, J., Wu, G., Caudy, M., Garapati, P., Gillespie, M., Kamdar, M.R., Jassal, B., Jupe, S., Matthews, L., May, B., Palatnik, S., Rothfels, K., Shamovsky, V., Song, H., Williams, M., Birney, E., Hermjakob, H., Stein, L. and D'Eustachio, P. (2014). "The Reactome pathway knowledgebase." Nucleic Acids Res 42(Database issue): D472-477.

Croker, A.K., Goodale, D., Chu, J., Postenka, C., Hedley, B.D., Hess, D.A. and Allan, A.L. (2009). "High aldehyde dehydrogenase and expression of cancer stem cell markers

References

223

selects for breast cancer cells with enhanced malignant and metastatic ability." J Cell Mol Med 13(8B): 2236-2252.

Cui, W., Wang, L.H., Wen, Y.Y., Song, M., Li, B.L., Chen, X.L., Xu, M., An, S.X., Zhao, J., Lu, Y.Y., Mi, X.Y. and Wang, E.H. (2010). "Expression and regulation mechanisms of Sonic Hedgehog in breast cancer." Cancer Sci 101(4): 927-933.

Cui, X., Schiff, R., Arpino, G., Osborne, C.K. and Lee, A.V. (2005). "Biology of progesterone receptor loss in breast cancer and its implications for endocrine therapy." J Clin Oncol 23(30): 7721-7735.

D'Angelo, R.C., Liu, X.W., Najy, A.J., Jung, Y.S., Won, J., Chai, K.X., Fridman, R. and Kim, H.R. (2014). "TIMP-1 via TWIST1 induces EMT phenotypes in human breast epithelial cells." Mol Cancer Res 12(9): 1324-1333.

Dai, C.L., Tiwari, A.K., Wu, C.P., Su, X.D., Wang, S.R., Liu, D.G., Ashby, C.R., Jr., Huang, Y., Robey, R.W., Liang, Y.J., Chen, L.M., Shi, C.J., Ambudkar, S.V., Chen, Z.S. and Fu, L.W. (2008). "Lapatinib (Tykerb, GW572016) reverses multidrug resistance in cancer cells by inhibiting the activity of ATP-binding cassette subfamily B member 1 and G member 2." Cancer Res 68(19): 7905-7914.

Dalal, B.I., Keown, P.A. and Greenberg, A.H. (1993). "Immunocytochemical localization of secreted transforming growth factor-beta 1 to the advancing edges of primary tumors and to lymph node metastases of human mammary carcinoma." Am J Pathol 143(2): 381-389.

Dalton, J.T., Barnette, K.G., Bohl, C.E., Hancock, M.L., Rodriguez, D., Dodson, S.T., Morton, R.A. and Steiner, M.S. (2011). "The selective androgen receptor modulator GTx-024 (enobosarm) improves lean body mass and physical function in healthy elderly men and postmenopausal women: results of a double-blind, placebo-controlled phase II trial." J Cachexia Sarcopenia Muscle 2(3): 153-161.

Dalton, W.S., Crowley, J.J., Salmon, S.S., Grogan, T.M., Laufman, L.R., Weiss, G.R. and Bonnet, J.D. (1995). "A phase III randomized study of oral verapamil as a chemosensitizer to reverse drug resistance in patients with refractory myeloma. A Southwest Oncology Group study." Cancer 75(3): 815-820.

Dalvai, M. and Bystricky, K. (2010). "Cell cycle and anti-estrogen effects synergize to regulate cell proliferation and ER target gene expression." PLoS One 5(6): e11011.

Darby, S., McGale, P., Correa, C., Taylor, C., Arriagada, R., Clarke, M., Cutter, D., Davies, C., Ewertz, M., Godwin, J., Gray, R., Pierce, L., Whelan, T., Wang, Y. and Peto, R. (2011). "Effect of radiotherapy after breast-conserving surgery on 10-year recurrence and 15-year breast cancer death: meta-analysis of individual patient data for 10,801 women in 17 randomised trials." Lancet 378(9804): 1707-1716.

Das, S., Samant, R.S. and Shevde, L.A. (2013). "Nonclassical activation of Hedgehog signaling enhances multidrug resistance and makes cancer cells refractory to Smoothened-targeting Hedgehog inhibition." J Biol Chem 288(17): 11824-11833.

Dauvois, S., Geng, C.S., Levesque, C., Merand, Y. and Labrie, F. (1991). "Additive inhibitory effects of an androgen and the antiestrogen EM-170 on estradiol-stimulated growth of human ZR-75-1 breast tumors in athymic mice." Cancer Res 51(12): 3131-3135.

Davies, C., Pan, H., Godwin, J., Gray, R., Arriagada, R., Raina, V., Abraham, M., Medeiros Alencar, V.H., Badran, A., Bonfill, X., Bradbury, J., Clarke, M., Collins, R., Davis, S.R., Delmestri, A., Forbes, J.F., Haddad, P., Hou, M.F., Inbar, M., Khaled, H., Kielanowska, J., Kwan, W.H., Mathew, B.S., Mittra, I., Muller, B., Nicolucci, A., Peralta, O., Pernas,

References

224

F., Petruzelka, L., Pienkowski, T., Radhika, R., Rajan, B., Rubach, M.T., Tort, S., Urrutia, G., Valentini, M., Wang, Y. and Peto, R. (2013). "Long-term effects of continuing adjuvant tamoxifen to 10 years versus stopping at 5 years after diagnosis of oestrogen receptor-positive breast cancer: ATLAS, a randomised trial." Lancet 381(9869): 805-816.

Dawson, J.P., Berger, M.B., Lin, C.C., Schlessinger, J., Lemmon, M.A. and Ferguson, K.M. (2005). "Epidermal growth factor receptor dimerization and activation require ligand-induced conformational changes in the dimer interface." Mol Cell Biol 25(17): 7734-7742.

Dean, M., Fojo, T. and Bates, S. (2005). "Tumour stem cells and drug resistance." Nat Rev Cancer 5(4): 275-284.

Debnath, J., Muthuswamy, S.K. and Brugge, J.S. (2003). "Morphogenesis and oncogenesis of MCF-10A mammary epithelial acini grown in three-dimensional basement membrane cultures." Methods 30(3): 256-268.

Del Casar, J.M., Gonzalez, L.O., Alvarez, E., Junquera, S., Marin, L., Gonzalez, L., Bongera, M., Vazquez, J. and Vizoso, F.J. (2009). "Comparative analysis and clinical value of the expression of metalloproteases and their inhibitors by intratumor stromal fibroblasts and those at the invasive front of breast carcinomas." Breast Cancer Res Treat 116(1): 39-52.

Demers, L.M. (1994). "Effects of Fadrozole (CGS 16949A) and Letrozole (CGS 20267) on the inhibition of aromatase activity in breast cancer patients." Breast Cancer Res Treat 30(1): 95-102.

Dennler, S., Itoh, S., Vivien, D., ten Dijke, P., Huet, S. and Gauthier, J.M. (1998). "Direct binding of Smad3 and Smad4 to critical TGF beta-inducible elements in the promoter of human plasminogen activator inhibitor-type 1 gene." EMBO J 17(11): 3091-3100.

DePasquale, J.A. (1999). "Rearrangement of the F-actin cytoskeleton in estradiol-treated MCF-7 breast carcinoma cells." Histochem Cell Biol 112(5): 341-350.

DePrimo, S.E., Diehn, M., Nelson, J.B., Reiter, R.E., Matese, J., Fero, M., Tibshirani, R., Brown, P.O. and Brooks, J.D. (2002). "Transcriptional programs activated by exposure of human prostate cancer cells to androgen." Genome Biol 3(7): RESEARCH0032.

Deshpande, A., Sicinski, P. and Hinds, P.W. (2005). "Cyclins and cdks in development and cancer: a perspective." Oncogene 24(17): 2909-2915.

Diaz, L.K., Cristofanilli, M., Zhou, X., Welch, K.L., Smith, T.L., Yang, Y., Sneige, N., Sahin, A.A. and Gilcrease, M.Z. (2005). "Beta4 integrin subunit gene expression correlates with tumor size and nuclear grade in early breast cancer." Mod Pathol 18(9): 1165-1175.

Dickler, M.N., Barry, W.T., Cirrincione, C.T., Ellis, M.J., Moynahan, M.E., Innocenti, F., Hurria, A., Rugo, H.S., Lake, D., Hahn, O.M., Schneider, B.P., Tripathy, D., Winer, E.P. and Hudis, C.A. (2015). "Phase III trial evaluating the addition of bevacizumab to letrozole as first-line endocrine therapy for treatment of hormone-receptor positive advanced breast cancer: CALGB 40503 (Alliance)". Paper presented at 2015 American Society of Clinical Oncology Annual Meeting.

Dieras, V., Vincent-Salomon, A., Degeorges, A., Beuzeboc, P., Mignot, L. and de Cremoux, P. (2007). "Trastuzumab (Herceptin) and breast cancer: mechanisms of resistance." Bull Cancer 94(3): 259-266.

References

225

Diestra, J.E., Scheffer, G.L., Catala, I., Maliepaard, M., Schellens, J.H., Scheper, R.J., Germa-Lluch, J.R. and Izquierdo, M.A. (2002). "Frequent expression of the multi-drug resistance-associated protein BCRP/MXR/ABCP/ABCG2 in human tumours detected by the BXP-21 monoclonal antibody in paraffin-embedded material." J Pathol 198(2): 213-219.

Dimitrakakis, C., Zhou, J., Wang, J., Belanger, A., LaBrie, F., Cheng, C., Powell, D. and Bondy, C. (2003). "A physiologic role for testosterone in limiting estrogenic stimulation of the breast." Menopause 10(4): 292-298.

Ding, R., Shi, J., Pabon, K. and Scotto, K.W. (2012). "Xanthines down-regulate the drug transporter ABCG2 and reverse multidrug resistance." Mol Pharmacol 81(3): 328-337.

Ding, X.W., Wu, J.H. and Jiang, C.P. (2010). "ABCG2: a potential marker of stem cells and novel target in stem cell and cancer therapy." Life Sci 86(17-18): 631-637.

Diop, N.K. and Hrycyna, C.A. (2005). "N-Linked glycosylation of the human ABC transporter ABCG2 on asparagine 596 is not essential for expression, transport activity, or trafficking to the plasma membrane." Biochemistry 44(14): 5420-5429.

Dontu, G., Abdallah, W.M., Foley, J.M., Jackson, K.W., Clarke, M.F., Kawamura, M.J. and Wicha, M.S. (2003). "In vitro propagation and transcriptional profiling of human mammary stem/progenitor cells." Genes Dev 17(10): 1253-1270.

Dowsett, M., Cuzick, J., Ingle, J., Coates, A., Forbes, J., Bliss, J., Buyse, M., Baum, M., Buzdar, A., Colleoni, M., Coombes, C., Snowdon, C., Gnant, M., Jakesz, R., Kaufmann, M., Boccardo, F., Godwin, J., Davies, C. and Peto, R. (2010). "Meta-analysis of breast cancer outcomes in adjuvant trials of aromatase inhibitors versus tamoxifen." J Clin Oncol 28(3): 509-518.

Doyle, L. and Ross, D.D. (2003). "Multidrug resistance mediated by the breast cancer resistance protein BCRP (ABCG2)." Oncogene 22(47): 7340-7358.

Doyle, L.A., Yang, W., Abruzzo, L.V., Krogmann, T., Gao, Y., Rishi, A.K. and Ross, D.D. (1998). "A multidrug resistance transporter from human MCF-7 breast cancer cells." Proc Natl Acad Sci U S A 95(26): 15665-15670.

Dunn, W.A., Jr. (1990). "Studies on the mechanisms of autophagy: maturation of the autophagic vacuole." J Cell Biol 110(6): 1935-1945.

Easton, D.F., Pooley, K.A., Dunning, A.M., Pharoah, P.D., Thompson, D., Ballinger, D.G., Struewing, J.P., Morrison, J., Field, H., Luben, R., Wareham, N., Ahmed, S., Healey, C.S., Bowman, R., Meyer, K.B., Haiman, C.A., Kolonel, L.K., Henderson, B.E., Le Marchand, L., Brennan, P., Sangrajrang, S., Gaborieau, V., Odefrey, F., Shen, C.Y., Wu, P.E., Wang, H.C., Eccles, D., Evans, D.G., Peto, J., Fletcher, O., Johnson, N., Seal, S., Stratton, M.R., Rahman, N., Chenevix-Trench, G., Bojesen, S.E., Nordestgaard, B.G., Axelsson, C.K., Garcia-Closas, M., Brinton, L., Chanock, S., Lissowska, J., Peplonska, B., Nevanlinna, H., Fagerholm, R., Eerola, H., Kang, D., Yoo, K.Y., Noh, D.Y., Ahn, S.H., Hunter, D.J., Hankinson, S.E., Cox, D.G., Hall, P., Wedren, S., Liu, J., Low, Y.L., Bogdanova, N., Schurmann, P., Dork, T., Tollenaar, R.A., Jacobi, C.E., Devilee, P., Klijn, J.G., Sigurdson, A.J., Doody, M.M., Alexander, B.H., Zhang, J., Cox, A., Brock, I.W., MacPherson, G., Reed, M.W., Couch, F.J., Goode, E.L., Olson, J.E., Meijers-Heijboer, H., van den Ouweland, A., Uitterlinden, A., Rivadeneira, F., Milne, R.L., Ribas, G., Gonzalez-Neira, A., Benitez, J., Hopper, J.L., McCredie, M., Southey, M., Giles, G.G., Schroen, C., Justenhoven, C., Brauch, H., Hamann, U., Ko, Y.D., Spurdle, A.B., Beesley, J., Chen, X., Mannermaa, A., Kosma, V.M., Kataja, V., Hartikainen, J., Day, N.E., Cox, D.R. and Ponder, B.A. (2007). "Genome-wide association study identifies novel breast cancer susceptibility loci." Nature 447(7148): 1087-1093.

References

226

Ee, P.L., He, X., Ross, D.D. and Beck, W.T. (2004a). "Modulation of breast cancer resistance protein (BCRP/ABCG2) gene expression using RNA interference." Mol Cancer Ther 3(12): 1577-1583.

Ee, P.L., Kamalakaran, S., Tonetti, D., He, X., Ross, D.D. and Beck, W.T. (2004b). "Identification of a novel estrogen response element in the breast cancer resistance protein (ABCG2) gene." Cancer Res 64(4): 1247-1251.

Ehata, S., Johansson, E., Katayama, R., Koike, S., Watanabe, A., Hoshino, Y., Katsuno, Y., Komuro, A., Koinuma, D., Kano, M.R., Yashiro, M., Hirakawa, K., Aburatani, H., Fujita, N. and Miyazono, K. (2011). "Transforming growth factor-beta decreases the cancer-initiating cell population within diffuse-type gastric carcinoma cells." Oncogene 30(14): 1693-1705.

Eide, T., Ramberg, H., Glackin, C., Tindall, D. and Tasken, K.A. (2013). "TWIST1, A novel androgen-regulated gene, is a target for NKX3-1 in prostate cancer cells." Cancer Cell Int 13(1): 4.

Ejendal, K.F., Diop, N.K., Schweiger, L.C. and Hrycyna, C.A. (2006). "The nature of amino acid 482 of human ABCG2 affects substrate transport and ATP hydrolysis but not substrate binding." Protein Sci 15(7): 1597-1607.

Elkin, M., Orgel, A. and Kleinman, H.K. (2004). "An angiogenic switch in breast cancer involves estrogen and soluble vascular endothelial growth factor receptor 1." J Natl Cancer Inst 96(11): 875-878.

Engel, M.E., McDonnell, M.A., Law, B.K. and Moses, H.L. (1999). "Interdependent SMAD and JNK signaling in transforming growth factor-beta-mediated transcription." J Biol Chem 274(52): 37413-37420.

Engelmann, K., Shen, H. and Finn, O.J. (2008). "MCF7 side population cells with characteristics of cancer stem/progenitor cells express the tumor antigen MUC1." Cancer Res 68(7): 2419-2426.

Faneyte, I.F., Kristel, P.M., Maliepaard, M., Scheffer, G.L., Scheper, R.J., Schellens, J.H. and van de Vijver, M.J. (2002). "Expression of the breast cancer resistance protein in breast cancer." Clin Cancer Res 8(4): 1068-1074.

Farmer, P., Bonnefoi, H., Becette, V., Tubiana-Hulin, M., Fumoleau, P., Larsimont, D., Macgrogan, G., Bergh, J., Cameron, D., Goldstein, D., Duss, S., Nicoulaz, A.L., Brisken, C., Fiche, M., Delorenzi, M. and Iggo, R. (2005). "Identification of molecular apocrine breast tumours by microarray analysis." Oncogene 24(29): 4660-4671.

Faro, A., Boj, S.F., Ambrosio, R., van den Broek, O., Korving, J. and Clevers, H. (2009). "T-cell factor 4 (tcf7l2) is the main effector of Wnt signaling during zebrafish intestine organogenesis." Zebrafish 6(1): 59-68.

Fedoruk, M.N., Gimenez-Bonafe, P., Guns, E.S., Mayer, L.D. and Nelson, C.C. (2004). "P-glycoprotein increases the efflux of the androgen dihydrotestosterone and reduces androgen responsive gene activity in prostate tumor cells." Prostate 59(1): 77-90.

Feldman, B.J. and Feldman, D. (2001). "The development of androgen-independent prostate cancer." Nat Rev Cancer 1(1): 34-45.

Feldmann, G., Dhara, S., Fendrich, V., Bedja, D., Beaty, R., Mullendore, M., Karikari, C., Alvarez, H., Iacobuzio-Donahue, C., Jimeno, A., Gabrielson, K.L., Matsui, W. and Maitra, A. (2007). "Blockade of hedgehog signaling inhibits pancreatic cancer invasion

References

227

and metastases: a new paradigm for combination therapy in solid cancers." Cancer Res 67(5): 2187-2196.

Fellner, S., Bauer, B., Miller, D.S., Schaffrik, M., Fankhanel, M., Spruss, T., Bernhardt, G., Graeff, C., Farber, L., Gschaidmeier, H., Buschauer, A. and Fricker, G. (2002). "Transport of paclitaxel (Taxol) across the blood-brain barrier in vitro and in vivo." J Clin Invest 110(9): 1309-1318.

Fiaschi, M., Rozell, B., Bergstrom, A. and Toftgard, R. (2009). "Development of mammary tumors by conditional expression of GLI1." Cancer Res 69(11): 4810-4817.

Figueira, R.C., Gomes, L.R., Neto, J.S., Silva, F.C., Silva, I.D. and Sogayar, M.C. (2009). "Correlation between MMPs and their inhibitors in breast cancer tumor tissue specimens and in cell lines with different metastatic potential." BMC Cancer 9: 20.

Finn, R.S., Crown, J.P., Lang, I., Boer, K., Bondarenko, I.M., Kulyk, S.O., Ettl, J., Patel, R., Pinter, T., Schmidt, M., Shparyk, Y., Thummala, A.R., Voytko, N.L., Fowst, C., Huang, X., Kim, S.T., Randolph, S. and Slamon, D.J. (2015). "The cyclin-dependent kinase 4/6 inhibitor palbociclib in combination with letrozole versus letrozole alone as first-line treatment of oestrogen receptor-positive, HER2-negative, advanced breast cancer (PALOMA-1/TRIO-18): a randomised phase 2 study." Lancet Oncol 16(1): 25-35.

Finn, R.S., Dering, J., Conklin, D., Kalous, O., Cohen, D.J., Desai, A.J., Ginther, C., Atefi, M., Chen, I., Fowst, C., Los, G. and Slamon, D.J. (2009). "PD 0332991, a selective cyclin D kinase 4/6 inhibitor, preferentially inhibits proliferation of luminal estrogen receptor-positive human breast cancer cell lines in vitro." Breast Cancer Res 11(5): R77.

Fracasso, P.M., Goldstein, L.J., de Alwis, D.P., Rader, J.S., Arquette, M.A., Goodner, S.A., Wright, L.P., Fears, C.L., Gazak, R.J., Andre, V.A., Burgess, M.F., Slapak, C.A. and Schellens, J.H. (2004). "Phase I study of docetaxel in combination with the P-glycoprotein inhibitor, zosuquidar, in resistant malignancies." Clin Cancer Res 10(21): 7220-7228.

Francis, P., Crown, J., Di Leo, A., Buyse, M., Balil, A., Andersson, M., Nordenskjold, B., Lang, I., Jakesz, R., Vorobiof, D., Gutierrez, J., van Hazel, G., Dolci, S., Jamin, S., Bendahmane, B., Gelber, R.D., Goldhirsch, A., Castiglione-Gertsch, M. and Piccart-Gebhart, M. (2008). "Adjuvant chemotherapy with sequential or concurrent anthracycline and docetaxel: Breast International Group 02-98 randomized trial." J Natl Cancer Inst 100(2): 121-133.

Friedenberg, W.R., Rue, M., Blood, E.A., Dalton, W.S., Shustik, C., Larson, R.A., Sonneveld, P. and Greipp, P.R. (2006). "Phase III study of PSC-833 (valspodar) in combination with vincristine, doxorubicin, and dexamethasone (valspodar/VAD) versus VAD alone in patients with recurring or refractory multiple myeloma (E1A95): a trial of the Eastern Cooperative Oncology Group." Cancer 106(4): 830-838.

Fryar, E.B., Das, J.R., Davis, J.H., Desoto, J.A., Laniyan, I., Southerland, W.M. and Bowen, D. (2006). "Raloxifene attenuation of 5-FU/methotrexate cytotoxicity in human breast cancer cells: the importance of sequence in combination chemotherapy." Anticancer Res 26(3A): 1861-1867.

Fuchs, I.B., Lichtenegger, W., Buehler, H., Henrich, W., Stein, H., Kleine-Tebbe, A. and Schaller, G. (2002). "The prognostic significance of epithelial-mesenchymal transition in breast cancer." Anticancer Res 22(6A): 3415-3419.

Fujita, N., Jaye, D.L., Kajita, M., Geigerman, C., Moreno, C.S. and Wade, P.A. (2003). "MTA3, a Mi-2/NuRD complex subunit, regulates an invasive growth pathway in breast cancer." Cell 113(2): 207-219.

References

228

Gadsby, D.C., Vergani, P. and Csanady, L. (2006). "The ABC protein turned chloride channel whose failure causes cystic fibrosis." Nature 440(7083): 477-483.

Gajewska, M., Zielniok, K. and Motyl, T. (2013). Autophagy in development and remodelling of mammary gland. Autophagy - A Double-Edged Sword - Cell Survival or Death? Y. Bailly, InTech: 443-463.

Gallego, M.I., Binart, N., Robinson, G.W., Okagaki, R., Coschigano, K.T., Perry, J., Kopchick, J.J., Oka, T., Kelly, P.A. and Hennighausen, L. (2001). "Prolactin, growth hormone, and epidermal growth factor activate Stat5 in different compartments of mammary tissue and exert different and overlapping developmental effects." Dev Biol 229(1): 163-175.

Gao, L., Schwartzman, J., Gibbs, A., Lisac, R., Kleinschmidt, R., Wilmot, B., Bottomly, D., Coleman, I., Nelson, P., McWeeney, S. and Alumkal, J. (2013). "Androgen receptor promotes ligand-independent prostate cancer progression through c-Myc upregulation." PLoS One 8(5): e63563.

Gao, W. and Dalton, J.T. (2007). "Expanding the therapeutic use of androgens via selective androgen receptor modulators (SARMs)." Drug Discov Today 12(5-6): 241-248.

Garcia-Mata, R., Bebok, Z., Sorscher, E.J. and Sztul, E.S. (1999). "Characterization and dynamics of aggresome formation by a cytosolic GFP-chimera." J Cell Biol 146(6): 1239-1254.

Garcia-Mata, R., Gao, Y.S. and Sztul, E. (2002). "Hassles with taking out the garbage: aggravating aggresomes." Traffic 3(6): 388-396.

Gaughan, L., Logan, I.R., Neal, D.E. and Robson, C.N. (2005). "Regulation of androgen receptor and histone deacetylase 1 by Mdm2-mediated ubiquitylation." Nucleic Acids Res 33(1): 13-26.

Geisler, J., King, N., Anker, G., Ornati, G., Di Salle, E., Lonning, P.E. and Dowsett, M. (1998). "In vivo inhibition of aromatization by exemestane, a novel irreversible aromatase inhibitor, in postmenopausal breast cancer patients." Clin Cancer Res 4(9): 2089-2093.

Geisler, J., King, N., Dowsett, M., Ottestad, L., Lundgren, S., Walton, P., Kormeset, P.O. and Lonning, P.E. (1996). "Influence of anastrozole (Arimidex), a selective, non-steroidal aromatase inhibitor, on in vivo aromatisation and plasma oestrogen levels in postmenopausal women with breast cancer." Br J Cancer 74(8): 1286-1291.

Gerrard, G., Payne, E., Baker, R.J., Jones, D.T., Potter, M., Prentice, H.G., Ethell, M., McCullough, H., Burgess, M., Mehta, A.B. and Ganeshaguru, K. (2004). "Clinical effects and P-glycoprotein inhibition in patients with acute myeloid leukemia treated with zosuquidar trihydrochloride, daunorubicin and cytarabine." Haematologica 89(7): 782-790.

Gianni, L., Romieu, G.H., Lichinitser, M., Serrano, S.V., Mansutti, M., Pivot, X., Mariani, P., Andre, F., Chan, A., Lipatov, O., Chan, S., Wardley, A., Greil, R., Moore, N., Prot, S., Pallaud, C. and Semiglazov, V. (2013). "AVEREL: a randomized phase III Trial evaluating bevacizumab in combination with docetaxel and trastuzumab as first-line therapy for HER2-positive locally recurrent/metastatic breast cancer." J Clin Oncol 31(14): 1719-1725.

Ginestier, C., Hur, M.H., Charafe-Jauffret, E., Monville, F., Dutcher, J., Brown, M., Jacquemier, J., Viens, P., Kleer, C.G., Liu, S., Schott, A., Hayes, D., Birnbaum, D., Wicha, M.S. and Dontu, G. (2007). "ALDH1 is a marker of normal and malignant human mammary stem cells and a predictor of poor clinical outcome." Cell Stem Cell 1(5): 555-567.

References

229

Girnita, A., Zheng, H., Gronberg, A., Girnita, L. and Stahle, M. (2012). "Identification of the cathelicidin peptide LL-37 as agonist for the type I insulin-like growth factor receptor." Oncogene 31(3): 352-365.

Goel, H.L., Underwood, J.M., Nickerson, J.A., Hsieh, C.C. and Languino, L.R. (2010). "Beta1 integrins mediate cell proliferation in three-dimensional cultures by regulating expression of the sonic hedgehog effector protein, GLI1." J Cell Physiol 224(1): 210-217.

Goel, S., Sharma, R., Hamilton, A. and Beith, J. (2009). "LHRH agonists for adjuvant therapy of early breast cancer in premenopausal women." Cochrane Database Syst Rev(4): CD004562.

Gokmen-Polar, Y., Goswami, C.P., Toroni, R.A., Sanders, K.L., Mehta, R., Sirimalle, U., Tanasa, B., Shen, C., Li, L., Ivan, M., Badve, S. and Sledge, G.W., Jr. (2014). "Gene expression analysis reveals distinct pathways of resistance to bevacizumab in xenograft models of human ER-positive breast cancer." J Cancer 5(8): 633-645.

Goler-Baron, V. and Assaraf, Y.G. (2011). "Structure and function of ABCG2-rich extracellular vesicles mediating multidrug resistance." PLoS One 6(1): e16007.

Goler-Baron, V., Sladkevich, I. and Assaraf, Y.G. (2012). "Inhibition of the PI3K-Akt signaling pathway disrupts ABCG2-rich extracellular vesicles and overcomes multidrug resistance in breast cancer cells." Biochem Pharmacol 83(10): 1340-1348.

Gonzalez-Angulo, A.M., Krop, I., Akcakanat, A., Chen, H., Liu, S., Li, Y., Culotta, K.S., Tarco, E., Piha-Paul, S., Moulder-Thompson, S., Velez-Bravo, V., Sahin, A.A., Doyle, L.A., Do, K.A., Winer, E.P., Mills, G.B., Kurzrock, R. and Meric-Bernstam, F. (2015). "SU2C phase Ib study of paclitaxel and MK-2206 in advanced solid tumors and metastatic breast cancer." J Natl Cancer Inst 107(3).

Gonzalez, L.O., Corte, M.D., Vazquez, J., Junquera, S., Sanchez, R., Alvarez, A.C., Rodriguez, J.C., Lamelas, M.L. and Vizoso, F.J. (2008). "Androgen receptor expresion in breast cancer: relationship with clinicopathological characteristics of the tumors, prognosis, and expression of metalloproteases and their inhibitors." BMC Cancer 8: 149.

Goss, P.E., Ingle, J.N., Pater, J.L., Martino, S., Robert, N.J., Muss, H.B., Piccart, M.J., Castiglione, M., Shepherd, L.E., Pritchard, K.I., Livingston, R.B., Davidson, N.E., Norton, L., Perez, E.A., Abrams, J.S., Cameron, D.A., Palmer, M.J. and Tu, D. (2008). "Late extended adjuvant treatment with letrozole improves outcome in women with early-stage breast cancer who complete 5 years of tamoxifen." J Clin Oncol 26(12): 1948-1955.

Gowda, P.S., Deng, J.D., Mishra, S., Bandyopadhyay, A., Liang, S., Lin, S., Mahalingam, D. and Sun, L.Z. (2013). "Inhibition of hedgehog and androgen receptor signaling pathways produced synergistic suppression of castration-resistant prostate cancer progression." Mol Cancer Res 11(11): 1448-1461.

Graham, J.D. and Clarke, C.L. (2002). "Expression and transcriptional activity of progesterone receptor A and progesterone receptor B in mammalian cells." Breast Cancer Res 4(5): 187-190.

Graham, T.R., Yacoub, R., Taliaferro-Smith, L., Osunkoya, A.O., Odero-Marah, V.A., Liu, T., Kimbro, K.S., Sharma, D. and O'Regan, R.M. (2010). "Reciprocal regulation of ZEB1 and AR in triple negative breast cancer cells." Breast Cancer Res Treat 123(1): 139-147.

References

230

Greeve, M.A., Allan, R.K., Harvey, J.M. and Bentel, J.M. (2004). "Inhibition of MCF-7 breast cancer cell proliferation by 5alpha-dihydrotestosterone; a role for p21(Cip1/Waf1)." J Mol Endocrinol 32(3): 793-810.

Gregory, P.A., Bert, A.G., Paterson, E.L., Barry, S.C., Tsykin, A., Farshid, G., Vadas, M.A., Khew-Goodall, Y. and Goodall, G.J. (2008). "The miR-200 family and miR-205 regulate epithelial to mesenchymal transition by targeting ZEB1 and SIP1." Nat Cell Biol 10(5): 593-601.

Groulx, J.F., Giroux, V., Beausejour, M., Boudjadi, S., Basora, N., Carrier, J.C. and Beaulieu, J.F. (2014). "Integrin alpha6A splice variant regulates proliferation and the Wnt/beta-catenin pathway in human colorectal cancer cells." Carcinogenesis 35(6): 1217-1227.

Gucalp, A., Tolaney, S., Isakoff, S.J., Ingle, J.N., Liu, M.C., Carey, L.A., Blackwell, K., Rugo, H., Nabell, L., Forero, A., Stearns, V., Doane, A.S., Danso, M., Moynahan, M.E., Momen, L.F., Gonzalez, J.M., Akhtar, A., Giri, D.D., Patil, S., Feigin, K.N., Hudis, C.A. and Traina, T.A. (2013). "Phase II trial of bicalutamide in patients with androgen receptor-positive, estrogen receptor-negative metastatic breast cancer." Clin Cancer Res 19(19): 5505-5512.

Guo, W., Pylayeva, Y., Pepe, A., Yoshioka, T., Muller, W.J., Inghirami, G. and Giancotti, F.G. (2006). "Beta 4 integrin amplifies ErbB2 signaling to promote mammary tumorigenesis." Cell 126(3): 489-502.

Gutierrez, M.C., Detre, S., Johnston, S., Mohsin, S.K., Shou, J., Allred, D.C., Schiff, R., Osborne, C.K. and Dowsett, M. (2005). "Molecular changes in tamoxifen-resistant breast cancer: relationship between estrogen receptor, HER-2, and p38 mitogen-activated protein kinase." J Clin Oncol 23(11): 2469-2476.

Guzel, E., Karatas, O.F., Duz, M.B., Solak, M., Ittmann, M. and Ozen, M. (2014). "Differential expression of stem cell markers and ABCG2 in recurrent prostate cancer." Prostate 74(15): 1498-1505.

Hackenberg, R., Luttchens, S., Hofmann, J., Kunzmann, R., Holzel, F. and Schulz, K.D. (1991). "Androgen sensitivity of the new human breast cancer cell line MFM-223." Cancer Res 51(20): 5722-5727.

Haider, A.J., Briggs, D., Self, T.J., Chilvers, H.L., Holliday, N.D. and Kerr, I.D. (2011). "Dimerization of ABCG2 analysed by bimolecular fluorescence complementation." PLoS One 6(10): e25818.

Hajra, K.M., Chen, D.Y. and Fearon, E.R. (2002). "The SLUG zinc-finger protein represses E-cadherin in breast cancer." Cancer Res 62(6): 1613-1618.

Hallett, R.M., Huang, C., Motazedian, A., Auf der Mauer, S., Pond, G.R., Hassell, J.A., Nordon, R.E. and Draper, J.S. (2015). "Treatment-induced cell cycle kinetics dictate tumor response to chemotherapy." Oncotarget 6(9): 7040-7052.

Haluska, P., Shaw, H.M., Batzel, G.N., Yin, D., Molina, J.R., Molife, L.R., Yap, T.A., Roberts, M.L., Sharma, A., Gualberto, A., Adjei, A.A. and de Bono, J.S. (2007). "Phase I dose escalation study of the anti insulin-like growth factor-I receptor monoclonal antibody CP-751,871 in patients with refractory solid tumors." Clin Cancer Res 13(19): 5834-5840.

Han, L., Shi, S., Gong, T., Zhang, Z. and Sun, X. (2013). "Cancer stem cells: therapeutic implications and perspectives in cancer therapy." Acta Pharmaceutica Sinica B 3(2): 65-75.

References

231

Han, S., Park, K., Kim, H.Y., Lee, M.S., Kim, H.J. and Kim, Y.D. (1999). "Reduced expression of p27Kip1 protein is associated with poor clinical outcome of breast cancer patients treated with systemic chemotherapy and is linked to cell proliferation and differentiation." Breast Cancer Res Treat 55(2): 161-167.

Hara, T., Miyazaki, H., Lee, A., Tran, C.P. and Reiter, R.E. (2008). "Androgen receptor and invasion in prostate cancer." Cancer Res 68(4): 1128-1135.

Harada, S., Mick, R., Roses, R.E., Graves, H., Niu, H., Sharma, A., Schueller, J.E., Nisenbaum, H., Czerniecki, B.J. and Zhang, P.J. (2011). "The significance of HER-2/neu receptor positivity and immunophenotype in ductal carcinoma in situ with early invasive disease." J Surg Oncol 104(5): 458-465.

Hazan, R.B., Phillips, G.R., Qiao, R.F., Norton, L. and Aaronson, S.A. (2000). "Exogenous expression of N-cadherin in breast cancer cells induces cell migration, invasion, and metastasis." J Cell Biol 148(4): 779-790.

He, B., Lee, L.W., Minges, J.T. and Wilson, E.M. (2002). "Dependence of selective gene activation on the androgen receptor NH2- and COOH-terminal interaction." J Biol Chem 277(28): 25631-25639.

He, D., Zhao, X.Q., Chen, X.G., Fang, Y., Singh, S., Talele, T.T., Qiu, H.J., Liang, Y.J., Wang, X.K., Zhang, G.Q., Chen, Z.S. and Fu, L.W. (2013). "BIRB796, the inhibitor of p38 mitogen-activated protein kinase, enhances the efficacy of chemotherapeutic agents in ABCB1 overexpression cells." PLoS One 8(1): e54181.

He, J., Peng, R., Yuan, Z., Wang, S., Peng, J., Lin, G., Jiang, X. and Qin, T. (2012). "Prognostic value of androgen receptor expression in operable triple-negative breast cancer: a retrospective analysis based on a tissue microarray." Med Oncol 29(2): 406-410.

He, T.C., Sparks, A.B., Rago, C., Hermeking, H., Zawel, L., da Costa, L.T., Morin, P.J., Vogelstein, B. and Kinzler, K.W. (1998). "Identification of c-MYC as a target of the APC pathway." Science 281(5382): 1509-1512.

Heinlein, C.A. and Chang, C. (2002). "Androgen receptor (AR) coregulators: an overview." Endocr Rev 23(2): 175-200.

Heldin, C.H. (2013). "Targeting the PDGF signaling pathway in tumor treatment." Cell Commun Signal 11: 97.

Henriksen, U., Fog, J.U., Litman, T. and Gether, U. (2005). "Identification of intra- and intermolecular disulfide bridges in the multidrug resistance transporter ABCG2." J Biol Chem 280(44): 36926-36934.

Heretsch, P., Tzagkaroulaki, L. and Giannis, A. (2010). "Modulators of the hedgehog signaling pathway." Bioorg Med Chem 18(18): 6613-6624.

Hess, D.A., Meyerrose, T.E., Wirthlin, L., Craft, T.P., Herrbrich, P.E., Creer, M.H. and Nolta, J.A. (2004). "Functional characterization of highly purified human hematopoietic repopulating cells isolated according to aldehyde dehydrogenase activity." Blood 104(6): 1648-1655.

Hicklin, D.J. and Ellis, L.M. (2005). "Role of the vascular endothelial growth factor pathway in tumor growth and angiogenesis." J Clin Oncol 23(5): 1011-1027.

Higgins, C.F. (1992). "ABC transporters: from microorganisms to man." Annu Rev Cell Biol 8: 67-113.

References

232

Ho, L.L., Kench, J.G., Handelsman, D.J., Scheffer, G.L., Stricker, P.D., Grygiel, J.G., Sutherland, R.L., Henshall, S.M., Allen, J.D. and Horvath, L.G. (2008). "Androgen regulation of multidrug resistance-associated protein 4 (MRP4/ABCC4) in prostate cancer." Prostate 68(13): 1421-1429.

Ho, M.M., Ng, A.V., Lam, S. and Hung, J.Y. (2007). "Side population in human lung cancer cell lines and tumors is enriched with stem-like cancer cells." Cancer Res 67(10): 4827-4833.

Holohan, C., Van Schaeybroeck, S., Longley, D.B. and Johnston, P.G. (2013). "Cancer drug resistance: an evolving paradigm." Nat Rev Cancer 13(10): 714-726.

Hong, J., Zhou, J., Fu, J., He, T., Qin, J., Wang, L., Liao, L. and Xu, J. (2011). "Phosphorylation of serine 68 of Twist1 by MAPKs stabilizes Twist1 protein and promotes breast cancer cell invasiveness." Cancer Res 71(11): 3980-3990.

Honjo, Y., Hrycyna, C.A., Yan, Q.W., Medina-Perez, W.Y., Robey, R.W., van de Laar, A., Litman, T., Dean, M. and Bates, S.E. (2001). "Acquired mutations in the MXR/BCRP/ABCP gene alter substrate specificity in MXR/BCRP/ABCP-overexpressing cells." Cancer Res 61(18): 6635-6639.

Hopper-Borge, E.A., Churchill, T., Paulose, C., Nicolas, E., Jacobs, J.D., Ngo, O., Kuang, Y., Grinberg, A., Westphal, H., Chen, Z.S., Klein-Szanto, A.J., Belinsky, M.G. and Kruh, G.D. (2011). "Contribution of Abcc10 (Mrp7) to in vivo paclitaxel resistance as assessed in Abcc10(-/-) mice." Cancer Res 71(10): 3649-3657.

Hopper, E., Belinsky, M.G., Zeng, H., Tosolini, A., Testa, J.R. and Kruh, G.D. (2001). "Analysis of the structure and expression pattern of MRP7 (ABCC10), a new member of the MRP subfamily." Cancer Lett 162(2): 181-191.

Horwitz, K.B., Costlow, M.E. and McGuire, W.L. (1975). "MCF-7; a human breast cancer cell line with estrogen, androgen, progesterone, and glucocorticoid receptors." Steroids 26(6): 785-795.

Housman, G., Byler, S., Heerboth, S., Lapinska, K., Longacre, M., Snyder, N. and Sarkar, S. (2014). "Drug resistance in cancer: an overview." Cancers (Basel) 6(3): 1769-1792.

Howell, A., Cuzick, J., Baum, M., Buzdar, A., Dowsett, M., Forbes, J.F., Hoctin-Boes, G., Houghton, J., Locker, G.Y. and Tobias, J.S. (2005). "Results of the ATAC (Arimidex, Tamoxifen, Alone or in Combination) trial after completion of 5 years' adjuvant treatment for breast cancer." Lancet 365(9453): 60-62.

Hsieh, T.F., Chen, C.C., Yu, A.L., Ma, W.L., Zhang, C., Shyr, C.R. and Chang, C. (2013). "Androgen receptor decreases the cytotoxic effects of chemotherapeutic drugs in upper urinary tract urothelial carcinoma cells." Oncol Lett 5(4): 1325-1330.

Huang, H., Zegarra-Moro, O.L., Benson, D. and Tindall, D.J. (2004). "Androgens repress Bcl-2 expression via activation of the retinoblastoma (RB) protein in prostate cancer cells." Oncogene 23(12): 2161-2176.

Hubensack, M., Muller, C., Hocherl, P., Fellner, S., Spruss, T., Bernhardt, G. and Buschauer, A. (2008). "Effect of the ABCB1 modulators elacridar and tariquidar on the distribution of paclitaxel in nude mice." J Cancer Res Clin Oncol 134(5): 597-607.

Huber, M.A., Kraut, N. and Beug, H. (2005). "Molecular requirements for epithelial-mesenchymal transition during tumor progression." Curr Opin Cell Biol 17(5): 548-558.

References

233

Huls, M., Russel, F.G. and Masereeuw, R. (2009). "The role of ATP binding cassette transporters in tissue defense and organ regeneration." J Pharmacol Exp Ther 328(1): 3-9.

Hunter, D.J., Kraft, P., Jacobs, K.B., Cox, D.G., Yeager, M., Hankinson, S.E., Wacholder, S., Wang, Z., Welch, R., Hutchinson, A., Wang, J., Yu, K., Chatterjee, N., Orr, N., Willett, W.C., Colditz, G.A., Ziegler, R.G., Berg, C.D., Buys, S.S., McCarty, C.A., Feigelson, H.S., Calle, E.E., Thun, M.J., Hayes, R.B., Tucker, M., Gerhard, D.S., Fraumeni, J.F., Jr., Hoover, R.N., Thomas, G. and Chanock, S.J. (2007). "A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer." Nat Genet 39(7): 870-874.

Hurtado, A., Holmes, K.A., Ross-Innes, C.S., Schmidt, D. and Carroll, J.S. (2011). "FOXA1 is a key determinant of estrogen receptor function and endocrine response." Nat Genet 43(1): 27-33.

Huss, W.J., Gray, D.R., Greenberg, N.M., Mohler, J.L. and Smith, G.J. (2005). "Breast cancer resistance protein-mediated efflux of androgen in putative benign and malignant prostate stem cells." Cancer Res 65(15): 6640-6650.

Hutchinson, L. (2010). "Targeted therapies: lapatinib is effective in patients with p95HER2-positive tumors." Nat Rev Clin Oncol 7(7): 358.

Hwang, R.F., Moore, T.T., Hattersley, M.M., Scarpitti, M., Yang, B., Devereaux, E., Ramachandran, V., Arumugam, T., Ji, B., Logsdon, C.D., Brown, J.L. and Godin, R. (2012). "Inhibition of the hedgehog pathway targets the tumor-associated stroma in pancreatic cancer." Mol Cancer Res 10(9): 1147-1157.

Ifergan, I., Scheffer, G.L. and Assaraf, Y.G. (2005). "Novel extracellular vesicles mediate an ABCG2-dependent anticancer drug sequestration and resistance." Cancer Res 65(23): 10952-10958.

Ikeda, H., Taira, N., Nogami, T., Shien, K., Okada, M., Shien, T., Doihara, H. and Miyoshi, S. (2011). "Combination treatment with fulvestrant and various cytotoxic agents (doxorubicin, paclitaxel, docetaxel, vinorelbine, and 5-fluorouracil) has a synergistic effect in estrogen receptor-positive breast cancer." Cancer Sci 102(11): 2038-2042.

Imai, Y., Asada, S., Tsukahara, S., Ishikawa, E., Tsuruo, T. and Sugimoto, Y. (2003). "Breast cancer resistance protein exports sulfated estrogens but not free estrogens." Mol Pharmacol 64(3): 610-618.

Imai, Y., Ishikawa, E., Asada, S. and Sugimoto, Y. (2005). "Estrogen-mediated post transcriptional down-regulation of breast cancer resistance protein/ABCG2." Cancer Res 65(2): 596-604.

Iqbal, N. (2014). "Human epidermal growth factor receptor 2 (HER2) in cancers: overexpression and therapeutic implications." Mol Biol Int 2014: 852748.

Iseri, O.D., Kars, M.D., Arpaci, F., Atalay, C., Pak, I. and Gunduz, U. (2011). "Drug resistant MCF-7 cells exhibit epithelial-mesenchymal transition gene expression pattern." Biomed Pharmacother 65(1): 40-45.

Ishitani, T., Ninomiya-Tsuji, J., Nagai, S., Nishita, M., Meneghini, M., Barker, N., Waterman, M., Bowerman, B., Clevers, H., Shibuya, H. and Matsumoto, K. (1999). "The TAK1-NLK-MAPK-related pathway antagonizes signalling between beta-catenin and transcription factor TCF." Nature 399(6738): 798-802.

References

234

Isola, J.J. (1993). "Immunohistochemical demonstration of androgen receptor in breast cancer and its relationship to other prognostic factors." J Pathol 170(1): 31-35.

Itoh, T., Karlsberg, K., Kijima, I., Yuan, Y.C., Smith, D., Ye, J. and Chen, S. (2005). "Letrozole-, anastrozole-, and tamoxifen-responsive genes in MCF-7aro cells: a microarray approach." Mol Cancer Res 3(4): 203-218.

Iwata, A., Christianson, J.C., Bucci, M., Ellerby, L.M., Nukina, N., Forno, L.S. and Kopito, R.R. (2005a). "Increased susceptibility of cytoplasmic over nuclear polyglutamine aggregates to autophagic degradation." Proc Natl Acad Sci U S A 102(37): 13135-13140.

Iwata, A., Riley, B.E., Johnston, J.A. and Kopito, R.R. (2005b). "HDAC6 and microtubules are required for autophagic degradation of aggregated huntingtin." J Biol Chem 280(48): 40282-40292.

Janknecht, R., Wells, N.J. and Hunter, T. (1998). "TGF-beta-stimulated cooperation of smad proteins with the coactivators CBP/p300." Genes Dev 12(14): 2114-2119.

Jennbacken, K., Tesan, T., Wang, W., Gustavsson, H., Damber, J.E. and Welen, K. (2010). "N-cadherin increases after androgen deprivation and is associated with metastasis in prostate cancer." Endocr Relat Cancer 17(2): 469-479.

Jeselsohn, R., Yelensky, R., Buchwalter, G., Frampton, G., Meric-Bernstam, F., Gonzalez-Angulo, A.M., Ferrer-Lozano, J., Perez-Fidalgo, J.A., Cristofanilli, M., Gomez, H., Arteaga, C.L., Giltnane, J., Balko, J.M., Cronin, M.T., Jarosz, M., Sun, J., Hawryluk, M., Lipson, D., Otto, G., Ross, J.S., Dvir, A., Soussan-Gutman, L., Wolf, I., Rubinek, T., Gilmore, L., Schnitt, S., Come, S.E., Pusztai, L., Stephens, P., Brown, M. and Miller, V.A. (2014). "Emergence of constitutively active estrogen receptor-alpha mutations in pretreated advanced estrogen receptor-positive breast cancer." Clin Cancer Res 20(7): 1757-1767.

Jia, Y., Zeng, Z.Z., Markwart, S.M., Rockwood, K.F., Ignatoski, K.M., Ethier, S.P. and Livant, D.L. (2004). "Integrin fibronectin receptors in matrix metalloproteinase-1-dependent invasion by breast cancer and mammary epithelial cells." Cancer Res 64(23): 8674-8681.

Jiang, Y., He, Y., Li, H., Li, H.N., Zhang, L., Hu, W., Sun, Y.M., Chen, F.L. and Jin, X.M. (2012). "Expressions of putative cancer stem cell markers ABCB1, ABCG2, and CD133 are correlated with the degree of differentiation of gastric cancer." Gastric Cancer 15(4): 440-450.

Jimenez-Salazar, J.E., Posadas-Rodriguez, P., Lazzarini-Lechuga, R.C., Luna-Lopez, A., Zentella-Dehesa, A., Gomez-Quiroz, L.E., Konigsberg, M., Dominguez-Gomez, G. and Damian-Matsumura, P. (2014). "Membrane-initiated estradiol signaling of epithelial-mesenchymal transition-associated mechanisms through regulation of tight junctions in human breast cancer cells." Horm Cancer 5(3): 161-173.

Johnson, D.R., Finch, R.A., Lin, Z.P., Zeiss, C.J. and Sartorelli, A.C. (2001a). "The pharmacological phenotype of combined multidrug-resistance mdr1a/1b- and mrp1-deficient mice." Cancer Res 61(4): 1469-1476.

Johnson, R.A., Ince, T.A. and Scotto, K.W. (2001b). "Transcriptional repression by p53 through direct binding to a novel DNA element." J Biol Chem 276(29): 27716-27720.

Johnson, R.W., Nguyen, M.P., Padalecki, S.S., Grubbs, B.G., Merkel, A.R., Oyajobi, B.O., Matrisian, L.M., Mundy, G.R. and Sterling, J.A. (2011). "TGF-beta promotion of Gli2-induced expression of parathyroid hormone-related protein, an important osteolytic

References

235

factor in bone metastasis, is independent of canonical Hedgehog signaling." Cancer Res 71(3): 822-831.

Johnston, S.R., Saccani-Jotti, G., Smith, I.E., Salter, J., Newby, J., Coppen, M., Ebbs, S.R. and Dowsett, M. (1995). "Changes in estrogen receptor, progesterone receptor, and pS2 expression in tamoxifen-resistant human breast cancer." Cancer Res 55(15): 3331-3338.

Jonker, J.W., Buitelaar, M., Wagenaar, E., Van Der Valk, M.A., Scheffer, G.L., Scheper, R.J., Plosch, T., Kuipers, F., Elferink, R.P., Rosing, H., Beijnen, J.H. and Schinkel, A.H. (2002). "The breast cancer resistance protein protects against a major chlorophyll-derived dietary phototoxin and protoporphyria." Proc Natl Acad Sci U S A 99(24): 15649-15654.

Jonker, J.W., Smit, J.W., Brinkhuis, R.F., Maliepaard, M., Beijnen, J.H., Schellens, J.H. and Schinkel, A.H. (2000). "Role of breast cancer resistance protein in the bioavailability and fetal penetration of topotecan." J Natl Cancer Inst 92(20): 1651-1656.

Kabos, P., Finlay-Schultz, J., Li, C., Kline, E., Finlayson, C., Wisell, J., Manuel, C.A., Edgerton, S.M., Harrell, J.C., Elias, A. and Sartorius, C.A. (2012). "Patient-derived luminal breast cancer xenografts retain hormone receptor heterogeneity and help define unique estrogen-dependent gene signatures." Breast Cancer Res Treat 135(2): 415-432.

Kameda, C., Tanaka, H., Yamasaki, A., Nakamura, M., Koga, K., Sato, N., Kubo, M., Kuroki, S., Tanaka, M. and Katano, M. (2009). "The Hedgehog pathway is a possible therapeutic target for patients with estrogen receptor-negative breast cancer." Anticancer Res 29(3): 871-879.

Kandouz, M., Lombet, A., Perrot, J.Y., Jacob, D., Carvajal, S., Kazem, A., Rostene, W., Therwath, A. and Gompel, A. (1999). "Proapoptotic effects of antiestrogens, progestins and androgen in breast cancer cells." J Steroid Biochem Mol Biol 69(1-6): 463-471.

Kang, H.Y., Lin, H.K., Hu, Y.C., Yeh, S., Huang, K.E. and Chang, C. (2001). "From transforming growth factor-beta signaling to androgen action: identification of Smad3 as an androgen receptor coregulator in prostate cancer cells." Proc Natl Acad Sci U S A 98(6): 3018-3023.

Kanzaki, A., Toi, M., Nakayama, K., Bando, H., Mutoh, M., Uchida, T., Fukumoto, M. and Takebayashi, Y. (2001). "Expression of multidrug resistance-related transporters in human breast carcinoma." Jpn J Cancer Res 92(4): 452-458.

Kasibhatla, S., Baichwal, V., Cai, S.X., Roth, B., Skvortsova, I., Skvortsov, S., Lukas, P., English, N.M., Sirisoma, N., Drewe, J., Pervin, A., Tseng, B., Carlson, R.O. and Pleiman, C.M. (2007). "MPC-6827: a small-molecule inhibitor of microtubule formation that is not a substrate for multidrug resistance pumps." Cancer Res 67(12): 5865-5871.

Kasper, M., Regl, G., Frischauf, A.M. and Aberger, F. (2006). "GLI transcription factors: mediators of oncogenic Hedgehog signalling." Eur J Cancer 42(4): 437-445.

Katayama, K., Yoshioka, S., Tsukahara, S., Mitsuhashi, J. and Sugimoto, Y. (2007). "Inhibition of the mitogen-activated protein kinase pathway results in the down-regulation of P-glycoprotein." Mol Cancer Ther 6(7): 2092-2102.

Kathawala, R.J., Gupta, P., Ashby, C.R., Jr. and Chen, Z.S. (2015). "The modulation of ABC transporter-mediated multidrug resistance in cancer: a review of the past decade." Drug Resist Updat 18: 1-17.

Kaufman, B., Mackey, J.R., Clemens, M.R., Bapsy, P.P., Vaid, A., Wardley, A., Tjulandin, S., Jahn, M., Lehle, M., Feyereislova, A., Revil, C. and Jones, A. (2009). "Trastuzumab plus

References

236

anastrozole versus anastrozole alone for the treatment of postmenopausal women with human epidermal growth factor receptor 2-positive, hormone receptor-positive metastatic breast cancer: results from the randomized phase III TAnDEM study." J Clin Oncol 27(33): 5529-5537.

Kauppila, S., Stenback, F., Risteli, J., Jukkola, A. and Risteli, L. (1998). "Aberrant type I and type III collagen gene expression in human breast cancer in vivo." J Pathol 186(3): 262-268.

Kawaguchi, Y., Kovacs, J.J., McLaurin, A., Vance, J.M., Ito, A. and Yao, T.P. (2003). "The deacetylase HDAC6 regulates aggresome formation and cell viability in response to misfolded protein stress." Cell 115(6): 727-738.

Kawauchi, T. (2012). "Cell adhesion and its endocytic regulation in cell migration during neural development and cancer metastasis." Int J Mol Sci 13(4): 4564-4590.

Kelly, R.J., Draper, D., Chen, C.C., Robey, R.W., Figg, W.D., Piekarz, R.L., Chen, X., Gardner, E.R., Balis, F.M., Venkatesan, A.M., Steinberg, S.M., Fojo, T. and Bates, S.E. (2011). "A pharmacodynamic study of docetaxel in combination with the P-glycoprotein antagonist tariquidar (XR9576) in patients with lung, ovarian, and cervical cancer." Clin Cancer Res 17(3): 569-580.

Kerbel, R.S. (2008). "Tumor angiogenesis." N Engl J Med 358(19): 2039-2049.

Keydar, I., Chen, L., Karby, S., Weiss, F.R., Delarea, J., Radu, M., Chaitcik, S. and Brenner, H.J. (1979). "Establishment and characterization of a cell line of human breast carcinoma origin." Eur J Cancer 15(5): 659-670.

Khorasanizadeh, S. and Rastinejad, F. (2001). "Nuclear-receptor interactions on DNA-response elements." Trends Biochem Sci 26(6): 384-390.

Kibbe, W.A. (2007). "OligoCalc: an online oligonucleotide properties calculator." Nucleic Acids Res 35(Web Server issue): W43-46.

Kim, M., Turnquist, H., Jackson, J., Sgagias, M., Yan, Y., Gong, M., Dean, M., Sharp, J.G. and Cowan, K. (2002). "The multidrug resistance transporter ABCG2 (breast cancer resistance protein 1) effluxes Hoechst 33342 and is overexpressed in hematopoietic stem cells." Clin Cancer Res 8(1): 22-28.

Kim, M.Y., Hsiao, S.J. and Kraus, W.L. (2001). "A role for coactivators and histone acetylation in estrogen receptor alpha-mediated transcription initiation." EMBO J 20(21): 6084-6094.

Kim, S.J., Kim, T.W., Lee, S.Y., Park, S.J., Kim, H.S., Chung, K.W., Lee, E.S. and Kang, H.S. (2004). "CpG methylation of the ERalpha and ERbeta genes in breast cancer." Int J Mol Med 14(2): 289-293.

Kim, Y., Jae, E. and Yoon, M. (2015). "Influence of Androgen Receptor Expression on the Survival Outcomes in Breast Cancer: A Meta-Analysis." J Breast Cancer 18(2): 134-142.

Kim, Y.S., Won, Y.S., Park, K.S., Song, B.J., Kim, J.S., Oh, S.J., Jeon, H.M., Jung, S.S. and Park, W.C. (2008). "Prognostic significance of HER2 gene amplification according to stage of breast cancer." J Korean Med Sci 23(3): 414-420.

Koga, K., Nakamura, M., Nakashima, H., Akiyoshi, T., Kubo, M., Sato, N., Kuroki, S., Nomura, M., Tanaka, M. and Katano, M. (2008). "Novel link between estrogen receptor alpha and hedgehog pathway in breast cancer." Anticancer Res 28(2A): 731-740.

References

237

Koinuma, D., Tsutsumi, S., Kamimura, N., Imamura, T., Aburatani, H. and Miyazono, K. (2009). "Promoter-wide analysis of Smad4 binding sites in human epithelial cells." Cancer Sci 100(11): 2133-2142.

Komiya, Y. and Habas, R. (2008). "Wnt signal transduction pathways." Organogenesis 4(2): 68-75.

Kong, W., Yang, H., He, L., Zhao, J.J., Coppola, D., Dalton, W.S. and Cheng, J.Q. (2008). "MicroRNA-155 is regulated by the transforming growth factor beta/Smad pathway and contributes to epithelial cell plasticity by targeting RhoA." Mol Cell Biol 28(22): 6773-6784.

Korolchuk, V.I., Saiki, S., Lichtenberg, M., Siddiqi, F.H., Roberts, E.A., Imarisio, S., Jahreiss, L., Sarkar, S., Futter, M., Menzies, F.M., O'Kane, C.J., Deretic, V. and Rubinsztein, D.C. (2011). "Lysosomal positioning coordinates cellular nutrient responses." Nat Cell Biol 13(4): 453-460.

Korpal, M., Lee, E.S., Hu, G. and Kang, Y. (2008). "The miR-200 family inhibits epithelial-mesenchymal transition and cancer cell migration by direct targeting of E-cadherin transcriptional repressors ZEB1 and ZEB2." J Biol Chem 283(22): 14910-14914.

Kousidou, O.C., Roussidis, A.E., Theocharis, A.D. and Karamanos, N.K. (2004). "Expression of MMPs and TIMPs genes in human breast cancer epithelial cells depends on cell culture conditions and is associated with their invasive potential." Anticancer Res 24(6): 4025-4030.

Krishnamachary, N. and Center, M.S. (1993). "The MRP gene associated with a non-P-glycoprotein multidrug resistance encodes a 190-kDa membrane bound glycoprotein." Cancer Res 53(16): 3658-3661.

Krishnamurthy, P., Ross, D.D., Nakanishi, T., Bailey-Dell, K., Zhou, S., Mercer, K.E., Sarkadi, B., Sorrentino, B.P. and Schuetz, J.D. (2004). "The stem cell marker Bcrp/ABCG2 enhances hypoxic cell survival through interactions with heme." J Biol Chem 279(23): 24218-24225.

Krop, I.E., Kim, S.B., Gonzalez-Martin, A., LoRusso, P.M., Ferrero, J.M., Smitt, M., Yu, R., Leung, A.C. and Wildiers, H. (2014). "Trastuzumab emtansine versus treatment of physician's choice for pretreated HER2-positive advanced breast cancer (TH3RESA): a randomised, open-label, phase 3 trial." Lancet Oncol 15(7): 689-699.

Kruijtzer, C.M., Beijnen, J.H., Rosing, H., ten Bokkel Huinink, W.W., Schot, M., Jewell, R.C., Paul, E.M. and Schellens, J.H. (2002). "Increased oral bioavailability of topotecan in combination with the breast cancer resistance protein and P-glycoprotein inhibitor GF120918." J Clin Oncol 20(13): 2943-2950.

Kubo, M., Nakamura, M., Tasaki, A., Yamanaka, N., Nakashima, H., Nomura, M., Kuroki, S. and Katano, M. (2004). "Hedgehog signaling pathway is a new therapeutic target for patients with breast cancer." Cancer Res 64(17): 6071-6074.

Kuenen-Boumeester, V., Van der Kwast, T.H., van Putten, W.L., Claassen, C., van Ooijen, B. and Henzen-Logmans, S.C. (1992). "Immunohistochemical determination of androgen receptors in relation to oestrogen and progesterone receptors in female breast cancer." Int J Cancer 52(4): 581-584.

Kuhl, M., Sheldahl, L.C., Malbon, C.C. and Moon, R.T. (2000). "Ca(2+)/calmodulin-dependent protein kinase II is stimulated by Wnt and Frizzled homologs and promotes ventral cell fates in Xenopus." J Biol Chem 275(17): 12701-12711.

References

238

Kuppens, I.E., Witteveen, E.O., Jewell, R.C., Radema, S.A., Paul, E.M., Mangum, S.G., Beijnen, J.H., Voest, E.E. and Schellens, J.H. (2007). "A phase I, randomized, open-label, parallel-cohort, dose-finding study of elacridar (GF120918) and oral topotecan in cancer patients." Clin Cancer Res 13(11): 3276-3285.

Kurebayashi, J., Kanomata, N., Kozuka, Y., Moriya, T., Kikukawa, N., Kawasaki, Y., Harada, S., Tamura, S., Nakayama, S., Ishihara, H., Noguchi, S. and Sonoo, H. (2011). "The cell cycle profile test is a prognostic indicator for breast cancer patients treated with postoperative 5-fluorouracil-based chemotherapy." Jpn J Clin Oncol 41(6): 739-746.

Kuwada, S.K. and Li, X. (2000). "Integrin alpha5/beta1 mediates fibronectin-dependent epithelial cell proliferation through epidermal growth factor receptor activation." Mol Biol Cell 11(7): 2485-2496.

Labelle, M., Begum, S. and Hynes, R.O. (2011). "Direct signaling between platelets and cancer cells induces an epithelial-mesenchymal-like transition and promotes metastasis." Cancer Cell 20(5): 576-590.

Labrie, F. (2006). "Dehydroepiandrosterone, androgens and the mammary gland." Gynecol Endocrinol 22(3): 118-130.

Labrie, F., Luu-The, V., Labrie, C., Belanger, A., Simard, J., Lin, S.X. and Pelletier, G. (2003). "Endocrine and intracrine sources of androgens in women: inhibition of breast cancer and other roles of androgens and their precursor dehydroepiandrosterone." Endocr Rev 24(2): 152-182.

Lai, C.F., Feng, X., Nishimura, R., Teitelbaum, S.L., Avioli, L.V., Ross, F.P. and Cheng, S.L. (2000). "Transforming growth factor-beta up-regulates the beta 5 integrin subunit expression via Sp1 and Smad signaling." J Biol Chem 275(46): 36400-36406.

Lamb, C., Simian, M., Molinolo, A., Pazos, P. and Lanari, C. (1999). "Regulation of cell growth of a progestin-dependent murine mammary carcinoma in vitro: progesterone receptor involvement in serum or growth factor-induced cell proliferation." J Steroid Biochem Mol Biol 70(4-6): 133-142.

Lamouille, S., Xu, J. and Derynck, R. (2014). "Molecular mechanisms of epithelial-mesenchymal transition." Nat Rev Mol Cell Biol 15(3): 178-196.

Laner-Plamberger, S., Kaser, A., Paulischta, M., Hauser-Kronberger, C., Eichberger, T. and Frischauf, A.M. (2009). "Cooperation between GLI and JUN enhances transcription of JUN and selected GLI target genes." Oncogene 28(13): 1639-1651.

Lanzino, M., Sisci, D., Morelli, C., Garofalo, C., Catalano, S., Casaburi, I., Capparelli, C., Giordano, C., Giordano, F., Maggiolini, M. and Ando, S. (2010). "Inhibition of cyclin D1 expression by androgen receptor in breast cancer cells--identification of a novel androgen response element." Nucleic Acids Res 38(16): 5351-5365.

Lapidot, T., Sirard, C., Vormoor, J., Murdoch, B., Hoang, T., Caceres-Cortes, J., Minden, M., Paterson, B., Caligiuri, M.A. and Dick, J.E. (1994). "A cell initiating human acute myeloid leukaemia after transplantation into SCID mice." Nature 367(6464): 645-648.

Lapointe, J., Fournier, A., Richard, V. and Labrie, C. (1999). "Androgens down-regulate bcl-2 protooncogene expression in ZR-75-1 human breast cancer cells." Endocrinology 140(1): 416-421.

Le, X.F., Claret, F.X., Lammayot, A., Tian, L., Deshpande, D., LaPushin, R., Tari, A.M. and Bast, R.C., Jr. (2003). "The role of cyclin-dependent kinase inhibitor p27Kip1 in anti-

References

239

HER2 antibody-induced G1 cell cycle arrest and tumor growth inhibition." J Biol Chem 278(26): 23441-23450.

Lee, G.Y., Kenny, P.A., Lee, E.H. and Bissell, M.J. (2007). "Three-dimensional culture models of normal and malignant breast epithelial cells." Nat Methods 4(4): 359-365.

Lee, S.H., Kim, H., Hwang, J.H., Lee, H.S., Cho, J.Y., Yoon, Y.S. and Han, H.S. (2012). "Breast cancer resistance protein expression is associated with early recurrence and decreased survival in resectable pancreatic cancer patients." Pathol Int 62(3): 167-175.

Lehmann, B.D., Bauer, J.A., Chen, X., Sanders, M.E., Chakravarthy, A.B., Shyr, Y. and Pietenpol, J.A. (2011). "Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies." J Clin Invest 121(7): 2750-2767.

Leong, K.G., Niessen, K., Kulic, I., Raouf, A., Eaves, C., Pollet, I. and Karsan, A. (2007). "Jagged1-mediated Notch activation induces epithelial-to-mesenchymal transition through Slug-induced repression of E-cadherin." J Exp Med 204(12): 2935-2948.

Leu, Y.W., Yan, P.S., Fan, M., Jin, V.X., Liu, J.C., Curran, E.M., Welshons, W.V., Wei, S.H., Davuluri, R.V., Plass, C., Nephew, K.P. and Huang, T.H. (2004). "Loss of estrogen receptor signaling triggers epigenetic silencing of downstream targets in breast cancer." Cancer Res 64(22): 8184-8192.

Lewis, J.E., Wahl, J.K., 3rd, Sass, K.M., Jensen, P.J., Johnson, K.R. and Wheelock, M.J. (1997). "Cross-talk between adherens junctions and desmosomes depends on plakoglobin." J Cell Biol 136(4): 919-934.

Li, C.W., Xia, W., Huo, L., Lim, S.O., Wu, Y., Hsu, J.L., Chao, C.H., Yamaguchi, H., Yang, N.K., Ding, Q., Wang, Y., Lai, Y.J., LaBaff, A.M., Wu, T.J., Lin, B.R., Yang, M.H., Hortobagyi, G.N. and Hung, M.C. (2012). "Epithelial-mesenchymal transition induced by TNF-alpha requires NF-kappaB-mediated transcriptional upregulation of Twist1." Cancer Res 72(5): 1290-1300.

Li, Y., Wang, L., Zhang, M., Melamed, J., Liu, X., Reiter, R., Wei, J., Peng, Y., Zou, X., Pellicer, A., Garabedian, M.J., Ferrari, A. and Lee, P. (2009). "LEF1 in androgen-independent prostate cancer: regulation of androgen receptor expression, prostate cancer growth, and invasion." Cancer Res 69(8): 3332-3338.

Liang, S.C., Yang, C.Y., Tseng, J.Y., Wang, H.L., Tung, C.Y., Liu, H.W., Chen, C.Y., Yeh, Y.C., Chou, T.Y., Yang, M.H., Whang-Peng, J. and Lin, C.H. (2015). "ABCG2 localizes to the nucleus and modulates CDH1 expression in lung cancer cells." Neoplasia 17(3): 265-278.

Liao, X., Siu, M.K., Au, C.W., Wong, E.S., Chan, H.Y., Ip, P.P., Ngan, H.Y. and Cheung, A.N. (2009). "Aberrant activation of hedgehog signaling pathway in ovarian cancers: effect on prognosis, cell invasion and differentiation." Carcinogenesis 30(1): 131-140.

Liao, X., Thrasher, J.B., Pelling, J., Holzbeierlein, J., Sang, Q.X. and Li, B. (2003). "Androgen stimulates matrix metalloproteinase-2 expression in human prostate cancer." Endocrinology 144(5): 1656-1663.

Liberato, M.H., Sonohara, S. and Brentani, M.M. (1993). "Effects of androgens on proliferation and progesterone receptor levels in T47D human breast cancer cells." Tumour Biol 14(1): 38-45.

References

240

Lieu, C., Heymach, J., Overman, M., Tran, H. and Kopetz, S. (2011). "Beyond VEGF: inhibition of the fibroblast growth factor pathway and antiangiogenesis." Clin Cancer Res 17(19): 6130-6139.

Lindahl, G., Saarinen, N., Abrahamsson, A. and Dabrosin, C. (2011). "Tamoxifen, flaxseed, and the lignan enterolactone increase stroma- and cancer cell-derived IL-1Ra and decrease tumor angiogenesis in estrogen-dependent breast cancer." Cancer Res 71(1): 51-60.

Lindberg, M.K., Moverare, S., Skrtic, S., Gao, H., Dahlman-Wright, K., Gustafsson, J.A. and Ohlsson, C. (2003). "Estrogen receptor (ER)-beta reduces ERalpha-regulated gene transcription, supporting a "ying yang" relationship between ERalpha and ERbeta in mice." Mol Endocrinol 17(2): 203-208.

Litman, T., Brangi, M., Hudson, E., Fetsch, P., Abati, A., Ross, D.D., Miyake, K., Resau, J.H. and Bates, S.E. (2000). "The multidrug-resistant phenotype associated with overexpression of the new ABC half-transporter, MXR (ABCG2)." J Cell Sci 113 ( Pt 11): 2011-2021.

Liu, E., Samad, F. and Mueller, B.M. (2013). "Local adipocytes enable estrogen-dependent breast cancer growth: Role of leptin and aromatase." Adipocyte 2(3): 165-169.

Liu, J.B., Dai, C.M., Su, X.Y., Cao, L., Qin, R. and Kong, Q.B. (2014). "Gene microarray assessment of multiple genes and signal pathways involved in androgen-dependent prostate cancer becoming androgen independent." Asian Pac J Cancer Prev 15(22): 9791-9795.

Liu, S., Chia, S.K., Mehl, E., Leung, S., Rajput, A., Cheang, M.C. and Nielsen, T.O. (2010). "Progesterone receptor is a significant factor associated with clinical outcomes and effect of adjuvant tamoxifen therapy in breast cancer patients." Breast Cancer Res Treat 119(1): 53-61.

Liu, Y., Peng, H. and Zhang, J.T. (2005). "Expression profiling of ABC transporters in a drug-resistant breast cancer cell line using AmpArray." Mol Pharmacol 68(2): 430-438.

Liu, Y.N., Liu, Y., Lee, H.J., Hsu, Y.H. and Chen, J.H. (2008). "Activated androgen receptor downregulates E-cadherin gene expression and promotes tumor metastasis." Mol Cell Biol 28(23): 7096-7108.

Lo, H.W., Hsu, S.C., Xia, W., Cao, X., Shih, J.Y., Wei, Y., Abbruzzese, J.L., Hortobagyi, G.N. and Hung, M.C. (2007). "Epidermal growth factor receptor cooperates with signal transducer and activator of transcription 3 to induce epithelial-mesenchymal transition in cancer cells via up-regulation of TWIST gene expression." Cancer Res 67(19): 9066-9076.

LoRusso, P.M., Rudin, C.M., Reddy, J.C., Tibes, R., Weiss, G.J., Borad, M.J., Hann, C.L., Brahmer, J.R., Chang, I., Darbonne, W.C., Graham, R.A., Zerivitz, K.L., Low, J.A. and Von Hoff, D.D. (2011). "Phase I trial of hedgehog pathway inhibitor vismodegib (GDC-0449) in patients with refractory, locally advanced or metastatic solid tumors." Clin Cancer Res 17(8): 2502-2511.

Lou, H. and Dean, M. (2007). "Targeted therapy for cancer stem cells: the patched pathway and ABC transporters." Oncogene 26(9): 1357-1360.

Lu, S., Liu, M., Epner, D.E., Tsai, S.Y. and Tsai, M.J. (1999). "Androgen regulation of the cyclin-dependent kinase inhibitor p21 gene through an androgen response element in the proximal promoter." Mol Endocrinol 13(3): 376-384.

References

241

Luo, X., Shi, Y.X., Li, Z.M. and Jiang, W.Q. (2010). "Expression and clinical significance of androgen receptor in triple negative breast cancer." Chin J Cancer 29(6): 585-590.

Lv, Z.D., Kong, B., Li, J.G., Qu, H.L., Wang, X.G., Cao, W.H., Liu, X.Y., Wang, Y., Yang, Z.C., Xu, H.M. and Wang, H.B. (2013). "Transforming growth factor-beta 1 enhances the invasiveness of breast cancer cells by inducing a Smad2-dependent epithelial-to-mesenchymal transition." Oncol Rep 29(1): 219-225.

Lykkesfeldt, A.E., Larsen, J.K., Christensen, I.J. and Briand, P. (1984). "Effects of the antioestrogen tamoxifen on the cell cycle kinetics of the human breast cancer cell line, MCF-7." Br J Cancer 49(6): 717-722.

Ma, L., Teruya-Feldstein, J. and Weinberg, R.A. (2007). "Tumour invasion and metastasis initiated by microRNA-10b in breast cancer." Nature 449(7163): 682-688.

Ma, M.T., He, M., Wang, Y., Jiao, X.Y., Zhao, L., Bai, X.F., Yu, Z.J., Wu, H.Z., Sun, M.L., Song, Z.G. and Wei, M.J. (2013). "MiR-487a resensitizes mitoxantrone (MX)-resistant breast cancer cells (MCF-7/MX) to MX by targeting breast cancer resistance protein (BCRP/ABCG2)." Cancer Lett 339(1): 107-115.

Macedo, L.F., Guo, Z., Tilghman, S.L., Sabnis, G.J., Qiu, Y. and Brodie, A. (2006). "Role of androgens on MCF-7 breast cancer cell growth and on the inhibitory effect of letrozole." Cancer Res 66(15): 7775-7782.

Macias, H. and Hinck, L. (2012). "Mammary gland development." Wiley Interdiscip Rev Dev Biol 1(4): 533-557.

Mackey, J.R., Martin, M., Pienkowski, T., Rolski, J., Guastalla, J.P., Sami, A., Glaspy, J., Juhos, E., Wardley, A., Fornander, T., Hainsworth, J., Coleman, R., Modiano, M.R., Vinholes, J., Pinter, T., Rodriguez-Lescure, A., Colwell, B., Whitlock, P., Provencher, L., Laing, K., Walde, D., Price, C., Hugh, J.C., Childs, B.H., Bassi, K., Lindsay, M.A., Wilson, V., Rupin, M., Houe, V. and Vogel, C. (2013). "Adjuvant docetaxel, doxorubicin, and cyclophosphamide in node-positive breast cancer: 10-year follow-up of the phase 3 randomised BCIRG 001 trial." Lancet Oncol 14(1): 72-80.

MacMillan, C.D., Leong, H.S., Dales, D.W., Robertson, A.E., Lewis, J.D., Chambers, A.F. and Tuck, A.B. (2014). "Stage of breast cancer progression influences cellular response to activation of the WNT/planar cell polarity pathway." Sci Rep 4: 6315.

Magbanua, M.J., Wolf, D.M., Yau, C., Davis, S.E., Crothers, J., Au, A., Haqq, C.M., Livasy, C., Rugo, H.S., Esserman, L., Park, J.W. and van 't Veer, L.J. (2015). "Serial expression analysis of breast tumors during neoadjuvant chemotherapy reveals changes in cell cycle and immune pathways associated with recurrence and response." Breast Cancer Res 17: 73.

Malhotra, G.K., Zhao, X., Band, H. and Band, V. (2010). "Histological, molecular and functional subtypes of breast cancers." Cancer Biol Ther 10(10): 955-960.

Maliepaard, M., Scheffer, G.L., Faneyte, I.F., van Gastelen, M.A., Pijnenborg, A.C., Schinkel, A.H., van De Vijver, M.J., Scheper, R.J. and Schellens, J.H. (2001). "Subcellular localization and distribution of the breast cancer resistance protein transporter in normal human tissues." Cancer Res 61(8): 3458-3464.

Mao, J., Wang, J., Liu, B., Pan, W., Farr, G.H., 3rd, Flynn, C., Yuan, H., Takada, S., Kimelman, D., Li, L. and Wu, D. (2001). "Low-density lipoprotein receptor-related protein-5 binds to Axin and regulates the canonical Wnt signaling pathway." Mol Cell 7(4): 801-809.

References

242

Mao, Q. and Unadkat, J.D. (2015). "Role of the breast cancer resistance protein (BCRP/ABCG2) in drug transport--an update." AAPS J 17(1): 65-82.

Marez, D., Legrand, M., Sabbagh, N., Lo Guidice, J.M., Spire, C., Lafitte, J.J., Meyer, U.A. and Broly, F. (1997). "Polymorphism of the cytochrome P450 CYP2D6 gene in a European population: characterization of 48 mutations and 53 alleles, their frequencies and evolution." Pharmacogenetics 7(3): 193-202.

Marti, A., Ritter, P.M., Jager, R., Lazar, H., Baltzer, A., Schenkel, J., Declercq, W., Vandenabeele, P. and Jaggi, R. (2001). "Mouse mammary gland involution is associated with cytochrome c release and caspase activation." Mech Dev 104(1-2): 89-98.

Martín, M., Loibl, S., von Minckwitz, G., Morales, S., Martinez, N., Guerrero, A., Anton, A., Aktas, B., Schoenegg, W., Muñoz, M., Garcia-Saenz, J.A., Gil, M., Ramos, M., Margeli, M., Carrasco, E., Liedtke, C., Wachsmann, G., Mehta, K. and De la Haba-Rodriguez, J.R. (2013). "Phase III trial evaluating the addition of bevacizumab to endocrine therapy as first-line treatment for advanced breast cancer: the letrozole/fulvestrant and avastin (LEA) study". Paper presented at 17th Biennial Meeting of the European Cancer Congress, Amsterdam, the Netherlands.

Martin, T.A., Mansel, R.E. and Jiang, W.G. (2010). "Loss of occludin leads to the progression of human breast cancer." Int J Mol Med 26(5): 723-734.

Martin, T.A., Watkins, G., Mansel, R.E. and Jiang, W.G. (2004). "Loss of tight junction plaque molecules in breast cancer tissues is associated with a poor prognosis in patients with breast cancer." Eur J Cancer 40(18): 2717-2725.

Maruhashi, T., Kii, I., Saito, M. and Kudo, A. (2010). "Interaction between periostin and BMP-1 promotes proteolytic activation of lysyl oxidase." J Biol Chem 285(17): 13294-13303.

Maschler, S., Wirl, G., Spring, H., Bredow, D.V., Sordat, I., Beug, H. and Reichmann, E. (2005). "Tumor cell invasiveness correlates with changes in integrin expression and localization." Oncogene 24(12): 2032-2041.

Massarweh, S., Osborne, C.K., Creighton, C.J., Qin, L., Tsimelzon, A., Huang, S., Weiss, H., Rimawi, M. and Schiff, R. (2008). "Tamoxifen resistance in breast tumors is driven by growth factor receptor signaling with repression of classic estrogen receptor genomic function." Cancer Res 68(3): 826-833.

Masuelli, L., Benvenuto, M., Fantini, M., Marzocchella, L., Sacchetti, P., Di Stefano, E., Tresoldi, I., Izzi, V., Bernardini, R., Palumbo, C., Mattei, M., Lista, F., Galvano, F., Modesti, A. and Bei, R. (2013). "Curcumin induces apoptosis in breast cancer cell lines and delays the growth of mammary tumors in neu transgenic mice." J Biol Regul Homeost Agents 27(1): 105-119.

Mayer, E.L. (2015). "Targeting breast cancer with CDK inhibitors." Curr Oncol Rep 17(5): 443.

McAuliffe, S.M., Morgan, S.L., Wyant, G.A., Tran, L.T., Muto, K.W., Chen, Y.S., Chin, K.T., Partridge, J.C., Poole, B.B., Cheng, K.H., Daggett, J., Jr., Cullen, K., Kantoff, E., Hasselbatt, K., Berkowitz, J., Muto, M.G., Berkowitz, R.S., Aster, J.C., Matulonis, U.A. and Dinulescu, D.M. (2012). "Targeting Notch, a key pathway for ovarian cancer stem cells, sensitizes tumors to platinum therapy." Proc Natl Acad Sci U S A 109(43): E2939-2948.

McDevitt, C.A., Collins, R.F., Conway, M., Modok, S., Storm, J., Kerr, I.D., Ford, R.C. and Callaghan, R. (2006). "Purification and 3D structural analysis of oligomeric human multidrug transporter ABCG2." Structure 14(11): 1623-1632.

References

243

McSherry, E.A., Brennan, K., Hudson, L., Hill, A.D. and Hopkins, A.M. (2011). "Breast cancer cell migration is regulated through junctional adhesion molecule-A-mediated activation of Rap1 GTPase." Breast Cancer Res 13(2): R31.

Meagher, E.A., Barry, O.P., Burke, A., Lucey, M.R., Lawson, J.A., Rokach, J. and FitzGerald, G.A. (1999). "Alcohol-induced generation of lipid peroxidation products in humans." J Clin Invest 104(6): 805-813.

Mealey, K.L., Barhoumi, R., Burghardt, R.C., Safe, S. and Kochevar, D.T. (2002). "Doxycycline induces expression of P glycoprotein in MCF-7 breast carcinoma cells." Antimicrob Agents Chemother 46(3): 755-761.

Merenbakh-Lamin, K., Ben-Baruch, N., Yeheskel, A., Dvir, A., Soussan-Gutman, L., Jeselsohn, R., Yelensky, R., Brown, M., Miller, V.A., Sarid, D., Rizel, S., Klein, B., Rubinek, T. and Wolf, I. (2013). "D538G mutation in estrogen receptor-alpha: A novel mechanism for acquired endocrine resistance in breast cancer." Cancer Res 73(23): 6856-6864.

Mi, Y.J., Liang, Y.J., Huang, H.B., Zhao, H.Y., Wu, C.P., Wang, F., Tao, L.Y., Zhang, C.Z., Dai, C.L., Tiwari, A.K., Ma, X.X., To, K.K., Ambudkar, S.V., Chen, Z.S. and Fu, L.W. (2010). "Apatinib (YN968D1) reverses multidrug resistance by inhibiting the efflux function of multiple ATP-binding cassette transporters." Cancer Res 70(20): 7981-7991.

Miles, D.W., Chan, A., Dirix, L.Y., Cortes, J., Pivot, X., Tomczak, P., Delozier, T., Sohn, J.H., Provencher, L., Puglisi, F., Harbeck, N., Steger, G.G., Schneeweiss, A., Wardley, A.M., Chlistalla, A. and Romieu, G. (2010). "Phase III study of bevacizumab plus docetaxel compared with placebo plus docetaxel for the first-line treatment of human epidermal growth factor receptor 2-negative metastatic breast cancer." J Clin Oncol 28(20): 3239-3247.

Miller, K., Wang, M., Gralow, J., Dickler, M., Cobleigh, M., Perez, E.A., Shenkier, T., Cella, D. and Davidson, N.E. (2007). "Paclitaxel plus bevacizumab versus paclitaxel alone for metastatic breast cancer." N Engl J Med 357(26): 2666-2676.

Miranda-Lorenzo, I., Dorado, J., Lonardo, E., Alcala, S., Serrano, A.G., Clausell-Tormos, J., Cioffi, M., Megias, D., Zagorac, S., Balic, A., Hidalgo, M., Erkan, M., Kleeff, J., Scarpa, A., Sainz, B., Jr. and Heeschen, C. (2014). "Intracellular autofluorescence: a biomarker for epithelial cancer stem cells." Nat Methods 11(11): 1161-1169.

Mistry, P., Stewart, A.J., Dangerfield, W., Okiji, S., Liddle, C., Bootle, D., Plumb, J.A., Templeton, D. and Charlton, P. (2001). "In vitro and in vivo reversal of P-glycoprotein-mediated multidrug resistance by a novel potent modulator, XR9576." Cancer Res 61(2): 749-758.

Mitra, D., Brumlik, M.J., Okamgba, S.U., Zhu, Y., Duplessis, T.T., Parvani, J.G., Lesko, S.M., Brogi, E. and Jones, F.E. (2009). "An oncogenic isoform of HER2 associated with locally disseminated breast cancer and trastuzumab resistance." Mol Cancer Ther 8(8): 2152-2162.

Mitra, S.K., Hanson, D.A. and Schlaepfer, D.D. (2005). "Focal adhesion kinase: in command and control of cell motility." Nat Rev Mol Cell Biol 6(1): 56-68.

Miyake, K., Mickley, L., Litman, T., Zhan, Z., Robey, R., Cristensen, B., Brangi, M., Greenberger, L., Dean, M., Fojo, T. and Bates, S.E. (1999). "Molecular cloning of cDNAs which are highly overexpressed in mitoxantrone-resistant cells: demonstration of homology to ABC transport genes." Cancer Res 59(1): 8-13.

References

244

Mizuarai, S., Aozasa, N. and Kotani, H. (2004). "Single nucleotide polymorphisms result in impaired membrane localization and reduced atpase activity in multidrug transporter ABCG2." Int J Cancer 109(2): 238-246.

Mizuno, E., Iura, T., Mukai, A., Yoshimori, T., Kitamura, N. and Komada, M. (2005). "Regulation of epidermal growth factor receptor down-regulation by UBPY-mediated deubiquitination at endosomes." Mol Biol Cell 16(11): 5163-5174.

Mo, W. and Zhang, J.T. (2012). "Human ABCG2: structure, function, and its role in multidrug resistance." Int J Biochem Mol Biol 3(1): 1-27.

Moggs, J.G., Murphy, T.C., Lim, F.L., Moore, D.J., Stuckey, R., Antrobus, K., Kimber, I. and Orphanides, G. (2005). "Anti-proliferative effect of estrogen in breast cancer cells that re-express ERalpha is mediated by aberrant regulation of cell cycle genes." J Mol Endocrinol 34(2): 535-551.

Mohammed, H., Russell, I.A., Stark, R., Rueda, O.M., Hickey, T.E., Tarulli, G.A., Serandour, A.A., Birrell, S.N., Bruna, A., Saadi, A., Menon, S., Hadfield, J., Pugh, M., Raj, G.V., Brown, G.D., D'Santos, C., Robinson, J.L., Silva, G., Launchbury, R., Perou, C.M., Stingl, J., Caldas, C., Tilley, W.D. and Carroll, J.S. (2015). "Progesterone receptor modulates ERalpha action in breast cancer." Nature 523(7560): 313-317.

Moinfar, F., Okcu, M., Tsybrovskyy, O., Regitnig, P., Lax, S.F., Weybora, W., Ratschek, M., Tavassoli, F.A. and Denk, H. (2003). "Androgen receptors frequently are expressed in breast carcinomas: potential relevance to new therapeutic strategies." Cancer 98(4): 703-711.

Moore, K.M., Thomas, G.J., Duffy, S.W., Warwick, J., Gabe, R., Chou, P., Ellis, I.O., Green, A.R., Haider, S., Brouilette, K., Saha, A., Vallath, S., Bowen, R., Chelala, C., Eccles, D., Tapper, W.J., Thompson, A.M., Quinlan, P., Jordan, L., Gillett, C., Brentnall, A., Violette, S., Weinreb, P.H., Kendrew, J., Barry, S.T., Hart, I.R., Jones, J.L. and Marshall, J.F. (2014). "Therapeutic targeting of integrin alphavbeta6 in breast cancer." J Natl Cancer Inst 106(8).

Moraes, R.C., Zhang, X., Harrington, N., Fung, J.Y., Wu, M.F., Hilsenbeck, S.G., Allred, D.C. and Lewis, M.T. (2007). "Constitutive activation of smoothened (SMO) in mammary glands of transgenic mice leads to increased proliferation, altered differentiation and ductal dysplasia." Development 134(6): 1231-1242.

Morozevich, G., Kozlova, N., Cheglakov, I., Ushakova, N. and Berman, A. (2009). "Integrin alpha5beta1 controls invasion of human breast carcinoma cells by direct and indirect modulation of MMP-2 collagenase activity." Cell Cycle 8(14): 2219-2225.

Morschhauser, F., Zinzani, P.L., Burgess, M., Sloots, L., Bouafia, F. and Dumontet, C. (2007). "Phase I/II trial of a P-glycoprotein inhibitor, Zosuquidar.3HCl trihydrochloride (LY335979), given orally in combination with the CHOP regimen in patients with non-Hodgkin's lymphoma." Leuk Lymphoma 48(4): 708-715.

Mosaffa, F., Lage, H., Afshari, J.T. and Behravan, J. (2009). "Interleukin-1 beta and tumor necrosis factor-alpha increase ABCG2 expression in MCF-7 breast carcinoma cell line and its mitoxantrone-resistant derivative, MCF-7/MX." Inflamm Res 58(10): 669-676.

Mote, P.A., Graham, J.D. and Clarke, C.L. (2007). "Progesterone receptor isoforms in normal and malignant breast." Ernst Schering Found Symp Proc(1): 77-107.

Mount, D.W. (2007). "Using the Basic Local Alignment Search Tool (BLAST)." CSH Protoc 2007: pdb top17.

References

245

Mouridsen, H., Giobbie-Hurder, A., Goldhirsch, A., Thurlimann, B., Paridaens, R., Smith, I., Mauriac, L., Forbes, J., Price, K.N., Regan, M.M., Gelber, R.D. and Coates, A.S. (2009). "Letrozole therapy alone or in sequence with tamoxifen in women with breast cancer." N Engl J Med 361(8): 766-776.

Mukherjee, S., Frolova, N., Sadlonova, A., Novak, Z., Steg, A., Page, G.P., Welch, D.R., Lobo-Ruppert, S.M., Ruppert, J.M., Johnson, M.R. and Frost, A.R. (2006). "Hedgehog signaling and response to cyclopamine differ in epithelial and stromal cells in benign breast and breast cancer." Cancer Biol Ther 5(6): 674-683.

Mullamitha, S.A., Ton, N.C., Parker, G.J., Jackson, A., Julyan, P.J., Roberts, C., Buonaccorsi, G.A., Watson, Y., Davies, K., Cheung, S., Hope, L., Valle, J.W., Radford, J.A., Lawrance, J., Saunders, M.P., Munteanu, M.C., Nakada, M.T., Nemeth, J.A., Davis, H.M., Jiao, Q., Prabhakar, U., Lang, Z., Corringham, R.E., Beckman, R.A. and Jayson, G.C. (2007). "Phase I evaluation of a fully human anti-alphav integrin monoclonal antibody (CNTO 95) in patients with advanced solid tumors." Clin Cancer Res 13(7): 2128-2135.

Munster, P.N., Thurn, K.T., Thomas, S., Raha, P., Lacevic, M., Miller, A., Melisko, M., Ismail-Khan, R., Rugo, H., Moasser, M. and Minton, S.E. (2011). "A phase II study of the histone deacetylase inhibitor vorinostat combined with tamoxifen for the treatment of patients with hormone therapy-resistant breast cancer." Br J Cancer 104(12): 1828-1835.

Murphy, G., Allan, J.A., Willenbrock, F., Cockett, M.I., O'Connell, J.P. and Docherty, A.J. (1992). "The role of the C-terminal domain in collagenase and stromelysin specificity." J Biol Chem 267(14): 9612-9618.

Muthuswamy, S.K., Gilman, M. and Brugge, J.S. (1999). "Controlled dimerization of ErbB receptors provides evidence for differential signaling by homo- and heterodimers." Mol Cell Biol 19(10): 6845-6857.

Nakagawa, H., Wakabayashi-Nakao, K., Tamura, A., Toyoda, Y., Koshiba, S. and Ishikawa, T. (2009). "Disruption of N-linked glycosylation enhances ubiquitin-mediated proteasomal degradation of the human ATP-binding cassette transporter ABCG2." FEBS J 276(24): 7237-7252.

Nakanishi, T., Karp, J.E., Tan, M., Doyle, L.A., Peters, T., Yang, W., Wei, D. and Ross, D.D. (2003). "Quantitative analysis of breast cancer resistance protein and cellular resistance to flavopiridol in acute leukemia patients." Clin Cancer Res 9(9): 3320-3328.

Nakanishi, T., Ross, D.D. (2012). "Breast cancer resistance protein (BCRP/ABCG2): its role in multidrug resistance and regulation of its gene expression." Chin J Cancer 31(2): 73-99.

Narayanan, R., Ahn, S., Cheney, M.D., Yepuru, M., Miller, D.D., Steiner, M.S. and Dalton, J.T. (2014). "Selective androgen receptor modulators (SARMs) negatively regulate triple-negative breast cancer growth and epithelial:mesenchymal stem cell signaling." PLoS One 9(7): e103202.

Natarajan, K., Xie, Y., Baer, M.R. and Ross, D.D. (2012). "Role of breast cancer resistance protein (BCRP/ABCG2) in cancer drug resistance." Biochem Pharmacol 83(8): 1084-1103.

Nawrocki Raby, B., Polette, M., Gilles, C., Clavel, C., Strumane, K., Matos, M., Zahm, J.M., Van Roy, F., Bonnet, N. and Birembaut, P. (2001). "Quantitative cell dispersion analysis: new test to measure tumor cell aggressiveness." Int J Cancer 93(5): 644-652.

References

246

Naylor, M.J., Lockefeer, J.A., Horseman, N.D. and Ormandy, C.J. (2003). "Prolactin regulates mammary epithelial cell proliferation via autocrine/paracrine mechanism." Endocrine 20(1-2): 111-114.

Need, E.F., Selth, L.A., Harris, T.J., Birrell, S.N., Tilley, W.D. and Buchanan, G. (2012). "Research resource: interplay between the genomic and transcriptional networks of androgen receptor and estrogen receptor alpha in luminal breast cancer cells." Mol Endocrinol 26(11): 1941-1952.

Ngeow, J., Stanuch, K., Mester, J.L., Barnholtz-Sloan, J.S. and Eng, C. (2014). "Second malignant neoplasms in patients with Cowden syndrome with underlying germline PTEN mutations." J Clin Oncol 32(17): 1818-1824.

Ni, M., Chen, Y., Lim, E., Wimberly, H., Bailey, S.T., Imai, Y., Rimm, D.L., Liu, X.S. and Brown, M. (2011). "Targeting androgen receptor in estrogen receptor-negative breast cancer." Cancer Cell 20(1): 119-131.

Ni, Z., Bikadi, Z., Rosenberg, M.F. and Mao, Q. (2010). "Structure and function of the human breast cancer resistance protein (BCRP/ABCG2)." Curr Drug Metab 11(7): 603-617.

Nichols, K.E., Malkin, D., Garber, J.E., Fraumeni, J.F., Jr. and Li, F.P. (2001). "Germ-line p53 mutations predispose to a wide spectrum of early-onset cancers." Cancer Epidemiol Biomarkers Prev 10(2): 83-87.

Nishiyama, M. and Kuga, T. (1989). "Central effects of the neurotropic mycotoxin fumitremorgin A in the rabbit (I). Effects on the spinal cord." Jpn J Pharmacol 50(2): 167-173.

Nishiyama, M. and Kuga, T. (1990). "Central effects of the neurotropic mycotoxin fumitremorgin A in the rabbit. (II). Effects on the brain stem." Jpn J Pharmacol 52(2): 201-208.

Nistico, P., Bissell, M.J. and Radisky, D.C. (2012). "Epithelial-mesenchymal transition: general principles and pathological relevance with special emphasis on the role of matrix metalloproteinases." Cold Spring Harb Perspect Biol 4(2).

Noronha, G., Cao, J., Chow, C.P., Dneprovskaia, E., Fine, R.M., Hood, J., Kang, X., Klebansky, B., Lohse, D., Mak, C.C., McPherson, A., Palanki, M.S., Pathak, V.P., Renick, J., Soll, R. and Zeng, B. (2008). "Inhibitors of ABL and the ABL-T315I mutation." Curr Top Med Chem 8(10): 905-921.

O'Day, S., Pavlick, A., Loquai, C., Lawson, D., Gutzmer, R., Richards, J., Schadendorf, D., Thompson, J.A., Gonzalez, R., Trefzer, U., Mohr, P., Ottensmeier, C., Chao, D., Zhong, B., de Boer, C.J., Uhlar, C., Marshall, D., Gore, M.E., Lang, Z., Hait, W. and Ho, P. (2011). "A randomised, phase II study of intetumumab, an anti-alphav-integrin mAb, alone and with dacarbazine in stage IV melanoma." Br J Cancer 105(3): 346-352.

O'Shaughnessy, J., Osborne, C., Pippen, J.E., Yoffe, M., Patt, D., Rocha, C., Koo, I.C., Sherman, B.M. and Bradley, C. (2011). "Iniparib plus chemotherapy in metastatic triple-negative breast cancer." N Engl J Med 364(3): 205-214.

O'Toole, S.A., Machalek, D.A., Shearer, R.F., Millar, E.K., Nair, R., Schofield, P., McLeod, D., Cooper, C.L., McNeil, C.M., McFarland, A., Nguyen, A., Ormandy, C.J., Qiu, M.R., Rabinovich, B., Martelotto, L.G., Vu, D., Hannigan, G.E., Musgrove, E.A., Christ, D., Sutherland, R.L., Watkins, D.N. and Swarbrick, A. (2011). "Hedgehog overexpression is associated with stromal interactions and predicts for poor outcome in breast cancer." Cancer Res 71(11): 4002-4014.

References

247

Ogretmen, B. and Safa, A.R. (2000). "Identification and characterization of the MDR1 promoter-enhancing factor 1 (MEF1) in the multidrug resistant HL60/VCR human acute myeloid leukemia cell line." Biochemistry 39(1): 194-204.

Ohkubo, T. and Ozawa, M. (2004). "The transcription factor Snail downregulates the tight junction components independently of E-cadherin downregulation." J Cell Sci 117(Pt 9): 1675-1685.

Olayioye, M.A., Graus-Porta, D., Beerli, R.R., Rohrer, J., Gay, B. and Hynes, N.E. (1998). "ErbB-1 and ErbB-2 acquire distinct signaling properties dependent upon their dimerization partner." Mol Cell Biol 18(9): 5042-5051.

Omoto, Y., Eguchi, H., Yamamoto-Yamaguchi, Y. and Hayashi, S. (2003). "Estrogen receptor (ER) beta1 and ERbetacx/beta2 inhibit ERalpha function differently in breast cancer cell line MCF7." Oncogene 22(32): 5011-5020.

Onitilo, A.A., Engel, J.M., Greenlee, R.T. and Mukesh, B.N. (2009). "Breast cancer subtypes based on ER/PR and Her2 expression: comparison of clinicopathologic features and survival." Clin Med Res 7(1-2): 4-13.

Ortmann, J., Prifti, S., Bohlmann, M.K., Rehberger-Schneider, S., Strowitzki, T. and Rabe, T. (2002). "Testosterone and 5 alpha-dihydrotestosterone inhibit in vitro growth of human breast cancer cell lines." Gynecol Endocrinol 16(2): 113-120.

Overmoyer, B., Sanz-Altimira, P., Partridge, A.H., Extermann, M., Liu, J., Winer, E., Lin, N., Hassett, M., Parker, L., Taylor, R., Hancock, M., Small, S. and Johnston, M. (2014). "Enobosarm for the treatment of metastatic, estrogen and androgen receptor positive, breast cancer. Final results of the primary endpoint and current progression free survival". Paper presented at San Antonio Breast Cancer Symposium, San Antonio, Texas.

Owens, M.A., Horten, B.C. and Da Silva, M.M. (2004). "HER2 amplification ratios by fluorescence in situ hybridization and correlation with immunohistochemistry in a cohort of 6556 breast cancer tissues." Clin Breast Cancer 5(1): 63-69.

Oyama, T., Iijima, K., Takei, H., Horiguchi, J., Iino, Y., Nakajima, T. and Koerner, F. (2000). "Atypical cystic lobule of the breast: an early stage of low-grade ductal carcinoma in-situ." Breast Cancer 7(4): 326-331.

Ozdamar, B., Bose, R., Barrios-Rodiles, M., Wang, H.R., Zhang, Y. and Wrana, J.L. (2005). "Regulation of the polarity protein Par6 by TGFbeta receptors controls epithelial cell plasticity." Science 307(5715): 1603-1609.

Panet-Raymond, V., Gottlieb, B., Beitel, L.K., Pinsky, L. and Trifiro, M.A. (2000). "Interactions between androgen and estrogen receptors and the effects on their transactivational properties." Mol Cell Endocrinol 167(1-2): 139-150.

Pao, W., Miller, V.A., Politi, K.A., Riely, G.J., Somwar, R., Zakowski, M.F., Kris, M.G. and Varmus, H. (2005). "Acquired resistance of lung adenocarcinomas to gefitinib or erlotinib is associated with a second mutation in the EGFR kinase domain." PLoS Med 2(3): e73.

Park, S., Koo, J., Park, H.S., Kim, J.H., Choi, S.Y., Lee, J.H., Park, B.W. and Lee, K.S. (2010). "Expression of androgen receptors in primary breast cancer." Ann Oncol 21(3): 488-492.

Park, S.Y., Kim, J.H., Lee, Y.J., Lee, S.J. and Kim, Y. (2013). "Surfactin suppresses TPA-induced breast cancer cell invasion through the inhibition of MMP-9 expression." Int J Oncol 42(1): 287-296.

References

248

Patnaik, A., Rosen, L.S., Tolaney, S.M., Tolcher, A.W., Goldman, J.W., Gandhi, L., Papadopoulos, K.P., Beeram, M., Rasco, D.W., Myrand, S.P., Kulanthaivel, P., Andrews, J.M., Frenzel, M., Cronier, D., Chan, E.M., Flaherty, K., Wen, P.Y. and Shapiro, G. (2014). "LY2835219, a novel cell cycle inhibitor selective for CDK4/6, in combination with fulvestrant for patients with hormone receptor positive (HR+) metastatic breast cancer". Paper presented at 2014 American Society of Clinical Oncology Annual Meeting.

Patrawala, L., Calhoun, T., Schneider-Broussard, R., Zhou, J., Claypool, K. and Tang, D.G. (2005). "Side population is enriched in tumorigenic, stem-like cancer cells, whereas ABCG2+ and ABCG2- cancer cells are similarly tumorigenic." Cancer Res 65(14): 6207-6219.

Pegram, M.D., Konecny, G.E., O'Callaghan, C., Beryt, M., Pietras, R. and Slamon, D.J. (2004). "Rational combinations of trastuzumab with chemotherapeutic drugs used in the treatment of breast cancer." J Natl Cancer Inst 96(10): 739-749.

Peinado, H., Quintanilla, M. and Cano, A. (2003). "Transforming growth factor beta-1 induces snail transcription factor in epithelial cell lines: mechanisms for epithelial mesenchymal transitions." J Biol Chem 278(23): 21113-21123.

Peles, E., Levy, R.B., Or, E., Ullrich, A. and Yarden, Y. (1991). "Oncogenic forms of the neu/HER2 tyrosine kinase are permanently coupled to phospholipase C gamma." EMBO J 10(8): 2077-2086.

Peng, H., Qi, J., Dong, Z. and Zhang, J.T. (2010). "Dynamic vs static ABCG2 inhibitors to sensitize drug resistant cancer cells." PLoS One 5(12): e15276.

Perou, C.M., Jeffrey, S.S., van de Rijn, M., Rees, C.A., Eisen, M.B., Ross, D.T., Pergamenschikov, A., Williams, C.F., Zhu, S.X., Lee, J.C., Lashkari, D., Shalon, D., Brown, P.O. and Botstein, D. (1999). "Distinctive gene expression patterns in human mammary epithelial cells and breast cancers." Proc Natl Acad Sci U S A 96(16): 9212-9217.

Peters, A.A., Buchanan, G., Ricciardelli, C., Bianco-Miotto, T., Centenera, M.M., Harris, J.M., Jindal, S., Segara, D., Jia, L., Moore, N.L., Henshall, S.M., Birrell, S.N., Coetzee, G.A., Sutherland, R.L., Butler, L.M. and Tilley, W.D. (2009). "Androgen receptor inhibits estrogen receptor-alpha activity and is prognostic in breast cancer." Cancer Res 69(15): 6131-6140.

Pohl, G., Rudas, M., Taucher, S., Stranzl, T., Steger, G.G., Jakesz, R., Pirker, R. and Filipits, M. (2003). "Expression of cell cycle regulatory proteins in breast carcinomas before and after preoperative chemotherapy." Breast Cancer Res Treat 78(1): 97-103.

Prall, O.W., Rogan, E.M., Musgrove, E.A., Watts, C.K. and Sutherland, R.L. (1998). "c-Myc or cyclin D1 mimics estrogen effects on cyclin E-Cdk2 activation and cell cycle reentry." Mol Cell Biol 18(8): 4499-4508.

Prat, A., Parker, J.S., Karginova, O., Fan, C., Livasy, C., Herschkowitz, J.I., He, X. and Perou, C.M. (2010). "Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer." Breast Cancer Res 12(5): R68.

Press, M.F., Pike, M.C., Chazin, V.R., Hung, G., Udove, J.A., Markowicz, M., Danyluk, J., Godolphin, W., Sliwkowski, M., Akita, R. and et al. (1993). "Her-2/neu expression in node-negative breast cancer: direct tissue quantitation by computerized image analysis and association of overexpression with increased risk of recurrent disease." Cancer Res 53(20): 4960-4970.

References

249

Provenzano, P.P., Eliceiri, K.W., Campbell, J.M., Inman, D.R., White, J.G. and Keely, P.J. (2006). "Collagen reorganization at the tumor-stromal interface facilitates local invasion." BMC Med 4(1): 38.

Puhalla, S., Bhattacharya, S. and Davidson, N.E. (2012). "Hormonal therapy in breast cancer: a model disease for the personalization of cancer care." Mol Oncol 6(2): 222-236.

Purdie, C.A., Quinlan, P., Jordan, L.B., Ashfield, A., Ogston, S., Dewar, J.A. and Thompson, A.M. (2014). "Progesterone receptor expression is an independent prognostic variable in early breast cancer: a population-based study." Br J Cancer 110(3): 565-572.

Purohit, V. (2000). "Can alcohol promote aromatization of androgens to estrogens? A review." Alcohol 22(3): 123-127.

Purushotham, A., Shamil, E., Cariati, M., Agbaje, O., Muhidin, A., Gillett, C., Mera, A., Sivanadiyan, K., Harries, M., Sullivan, R., Pinder, S.E., Garmo, H. and Holmberg, L. (2014). "Age at diagnosis and distant metastasis in breast cancer--a surprising inverse relationship." Eur J Cancer 50(10): 1697-1705.

Pusztai, L., Wagner, P., Ibrahim, N., Rivera, E., Theriault, R., Booser, D., Symmans, F.W., Wong, F., Blumenschein, G., Fleming, D.R., Rouzier, R., Boniface, G. and Hortobagyi, G.N. (2005). "Phase II study of tariquidar, a selective P-glycoprotein inhibitor, in patients with chemotherapy-resistant, advanced breast carcinoma." Cancer 104(4): 682-691.

Qiao, L., Liang, Y., Mira, R.R., Lu, Y., Gu, J. and Zheng, Q. (2014). "Mammalian target of rapamycin (mTOR) inhibitors and combined chemotherapy in breast cancer: a meta-analysis of randomized controlled trials." Int J Clin Exp Med 7(10): 3333-3343.

Qin, L., Chen, X., Wu, Y., Feng, Z., He, T., Wang, L., Liao, L. and Xu, J. (2011). "Steroid receptor coactivator-1 upregulates integrin alpha(5) expression to promote breast cancer cell adhesion and migration." Cancer Res 71(5): 1742-1751.

Qu, Z., Van Ginkel, S., Roy, A.M., Westbrook, L., Nasrin, M., Maxuitenko, Y., Frost, A.R., Carey, D., Wang, W., Li, R., Grizzle, W.E., Thottassery, J.V. and Kern, F.G. (2008). "Vascular endothelial growth factor reduces tamoxifen efficacy and promotes metastatic colonization and desmoplasia in breast tumors." Cancer Res 68(15): 6232-6240.

Quail, D.F., Maciel, T.J., Rogers, K. and Postovit, L.M. (2012). "A unique 3D in vitro cellular invasion assay." J Biomol Screen 17(8): 1088-1095.

Qualtrough, D., Rees, P., Speight, B., Williams, A.C. and Paraskeva, C. (2015). "The Hedgehog inhibitor cyclopamine reduces β-catenin-Tcf transcriptional activity, induces E-cadherin expression, and reduces invasion in colorectal cancer cells." Cancers 7(3): 1885-1899.

Rabindran, S.K., Ross, D.D., Doyle, L.A., Yang, W. and Greenberger, L.M. (2000). "Fumitremorgin C reverses multidrug resistance in cells transfected with the breast cancer resistance protein." Cancer Res 60(1): 47-50.

Radhakrishna, S. (2014). Molecular pathways of carcinogenesis. Breast Diseases: Imaging and Clinical Management, Springer.

Radisky, E.S. and Radisky, D.C. (2010). "Matrix metalloproteinase-induced epithelial-mesenchymal transition in breast cancer." J Mammary Gland Biol Neoplasia 15(2): 201-212.

Rahman, M., Miyamoto, H. and Chang, C. (2004). "Androgen receptor coregulators in prostate cancer: mechanisms and clinical implications." Clin Cancer Res 10(7): 2208-2219.

References

250

Rahman, N., Seal, S., Thompson, D., Kelly, P., Renwick, A., Elliott, A., Reid, S., Spanova, K., Barfoot, R., Chagtai, T., Jayatilake, H., McGuffog, L., Hanks, S., Evans, D.G., Eccles, D., Easton, D.F. and Stratton, M.R. (2007). "PALB2, which encodes a BRCA2-interacting protein, is a breast cancer susceptibility gene." Nat Genet 39(2): 165-167.

Ramaswamy, B., Lu, Y., Teng, K.Y., Nuovo, G., Li, X., Shapiro, C.L. and Majumder, S. (2012). "Hedgehog signaling is a novel therapeutic target in tamoxifen-resistant breast cancer aberrantly activated by PI3K/AKT pathway." Cancer Res 72(19): 5048-5059.

Reis-Filho, J.S. and Tutt, A.N. (2008). "Triple negative tumours: a critical review." Histopathology 52(1): 108-118.

Renoir, J.M., Marsaud, V. and Lazennec, G. (2013). "Estrogen receptor signaling as a target for novel breast cancer therapeutics." Biochem Pharmacol 85(4): 449-465.

Rexer, B.N., Ghosh, R., Narasanna, A., Estrada, M.V., Chakrabarty, A., Song, Y., Engelman, J.A. and Arteaga, C.L. (2013). "Human breast cancer cells harboring a gatekeeper T798M mutation in HER2 overexpress EGFR ligands and are sensitive to dual inhibition of EGFR and HER2." Clin Cancer Res 19(19): 5390-5401.

Robert, N.J., Dieras, V., Glaspy, J., Brufsky, A.M., Bondarenko, I., Lipatov, O.N., Perez, E.A., Yardley, D.A., Chan, S.Y., Zhou, X., Phan, S.C. and O'Shaughnessy, J. (2011). "RIBBON-1: randomized, double-blind, placebo-controlled, phase III trial of chemotherapy with or without bevacizumab for first-line treatment of human epidermal growth factor receptor 2-negative, locally recurrent or metastatic breast cancer." J Clin Oncol 29(10): 1252-1260.

Robertson, J.F., Ferrero, J.M., Bourgeois, H., Kennecke, H., de Boer, R.H., Jacot, W., McGreivy, J., Suzuki, S., Zhu, M., McCaffery, I., Loh, E., Gansert, J.L. and Kaufman, P.A. (2013). "Ganitumab with either exemestane or fulvestrant for postmenopausal women with advanced, hormone-receptor-positive breast cancer: a randomised, controlled, double-blind, phase 2 trial." Lancet Oncol 14(3): 228-235.

Robey, R.W., Honjo, Y., Morisaki, K., Nadjem, T.A., Runge, S., Risbood, M., Poruchynsky, M.S. and Bates, S.E. (2003). "Mutations at amino-acid 482 in the ABCG2 gene affect substrate and antagonist specificity." Br J Cancer 89(10): 1971-1978.

Robey, R.W., Polgar, O., Deeken, J., To, K.W. and Bates, S.E. (2007). "ABCG2: determining its relevance in clinical drug resistance." Cancer Metastasis Rev 26(1): 39-57.

Robinson, D.R., Wu, Y.M., Vats, P., Su, F., Lonigro, R.J., Cao, X., Kalyana-Sundaram, S., Wang, R., Ning, Y., Hodges, L., Gursky, A., Siddiqui, J., Tomlins, S.A., Roychowdhury, S., Pienta, K.J., Kim, S.Y., Roberts, J.S., Rae, J.M., Van Poznak, C.H., Hayes, D.F., Chugh, R., Kunju, L.P., Talpaz, M., Schott, A.F. and Chinnaiyan, A.M. (2013). "Activating ESR1 mutations in hormone-resistant metastatic breast cancer." Nat Genet 45(12): 1446-1451.

Robinson, J.L., Macarthur, S., Ross-Innes, C.S., Tilley, W.D., Neal, D.E., Mills, I.G. and Carroll, J.S. (2011). "Androgen receptor driven transcription in molecular apocrine breast cancer is mediated by FoxA1." EMBO J 30(15): 3019-3027.

Rodriguez Fernandez, J.L., Geiger, B., Salomon, D., Sabanay, I., Zoller, M. and Ben-Ze'ev, A. (1992). "Suppression of tumorigenicity in transformed cells after transfection with vinculin cDNA." J Cell Biol 119(2): 427-438.

Romano, L.A. and Runyan, R.B. (2000). "Slug is an essential target of TGFbeta2 signaling in the developing chicken heart." Dev Biol 223(1): 91-102.

References

251

Roninson, I.B., Chin, J.E., Choi, K.G., Gros, P., Housman, D.E., Fojo, A., Shen, D.W., Gottesman, M.M. and Pastan, I. (1986). "Isolation of human mdr DNA sequences amplified in multidrug-resistant KB carcinoma cells." Proc Natl Acad Sci U S A 83(12): 4538-4542.

Ros, J.E., Libbrecht, L., Geuken, M., Jansen, P.L. and Roskams, T.A. (2003). "High expression of MDR1, MRP1, and MRP3 in the hepatic progenitor cell compartment and hepatocytes in severe human liver disease." J Pathol 200(5): 553-560.

Roses, R.E., Paulson, E.C., Sharma, A., Schueller, J.E., Nisenbaum, H., Weinstein, S., Fox, K.R., Zhang, P.J. and Czerniecki, B.J. (2009). "HER-2/neu overexpression as a predictor for the transition from in situ to invasive breast cancer." Cancer Epidemiol Biomarkers Prev 18(5): 1386-1389.

Rosman, D.S., Phukan, S., Huang, C.C. and Pasche, B. (2008). "TGFBR1*6A enhances the migration and invasion of MCF-7 breast cancer cells through RhoA activation." Cancer Res 68(5): 1319-1328.

Rossouw, J.E., Anderson, G.L., Prentice, R.L., LaCroix, A.Z., Kooperberg, C., Stefanick, M.L., Jackson, R.D., Beresford, S.A., Howard, B.V., Johnson, K.C., Kotchen, J.M. and Ockene, J. (2002). "Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results From the Women's Health Initiative randomized controlled trial." JAMA 288(3): 321-333.

Rothman, M.S., Carlson, N.E., Xu, M., Wang, C., Swerdloff, R., Lee, P., Goh, V.H., Ridgway, E.C. and Wierman, M.E. (2011). "Reexamination of testosterone, dihydrotestosterone, estradiol and estrone levels across the menstrual cycle and in postmenopausal women measured by liquid chromatography-tandem mass spectrometry." Steroids 76(1-2): 177-182.

Roylance, R., Gorman, P., Papior, T., Wan, Y.L., Ives, M., Watson, J.E., Collins, C., Wortham, N., Langford, C., Fiegler, H., Carter, N., Gillett, C., Sasieni, P., Pinder, S., Hanby, A. and Tomlinson, I. (2006). "A comprehensive study of chromosome 16q in invasive ductal and lobular breast carcinoma using array CGH." Oncogene 25(49): 6544-6553.

Ruan, W. and Kleinberg, D.L. (1999). "Insulin-like growth factor I is essential for terminal end bud formation and ductal morphogenesis during mammary development." Endocrinology 140(11): 5075-5081.

Ruff, P., Vorobiof, D.A., Jordaan, J.P., Demetriou, G.S., Moodley, S.D., Nosworthy, A.L., Werner, I.D., Raats, J. and Burgess, L.J. (2009). "A randomized, placebo-controlled, double-blind phase 2 study of docetaxel compared to docetaxel plus zosuquidar (LY335979) in women with metastatic or locally recurrent breast cancer who have received one prior chemotherapy regimen." Cancer Chemother Pharmacol 64(4): 763-768.

Sabol, M., Trnski, D., Uzarevic, Z., Ozretic, P., Musani, V., Rafaj, M., Cindric, M. and Levanat, S. (2014). "Combination of cyclopamine and tamoxifen promotes survival and migration of MCF-7 breast cancer cells - interaction of Hedgehog-Gli and estrogen receptor signaling pathways." PLoS One 9(12): e114510.

Sachse, C., Brockmoller, J., Bauer, S. and Roots, I. (1997). "Cytochrome P450 2D6 variants in a Caucasian population: allele frequencies and phenotypic consequences." Am J Hum Genet 60(2): 284-295.

Saeki, T., Nomizu, T., Toi, M., Ito, Y., Noguchi, S., Kobayashi, T., Asaga, T., Minami, H., Yamamoto, N., Aogi, K., Ikeda, T., Ohashi, Y., Sato, W. and Tsuruo, T. (2007). "Dofequidar fumarate (MS-209) in combination with cyclophosphamide, doxorubicin,

References

252

and fluorouracil for patients with advanced or recurrent breast cancer." J Clin Oncol 25(4): 411-417.

Safarpour, D., Pakneshan, S. and Tavassoli, F.A. (2014). "Androgen receptor (AR) expression in 400 breast carcinomas: is routine AR assessment justified?" Am J Cancer Res 4(4): 353-368.

Saitoh, T. and Katoh, M. (2002). "Expression and regulation of WNT5A and WNT5B in human cancer: up-regulation of WNT5A by TNFalpha in MKN45 cells and up-regulation of WNT5B by beta-estradiol in MCF-7 cells." Int J Mol Med 10(3): 345-349.

Sakurai, K., Enomoto, K., Matsuo, S., Amano, S. and Shiono, M. (2011). "CYP3A4 expression to predict treatment response to docetaxel for metastasis and recurrence of primary breast cancer." Surg Today 41(5): 674-679.

Sampath, J., Adachi, M., Hatse, S., Naesens, L., Balzarini, J., Flatley, R.M., Matherly, L.H. and Schuetz, J.D. (2002). "Role of MRP4 and MRP5 in biology and chemotherapy." AAPS PharmSci 4(3): E14.

Sandhiya, S., Melvin, G., Kumar, S.S. and Dkhar, S.A. (2013). "The dawn of hedgehog inhibitors: Vismodegib." J Pharmacol Pharmacother 4(1): 4-7.

Sarkadi, B., L., Homolya, G., Szakacs, A., Varadi (2006). "Human Multidrug Resistance ABCB and ABCG Transporters: Participation in a Chemoimmunity Defense System." Physiol Rev 86: 1179-1236.

Sarrio, D., Rodriguez-Pinilla, S.M., Hardisson, D., Cano, A., Moreno-Bueno, G. and Palacios, J. (2008). "Epithelial-mesenchymal transition in breast cancer relates to the basal-like phenotype." Cancer Res 68(4): 989-997.

Saunders, R.M., Holt, M.R., Jennings, L., Sutton, D.H., Barsukov, I.L., Bobkov, A., Liddington, R.C., Adamson, E.A., Dunn, G.A. and Critchley, D.R. (2006). "Role of vinculin in regulating focal adhesion turnover." Eur J Cell Biol 85(6): 487-500.

Scaltriti, M., Chandarlapaty, S., Prudkin, L., Aura, C., Jimenez, J., Angelini, P.D., Sanchez, G., Guzman, M., Parra, J.L., Ellis, C., Gagnon, R., Koehler, M., Gomez, H., Geyer, C., Cameron, D., Arribas, J., Rosen, N. and Baselga, J. (2010). "Clinical benefit of lapatinib-based therapy in patients with human epidermal growth factor receptor 2-positive breast tumors coexpressing the truncated p95HER2 receptor." Clin Cancer Res 16(9): 2688-2695.

Scaltriti, M., Rojo, F., Ocana, A., Anido, J., Guzman, M., Cortes, J., Di Cosimo, S., Matias-Guiu, X., Ramon y Cajal, S., Arribas, J. and Baselga, J. (2007). "Expression of p95HER2, a truncated form of the HER2 receptor, and response to anti-HER2 therapies in breast cancer." J Natl Cancer Inst 99(8): 628-638.

Schinkel, A.H., Mayer, U., Wagenaar, E., Mol, C.A., van Deemter, L., Smit, J.J., van der Valk, M.A., Voordouw, A.C., Spits, H., van Tellingen, O., Zijlmans, J.M., Fibbe, W.E. and Borst, P. (1997). "Normal viability and altered pharmacokinetics in mice lacking mdr1-type (drug-transporting) P-glycoproteins." Proc Natl Acad Sci U S A 94(8): 4028-4033.

Schwartzberg, L.S., Franco, S.X., Florance, A., O'Rourke, L., Maltzman, J. and Johnston, S. (2010). "Lapatinib plus letrozole as first-line therapy for HER-2+ hormone receptor-positive metastatic breast cancer." Oncologist 15(2): 122-129.

Scotto, K.W. (2003). "Transcriptional regulation of ABC drug transporters." Oncogene 22(47): 7496-7511.

References

253

Sequist, L.V., Rolfe, L. and Allen, A.R. (2015). "Rociletinib in EGFR-Mutated Non-Small-Cell Lung Cancer." N Engl J Med 373(6): 578-579.

Shah, N.P., Nicoll, J.M., Nagar, B., Gorre, M.E., Paquette, R.L., Kuriyan, J. and Sawyers, C.L. (2002). "Multiple BCR-ABL kinase domain mutations confer polyclonal resistance to the tyrosine kinase inhibitor imatinib (STI571) in chronic phase and blast crisis chronic myeloid leukemia." Cancer Cell 2(2): 117-125.

Shao, S., Zhao, X., Zhang, X., Luo, M., Zuo, X., Huang, S., Wang, Y. and Gu, S. (2015). "Notch1 signaling regulates the epithelial-mesenchymal transition and invasion of breast cancer in a Slug-dependent manner." Mol Cancer 14(1): 28.

Sharma, D., Blum, J., Yang, X., Beaulieu, N., Macleod, A.R. and Davidson, N.E. (2005). "Release of methyl CpG binding proteins and histone deacetylase 1 from the Estrogen receptor alpha (ER) promoter upon reactivation in ER-negative human breast cancer cells." Mol Endocrinol 19(7): 1740-1751.

Shatkina, L., Mink, S., Rogatsch, H., Klocker, H., Langer, G., Nestl, A. and Cato, A.C. (2003). "The cochaperone Bag-1L enhances androgen receptor action via interaction with the NH2-terminal region of the receptor." Mol Cell Biol 23(20): 7189-7197.

Shaw, G., Price, A.M., Ktori, E., Bisson, I., Purkis, P.E., McFaul, S., Oliver, R.T. and Prowse, D.M. (2008). "Hedgehog signalling in androgen independent prostate cancer." Eur Urol 54(6): 1333-1343.

Sheldahl, L.C., Slusarski, D.C., Pandur, P., Miller, J.R., Kuhl, M. and Moon, R.T. (2003). "Dishevelled activates Ca2+ flux, PKC, and CamKII in vertebrate embryos." J Cell Biol 161(4): 769-777.

Shen, T., Kuang, Y.H., Ashby, C.R., Lei, Y., Chen, A., Zhou, Y., Chen, X., Tiwari, A.K., Hopper-Borge, E., Ouyang, J. and Chen, Z.S. (2009). "Imatinib and nilotinib reverse multidrug resistance in cancer cells by inhibiting the efflux activity of the MRP7 (ABCC10)." PLoS One 4(10): e7520.

Shibata, M.A., Morimoto, J., Shibata, E., Kurose, H., Akamatsu, K., Li, Z.L., Kusakabe, M., Ohmichi, M. and Otsuki, Y. (2010). "Raloxifene inhibits tumor growth and lymph node metastasis in a xenograft model of metastatic mammary cancer." BMC Cancer 10: 566.

Shou, J., Massarweh, S., Osborne, C.K., Wakeling, A.E., Ali, S., Weiss, H. and Schiff, R. (2004). "Mechanisms of tamoxifen resistance: increased estrogen receptor-HER2/neu cross-talk in ER/HER2-positive breast cancer." J Natl Cancer Inst 96(12): 926-935.

Shtutman, M., Zhurinsky, J., Simcha, I., Albanese, C., D'Amico, M., Pestell, R. and Ben-Ze'ev, A. (1999). "The cyclin D1 gene is a target of the beta-catenin/LEF-1 pathway." Proc Natl Acad Sci U S A 96(10): 5522-5527.

Shufelt, C.L. and Braunstein, G.D. (2008). "Testosterone and the breast." Menopause Int 14(3): 117-122.

Silberstein, G.B. (2001). "Postnatal mammary gland morphogenesis." Microsc Res Tech 52(2): 155-162.

Silva, J.M., Hamel, M., Sahmi, M. and Price, C.A. (2006). "Control of oestradiol secretion and of cytochrome P450 aromatase messenger ribonucleic acid accumulation by FSH involves different intracellular pathways in oestrogenic bovine granulosa cells in vitro." Reproduction 132(6): 909-917.

References

254

Singh, R.R., Kunkalla, K., Qu, C., Schlette, E., Neelapu, S.S., Samaniego, F. and Vega, F. (2011). "ABCG2 is a direct transcriptional target of hedgehog signaling and involved in stroma-induced drug tolerance in diffuse large B-cell lymphoma." Oncogene 30(49): 4874-4886.

Singh, S.K., Hawkins, C., Clarke, I.D., Squire, J.A., Bayani, J., Hide, T., Henkelman, R.M., Cusimano, M.D. and Dirks, P.B. (2004). "Identification of human brain tumour initiating cells." Nature 432(7015): 396-401.

Sirab, N., Terry, S., Giton, F., Caradec, J., Chimingqi, M., Moutereau, S., Vacherot, F., de la Taille, A., Kouyoumdjian, J.C. and Loric, S. (2012a). "Androgens regulate Hedgehog signalling and proliferation in androgen-dependent prostate cells." Int J Cancer 131(6): 1297-1306.

Sirab, N., Terry, S., Giton, F., Caradec, J., Chimingqi, M., Moutereau, S., Vacherot, F., Taille Ade, L., Kouyoumdjian, J.C. and Loric, S. (2012b). "Androgens regulate Hedgehog signalling and proliferation in androgen-dependent prostate cells." Int J Cancer 131(6): 1297-1306.

Sisci, D., Middea, E., Morelli, C., Lanzino, M., Aquila, S., Rizza, P., Catalano, S., Casaburi, I., Maggiolini, M. and Ando, S. (2010). "17beta-estradiol enhances alpha(5) integrin subunit gene expression through ERalpha-Sp1 interaction and reduces cell motility and invasion of ERalpha-positive breast cancer cells." Breast Cancer Res Treat 124(1): 63-77.

Slamon, D.J., Clark, G.M., Wong, S.G., Levin, W.J., Ullrich, A. and McGuire, W.L. (1987). "Human breast cancer: correlation of relapse and survival with amplification of the HER-2/neu oncogene." Science 235(4785): 177-182.

Smith, I.E., Pierga, J.Y., Biganzoli, L., Cortes-Funes, H., Thomssen, C., Pivot, X., Fabi, A., Xu, B., Stroyakovskiy, D., Franke, F.A., Kaufman, B., Mainwaring, P., Pienkowski, T., De Valk, B., Kwong, A., Gonzalez-Trujillo, J.L., Koza, I., Petrakova, K., Pereira, D. and Pritchard, K.I. (2011). "First-line bevacizumab plus taxane-based chemotherapy for locally recurrent or metastatic breast cancer: safety and efficacy in an open-label study in 2,251 patients." Ann Oncol 22(3): 595-602.

Smith, L.M., Wise, S.C., Hendricks, D.T., Sabichi, A.L., Bos, T., Reddy, P., Brown, P.H. and Birrer, M.J. (1999). "cJun overexpression in MCF-7 breast cancer cells produces a tumorigenic, invasive and hormone resistant phenotype." Oncogene 18(44): 6063-6070.

Soltoff, S.P., Carraway, K.L., 3rd, Prigent, S.A., Gullick, W.G. and Cantley, L.C. (1994). "ErbB3 is involved in activation of phosphatidylinositol 3-kinase by epidermal growth factor." Mol Cell Biol 14(6): 3550-3558.

Somboonporn, W. and Davis, S.R. (2004). "Testosterone effects on the breast: implications for testosterone therapy for women." Endocr Rev 25(3): 374-388.

Sorlie, T., Perou, C.M., Tibshirani, R., Aas, T., Geisler, S., Johnsen, H., Hastie, T., Eisen, M.B., van de Rijn, M., Jeffrey, S.S., Thorsen, T., Quist, H., Matese, J.C., Brown, P.O., Botstein, D., Lonning, P.E. and Borresen-Dale, A.L. (2001). "Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications." Proc Natl Acad Sci U S A 98(19): 10869-10874.

Sorlie, T., Tibshirani, R., Parker, J., Hastie, T., Marron, J.S., Nobel, A., Deng, S., Johnsen, H., Pesich, R., Geisler, S., Demeter, J., Perou, C.M., Lonning, P.E., Brown, P.O., Borresen-Dale, A.L. and Botstein, D. (2003). "Repeated observation of breast tumor subtypes in independent gene expression data sets." Proc Natl Acad Sci U S A 100(14): 8418-8423.

References

255

Soule, H.D., Vazguez, J., Long, A., Albert, S. and Brennan, M. (1973). "A human cell line from a pleural effusion derived from a breast carcinoma." J Natl Cancer Inst 51(5): 1409-1416.

Souzaki, M., Kubo, M., Kai, M., Kameda, C., Tanaka, H., Taguchi, T., Tanaka, M., Onishi, H. and Katano, M. (2011). "Hedgehog signaling pathway mediates the progression of non-invasive breast cancer to invasive breast cancer." Cancer Sci 102(2): 373-381.

Sparano, J.A., Vrdoljak, E., Rixe, O., Xu, B., Manikhas, A., Medina, C., Da Costa, S.C., Ro, J., Rubio, G., Rondinon, M., Perez Manga, G., Peck, R., Poulart, V. and Conte, P. (2010). "Randomized phase III trial of ixabepilone plus capecitabine versus capecitabine in patients with metastatic breast cancer previously treated with an anthracycline and a taxane." J Clin Oncol 28(20): 3256-3263.

Steinway, S.N., Zanudo, J.G., Ding, W., Rountree, C.B., Feith, D.J., Loughran, T.P., Jr. and Albert, R. (2014). "Network modeling of TGFbeta signaling in hepatocellular carcinoma epithelial-to-mesenchymal transition reveals joint sonic hedgehog and Wnt pathway activation." Cancer Res 74(21): 5963-5977.

Sterling, J.A., Oyajobi, B.O., Grubbs, B., Padalecki, S.S., Munoz, S.A., Gupta, A., Story, B., Zhao, M. and Mundy, G.R. (2006). "The hedgehog signaling molecule Gli2 induces parathyroid hormone-related peptide expression and osteolysis in metastatic human breast cancer cells." Cancer Res 66(15): 7548-7553.

Stracker, T.H., Usui, T. and Petrini, J.H. (2009). "Taking the time to make important decisions: the checkpoint effector kinases Chk1 and Chk2 and the DNA damage response." DNA Repair (Amst) 8(9): 1047-1054.

Strom, A., Hartman, J., Foster, J.S., Kietz, S., Wimalasena, J. and Gustafsson, J.A. (2004). "Estrogen receptor beta inhibits 17beta-estradiol-stimulated proliferation of the breast cancer cell line T47D." Proc Natl Acad Sci U S A 101(6): 1566-1571.

Studzian, M., Bartosz, G. and Pulaski, L. (2015). "Endocytosis of ABCG2 drug transporter caused by binding of 5D3 antibody: trafficking mechanisms and intracellular fate." Biochim Biophys Acta 1853(8): 1759-1771.

Suga, K., Imai, K., Eguchi, H., Hayashi, S., Higashi, Y. and Nakachi, K. (2001). "Molecular significance of excess body weight in postmenopausal breast cancer patients, in relation to expression of insulin-like growth factor I receptor and insulin-like growth factor II genes." Jpn J Cancer Res 92(2): 127-134.

Sun, Y., Wang, B.E., Leong, K.G., Yue, P., Li, L., Jhunjhunwala, S., Chen, D., Seo, K., Modrusan, Z., Gao, W.Q., Settleman, J. and Johnson, L. (2012). "Androgen deprivation causes epithelial-mesenchymal transition in the prostate: implications for androgen-deprivation therapy." Cancer Res 72(2): 527-536.

Sun, Y., Wang, Y., Fan, C., Gao, P., Wang, X., Wei, G. and Wei, J. (2014). "Estrogen promotes stemness and invasiveness of ER-positive breast cancer cells through Gli1 activation." Mol Cancer 13: 137.

Suvannasankha, A., Minderman, H., O'Loughlin, K.L., Nakanishi, T., Ford, L.A., Greco, W.R., Wetzler, M., Ross, D.D. and Baer, M.R. (2004). "Breast cancer resistance protein (BCRP/MXR/ABCG2) in adult acute lymphoblastic leukaemia: frequent expression and possible correlation with shorter disease-free survival." Br J Haematol 127(4): 392-398.

Suzuki, M., Suzuki, H., Sugimoto, Y. and Sugiyama, Y. (2003). "ABCG2 transports sulfated conjugates of steroids and xenobiotics." J Biol Chem 278(25): 22644-22649.

References

256

Suzuki, R., Ye, W., Rylander-Rudqvist, T., Saji, S., Colditz, G.A. and Wolk, A. (2005). "Alcohol and postmenopausal breast cancer risk defined by estrogen and progesterone receptor status: a prospective cohort study." J Natl Cancer Inst 97(21): 1601-1608.

Svensson, J., Moverare-Skrtic, S., Windahl, S., Swanson, C. and Sjogren, K. (2010). "Stimulation of both estrogen and androgen receptors maintains skeletal muscle mass in gonadectomized male mice but mainly via different pathways." J Mol Endocrinol 45(1): 45-57.

Swain, S.M., Kim, S.B., Cortes, J., Ro, J., Semiglazov, V., Campone, M., Ciruelos, E., Ferrero, J.M., Schneeweiss, A., Knott, A., Clark, E., Ross, G., Benyunes, M.C. and Baselga, J. (2013). "Pertuzumab, trastuzumab, and docetaxel for HER2-positive metastatic breast cancer (CLEOPATRA study): overall survival results from a randomised, double-blind, placebo-controlled, phase 3 study." Lancet Oncol 14(6): 461-471.

Swiecicki, P.L., Atherton, P.J., Finnes, H.D., Puttabasavaiah, S. and Goetz, M.P. (2013). "CYP3A inhibitors and adverse outcomes in patients treated with docetaxel chemotherapy". Paper presented at 2013 American Society of Clinical Oncology Annual Meeting.

Szelei, J., Jimenez, J., Soto, A.M., Luizzi, M.F. and Sonnenschein, C. (1997). "Androgen-induced inhibition of proliferation in human breast cancer MCF-7 cells transfected with androgen receptor." Endocrinology 138(4): 1406-1412.

Tabuchi, Y., Matsuoka, J., Gunduz, M., Imada, T., Ono, R., Ito, M., Motoki, T., Yamatsuji, T., Shirakawa, Y., Takaoka, M., Haisa, M., Tanaka, N., Kurebayashi, J., Jordan, V.C. and Naomoto, Y. (2009). "Resistance to paclitaxel therapy is related with Bcl-2 expression through an estrogen receptor mediated pathway in breast cancer." Int J Oncol 34(2): 313-319.

Taipale, J., Chen, J.K., Cooper, M.K., Wang, B., Mann, R.K., Milenkovic, L., Scott, M.P. and Beachy, P.A. (2000). "Effects of oncogenic mutations in Smoothened and Patched can be reversed by cyclopamine." Nature 406(6799): 1005-1009.

Takayama, S., Ishii, S., Ikeda, T., Masamura, S., Doi, M. and Kitajima, M. (2005). "The relationship between bone metastasis from human breast cancer and integrin alpha(v)beta3 expression." Anticancer Res 25(1A): 79-83.

Talbot, L.J., Bhattacharya, S.D. and Kuo, P.C. (2012). "Epithelial-mesenchymal transition, the tumor microenvironment, and metastatic behavior of epithelial malignancies." Int J Biochem Mol Biol 3(2): 117-136.

Tang, V.W. and Goodenough, D.A. (2003). "Paracellular ion channel at the tight junction." Biophys J 84(3): 1660-1673.

ten Haaf, A., Bektas, N., von Serenyi, S., Losen, I., Arweiler, E.C., Hartmann, A., Knuchel, R. and Dahl, E. (2009). "Expression of the glioma-associated oncogene homolog (GLI) 1 in human breast cancer is associated with unfavourable overall survival." BMC Cancer 9: 298.

Terry, K.L., Willett, W.C., Rich-Edwards, J.W., Hunter, D.J. and Michels, K.B. (2005). "Menstrual cycle characteristics and incidence of premenopausal breast cancer." Cancer Epidemiol Biomarkers Prev 14(6): 1509-1513.

Thaiparambil, J.T., Bender, L., Ganesh, T., Kline, E., Patel, P., Liu, Y., Tighiouart, M., Vertino, P.M., Harvey, R.D., Garcia, A. and Marcus, A.I. (2011). "Withaferin A inhibits breast cancer invasion and metastasis at sub-cytotoxic doses by inducing vimentin disassembly and serine 56 phosphorylation." Int J Cancer 129(11): 2744-2755.

References

257

Thiantanawat, A., Long, B.J. and Brodie, A.M. (2003). "Signaling pathways of apoptosis activated by aromatase inhibitors and antiestrogens." Cancer Res 63(22): 8037-8050.

Thomas, C. and Gustafsson, J.A. (2011). "The different roles of ER subtypes in cancer biology and therapy." Nat Rev Cancer 11(8): 597-608.

To, K.K. and Tomlinson, B. (2013). "Targeting the ABCG2-overexpressing multidrug resistant (MDR) cancer cells by PPARgamma agonists." Br J Pharmacol 170(5): 1137-1151.

Topper, Y.J. and Freeman, C.S. (1980). "Multiple hormone interactions in the developmental biology of the mammary gland." Physiol Rev 60(4): 1049-1106.

Torre, L.A., Bray, F., Siegel, R.L., Ferlay, J., Lortet-Tieulent, J. and Jemal, A. (2015). "Global cancer statistics, 2012." CA Cancer J Clin 65(2): 87-108.

Tsai, J.H. and Yang, J. (2013). "Epithelial-mesenchymal plasticity in carcinoma metastasis." Genes Dev 27(20): 2192-2206.

Valero, V., Forbes, J., Pegram, M.D., Pienkowski, T., Eiermann, W., von Minckwitz, G., Roche, H., Martin, M., Crown, J., Mackey, J.R., Fumoleau, P., Rolski, J., Mrsic-Krmpotic, Z., Jagiello-Gruszfeld, A., Riva, A., Buyse, M., Taupin, H., Sauter, G., Press, M.F. and Slamon, D.J. (2011). "Multicenter phase III randomized trial comparing docetaxel and trastuzumab with docetaxel, carboplatin, and trastuzumab as first-line chemotherapy for patients with HER2-gene-amplified metastatic breast cancer (BCIRG 007 study): two highly active therapeutic regimens." J Clin Oncol 29(2): 149-156.

Vallin, J., Thuret, R., Giacomello, E., Faraldo, M.M., Thiery, J.P. and Broders, F. (2001). "Cloning and characterization of three Xenopus slug promoters reveal direct regulation by Lef/beta-catenin signaling." J Biol Chem 276(32): 30350-30358.

van der Horst, P.H., Wang, Y., Vandenput, I., Kuhne, L.C., Ewing, P.C., van Ijcken, W.F., van der Zee, M., Amant, F., Burger, C.W. and Blok, L.J. (2012). "Progesterone inhibits epithelial-to-mesenchymal transition in endometrial cancer." PLoS One 7(1): e30840.

van Herwaarden, A.E., Jonker, J.W., Wagenaar, E., Brinkhuis, R.F., Schellens, J.H., Beijnen, J.H. and Schinkel, A.H. (2003). "The breast cancer resistance protein (Bcrp1/Abcg2) restricts exposure to the dietary carcinogen 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine." Cancer Res 63(19): 6447-6452.

Varadwaj, P., Misra, K., Sharma, A. and Kumar, R. (2010). "Mitoxantrone: an agent with promises for anticancer therapies " Electronic Journal of Biology 6(2): 36-42.

Vares, G., Cui, X., Wang, B., Nakajima, T. and Nenoi, M. (2013). "Generation of breast cancer stem cells by steroid hormones in irradiated human mammary cell lines." PLoS One 8(10): e77124.

Vasiliou, V., Vasiliou, K. and Nebert, D.W. (2009). "Human ATP-binding cassette (ABC) transporter family." Hum Genomics 3(3): 281-290.

Vega, S., Morales, A.V., Ocana, O.H., Valdes, F., Fabregat, I. and Nieto, M.A. (2004). "Snail blocks the cell cycle and confers resistance to cell death." Genes Dev 18(10): 1131-1143.

Veronesi, U., Cascinelli, N., Mariani, L., Greco, M., Saccozzi, R., Luini, A., Aguilar, M. and Marubini, E. (2002). "Twenty-year follow-up of a randomized study comparing breast-conserving surgery with radical mastectomy for early breast cancer." N Engl J Med 347(16): 1227-1232.

References

258

Verrijdt, G., Haelens, A. and Claessens, F. (2003). "Selective DNA recognition by the androgen receptor as a mechanism for hormone-specific regulation of gene expression." Mol Genet Metab 78(3): 175-185.

Vilaboa, N.E., Galan, A., Troyano, A., de Blas, E. and Aller, P. (2000). "Regulation of multidrug resistance 1 (MDR1)/P-glycoprotein gene expression and activity by heat-shock transcription factor 1 (HSF1)." J Biol Chem 275(32): 24970-24976.

Visvader, J.E. and Lindeman, G.J. (2008). "Cancer stem cells in solid tumours: accumulating evidence and unresolved questions." Nat Rev Cancer 8(10): 755-768.

Wakabayashi, K., Nakagawa, H., Tamura, A., Koshiba, S., Hoshijima, K., Komada, M. and Ishikawa, T. (2007). "Intramolecular disulfide bond is a critical check point determining degradative fates of ATP-binding cassette (ABC) transporter ABCG2 protein." J Biol Chem 282(38): 27841-27846.

Walsh, T., Casadei, S., Coats, K.H., Swisher, E., Stray, S.M., Higgins, J., Roach, K.C., Mandell, J., Lee, M.K., Ciernikova, S., Foretova, L., Soucek, P. and King, M.C. (2006). "Spectrum of mutations in BRCA1, BRCA2, CHEK2, and TP53 in families at high risk of breast cancer." JAMA 295(12): 1379-1388.

Walsh, T., Lee, M.K., Casadei, S., Thornton, A.M., Stray, S.M., Pennil, C., Nord, A.S., Mandell, J.B., Swisher, E.M. and King, M.C. (2010). "Detection of inherited mutations for breast and ovarian cancer using genomic capture and massively parallel sequencing." Proc Natl Acad Sci U S A 107(28): 12629-12633.

Wang, C., Mayer, J.A., Mazumdar, A., Fertuck, K., Kim, H., Brown, M. and Brown, P.H. (2011a). "Estrogen induces c-myc gene expression via an upstream enhancer activated by the estrogen receptor and the AP-1 transcription factor." Mol Endocrinol 25(9): 1527-1538.

Wang, C., Xu, C.X., Bu, Y., Bottum, K.M. and Tischkau, S.A. (2014). "Beta-naphthoflavone (DB06732) mediates estrogen receptor-positive breast cancer cell cycle arrest through AhR-dependent regulation of PI3K/AKT and MAPK/ERK signaling." Carcinogenesis 35(3): 703-713.

Wang, C.X., Koay, D.C., Edwards, A., Lu, Z., Mor, G., Ocal, I.T. and Digiovanna, M.P. (2005). "In vitro and in vivo effects of combination of Trastuzumab (Herceptin) and Tamoxifen in breast cancer." Breast Cancer Res Treat 92(3): 251-263.

Wang, G., Wang, J. and Sadar, M.D. (2008a). "Crosstalk between the androgen receptor and beta-catenin in castrate-resistant prostate cancer." Cancer Res 68(23): 9918-9927.

Wang, H., Lee, E.W., Zhou, L., Leung, P.C., Ross, D.D., Unadkat, J.D. and Mao, Q. (2008b). "Progesterone receptor (PR) isoforms PRA and PRB differentially regulate expression of the breast cancer resistance protein in human placental choriocarcinoma BeWo cells." Mol Pharmacol 73(3): 845-854.

Wang, H., Zhou, L., Gupta, A., Vethanayagam, R.R., Zhang, Y., Unadkat, J.D. and Mao, Q. (2006a). "Regulation of BCRP/ABCG2 expression by progesterone and 17beta-estradiol in human placental BeWo cells." Am J Physiol Endocrinol Metab 290(5): E798-807.

Wang, X.H., Meng, X.W., Sun, X., Liu, B.R., Han, M.Z., Du, Y.J., Song, Y.Y. and Xu, W. (2011b). "Wnt/beta-catenin signaling regulates MAPK and Akt1 expression and growth of hepatocellular carcinoma cells." Neoplasma 58(3): 239-244.

References

259

Wang, Y., He, X., Yu, Q. and Eng, C. (2013). "Androgen receptor-induced tumor suppressor, KLLN, inhibits breast cancer growth and transcriptionally activates p53/p73-mediated apoptosis in breast carcinomas." Hum Mol Genet 22(11): 2263-2272.

Wang, Y., Ji, P., Liu, J., Broaddus, R.R., Xue, F. and Zhang, W. (2009a). "Centrosome-associated regulators of the G(2)/M checkpoint as targets for cancer therapy." Mol Cancer 8: 8.

Wang, Y., Romigh, T., He, X., Tan, M.H., Orloff, M.S., Silverman, R.H., Heston, W.D. and Eng, C. (2011c). "Differential regulation of PTEN expression by androgen receptor in prostate and breast cancers." Oncogene 30(42): 4327-4338.

Wang, Y. and Zhou, B.P. (2013). "Epithelial-mesenchymal transition---a hallmark of breast cancer metastasis." Cancer Hallm 1(1): 38-49.

Wang, Y.H., Li, F., Luo, B., Wang, X.H., Sun, H.C., Liu, S., Cui, Y.Q. and Xu, X.X. (2009b). "A side population of cells from a human pancreatic carcinoma cell line harbors cancer stem cell characteristics." Neoplasma 56(5): 371-378.

Wang, Z., Banerjee, S., Li, Y., Rahman, K.M., Zhang, Y. and Sarkar, F.H. (2006b). "Down-regulation of notch-1 inhibits invasion by inactivation of nuclear factor-kappaB, vascular endothelial growth factor, and matrix metalloproteinase-9 in pancreatic cancer cells." Cancer Res 66(5): 2778-2784.

Watts, C.K., Brady, A., Sarcevic, B., deFazio, A., Musgrove, E.A. and Sutherland, R.L. (1995). "Antiestrogen inhibition of cell cycle progression in breast cancer cells in associated with inhibition of cyclin-dependent kinase activity and decreased retinoblastoma protein phosphorylation." Mol Endocrinol 9(12): 1804-1813.

Webb, D.J., Parsons, J.T. and Horwitz, A.F. (2002). "Adhesion assembly, disassembly and turnover in migrating cells -- over and over and over again." Nat Cell Biol 4(4): E97-100.

Wei, L.L., Hawkins, P., Baker, C., Norris, B., Sheridan, P.L. and Quinn, P.G. (1996). "An amino-terminal truncated progesterone receptor isoform, PRc, enhances progestin-induced transcriptional activity." Mol Endocrinol 10(11): 1379-1387.

Wei, L.L., Norris, B.M. and Baker, C.J. (1997). "An N-terminally truncated third progesterone receptor protein, PR(C), forms heterodimers with PR(B) but interferes in PR(B)-DNA binding." J Steroid Biochem Mol Biol 62(4): 287-297.

Wei, Y., Ma, Y., Zhao, Q., Ren, Z., Li, Y., Hou, T. and Peng, H. (2012). "New use for an old drug: inhibiting ABCG2 with sorafenib." Mol Cancer Ther 11(8): 1693-1702.

Welch, D.R., Fabra, A. and Nakajima, M. (1990). "Transforming growth factor beta stimulates mammary adenocarcinoma cell invasion and metastatic potential." Proc Natl Acad Sci U S A 87(19): 7678-7682.

Wellings, S.R. and Jensen, H.M. (1973). "On the origin and progression of ductal carcinoma in the human breast." J Natl Cancer Inst 50(5): 1111-1118.

Wen, X., Lai, C.K., Evangelista, M., Hongo, J.A., de Sauvage, F.J. and Scales, S.J. (2010). "Kinetics of hedgehog-dependent full-length Gli3 accumulation in primary cilia and subsequent degradation." Mol Cell Biol 30(8): 1910-1922.

Westerfeld, C. (2010). "ABC transporters in ophthalmic disease." Methods Mol Biol 637: 221-230.

References

260

Wicki, A., Lehembre, F., Wick, N., Hantusch, B., Kerjaschki, D. and Christofori, G. (2006). "Tumor invasion in the absence of epithelial-mesenchymal transition: podoplanin-mediated remodeling of the actin cytoskeleton." Cancer Cell 9(4): 261-272.

Wilcken, N., Hornbuckle, J. and Ghersi, D. (2003). "Chemotherapy alone versus endocrine therapy alone for metastatic breast cancer." Cochrane Database Syst Rev(2): CD002747.

Williams, C., Edvardsson, K., Lewandowski, S.A., Strom, A. and Gustafsson, J.A. (2008). "A genome-wide study of the repressive effects of estrogen receptor beta on estrogen receptor alpha signaling in breast cancer cells." Oncogene 27(7): 1019-1032.

Winklbauer, R., Medina, A., Swain, R.K. and Steinbeisser, H. (2001). "Frizzled-7 signalling controls tissue separation during Xenopus gastrulation." Nature 413(6858): 856-860.

Winklmayr, M., Schmid, C., Laner-Plamberger, S., Kaser, A., Aberger, F., Eichberger, T. and Frischauf, A.M. (2010). "Non-consensus GLI binding sites in Hedgehog target gene regulation." BMC Mol Biol 11: 2.

Wolf, K., Te Lindert, M., Krause, M., Alexander, S., Te Riet, J., Willis, A.L., Hoffman, R.M., Figdor, C.G., Weiss, S.J. and Friedl, P. (2013). "Physical limits of cell migration: control by ECM space and nuclear deformation and tuning by proteolysis and traction force." J Cell Biol 201(7): 1069-1084.

Wu, J., Lu, L.Y. and Yu, X. (2010). "The role of BRCA1 in DNA damage response." Protein Cell 1(2): 117-123.

Wu, Y., Ginther, C., Kim, J., Mosher, N., Chung, S., Slamon, D. and Vadgama, J.V. (2012a). "Expression of Wnt3 activates Wnt/beta-catenin pathway and promotes EMT-like phenotype in trastuzumab-resistant HER2-overexpressing breast cancer cells." Mol Cancer Res 10(12): 1597-1606.

Wu, Y., Zhao, W., Zhao, J., Pan, J., Wu, Q., Zhang, Y., Bauman, W.A. and Cardozo, C.P. (2007). "Identification of androgen response elements in the insulin-like growth factor I upstream promoter." Endocrinology 148(6): 2984-2993.

Wu, Y. and Zhou, B.P. (2008). "New insights of epithelial-mesenchymal transition in cancer metastasis." Acta Biochim Biophys Sin (Shanghai) 40(7): 643-650.

Wu, Y. and Zhou, B.P. (2010). "TNF-alpha/NF-kappaB/Snail pathway in cancer cell migration and invasion." Br J Cancer 102(4): 639-644.

Wu, Y.J., Muldoon, L.L., Gahramanov, S., Kraemer, D.F., Marshall, D.J. and Neuwelt, E.A. (2012b). "Targeting alphaV-integrins decreased metastasis and increased survival in a nude rat breast cancer brain metastasis model." J Neurooncol 110(1): 27-36.

Xiao, Q. and Ge, G. (2012). "Lysyl oxidase, extracellular matrix remodeling and cancer metastasis." Cancer Microenviron 5(3): 261-273.

Xie, Y., Xu, K., Linn, D.E., Yang, X., Guo, Z., Shimelis, H., Nakanishi, T., Ross, D.D., Chen, H., Fazli, L., Gleave, M.E. and Qiu, Y. (2008). "The 44-kDa Pim-1 kinase phosphorylates BCRP/ABCG2 and thereby promotes its multimerization and drug-resistant activity in human prostate cancer cells." J Biol Chem 283(6): 3349-3356.

Xu, J., Lamouille, S. and Derynck, R. (2009). "TGF-beta-induced epithelial to mesenchymal transition." Cell Res 19(2): 156-172.

References

261

Xu, J., Liu, Y., Yang, Y., Bates, S. and Zhang, J.T. (2004). "Characterization of oligomeric human half-ABC transporter ATP-binding cassette G2." J Biol Chem 279(19): 19781-19789.

Xu, X.L. and Kapoun, A.M. (2009). "Heterogeneous activation of the TGFbeta pathway in glioblastomas identified by gene expression-based classification using TGFbeta-responsive genes." J Transl Med 7: 12.

Xu, Y., Sun, Y., Yao, L., Shi, L., Wu, Y., Ouyang, T., Li, J., Wang, T., Fan, Z., Fan, T., Lin, B., He, L., Li, P. and Xie, Y. (2008). "Association between CYP2D6 *10 genotype and survival of breast cancer patients receiving tamoxifen treatment." Ann Oncol 19(8): 1423-1429.

Yang, S. and Kim, H.M. (2014). "ROCK inhibition activates MCF-7 cells." PLoS One 9(2): e88489.

Yasuda, S., Itagaki, S., Hirano, T. and Iseki, K. (2006). "Effects of sex hormones on regulation of ABCG2 expression in the placental cell line BeWo." J Pharm Pharm Sci 9(1): 133-139.

Yasuda, S., Kobayashi, M., Itagaki, S., Hirano, T. and Iseki, K. (2009). "Response of the ABCG2 promoter in T47D cells and BeWo cells to sex hormone treatment." Mol Biol Rep 36(7): 1889-1896.

Ye, J., Coulouris, G., Zaretskaya, I., Cutcutache, I., Rozen, S. and Madden, T.L. (2012). "Primer-BLAST: a tool to design target-specific primers for polymerase chain reaction." BMC Bioinformatics 13: 134.

Yilmaz, M. and Christofori, G. (2009). "EMT, the cytoskeleton, and cancer cell invasion." Cancer Metastasis Rev 28(1-2): 15-33.

Yin, L., Castagnino, P. and Assoian, R.K. (2008). "ABCG2 expression and side population abundance regulated by a transforming growth factor beta-directed epithelial-mesenchymal transition." Cancer Res 68(3): 800-807.

Yoh, K., Ishii, G., Yokose, T., Minegishi, Y., Tsuta, K., Goto, K., Nishiwaki, Y., Kodama, T., Suga, M. and Ochiai, A. (2004). "Breast cancer resistance protein impacts clinical outcome in platinum-based chemotherapy for advanced non-small cell lung cancer." Clin Cancer Res 10(5): 1691-1697.

Yook, J.I., Li, X.Y., Ota, I., Fearon, E.R. and Weiss, S.J. (2005). "Wnt-dependent regulation of the E-cadherin repressor snail." J Biol Chem 280(12): 11740-11748.

Yoshida, K., Saito, T., Kamida, A., Matsumoto, K., Saeki, K., Mochizuki, M., Sasaki, N. and Nakagawa, T. (2013). "Transforming growth factor-beta transiently induces vimentin expression and invasive capacity in a canine mammary gland tumor cell line." Res Vet Sci 94(3): 539-541.

Yoshida, R., Kimura, N., Harada, Y. and Ohuchi, N. (2001). "The loss of E-cadherin, alpha- and beta-catenin expression is associated with metastasis and poor prognosis in invasive breast cancer." Int J Oncol 18(3): 513-520.

Younis, L.K., El Sakka, H. and Haque, I. (2007). "The prognostic value of E-cadherin expression in breast cancer." Int J Health Sci (Qassim) 1(1): 43-51.

Yu, L., Hebert, M.C. and Zhang, Y.E. (2002). "TGF-beta receptor-activated p38 MAP kinase mediates Smad-independent TGF-beta responses." EMBO J 21(14): 3749-3759.

References

262

Yuan, J.H., Cheng, J.Q., Jiang, L.Y., Ji, W.D., Guo, L.F., Liu, J.J., Xu, X.Y., He, J.S., Wang, X.M. and Zhuang, Z.X. (2008). "Breast cancer resistance protein expression and 5-fluorouracil resistance." Biomed Environ Sci 21(4): 290-295.

Yue, J. and Mulder, K.M. (2000). "Activation of the mitogen-activated protein kinase pathway by transforming growth factor-beta." Methods Mol Biol 142: 125-131.

Zaarur, N., Meriin, A.B., Bejarano, E., Xu, X., Gabai, V.L., Cuervo, A.M. and Sherman, M.Y. (2014). "Proteasome failure promotes positioning of lysosomes around the aggresome via local block of microtubule-dependent transport." Mol Cell Biol 34(7): 1336-1348.

Zavadil, J., Bitzer, M., Liang, D., Yang, Y.C., Massimi, A., Kneitz, S., Piek, E. and Bottinger, E.P. (2001). "Genetic programs of epithelial cell plasticity directed by transforming growth factor-beta." Proc Natl Acad Sci U S A 98(12): 6686-6691.

Zavadil, J., Cermak, L., Soto-Nieves, N. and Bottinger, E.P. (2004). "Integration of TGF-beta/Smad and Jagged1/Notch signalling in epithelial-to-mesenchymal transition." EMBO J 23(5): 1155-1165.

Zeng, X., Huang, H., Tamai, K., Zhang, X., Harada, Y., Yokota, C., Almeida, K., Wang, J., Doble, B., Woodgett, J., Wynshaw-Boris, A., Hsieh, J.C. and He, X. (2008). "Initiation of Wnt signaling: control of Wnt coreceptor Lrp6 phosphorylation/activation via frizzled, dishevelled and axin functions." Development 135(2): 367-375.

Zhang, G., Wang, Z., Luo, W., Jiao, H., Wu, J. and Jiang, C. (2013a). "Expression of potential cancer stem cell marker ABCG2 is associated with malignant behaviors of hepatocellular carcinoma." Gastroenterol Res Pract 2013: 782581.

Zhang, G.J., Kimijima, I., Onda, M., Kanno, M., Sato, H., Watanabe, T., Tsuchiya, A., Abe, R. and Takenoshita, S. (1999). "Tamoxifen-induced apoptosis in breast cancer cells relates to down-regulation of bcl-2, but not bax and bcl-X(L), without alteration of p53 protein levels." Clin Cancer Res 5(10): 2971-2977.

Zhang, W., Mojsilovic-Petrovic, J., Andrade, M.F., Zhang, H., Ball, M. and Stanimirovic, D.B. (2003). "The expression and functional characterization of ABCG2 in brain endothelial cells and vessels." FASEB J 17(14): 2085-2087.

Zhang, X., Harrington, N., Moraes, R.C., Wu, M.F., Hilsenbeck, S.G. and Lewis, M.T. (2009). "Cyclopamine inhibition of human breast cancer cell growth independent of Smoothened (Smo)." Breast Cancer Res Treat 115(3): 505-521.

Zhang, X., Li, Y., Zhang, Y., Song, J., Wang, Q., Zheng, L. and Liu, D. (2013b). "Beta-elemene blocks epithelial-mesenchymal transition in human breast cancer cell line MCF-7 through Smad3-mediated down-regulation of nuclear transcription factors." PLoS One 8(3): e58719.

Zhang, Y., Feng, X.H. and Derynck, R. (1998). "Smad3 and Smad4 cooperate with c-Jun/c-Fos to mediate TGF-beta-induced transcription." Nature 394(6696): 909-913.

Zhao, Y.G., Xiao, A.Z., Park, H.I., Newcomer, R.G., Yan, M., Man, Y.G., Heffelfinger, S.C. and Sang, Q.X. (2004). "Endometase/matrilysin-2 in human breast ductal carcinoma in situ and its inhibition by tissue inhibitors of metalloproteinases-2 and -4: a putative role in the initiation of breast cancer invasion." Cancer Res 64(2): 590-598.

Zhou, J., Ng, S., Adesanya-Famuiya, O., Anderson, K. and Bondy, C.A. (2000). "Testosterone inhibits estrogen-induced mammary epithelial proliferation and suppresses estrogen receptor expression." FASEB J 14(12): 1725-1730.

References

263

Zhou, Q., Atadja, P. and Davidson, N.E. (2007). "Histone deacetylase inhibitor LBH589 reactivates silenced estrogen receptor alpha (ER) gene expression without loss of DNA hypermethylation." Cancer Biol Ther 6(1): 64-69.

Zhou, W., Wang, G. and Guo, S. (2013). "Regulation of angiogenesis via Notch signaling in breast cancer and cancer stem cells." Biochim Biophys Acta 1836(2): 304-320.

Zhu, M.L. and Kyprianou, N. (2010). "Role of androgens and the androgen receptor in epithelial-mesenchymal transition and invasion of prostate cancer cells." FASEB J 24(3): 769-777.

Zhu, Y., Rice, C.D., Pang, Y., Pace, M. and Thomas, P. (2003). "Cloning, expression, and characterization of a membrane progestin receptor and evidence it is an intermediary in meiotic maturation of fish oocytes." Proc Natl Acad Sci U S A 100(5): 2231-2236.

Zuo, L., Li, W. and You, S. (2010). "Progesterone reverses the mesenchymal phenotypes of basal phenotype breast cancer cells via a membrane progesterone receptor mediated pathway." Breast Cancer Res 12(3): R34.

Zutter, M.M., Mazoujian, G. and Santoro, S.A. (1990). "Decreased expression of integrin adhesive protein receptors in adenocarcinoma of the breast." Am J Pathol 137(4): 863-870.

Zutter, M.M., Santoro, S.A., Staatz, W.D. and Tsung, Y.L. (1995). "Re-expression of the alpha 2 beta 1 integrin abrogates the malignant phenotype of breast carcinoma cells." Proc Natl Acad Sci U S A 92(16): 7411-7415.

Appendix 1

264

APPENDIX 1 BUFFERS & SOLUTIONS

1. 2% (w/v) Agarose

Agarose powder 6g

1× TAE52 300mL

10mg/mL Ethidium bromide20

8μL

Agarose and 1× TAE were heated in a microwave to dissolve the agarose. Ethidium bromide was added and the solution was stored at room temperature. Prior to use, agarose was heated in a microwave until melted, then cooled to ~70ºC before pouring into gel casting trays.

2. 1mg/mL 7-Aminoactinomycin D (7-AAD)

7-AAD 1mg

Methanol 50μL

PBS (with Ca2+and Mg2+)33

950μL

7-AAD was dissolved in methanol, PBS was added and the solution was stored at 4ºC protected from light.

3. 10% (w/v) Ammonium Persulphate (APS)

APS 0.1g

ddH2O 1mL

Ammonium persulphate was dissolved in ddH2O and the solution was stored at 4ºC for up to 2 weeks.

4. Blocking Buffer

Bovine serum albumin (BSA)

0.1g

Horse serum 1mL

10% Sodium azide45 2mg

PBS32 9mL

BSA was dissolved in PBS, the solution combined with horse serum and sodium azide and stored at 4ºC protected from light.

5. 10mg/mL Bromophenol Blue

Bromophenol blue 10mg

ddH2O 1mL

Bromophenol blue was dissolved in ddH2O and the solution was stored at room temperature.

6. 12mM Calcium Chloride

Calcium chloride 0.133g

ddH2O 100mL

Calcium chloride was dissolved in ddH2O and the solution was filtered through a 0.2µm filter, autoclaved, and stored at room temperature.

7. Cell Lysis Buffer (Subcellular

Fractionation)

1M Tris pH859 10μL

4M Sodium chloride46 2.5μL

2M Magnesium chloride27

1.5μL

NP40 5μL

Appendix 1

265

ddH2O 951μL

200mM PMSF31 5μL

40× Protease inhibitor cocktail37

25μL

Tris, sodium chloride, magnesium chloride, NP40 and ddH2O were combined in a 1.5mL tube and immediately before use, PMSF and protease inhibitors were added.

8. 50mM Chloroquine

Chloroquine 257mg

ddH2O 10mL

Chloroquine was dissolved in ddH2O in a laminar flow hood and the solution was stored protected from light at room temperature.

9. 20mg/mL Cyclopamine

Cyclopamine 20mg

100% Ethanol 1mL

Cyclopamine was dissolved in 100% ethanol and the solution was stored at -20ºC.

10. 1mM Cyclopamine

Cyclopamine (20mg/mL)9

2.06μL

100% Ethanol 97.94μL

Cyclopamine and ethanol were combined and the solution was stored at -20ºC.

11. Developer Solution

Solution A (1L)

Solution B (0.25L)

ddH2O 1.25L

Solution A and ddH2O were combined and then solution B added. Developer was stored at room temperature.

12. 10-2M DHT

5α-dihydrotestosterone (DHT)

0.0029g

100% Ethanol 1mL

DHT was dissolved in ethanol and the solution was stored at -20ºC. 10-

2M DHT was serially diluted in 100% ethanol as required and stored at -20ºC.

13. 2.72 kunitz units/µL DNase

DNase 1500 kunitz

units

ddH2O 551.5µL

DNase was dissolved in ddH2O and the solution stored at 4ºC.

14. 1kb Plus DNA Ladder™

1kb Plus DNA ladder™

50μL

6× DNA loading buffer15

166.7μL

Storage buffer49 783.3μL

1kb Plus DNA ladder™, 6× loading buffer and storage buffer were combined and the solution was stored in 1mL aliquots at -20ºC.

15. 6× DNA Loading Buffer

Sucrose 3.5g

0.1M EDTA18 5mL

Bromophenol blue 100μL

Appendix 1

266

(10mg/mL)5

Sucrose was dissolved in 0.1M EDTA, bromophenol blue was added, and the solution stored at room temperature.

16. 10mM dNTP Mix

dATP (100mM) 10μL

dTTP (100mM) 10μL

dCTP (100mM) 10μL

dGTP (100mM) 10μL

ddH2O 60μL

dATP, dTTP, dCTP, dGTP and ddH2O were combined and the solution was stored in 20µL aliquots at -20ºC.

17. Enhanced Chemiluminescence (ECL)

Solution A

Solution B

Equal volumes of solution A and solution B were combined as required. ECL was prepared immediately prior to use.

18. 0.5M EDTA pH8.0

EDTA 186.12g

Sodium hydroxide pellets

20g

ddH2O 1L

EDTA and sodium hydroxide pellets were dissolved in ~500mL ddH2O, the pH adjusted to 8.0 and the solution made up to 1L with ddH2O, autoclaved and stored at room temperature. 0.5M EDTA was diluted as required in ddH2O.

19. 70% / 75% / 95% Ethanol (EtOH)

95% 75% 70%

100% Ethanol

95mL 75mL 70mL

ddH2O 5mL 25mL 30mL

Ethanol and ddH2O were combined and the solution was stored at room temperature.

20. 10mg/mL Ethidium Bromide

Ethidium bromide 10mg

ddH2O 1mL

Ethidium bromide was dissolved in ddH2O and the solution was stored at room temperature protected from light.

21. Fixer Solution

Solution A (0.5L)

ddH2O 2L

Solution A was added to ddH2O and the solution shaken to combine. Fixer was stored at room temperature.

22. 4% (v/v) Formaldehyde

40% Formaldehyde 1mL

PBS32 9mL

Formaldehyde and PBS were combined and the solution was stored at room temperature.

23. 5mg/mL Hoechst 33342

Hoechst 33342 25mg

ddH2O 5mL

Hoechst 33342 was dissolved in ddH2O and the solution was stored

Appendix 1

267

in 100µL aliquots at -20ºC protected from light.

24. 1M Hydrochloric Acid (HCl)

10M HCl 10mL

ddH2O 90mL

HCl and ddH2O were combined and the solution was stored at room temperature.

25. 5mg/mL KO143

KO143 1mg

DMSO 200μL

KO143 was dissolved in DMSO and the solution was stored at -20ºC.

26. 1mM KO143

KO143 (5mg/mL)25 9.4µL

DMSO 990.6μL

KO143 was diluted in DMSO to obtain a working concentration of 1mM and the solution was stored at -20ºC.

27. 2M Magnesium Chloride

Magnesium chloride 1.9g

ddH2O 10mL

Magnesium chloride was dissolved in ddH2O and the solution stored at room temperature. 2M magnesium chloride was diluted as required in ddH2O, and for PBS with Ca2+ and Mg2+, the diluted solution was passed through a 0.2μm filter and autoclaved prior to use.

28. 10mM MG132

MG132 4.756g

100% Ethanol 1mL

MG132 was dissolved in ethanol and the solution was stored in 100μL aliquots at -20ºC.

29. Mounting Medium

Polyvinyl alcohol (PVA)

20g

1M Tris pH7.459 50mL

1M Sodium dihydrogen orthophosphate dihydrate47

As required

Glycerol 30mL

Chlorobutanol 100mg

ddH2O 75mL

To obtain Tris-PO4 pH7.4 buffer, Tris was titrated with sodium dihydrogen orthophosphate dihydrate. 5mL Tris-PO4 pH7.4 buffer, PVA and 75mL ddH2O were combined in a conical flask, the opening of the flask was covered with parafilm and a small depression was made in the centre of the film. The flask was incubated in a 60ºC waterbath with occasional swirling overnight or until all components were dissolved, then the solution was cooled to room temperature. Glycerol was added slowly and chlorobutanol was dissolved in the solution, which was stored at 4ºC overnight to disperse air bubbles. Mounting medium was stored in airtight containers (capped 5mL or 10mL syringes) at 4ºC.

Appendix 1

268

30. Nuclear Lysis Buffer (for Subcellular Fractionation)

1M Tris pH859 50μL

0.5M EDTA18 20μL

20% SDS42 50μL

ddH2O 850μL

200mM PMSF31 5μL

40× Protease inhibitor cocktail37

25μL

Tris, EDTA, SDS and ddH2O were combined on ice in a 1.5mL tube. PMSF and protease inhibitor cocktail were added immediately before use.

31. 200mM PMSF

PMSF 348.4mg

Isopropanol 10mL

PMSF was dissolved in isopropanol in a fume hood and the solution was stored in 1mL aliquots at -20ºC.

32. Phosphate Buffered Saline (PBS)

Sodium chloride 8g

Potassium chloride 0.2g

Disodium hydrogen orthophosphate

1.44g

Potassium dihydrogen orthophosphate

0.44g

ddH2O 1L

Sodium chloride, potassium chloride, disodium hydrogen orthophosphate and potassium dihydrogen orthophosphate were dissolved in ~800mL ddH2O. The pH was adjusted to 7.2 or 7.4 using 1M sodium hydroxide or 1M hydrochloric acid, the volume was

made up to 1L with ddH2O, and the solution was autoclaved then stored at room temperature.

33. PBS with Ca2+ and Mg2+

12mM Calcium chloride6

50mL

0.01M Magnesium chloride27

50mL

PBS32 400mL

Calcium chloride and magnesium chloride were added to PBS to obtain a final concentration of 0.133g/L calcium chloride and 0.1g/L magnesium chloride. The solution was stored at room temperature.

34. PBS/1% BSA

BSA 0.05g

PBS32 5mL

BSA was dissolved in PBS and the solution was stored at 4ºC.

35. 5× PCR Buffer

Taq 10× PCR buffer (supplied with Taq DNA polymerase)

5mL

10mM dNTP16 500μL

ddH2O 4.5mL

Taq 10× PCR buffer, dNTP and ddH2O were combined and the solution was stored in 1mL aliquots at -20ºC.

Appendix 1

269

36. 300µM Phalloidin Red

Phalloidin Red 0.1mg

DMSO 255.3µL

Phalloidin Red was dissolved in DMSO and the solution was stored in 50µL aliquots at -20ºC.

37. 40× Protease Inhibitor Cocktail

Protease inhibitor cocktail tablets

4

ddH2O 1mL

Protease inhibitor cocktail tablets were dissolved in ddH2O and the solution was stored in 100µL aliquots at -20ºC.

38. 1mg/mL Rhodamine 123

Rhodamine 123 5mg

100% Ethanol 5mL

Rhodamine 123 was dissolved in ethanol and the solution was stored protected from light in 1mL aliquots at -20ºC.

39. RPMI 1640/PS

RPMI 1640 (sachet) 10.4g

Sodium hydrogen carbonate

2g

10,000U/mL Penicillin/10,000μg/mL streptomycin (PS)

10mL

ddH2O 1L

RPMI 1640 powder and sodium hydrogen carbonate were dissolved in ddH2O and the solution was sterilised using a 0.2µm filter in a laminar flow hood. RPMI 1640 and penicillin/streptomycin (PS) were combined and stored at 4ºC.

40. RPMI/5%CSS/PS

RPMI/PS39 190mL

Charcoal-treated foetal calf serum (CSS)

10mL

CSS was added to RPMI/PS and the solution was stored at 4ºC.

41. RPMI/10% (/2%) FCS/PS

RPMI/ 10%FCS

RPMI/ 2%FCS

RPMI/PS39 450mL 196mL

Foetal calf serum (FCS)

50mL 4mL

FCS was added to RPMI/PS and the solution was stored at 4ºC.

42. 20% (w/v) SDS

SDS 20g

ddH2O 100mL

SDS was dissolved in ddH2O (final volume 100mL) and the solution was stored at room temperature. During manipulation of SDS powder, protective gloves and a face mask were worn.

43. 12% Separating Gel

ddH2O 6.53mL

1M Tris pH8.859 3.75mL

40% Acrylamide (37.5:1)

4.50mL

20% SDS42 75μL

10% APS3 75μL

TEMED 7.5μL

Appendix 1

270

ddH2O, Tris, acrylamide and SDS were combined and immediately prior to use, APS and TEMED were added and the solution inverted to mix.

44. 3M Sodium Acetate pH4.6

Sodium acetate 49.2g

ddH2O 200mL

Sodium acetate was dissolved in ~160mL ddH2O, pH was adjusted to 4.6 with 1M sodium hydroxide or 1M hydrochloric acid, and the solution was autoclaved then stored at room temperature.

45. 10% (w/v) Sodium Azide

Sodium azide 0.1g

ddH2O 1mL

Sodium azide was dissolved in ddH2O and the solution was stored at 4ºC.

46. 10M Sodium Chloride

Sodium chloride 5.84mg

ddH2O 10mL

Sodium chloride was dissolved in ddH2O, the solution was autoclaved and stored at room temperature. 10M sodium chloride was diluted as required in ddH2O.

47. 1M Sodium Dihydrogen

Orthophosphate Dihydrate

Sodium dihydrogen orthophosphate dihydrate

156g

ddH2O 1L

Sodium dihydrogen orthophosphate dihydrate was dissolved in ddH2O to

a final volume of 1L and the solution autoclaved then stored at room temperature.

48. 4% Stacking Gel

ddH2O 7.70mL


40% Acrylamide (37.5:1)

1mL

20% SDS42 50μL

10% APS3 50μL

TEMED 10μL

ddH2O, Tris, acrylamide and SDS were combined and immediately prior to use, APS and TEMED were added and the solution inverted to mix.

49. Storage Buffer (for 1kb Plus DNA Ladder™)

1M Tris pH7.559 10μL

0.5M EDTA pH818 20μL

4M Sodium chloride46 125μL

ddH2O 9.845mL

Tris, EDTA, sodium chloride and ddH2O were combined and the solution was stored at room temperature.

50. 20% (w/v) Sucrose

Sucrose 4g

ddH2O 20mL

Sucrose was dissolved in ddH2O to a final volume of 20mL and the solution was stored at room temperature.

Appendix 1

271

51. 50× TAE Buffer

Tris 242g

Glacial acetic acid 57.1mL

0.5M EDTA pH818 100mL

ddH2O 1L

Tris was dissolved in ~600mL ddH2O, the glacial acetic acid and EDTA were added, and the solution was made up to 1L with ddH2O. 50× TAE buffer was autoclaved and stored at room temperature.

52. 1× TAE Buffer

50× TAE buffer51 100mL

ddH2O 4900mL

50× TAE buffer and ddH2O were combined and the solution was stored at room temperature.

53. 1% (w/v) Toluidine Blue O

Toluidine blue O 1g

Borax 1g

ddH2O 100mL

Borax was dissolved in ~80mL ddH2O and then Toluidine Blue O was added. The solution was adjusted to 100mL and stored at room temperature. The solution was filter sterilised on the day of use.

54. Tris-Buffered Saline (TBS)

4M Sodium chloride46 18.75mL

1M Tris pH7.459 25mL

ddH2O 500mL

Sodium chloride, Tris and ddH2O were combined and the solution was stored at room temperature.

55. TBST

TBS54 500mL

Tween-20 1mL

TBS and Tween-20 were combined and the solution was stored at room temperature.

56. TBS/3% Blotto

TBS54 10mL

Skim milk powder 0.3g

Skim milk powder was dissolved in TBS and the solution constantly agitated on a horizontal shaker at room temperature. TBS/3% blotto was prepared on the day of use.

57. TBST/1% Blotto

TBST55 10mL

Skim milk powder 0.1g

Skim milk powder was dissolved in TBST and the solution constantly agitated on a horizontal shaker at room temperature. TBST/1% blotto was prepared on the day of use.

58. Transfer Buffer

Glycine 14.4g

Tris 3.03g

ddH2O 800mL

Methanol 200mL

Glycine and Tris were dissolved to a final volume of 800mL ddH2O and the solution was made up to 1L with methanol. Transfer buffer was prepared on the day of use and chilled at -20ºC prior to use.

Appendix 1

272

59. 1M Tris

Tris 121.1g

ddH2O 1L

Tris was dissolved in ~800mL ddH2O, the pH adjusted to 6.8, 7.4, 8.0 or 8.8 with 1M sodium hydroxide or 1M hydrochloric acid as required, and the solution made up to 1L with ddH2O. The solution was autoclaved, then stored at room temperature.

60. 10% (v/v) Triton-X 100

Triton-X 100 10mL

PBS32 100mL

Triton-X 100 was dissolved in PBS and the solution was stored at 4ºC.

61. 0.2% (v/v) Triton-X 100

Triton-X 100 (10% (v/v))60

200μL

PBS32 9.8mL

Triton-X 100 and PBS were combined, mixed by inversion, and the solution was stored at 4ºC.

62. 10× Western Loading Buffer

Glycerol 12.5mL


20% SDS42 2.5mL

2-Mercaptoethanol (2-ME)

2.5g

Bromophenol blue (10mg/mL)5

0.25mL

ddH2O 25mL

Glycerol, Tris, SDS, 2-ME, bromophenol blue and ddH2O were combined in a fume hood and the

solution stored as 1mL aliquots at -20ºC.

63. 10× Western Running Buffer

Tris 60g

Glycine 288g

SDS 20g

ddH2O 2L

Tris and glycine were dissolved in ~1.8L ddH2O, SDS was added, and the volume made up to 2L with ddH2O. The solution was stored at room temperature and adjusted to 1× with ddH2O as required.

64. Whole Cell Lysis Buffer

20% Sucrose50 2.5mL

20% SDS42 0.5mL


2-Mercaptoethanol (2-ME)

0.25mL

ddH2O 1.5mL

Sucrose, SDS, Tris, 2-ME and ddH2O were combined in a fume hood and the solution was stored protected from light in a fume hood for up to 6 weeks.

A

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APP

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273

http://www.sabiosciences.com/genetable.php?pcatn=PAHS-090Z

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CT30

, HEL

113

VPS

13A

V

acuo

lar p

rote

in so

rting

13

hom

olog

ue A

C

HA

C, C

HO

REI

N

WN

T11

Win

gles

s-ty

pe M

MTV

inte

grat

ion

site

fam

ily, m

embe

r 11

HW

NT1

1 W

NT5

A

Win

gles

s-ty

pe M

MTV

inte

grat

ion

site

fam

ily, m

embe

r 5A

hW

NT5

A

WN

T5B

Win

gles

s-ty

pe M

MTV

inte

grat

ion

site

fam

ily, m

embe

r 5B

-

ZEB

1 Zi

nc fi

nger

E-b

ox b

indi

ng h

omeo

box

1 A

REB

6, B

ZP, D

ELTA

EF1,

FEC

D6,

NIL

2A, P

PCD

3, T

CF8

,

275

A

ppen

dix

2

ZFH

EP, Z

FHX

1A

ZEB

2 Zi

nc fi

nger

E-b

ox b

indi

ng h

omeo

box

2 H

SPC

082,

SIP

-1, S

IP1,

SM

AD

IP1,

ZFH

X1B

A

CTB

B

eta-

actin

B

RW

S1, P

S1TP

5BP1

B

2M

Bet

a-2-

mic

rogl

obul

in

- G

APD

H

Gly

cera

ldeh

yde-

3-ph

osph

ate

dehy

drog

enas

e G

3PD

, GA

PD

HPR

T1

Hyp

oxan

thin

e ph

osph

orib

osyl

trans

fera

se 1

H

GPR

T, H

PRT

RPL

P0

Rib

osom

al p

rote

in, l

arge

, P0

L10E

, LP0

, P0,

PR

LP0,

RPP

0 H

GD

C

Hum

an g

enom

ic D

NA

con

tam

inat

ion

HIG

X1A

R

TC

Rev

erse

tran

scrip

tion

cont

rol

RTC

R

TC

Rev

erse

tran

scrip

tion

cont

rol

RTC

R

TC

Rev

erse

tran

scrip

tion

cont

rol

RTC

PP

C

Posi

tive

PCR

con

trol

PPC

PP

C

Posi

tive

PCR

con

trol

PPC

PP

C

Posi

tive

PCR

con

trol

PPC

276

Appendix 3

Appendix 3

278

(C)

(D)

Amplification and melt curves from analysis of the RT2 Profiler Human EMT PCR Arrays. Expression of 84 EMT-associated genes in the PCR arrays were evaluated by RT-qPCR in (A) & (B) MCF-7 and (C) & (D) T-47D cells following treatment of the cells for 24 hours with 10-8M DHT and/or 2µM cyclopamine.

A

ppen

dix

4

APP

END

IX 4

R

T2 PR

OFI

LER

EM

T PC

R A

RR

AY

FO

LD R

EGU

LATI

ON

DA

TA (M

CF-

7)

Reg

ulat

ion

(com

pari

ng to

0.1

%(v

/v) e

than

ol c

ontr

ol g

roup

) 10

-8M

DH

T 2μ

M C

yclo

pam

ine

10-8

M D

HT

+ 2

μM C

yclo

pam

ine

Fo

ld R

egul

atio

n C

omm

ents

Fo

ld R

egul

atio

n C

omm

ents

Fo

ld R

egul

atio

n C

omm

ents

AH

NA

K

1.20

58

OK

AY

-1

.045

4 O

KA

Y

1.21

76

OK

AY

A

KT1

-1

.117

3 O

KA

Y

-1.0

747

OK

AY

1.

031

OK

AY

B

MP1

1.

0792

O

KA

Y

1.02

53

OK

AY

1.

2346

O

KA

Y

BM

P2

-3.3

636

B

-1.1

439

B

-2.5

071

B

BM

P7

-1.5

801

OK

AY

1.

0042

O

KA

Y

-1.1

696

OK

AY

C

ALD

1 -1

.705

3 B

-1

.937

2 B

-6

.302

8 B

C

AM

K2N

1 -1

3682

.080

5 A

-1

.002

8 O

KA

Y

1.06

73

OK

AY

C

AV

2 1.

0353

O

KA

Y

-1.2

092

OK

AY

-1

.400

6 O

KA

Y

CD

H1

1.18

1 O

KA

Y

1.10

65

OK

AY

1.

168

OK

AY

C

DH

2 -1

.222

6 B

1.

4399

B

1.

2781

B

C

OL1

A2

1.00

7 C

-1

.016

8 C

1.

0822

C

C

OL3

A1

5.85

63

A

3.42

48

A

5.29

27

A

CO

L5A

2 1.

1487

O

KA

Y

-1.0

747

OK

AY

-1

.032

4 O

KA

Y

CTN

NB

1 -1

.328

7 O

KA

Y

-1.3

986

OK

AY

-1

.62

OK

AY

D

SC2

1.14

87

OK

AY

-1

.097

3 O

KA

Y

-1.8

1 O

KA

Y

DSP

2.

9485

O

KA

Y

2.72

45

OK

AY

2.

8759

O

KA

Y

EGFR

-1

.164

7 O

KA

Y

1.14

55

OK

AY

1.

0454

O

KA

Y

ERB

B3

1.12

51

OK

AY

1.

0253

O

KA

Y

1.07

47

OK

AY

ES

R1

-1.1

096

OK

AY

-1

.045

4 O

KA

Y

1.05

26

OK

AY

F1

1R

1.09

43

OK

AY

-1

.519

9 O

KA

Y

1.06

73

OK

AY

FG

FBP1

1.

007

C

-1.0

168

C

1.08

22

C

FN1

1.27

46

OK

AY

1.

1859

O

KA

Y

1.27

81

OK

AY

279

A

ppen

dix

4

FOX

C2

1.00

7 C

2.

307

B

3.82

11

B

FZD

7 2.

3457

O

KA

Y

2.61

35

OK

AY

1.

9507

O

KA

Y

GN

G11

1.

007

C

-1.0

168

C

1.08

22

C

GSC

-1

.094

3 O

KA

Y

-1.1

925

OK

AY

-1

.532

6 O

KA

Y

GSK

3B

1.12

51

OK

AY

1.

1219

O

KA

Y

1.19

25

OK

AY

IG

FBP4

1.

3195

O

KA

Y

1.08

37

OK

AY

-1

.011

2 O

KA

Y

IL1R

N

1.39

47

OK

AY

1.

4006

O

KA

Y

1.30

5 O

KA

Y

ILK

-1

.057

O

KA

Y

1.01

12

OK

AY

-1

.068

8 O

KA

Y

ITG

A5

-2.3

295

OK

AY

1.

325

OK

AY

-1

.822

6 O

KA

Y

ITG

AV

1.

3379

O

KA

Y

1.11

42

OK

AY

1.

226

OK

AY

IT

GB

1 1.

007

OK

AY

-1

.052

6 O

KA

Y

-1.0

614

OK

AY

JA

G1

1.26

58

OK

AY

-1

.045

4 O

KA

Y

1.06

O

KA

Y

KRT

14

1.44

39

B

-1.4

181

B

1.36

04

B

KRT

19

1.59

11

OK

AY

1.

1777

O

KA

Y

1.21

76

OK

AY

K

RT7

-1.6

702

B

-2.2

408

B

1.09

73

B

MA

P1B

2.

3784

O

KA

Y

1.25

35

OK

AY

2.

3522

O

KA

Y

MM

P2

1.00

7 C

-1

.016

8 C

1.

0822

C

M

MP3

1.

007

C

-1.0

168

C

1.08

22

C

MM

P9

2.21

91

OK

AY

2.

6684

O

KA

Y

2.83

63

OK

AY

M

SN

1.00

7 C

1.

7005

B

1.

9106

B

M

ST1R

-1

.222

6 O

KA

Y

-1.2

346

OK

AY

-1

.106

5 O

KA

Y

NO

DA

L -1

.057

B

-2

.609

9 B

-1

.169

6 B

N

OTC

H1

1.17

28

OK

AY

1.

0324

O

KA

Y

-1.1

065

OK

AY

N

UD

T13

1.44

39

OK

AY

1.

0112

O

KA

Y

1.12

82

OK

AY

O

CLN

1.

2834

O

KA

Y

1.17

77

OK

AY

1.

1204

O

KA

Y

PDG

FRB

-1

.394

7 B

-1

.428

B

-1

.297

7 B

PL

EK2

-1.2

142

OK

AY

-1

.045

4 O

KA

Y

-1.0

253

OK

AY

PP

PDE2

-1

.156

7 O

KA

Y

-1.0

31

OK

AY

-1

.018

2 O

KA

Y

PTK

2 -1

.101

9 O

KA

Y

-1.0

454

OK

AY

1.

0381

O

KA

Y

PTP4

A1

1.58

01

OK

AY

1.

4804

O

KA

Y

1.53

05

OK

AY

R

AC

1 1.

1251

O

KA

Y

1.07

62

OK

AY

1.

0747

O

KA

Y

RG

S2

-1.6

245

B

1.44

99

B

2.43

51

B

280

A

ppen

dix

4

SER

PIN

E1

1.64

72

OK

AY

1.

5115

O

KA

Y

1.26

05

OK

AY

SI

P1

-1.0

57

OK

AY

1.

0688

O

KA

Y

1.06

O

KA

Y

SMA

D2

1.07

92

OK

AY

1.

0468

O

KA

Y

-1.0

253

OK

AY

SN

AI1

-1

.181

B

-1

.016

8 B

-1

.712

4 B

SN

AI2

8.

3977

O

KA

Y

-1.0

673

OK

AY

5.

7918

O

KA

Y

SNA

I3

-1.6

702

OK

AY

-2

.240

8 O

KA

Y

-1.3

623

OK

AY

SO

X10

1.

007

C

-1.0

168

C

1.82

01

B

SPA

RC

-1

.972

5 B

1.

2799

A

-1

.262

3 B

SP

P1

-1.4

743

B

-1.5

094

B

-1.3

717

B

STA

T3

1.11

73

OK

AY

1.

0989

O

KA

Y

1.17

61

OK

AY

ST

EAP1

-1

.181

B

1.

8226

B

-1

.098

9 B

TC

F3

-1.2

834

OK

AY

1.

0042

O

KA

Y

-1.0

042

OK

AY

TC

F4

1.00

7 C

-1

.016

8 C

1.

1282

B

TF

PI2

2.47

94

OK

AY

1.

0112

O

KA

Y

2.11

99

OK

AY

TG

FB1

-1.0

792

OK

AY

1.

0112

O

KA

Y

1.08

98

OK

AY

TG

FB2

1.00

7 O

KA

Y

1.31

59

OK

AY

1.

0168

O

KA

Y

TGFB

3 -1

.189

2 O

KA

Y

-1.0

31

OK

AY

-1

.244

9 O

KA

Y

TIM

P1

1.22

26

OK

AY

1.

1696

O

KA

Y

-1.1

777

OK

AY

TM

EFF1

1.

0718

O

KA

Y

1.24

49

OK

AY

1.

2092

O

KA

Y

TMEM

132A

-1

.248

3 O

KA

Y

-1.1

127

OK

AY

1.

0098

O

KA

Y

TSPA

N13

1.

181

OK

AY

1.

0762

O

KA

Y

1.26

05

OK

AY

TW

IST1

1.

5692

B

-1

.002

8 B

2.

0056

B

V

CA

N

-1.5

911

B

-1.5

411

B

-1.4

804

B

VIM

-1

.101

9 O

KA

Y

1.15

35

OK

AY

-1

.381

3 O

KA

Y

VPS

13A

-1

.086

7 O

KA

Y

-1.0

6 O

KA

Y

1.04

54

OK

AY

W

NT1

1 1.

007

C

-1.0

168

C

1.08

22

C

WN

T5A

-1

.042

5 B

-1

.120

4 B

1.

8974

B

W

NT5

B 2.

2038

A

1.

5867

A

2.

0619

A

ZE

B1

1.09

43

B

1.14

55

B

-1.3

813

B

ZEB

2 1.

1728

O

KA

Y

-1.1

519

OK

AY

-1

.967

A

A

CTB

1.

014

OK

AY

1.

0541

O

KA

Y

1.11

27

OK

AY

B

2M

-1.0

943

OK

AY

-1

.002

8 O

KA

Y

-1.1

535

OK

AY

281

A

ppen

dix

4

GA

PDH

1.

007

OK

AY

1.

0042

O

KA

Y

-1.1

065

OK

AY

H

PRT1

-1

.042

5 O

KA

Y

-1.0

381

OK

AY

1.

1127

O

KA

Y

RPL

P0

1.11

73

OK

AY

-1

.016

8 O

KA

Y

1.03

1 O

KA

Y

HG

DC

1.

007

C

-1.0

168

C

1.08

22

C

RTC

-1

.292

4 O

KA

Y

-1.1

519

OK

AY

1.

031

OK

AY

R

TC

-1.0

497

OK

AY

-1

.082

2 O

KA

Y

1.09

73

OK

AY

R

TC

-1.0

497

OK

AY

-1

.184

3 O

KA

Y

-1.0

541

OK

AY

PP

C

1 O

KA

Y

-1.0

6 O

KA

Y

-1.0

468

OK

AY

PP

C

-1.0

792

OK

AY

-1

.097

3 O

KA

Y

-1.1

142

OK

AY

PP

C

1.02

81

OK

AY

-1

.002

8 O

KA

Y

-1.0

688

OK

AY

Com

men

ts:

A: A

vera

ge th

resh

old

cycl

e is

rela

tivel

y hi

gh (>

30) i

n ei

ther

the

cont

rol o

r the

test

sam

ple,

and

is re

ason

ably

low

in th

e ot

her s

ampl

e (<

30).

Th

ese

data

mea

n th

at g

ene

expr

essi

on is

rela

tivel

y lo

w in

one

sam

ple

and

reas

onab

ly d

etec

ted

in th

e ot

her s

ampl

e su

gges

ting

that

the

actu

al

fold

-cha

nge

valu

e is

at l

east

as la

rge

as th

e ca

lcul

ated

and

repo

rted

fold

-cha

nge

resu

lt.

This

fol

d-ch

ange

may

als

o ha

ve g

reat

er v

aria

tions

if

p-va

lue

>0.0

5; t

here

fore

, it

is i

mpo

rtant

to

have

a s

uffic

ient

num

ber

of b

iolo

gica

l re

plic

ates

to v

alid

ate

the

resu

lt fo

r thi

s gen

e.

B: A

vera

ge th

resh

old

cycl

e is

rela

tivel

y hi

gh (>

30),

mea

ning

that

its

rela

tive

expr

essi

on le

vel i

s lo

w, i

n bo

th c

ontro

l and

test

sam

ples

, and

the

p-va

lue

for t

he fo

ld-c

hang

e is

eith

er u

nava

ilabl

e or

rela

tivel

y hi

gh (p

>0.0

5).

This

fold

-cha

nge

may

als

o ha

ve g

reat

er v

aria

tions

; the

refo

re, i

t is i

mpo

rtant

to h

ave

a su

ffic

ient

num

ber o

f bio

logi

cal r

eplic

ates

to v

alid

ate

the

resu

lt fo

r thi

s gen

e.

C: A

vera

ge th

resh

old

cycl

e is

eith

er n

ot d

eter

min

ed o

r gr

eate

r th

an th

e de

fined

cut

-off

val

ue (

defa

ult 3

5), i

n bo

th s

ampl

es m

eani

ng th

at it

s ex

pres

sion

was

und

etec

ted,

mak

ing

this

fold

-cha

nge

resu

lt er

rone

ous a

nd u

n-in

terp

reta

ble.

282

A

ppen

dix

5

APP

END

IX 5

R

T2 PR

OFI

LER

EM

T PC

R A

RR

AY

FO

LD R

EGU

LATI

ON

DA

TA (T

-47D

)

Reg

ulat

ion

(com

pari

ng to

0.1

%(v

/v) e

than

ol c

ontr

ol g

roup

) 10

-8M

DH

T 2μ

M C

yclo

pam

ine

10-8

M D

HT

+ 2

μM C

yclo

pam

ine

Fo

ld R

egul

atio

n C

omm

ents

Fo

ld R

egul

atio

n C

omm

ents

Fo

ld R

egul

atio

n C

omm

ents

AH

NA

K

-1.3

775

OK

AY

-1

.802

5 O

KA

Y

-1.3

832

OK

AY

AK

T1

-1.4

359

OK

AY

-1

.602

1 O

KA

Y

-2.3

102

OK

AY

BM

P1

-1.3

031

OK

AY

-1

.547

6 O

KA

Y

-1.2

906

OK

AY

BM

P2

-1.4

763

C

-2.1

14

C

-1.3

641

C

B

MP7

-2

.332

7 A

-1

.257

O

KA

Y

-2.2

008

A

C

ALD

1 1.

4123

O

KA

Y

-1.4

142

OK

AY

1.

2243

O

KA

Y

C

AM

K2N

1 -4

.146

8 O

KA

Y

-1.1

975

OK

AY

-1

.364

1 O

KA

Y

C

AV

2 -1

.476

3 C

-2

.114

C

-1

.364

1 C

CD

H1

-1.3

398

OK

AY

-1

.484

5 O

KA

Y

-1.2

995

OK

AY

CD

H2

-2.5

527

B

-1.4

142

B

1.75

56

B

C

OL1

A2

1.39

28

B

-2.3

295

B

-1.5

032

B

C

OL3

A1

-1.4

763

C

-1.1

975

B

-1.3

641

C

C

OL5

A2

-1.7

195

OK

AY

-1

.366

O

KA

Y

-1.5

562

OK

AY

CTN

NB

1 -1

.539

O

KA

Y

-1.9

453

OK

AY

-1

.956

1 O

KA

Y

D

SC2

-1.5

933

OK

AY

-1

.624

5 O

KA

Y

-1.7

148

OK

AY

DSP

-2

.300

6 O

KA

Y

-1.5

911

OK

AY

-2

.111

1 O

KA

Y

EG

FR

1.08

52

OK

AY

-1

.375

5 O

KA

Y

1.01

54

OK

AY

ERB

B3

-1.4

763

OK

AY

-1

.515

7 O

KA

Y

-1.3

268

OK

AY

ESR

1 -1

.855

7 O

KA

Y

-1.4

641

OK

AY

-1

.492

8 O

KA

Y

F1

1R

-1.3

213

OK

AY

-1

.536

9 O

KA

Y

-1.2

728

OK

AY

FGFB

P1

-1.4

661

B

-2.4

794

B

-2.2

161

B

FN

1 -1

.672

5 O

KA

Y

-1.7

291

OK

AY

-1

.679

5 O

KA

Y

283

A

ppen

dix

5

FOX

C2

-1.4

763

C

-2.1

14

C

-1.3

641

C

FZ

D7

-1.7

925

OK

AY

-2

.114

O

KA

Y

-2.1

258

OK

AY

GN

G11

1.

0267

O

KA

Y

-1.2

746

OK

AY

1.

3122

O

KA

Y

G

SC

-1.0

585

OK

AY

-1

.301

3 O

KA

Y

-1.2

466

OK

AY

GSK

3B

-1.3

585

OK

AY

-1

.292

4 O

KA

Y

-1.3

177

OK

AY

IGFB

P4

-1.8

429

OK

AY

-1

.945

3 O

KA

Y

-1.7

63

OK

AY

IL1R

N

-2.8

324

B

1.31

95

B

-4.9

52

B

IL

K

-1.3

122

OK

AY

-1

.424

1 O

KA

Y

-1.3

547

OK

AY

ITG

A5

-5.1

766

OK

AY

-1

.790

1 O

KA

Y

-2.8

245

OK

AY

ITG

AV

1.

108

OK

AY

-1

.484

5 O

KA

Y

1.05

85

OK

AY

ITG

B1

-1.4

459

OK

AY

-1

.474

3 O

KA

Y

-1.5

032

OK

AY

JAG

1 -1

.215

9 O

KA

Y

-1.5

157

OK

AY

-1

.179

4 O

KA

Y

K

RT14

-1

.321

3 B

1.

0281

B

1.

456

B

K

RT19

2.

7664

O

KA

Y

1.80

25

OK

AY

3.

0994

O

KA

Y

K

RT7

2.06

77

OK

AY

2

OK

AY

2.

0878

O

KA

Y

M

AP1

B

-1.1

583

OK

AY

-2

.496

7 O

KA

Y

1.00

14

OK

AY

MM

P2

-1.4

763

C

-2.1

14

C

-1.3

641

C

M

MP3

-1

.476

3 C

-1

.741

1 B

-1

.364

1 C

MM

P9

-2.6

796

OK

AY

-1

.879

O

KA

Y

-2.4

083

OK

AY

MSN

-1

.476

3 C

-1

.635

8 B

1.

0295

B

MST

1R

-1.7

076

OK

AY

-1

.958

8 O

KA

Y

-1.8

378

OK

AY

NO

DA

L -1

.539

O

KA

Y

-1.4

54

OK

AY

-1

.775

2 A

NO

TCH

1 -1

.695

8 O

KA

Y

-1.4

948

OK

AY

-1

.644

9 O

KA

Y

N

UD

T13

-1.3

679

OK

AY

-1

.580

1 O

KA

Y

-1.3

177

OK

AY

OC

LN

-1.7

315

OK

AY

-2

.828

4 O

KA

Y

-1.6

223

OK

AY

PDG

FRB

-1

.476

3 C

-2

.114

C

-1

.364

1 C

PLEK

2 -2

.606

3 O

KA

Y

-1.7

777

OK

AY

-2

.510

5 O

KA

Y

PP

PDE2

-1

.241

4 O

KA

Y

-1.3

947

OK

AY

-1

.163

1 O

KA

Y

PT

K2

-1.4

969

OK

AY

-1

.494

8 O

KA

Y

-1.4

32

OK

AY

PTP4

A1

-1.2

852

OK

AY

-1

.239

7 O

KA

Y

-1.3

454

OK

AY

RA

C1

-1.2

852

OK

AY

-1

.337

9 O

KA

Y

-1.2

553

OK

AY

RG

S2

-1.0

439

B

-1.3

566

B

-1.9

159

B

284

A

ppen

dix

5

SER

PIN

E1

-8.1

794

B

-16.

2234

B

-2

.025

1 B

SIP1

-1

.312

2 O

KA

Y

-1.4

142

OK

AY

-1

.354

7 O

KA

Y

SM

AD

2 -1

.517

8 O

KA

Y

-1.4

743

OK

AY

-1

.422

1 O

KA

Y

SN

AI1

-3

.142

7 B

-1

.753

2 B

-3

.453

4 B

SNA

I2

-1.4

763

C

-2.1

14

C

-1.3

086

B

SN

AI3

-1

.426

O

KA

Y

-1.7

291

OK

AY

-1

.622

3 O

KA

Y

SO

X10

-4

.353

B

-3

.890

6 B

-1

.656

3 B

SPA

RC

-1

.111

1 B

-1

.840

4 B

-1

.691

1 B

SPP1

-1

.476

3 C

-2

.114

C

-1

.364

1 C

STA

T3

-1.1

991

OK

AY

-1

.310

4 O

KA

Y

-1.1

876

OK

AY

STEA

P1

4.71

74

OK

AY

-1

.109

6 O

KA

Y

5.39

64

OK

AY

TCF3

-1

.267

5 O

KA

Y

-1.2

226

OK

AY

-1

.364

1 O

KA

Y

TC

F4

-1.2

075

OK

AY

1.

057

OK

AY

-1

.588

9 O

KA

Y

TF

PI2

-2.9

12

B

-1.0

644

B

1.06

58

B

TG

FB1

-4.1

182

OK

AY

-2

.620

8 O

KA

Y

-3.1

34

OK

AY

TGFB

2 1.

2906

O

KA

Y

1.27

46

OK

AY

1.

0439

O

KA

Y

TG

FB3

-4.3

832

OK

AY

-1

.424

1 O

KA

Y

-1.7

387

OK

AY

TIM

P1

-2.2

222

OK

AY

-1

.853

2 O

KA

Y

-2.1

406

OK

AY

TMEF

F1

1.04

83

OK

AY

-1

.049

7 O

KA

Y

-1.1

876

OK

AY

TMEM

132A

-1

.224

3 O

KA

Y

-1.7

532

OK

AY

-1

.179

4 O

KA

Y

TS

PAN

13

-1.3

305

OK

AY

-1

.310

4 O

KA

Y

-1.2

816

OK

AY

TWIS

T1

-2.4

829

OK

AY

-1

.356

6 O

KA

Y

-1.9

972

OK

AY

VC

AN

-4

.146

8 O

KA

Y

-1.4

241

OK

AY

-2

.883

9 O

KA

Y

V

IM

-1.6

725

OK

AY

-1

.827

7 O

KA

Y

-2.0

111

OK

AY

VPS

13A

-1

.387

O

KA

Y

-1.3

947

OK

AY

-1

.336

1 O

KA

Y

W

NT1

1 -1

.339

8 B

1.

0353

B

-1

.545

4 B

WN

T5A

-1

.312

2 B

-1

.283

4 B

1.

1583

B

WN

T5B

-2.0

028

B

-1.4

743

B

1.11

11

B

ZE

B1

-1.4

763

C

1.15

67

B

1.47

63

B

ZE

B2

1.16

31

B

-3.5

064

B

1.26

75

B

A

CTB

-1

.232

9 O

KA

Y

-1.3

104

OK

AY

-1

.238

O

KA

Y

B

2M

1.07

03

OK

AY

1.

0792

O

KA

Y

1.11

11

OK

AY

285

A

ppen

dix

5

GA

PDH

2.

0534

O

KA

Y

1.89

21

OK

AY

2.

0591

O

KA

Y

H

PRT1

-1

.330

5 O

KA

Y

-1.1

096

OK

AY

-1

.462

1 O

KA

Y

R

PLP0

-1

.339

8 O

KA

Y

-1.4

044

OK

AY

-1

.264

O

KA

Y

H

GD

C

-1.4

763

C

-2.1

14

C

-1.3

641

C

R

TC

-1.5

073

OK

AY

-2

.099

4 O

KA

Y

-1.3

361

OK

AY

RTC

-1

.276

3 O

KA

Y

-1.8

15

OK

AY

-1

.187

6 O

KA

Y

R

TC

-1.3

585

OK

AY

-2

.128

7 O

KA

Y

-1.3

547

OK

AY

PPC

-1

.445

9 O

KA

Y

-2.0

705

OK

AY

-1

.432

O

KA

Y

PP

C

-1.3

967

OK

AY

-1

.931

9 O

KA

Y

-1.2

38

OK

AY

PPC

-2

.284

7 O

KA

Y

-1.9

588

OK

AY

-1

.255

3 O

KA

Y

C

omm

ents

: A

: Ave

rage

thre

shol

d cy

cle

is re

lativ

ely

high

(>30

) in

eith

er th

e co

ntro

l or t

he te

st sa

mpl

e, a

nd is

reas

onab

ly lo

w in

the

othe

r sam

ple

(<30

).

Th

ese

data

mea

n th

at g

ene

expr

essi

on is

rel

ativ

ely

low

in o

ne s

ampl

e an

d re

ason

ably

det

ecte

d in

the

othe

r sa

mpl

e su

gges

ting

that

the

actu

al

fold

-cha

nge

valu

e is

at l

east

as la

rge

as th

e ca

lcul

ated

and

repo

rted

fold

-cha

nge

resu

lt.

This

fold

-cha

nge

may

als

o ha

ve g

reat

er v

aria

tions

if p

-val

ue >

0.05

; the

refo

re, i

t is i

mpo

rtant

to h

ave

a su

ffic

ient

num

ber o

f bio

logi

cal r

eplic

ates

to

val

idat

e th

e re

sult

for t

his g

ene.

B

: Ave

rage

thre

shol

d cy

cle

is re

lativ

ely

high

(>30

), m

eani

ng th

at it

s rel

ativ

e ex

pres

sion

leve

l is l

ow, i

n bo

th c

ontro

l and

test

sam

ples

, and

the

p-va

lue

for t

he fo

ld-c

hang

e is

eith

er u

nava

ilabl

e or

rela

tivel

y hi

gh (p

>0.0

5).

This

fold

-cha

nge

may

als

o ha

ve g

reat

er v

aria

tions

; the

refo

re, i

t is

impo

rtant

to h

ave

a su

ffic

ient

num

ber o

f bio

logi

cal r

eplic

ates

to v

alid

ate

the

resu

lt fo

r thi

s gen

e.

C: A

vera

ge th

resh

old

cycl

e is

eith

er n

ot d

eter

min

ed o

r gr

eate

r th

an th

e de

fined

cut

-off

val

ue (

defa

ult 3

5), i

n bo

th s

ampl

es m

eani

ng th

at it

s ex

pres

sion

was

und

etec

ted,

mak

ing

this

fold

-cha

nge

resu

lt er

rone

ous a

nd u

n-in

terp

reta

ble.

286

A

ppen

dix

6

APP

END

IX 6

D

ESC

RIP

TIO

N O

F G

ENES

SC

REE

NED

IN T

HE

RT2 P

RO

FILE

R B

REA

ST C

AN

CER

PC

R A

RR

AY

(P

AH

S-13

1A)

Sym

bol

Des

crip

tion

Gen

e N

ame

AB

CB

1 A

TP-b

indi

ng c

asse

tte, s

ub-f

amily

B (M

DR

/TA

P), m

embe

r 1

AB

C20

, CD

243,

CLC

S, G

P170

, MD

R1,

P-G

P, P

GY

1 A

BC

G2

ATP

-bin

ding

cas

sette

, sub

-fam

ily G

(WH

ITE)

, mem

ber 2

A

BC

15, A

BC

P, B

CR

P, B

CR

P1, B

MD

P, C

D33

8, C

Dw

338,

ES

T157

481,

GO

UT1

, MRX

, MX

R, M

XR

-1, M

XR

1, U

AQ

TL1

AD

AM

23

AD

AM

met

allo

pept

idas

e do

mai

n 23

M

DC

-3, M

DC

3 A

KT1

V

-akt

mur

ine

thym

oma

vira

l onc

ogen

e ho

mol

ogue

1

AK

T, C

WS6

, PK

B, P

KB

-ALP

HA

, PR

KB

A, R

AC

, RA

C-A

LPH

A

APC

A

deno

mat

ous p

olyp

osis

col

i B

TPS2

, DP2

, DP2

.5, D

P3, G

S, P

PP1R

46

AR

A

ndro

gen

rece

ptor

A

IS, A

R8,

DH

TR, H

UM

AR

A, H

YSP

1, K

D, N

R3C

4, S

BM

A,

SMA

X1,

TFM

A

TM

Ata

xia

tela

ngie

ctas

ia m

utat

ed

AT1

, ATA

, ATC

, ATD

, ATD

C, A

TE, T

EL1,

TEL

O1

BA

D

BC

L2-a

ssoc

iate

d ag

onis

t of c

ell d

eath

B

BC

2, B

CL2

L8

BC

L2

B-c

ell C

LL/ly

mph

oma

2 B

cl-2

, PPP

1R50

B

IRC

5 B

acul

ovira

l IA

P re

peat

con

tain

ing

5 A

PI4,

EPR

-1

BR

CA

1 B

reas

t can

cer 1

, ear

ly o

nset

B

RC

AI,

BR

CC

1, B

RO

VC

A1,

FA

NC

S, IR

IS, P

NC

A4,

PPP

1R53

, PS

CP,

RN

F53

BR

CA

2 B

reas

t can

cer 2

, ear

ly o

nset

B

RC

C2,

BR

OV

CA

2, F

AC

D, F

AD

, FA

D1,

FA

NC

D, F

AN

CD

1,

GLM

3, P

NC

A2,

XR

CC

11

CC

NA

1 C

yclin

A1

CT1

46

CC

ND

1 C

yclin

D1

BC

L1, D

11S2

87E,

PR

AD

1, U

21B

31

CC

ND

2 C

yclin

D2

KIA

K00

02, M

PPH

3 C

CN

E1

Cyc

lin E

1 C

CN

E, p

CC

NE1

C

DH

1 C

adhe

rin 1

, typ

e 1,

E-c

adhe

rin (e

pith

elia

l) A

rc-1

, CD

324,

CD

HE,

EC

AD

, LC

AM

, UV

O

CD

H13

C

adhe

rin 1

3, H

-cad

herin

(hea

rt)

CD

HH

, P10

5 C

DK

2 C

yclin

-dep

ende

nt k

inas

e 2

CD

KN

2, p

33(C

DK

2)

CD

KN

1A

Cyc

lin-d

epen

dent

kin

ase

inhi

bito

r 1A

(p21

, Cip

1)

CA

P20,

CD

KN

1, C

IP1,

MD

A-6

, P21

, SD

I1, W

AF1

, p21

CIP

1 C

DK

N1C

C

yclin

-dep

ende

nt k

inas

e in

hibi

tor 1

C (p

57, K

ip2)

B

WC

R, B

WS,

KIP

2, W

BS,

p57

, p57

Kip

2

287

A

ppen

dix

6

CD

KN

2A

Cyc

lin-d

epen

dent

kin

ase

inhi

bito

r 2A

(mel

anom

a, p

16, i

nhib

its C

DK

4)

AR

F, C

DK

4I, C

DK

N2,

CM

M2,

INK

4, IN

K4A

, MLM

, MTS

-1,

MTS

1, P

14, P

14A

RF,

P16

, P16

-INK

4A, P

16IN

K4,

P16

INK

4A,

P19,

P19

AR

F, T

P16

CSF

1 C

olon

y st

imul

atin

g fa

ctor

1 (m

acro

phag

e)

CSF

-1, M

CSF

C

ST6

Cys

tatin

E/M

-

CTN

NB

1 C

aten

in (c

adhe

rin-a

ssoc

iate

d pr

otei

n), b

eta

1, 8

8kD

a C

TNN

B, M

RD

19, a

rmad

illo

CTS

D

Cat

heps

in D

C

LN10

, CPS

D, H

EL-S

-130

P EG

F Ep

ider

mal

gro

wth

fact

or

HO

MG

4, U

RG

EG

FR

Epid

erm

al g

row

th fa

ctor

rece

ptor

ER

BB

, ER

BB

1, H

ER1,

NIS

BD

2, P

IG61

, mEN

A

ERB

B2

V-e

rb-b

2 er

ythr

obla

stic

leuk

emia

vira

l onc

ogen

e ho

mol

og 2

, ne

uro/

glio

blas

tom

a de

rived

onc

ogen

e ho

mol

ogue

(avi

an)

CD

340,

HER

-2, H

ER-2

, neu

, HER

2, M

LN 1

9, N

EU, N

GL,

TK

R1

ESR

1 O

estro

gen

rece

ptor

1

ER, E

SR, E

SRA

, EST

RR

, Era

, NR

3A1

ESR

2 O

estro

gen

rece

ptor

2 (E

R b

eta)

ER

-BET

A, E

SR-B

ETA

, ESR

B, E

STR

B, E

rb, N

R3A

2 FO

XA

1 Fo

rkhe

ad b

ox A

1 H

NF3

A, T

CF3

A

GA

TA3

GA

TA b

indi

ng p

rote

in 3

H

DR

, HD

RS

GLI

1 G

LI fa

mily

zin

c fin

ger 1

G

LI

GR

B7

Gro

wth

fact

or re

cept

or-b

ound

pro

tein

7

- G

STP1

G

luta

thio

ne S

-tran

sfer

ase

pi 1

D

FN7,

FA

EES3

, GST

3, G

STP,

HEL

-S-2

2, P

I H

IC1

Hyp

erm

ethy

late

d in

can

cer 1

ZB

TB29

, ZN

F901

, hic

-1

ID1

Inhi

bito

r of D

NA

bin

ding

1, d

omin

ant n

egat

ive

helix

-loop

-hel

ix p

rote

in

ID, b

HLH

b24

IGF1

In

sulin

-like

gro

wth

fact

or 1

(som

atom

edin

C)

IGF-

I, IG

FI, M

GF

IGF1

R

Insu

lin-li

ke g

row

th fa

ctor

1 re

cept

or

CD

221,

IGFI

R, I

GFR

, JTK

13

IGFB

P3

Insu

lin-li

ke g

row

th fa

ctor

bin

ding

pro

tein

3

BP-

53, I

BP3

IL

6 In

terle

ukin

6 (i

nter

fero

n, b

eta

2)

BSF

2, H

GF,

HSF

, IFN

B2,

IL-6

JU

N

Jun

prot

o-on

coge

ne

AP-

1, A

P1, c

-Jun

K

RT18

K

erat

in 1

8 C

K-1

8, C

YK

18, K

18

KRT

19

Ker

atin

19

CK

19, K

19, K

1CS

KRT

5 K

erat

in 5

C

K5,

DD

D, D

DD

1, E

BS2

, K5,

KRT

5A

KRT

8 K

erat

in 8

C

AR

D2,

CK

-8, C

K8,

CY

K8,

K2C

8, K

8, K

O

MA

PK1

Mito

gen-

activ

ated

pro

tein

kin

ase

1 ER

K, E

RK

-2, E

RK

2, E

RT1,

MA

PK2,

P42

MA

PK, P

RKM

1,

PRK

M2,

p38

, p40

, p41

, p41

map

k, p

42-M

APK

M

APK

3 M

itoge

n-ac

tivat

ed p

rote

in k

inas

e 3

ERK

-1, E

RK

1, E

RT2

, HS4

4KD

AP,

HU

MK

ER1A

, P44

ERK

1,

288

A

ppen

dix

6

P44M

APK

, PR

KM

3, p

44-E

RK

1, p

44-M

APK

M

APK

8 M

itoge

n-ac

tivat

ed p

rote

in k

inas

e 8

JNK

, JN

K-4

6, JN

K1,

JNK

1A2,

JNK

21B

1, 2

, PRK

M8,

SA

PK1,

SA

PK1c

M

GM

T O

-6-m

ethy

lgua

nine

-DN

A m

ethy

ltran

sfer

ase

- M

KI6

7 A

ntig

en id

entif

ied

by m

onoc

lona

l ant

ibod

y K

i-67

KIA

, MIB

-, M

IB-1

, PPP

1R10

5 M

LH1

Mut

L ho

mol

og 1

, col

on c

ance

r, no

npol

ypos

is ty

pe 2

(E. c

oli)

CO

CA

2, F

CC

2, H

NPC

C, H

NPC

C2,

hM

LH1

MM

P2

Mat

rix m

etal

lope

ptid

ase

2 (g

elat

inas

e A

, 72k

Da

gela

tinas

e, 7

2kD

a ty

pe IV

co

llage

nase

) C

LG4,

CLG

4A, M

MP-

2, M

MP-

II, M

ON

A, T

BE-

1

MM

P9

Mat

rix m

etal

lope

ptid

ase

9 (g

elat

inas

e B

, 92k

Da

gela

tinas

e, 9

2kD

a ty

pe IV

co

llage

nase

) C

LG4B

, GEL

B, M

AN

DP2

, MM

P-9

MU

C1

Muc

in 1

, cel

l sur

face

ass

ocia

ted

AD

MC

KD

, AD

MC

KD

1, C

A 1

5-3,

CD

227,

EM

A, H

23A

G, K

L-6,

M

AM

6, M

CD

, MCK

D, M

CK

D1,

MU

C-1

, MU

C-1

, SEC

, MU

C-1

, X

, MU

C1,

ZD

, PEM

, PEM

T, P

UM

M

YC

V

-myc

mye

locy

tom

atos

is v

iral o

ncog

ene

hom

olog

(avi

an)

MR

TL, M

YC

C, b

HLH

e39,

c-M

yc

NM

E1

Non

-met

asta

tic c

ells

1, p

rote

in (N

M23

A) e

xpre

ssed

in

AW

D, G

AA

D, N

B, N

BS,

ND

KA

, ND

PK-A

, ND

PKA

, NM

23,

NM

23-H

1 N

OTC

H1

Not

ch 1

A

OS5

, AO

VD

1, T

AN

1, h

N1

NR

3C1

Nuc

lear

rece

ptor

subf

amily

3, g

roup

C, m

embe

r 1 (g

luco

corti

coid

rece

ptor

) G

CC

R, G

CR

, GC

RST

, GR

, GR

L PG

R

Prog

este

rone

rece

ptor

N

R3C

3, P

R

PLA

U

Plas

min

ogen

act

ivat

or, u

roki

nase

A

TF, B

DPL

T5, Q

PD, U

PA, U

RK

, u-P

A

PRD

M2

PR d

omai

n co

ntai

ning

2, w

ith Z

NF

dom

ain

HU

MH

OX

Y1,

KM

T8, M

TB-Z

F, R

IZ, R

IZ1,

RIZ

2 PT

EN

Phos

phat

ase

and

tens

in h

omol

ogue

10

q23d

el, B

ZS, C

WS1

, DEC

, GLM

2, M

HA

M, M

MA

C1,

PTE

N1,

TE

P1

PTG

S2

Pros

tagl

andi

n-en

dope

roxi

de sy

ntha

se 2

(pro

stag

land

in G

/H sy

ntha

se a

nd

cycl

ooxy

gena

se)

CO

X-2

, CO

X2,

GR

IPG

HS,

PG

G, H

S, P

GH

S-2,

PH

S-2,

hC

ox-2

PYC

AR

D

PYD

and

CA

RD

dom

ain

cont

aini

ng

ASC

, CA

RD

5, T

MS,

TM

S-1,

TM

S1

RA

RB

R

etin

oic

acid

rece

ptor

, bet

a H

AP,

MC

OPS

12, N

R1B

2, R

RB

2 R

ASS

F1

Ras

ass

ocia

tion

(Ral

GD

S/A

F-6)

dom

ain

fam

ily m

embe

r 1

123F

2, N

OR

E2A

, RA

SSF1

A, R

DA

32, R

EH3P

21

RB

1 R

etin

obla

stom

a 1

OSR

C, P

PP1R

130,

RB

, p10

5-R

b, p

Rb,

pp1

10

SER

PIN

E1

Serp

in p

eptid

ase

inhi

bito

r, cl

ade

E (n

exin

, pla

smin

ogen

act

ivat

or in

hibi

tor

type

1),

mem

ber 1

PA

I, PA

I-1, P

AI1

, PLA

NH

1

SFN

St

ratif

in

YW

HA

S

289

A

ppen

dix

6

SFR

P1

Secr

eted

friz

zled

-rela

ted

prot

ein

1 FR

P, F

RP-

1, F

RP1

, Frz

A, S

AR

P2

SLC

39A

6 So

lute

car

rier f

amily

39

(zin

c tra

nspo

rter)

, mem

ber 6

LI

V-1

, ZIP

6 SL

IT2

Slit

hom

olog

2 (D

roso

phila

) SL

IL3,

Slit

-2

SNA

I2

Snai

l hom

olog

2 (D

roso

phila

) SL

UG

, SLU

GH

1, S

NA

IL2,

WS2

D

SRC

V

-src

sarc

oma

(Sch

mid

t-Rup

pin

A-2

) vira

l onc

ogen

e ho

mol

ogue

(avi

an)

ASV

, SR

C1,

c-S

RC

, p60

-Src

TF

F3

Tref

oil f

acto

r 3 (i

ntes

tinal

) IT

F, P

1B, T

FI

TGFB

1 Tr

ansf

orm

ing

grow

th fa

ctor

, bet

a 1

CED

, DPD

1, L

AP,

TG

FB, T

GFb

eta

THB

S1

Thro

mbo

spon

din

1 TH

BS,

TH

BS-

1, T

SP, T

SP-1

, TSP

1 TP

53

Tum

our p

rote

in p

53

BC

C7,

LFS

1, P

53, T

RP5

3 TP

73

Tum

our p

rote

in p

73

P73

TWIS

T1

Twis

t hom

olog

ue 1

(Dro

soph

ila)

AC

S3, B

PES2

, BPE

S3, C

RS,

CR

S1, C

SO, S

CS,

TW

IST,

bH

LHa3

8 V

EGFA

V

ascu

lar e

ndot

helia

l gro

wth

fact

or A

M

VC

D1,

VEG

F, V

PF

XB

P1

X-b

ox b

indi

ng p

rote

in 1

TR

EB-5

, TR

EB5,

XB

P-1,

XB

P2

B2M

B

eta-

2-m

icro

glob

ulin

-

HPR

T1

Hyp

oxan

thin

e ph

osph

orib

osyl

trans

fera

se 1

H

GPR

T, H

PRT

RPL

13A

R

ibos

omal

pro

tein

L13

a L1

3A, T

STA

1 G

APD

H

Gly

cera

ldeh

yde-

3-ph

osph

ate

dehy

drog

enas

e G

3PD

, GA

PD, H

EL-S

-162

eP

AC

TB

Act

in, b

eta

BR

WS1

, PS1

TP5B

P1

HG

DC

H

uman

Gen

omic

DN

A C

onta

min

atio

n H

IGX

1A

RTC

R

ever

se T

rans

crip

tion

Con

trol

RTC

R

TC

Rev

erse

Tra

nscr

iptio

n C

ontro

l R

TC

RTC

R

ever

se T

rans

crip

tion

Con

trol

RTC

PP

C

Posi

tive

PCR

Con

trol

PPC

PP

C

Posi

tive

PCR

Con

trol

PPC

PP

C

Posi

tive

PCR

Con

trol

PPC

Gen

e T

able

290

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VIVIAN YAR LI CHUA - the UWA Profiles and Research Repository€¦ · regulation of gene expression by the androgen receptor and hedgehog pathways in breast cancer cells. vivian yar