The Role of miR-605 and its Variant in Li-Fraumeni Syndrome

by

Badr Idsaid

A thesis submitted in conformity with the requirements

for the degree of Master of Science

Department of Medical Biophysics

University of Toronto

© Copyright by Badr Idsaid 2014

ii

The Role of miR-605 and its Variant in Li-Fraumeni Syndrome

Badr Idsaid

Master of Science

Department of Medical Biophysics

University of Toronto

2014

Abstract

Li-Fraumeni Syndrome (LFS) is a rare cancer predisposition syndrome, typically involving

germline mutations in the TP53 gene. Despite the high penetrance of TP53 mutations, LFS

patients display striking phenotypic differences, suggesting the presence of secondary risk loci.

To date, all genetic modifiers in LFS have been shown to map to either TP53 or its principal

negative regulator, Mdm2. Given this strong association, we set out to interrogate the

contribution of a recently-described miRNA regulator of the p53-MDM2 loop, called miR-605.

We hypothesized that, if functional, the miR-605 gene and its variant (rs2043556) could impact

cancer risk in TP53 mutation carriers. Consistent with this proposition, the variant allele of miR-

605 was associated with a significant acceleration in tumor onset and caused a decrease in the

processing efficiency of its host miRNA. We also demonstrate that miR-605 overexpression

activates the MAPK pathway and leads to tumor suppression in TP53 mutant cell lines.

iii

Acknowledgments

I owe my deepest gratitude to my supervisor, Dr. David Malkin, for giving me the opportunity

and encouragement to pursue this topic. Many thanks as well to members of my advisory

committee, namely, Dr. Fei-Fei Liu and Dr. Annie Huang, for their thoughtful advice and

guidance. Finally, I am grateful to members of the Malkin and Tabori labs for their valuable

feedback and support throughout the course of my master’s degree. This project would not have

been possible without the time and effort of these contributors.

iv

Table of Contents

1

Chapter 1: Introduction………………………………………………………

1

1.1 TP53………………………………………………………….……………. 1

1.1.1 TP53 Activation…………………………………………………………… 2

1.1.1.1 p53 Stabilization…………………………………………………................ 2

1.1.1.2 MDM2 Inhibition………………………………………………….............. 4

1.1.2 TP53 Program………………………………………………....................... 5

1.1.2.1 Cell Cycle Arrest…………………………………………………………...... 6

1.1.2.2 Apoptosis………………………………………………………………....... 7

1.2 Li-Fraumeni Syndrome………………………………………………......... 9

1.2.1 Clinical Diagnosis………………………………………………………..... 9

1.2.2 Cancer Risk………………………………………………………………... 10

1.2.3 p53 Connection……..……………………………………………………... 11

1.2.4 TP53 Genotype:Phenotype Correlations…………………………………... 12

1.2.5 Secondary Modifiers in Li-Fraumeni Syndrome………………………….. 13

1.3 MicroRNAs………………………………………………………………... 15

1.3.1 Function and Biogenesis…………………………………………………... 15

1.3.2 The MicroRNAs-TP53 Network…………………………………………. 16

1.3.3 Genetic Variations in MicroRNAs………………………………………… 18

1.3.4 miR-605 and its Variant: a Role in Li-Fraumeni Syndrome?....................... 19

2 Chapter 2: Methods………………………………………………………...... 20

3 Chapter 3: Results…………………………………………………………… 25

3.1 Functional Impact of the miR-605 SNP…………………………………… 25

3.1.1 The miR-605 SNP modifies the age of cancer onset in LFS patients……... 25

3.1.2 The miR-605 SNP affects the processing efficiency of pre-miR-605……. 27

3.2 Role of miR-605 in TP53 Mutant cells……………………………………. 28

3.2.1 miR-605 affects cell viability and colony formation in TP53 mutant cells.. 28

3.2.2 miR-605 affects the chemosensitivity and migration of TP53 mutant cells. 30

3.2.3 miR-605 overexpression activates the MAPK pathway…………………… . 33

4 Chapter 4: Discussion……………………………………………………….. 35

4.1 miR-605 SNP and LFS Cancer Risk………………………………………. 35

4.2 miR-605 Action and Signalling in TP53 Mutant Cells……………………. 37

4.3 Study Limitations………………………………………………………...... 39

5 Chapter 5: Conclusion/Future Perspectives…………...……………….......... 41

v

List of Figures

Introduction

Figure 1: Scheme of p53 protein domains and sites of post-translational modifications

Results

Figure 1: Representative SNP-RFLP genotyping of the miR-605 SNP

Figure 2a: Age of cancer onset in TP53 mutation carriers according to miR-605 genotype

Figure 2b: Percentage of unaffected TP53 mutation carriers for each miR-605 genotype

Figure 3: Schematic representation of SNP expression experiment

Figure 4a: Sanger sequencing of the pre-miR-605-A and pre-miR-605-G vectors

Figure 4b: Impact of the miR-605 SNP on mature miR-605 levels

Figure 4c: Impact of the miR-605 SNP on precursor miR-605 levels

Figure 4d: Processing efficiency of pre-miR-605 according to genotype

Figure 5a: Effect of miR-605 overexpression on cell viability in TP53 mutant cells

Figure 5b: Effect of miR-605 overexpression on colony formation in TP53 mutant cells

Figure 5c: Representative plates from colony formation assay

Figure 5d: Western Blot targeting Mdm2, p53 and Vinculin in RD cells

Figure 6a: Effect of miR-605 on RD and Rh30 chemosensitivity to Actinomycin D

Figure 6b: Effect of miR-605 on RD and Rh30 chemosensitivity to Doxorubicin

Figure 6c: Effect of miR-605 on RD and Rh30 chemosensitivity to Etoposide

Figure 7a: Effect of miR-605 overexpression on cell migration in TP53 mutant cells

Figure 7b: Representative inserts from migration assay

Figure 8: Western Blot targeting MAPK proteins in RD cells

vi

List of Appendices

Appendix 1

Supplementary Figure 1: Secondary structures of wild-type and variant pre-miR-605

Supplementary Figure 2: Sequence of miR-605 PCR primers

Supplementary Figure 3: Representative Sanger sequencing of miR-605 genotypes

Appendix 2

Supplementary Table 1: Validated functional pre-miRNA SNPs

Supplementary Table 2: Predicted miR-605 targets in MAPK and/or p53 signaling

vii

List of Abbreviations

ARF Alternate Reading Frame Protein

Arg72Pro Arginine-to-Proline Substitution at Codon 72

Bcl-2 B-cell Lymphoma 2

BH3 Bcl-2 Homology 3

CDK2 Cyclin-Dependent-Kinase 2

CNV Copy Number Variation

Cyt C Cytochrome C

E2F E2 Promoter Binding Factor

ERK Extracellular-Signal-Regulated Kinase

JNK c-Jun N-terminal Kinase

Kb Kilo-Base Pair

LFS Li-Fraumeni Syndrome

LFS-C Li-Fraumeni Syndrome-Classic

LFS-L Li-Fraumeni Syndrome-Like

MAF Minor Allele Frequency

MAPK Mitogen-Activated Protein Kinase

MDM2 Mouse Double Minute 2

MDMX Mouse Double Minute X

miRNA MicroRNA

mRNA Messenger RNA

p21/CDKN1 Cyclin-dependent Kinase Inhibitor 1

p38 p38 MAP Kinase

p53 tumor protein, 53kDa

PCR Polymerase Chain Reaction

PEX4 Polymorphism in Exon 4

PIN3 Polymorphism in Intron 3

viii

pRB Retinoblastoma Tumor Suppressor

pre-miRNA Precursor-miRNA

pri-miRNA Primary-miRNA

qRT-PCR Quantitative Reverse Transcriptase Polymerase Chain Reaction

RE Response Element

RISC RNA-induced Silencing Complex

RMS Rhabdomyosarcoma

Ser Serine

SNP Single Nucleotide Polymorphism

SNP309 Single Nucleotide Polymorphism Codon 309

SNP-RFLP SNP-Restriction Fragment Length Polymorphism

Trp53 Transformation Related Protein 53

UTR Untranslated Region

1

CHAPTER 1

INTRODUCTION

1.1 TP53

The p53 protein, dubbed “the guardian of the genome”, plays a crucial role in

coordinating cellular defenses against cancer. Initially discovered because of its association with

the large T antigen of the Simian polyomavirus (SV40), early studies of this gene (TP53) and its

encoded product (p53) showed elevated expression in human cancer cell lines and the ability to

transform normal cells1,2,3

. These initial findings strongly indicated that TP53 was a novel

oncogene. However, with the discovery of inactivating TP53 alterations in human cancer cell

lines and tumors, and later by the finding that patients with Li-Fraumeni Syndrome had inherited

TP53 mutations, it became clear that TP53 was, in fact, a tumor suppressor gene and not an

oncogene as had been earlier suggested4,5,6

. Studies revealed that the “wild-type” allele used in

prior experiments was actually a mutant TP53 gene and that wild-type p53 could in fact suppress

cellular transformation7. Subsequent work on the mouse TP53 gene (Trp53) in heterozygous

(Trp53 +/-) and knockout (Trp53 -/-) mice –both highly tumorigenic breeds– would further

confirm the tumor suppressive role of the p53 protein8,9

. Today, it is clear that p53 dysfunction is

an important step in the transformation process of normal cells into cancer cells10

.

The TP53 gene spans approximately 20-Kb on the short arm of chromosome 17

(17p13.1) and consists of 11 exons, the first of which is non-coding9. The structure of the p53

protein reflects its role as a sequence-specific DNA binding transcription factor11

. p53 consists

of 393 amino acids that together make up four important functional domains: an N-terminal

domain, a DNA binding domain, a tetramerization domain and a C-terminal domain12

. The C-

terminal lysine-rich domain plays a key role in regulating the activity and nuclear localization of

2

the p53 protein. Meanwhile, the tetramerization domain enables p53 to combine into its active

homo-tetrameric form and the all-important DNA binding domain allows it to bind DNA at

cognate recognition sequences. Finally, a transcriptional activation domain at its N-terminus

binds components of the transcriptional machinery and other co-activators and negative

regulators.

Figure 1: Scheme of p53 protein domains and sites of post-translational modifications.

TAD: N-terminal transactivation domain; DBD: DNA-Binding domain; TET: Tetramerization

domain; REG: C-terminal regulatory domain (adapted from the p53 website https://p53.free.fr)

1.1.1 TP53 Activation

In response to a broad array of cellular stresses (e.g. DNA damage, oxidative stress,

hypoxia and nucleotide depletion), p53 activates several protective mechanisms, including DNA

repair, cell cycle arrest and apoptosis13

. Activation of the p53 response helps ensure that no cell

with high or irreparable levels of DNA damage can propagate its corrupted genome. Under

conditions of cellular damage, the p53 protein, which typically has a very short-half life, is

rapidly stabilized by several post-translational modifications. In addition, p53 is liberated from

the inhibition of a number of cellular repressors, especially MDM2. As a result, nuclear levels of

3

p53 quickly rise and activated p53 acts as a sequence-specific transcription factor, leading to the

transcription – and sometimes the repression – of a number of different genes14

.

1.1.1.1 p53 Stabilization

Under normal conditions, the half-life of the p53 protein ranges between 5-30 min15

,

mainly due to the action of MDM2-mediated proteosomal degradation16

. In response to stress, a

number of different post-translational modifications act to rapidly stabilize p53. These

modifications are thought to stabilize the p53 protein by controlling its interaction with multiple

cellular factors, but particularly its association with the MDM2 protein. At least 36 different N-

and C-terminal amino acid residues are known to be affected by phosphorylation, acetylation,

methylation, ubiquitination and sumoylation17

. Out of these modifications, phosphorylation is

regarded as the most prolific and well-studied mode of p53 stabilization. Multiple protein kinases

including ATM (mutated in ataxia-telangiectasia); ATR (A-T and Rad3-related); DNA-PK

(DNA-dependent protein kinase), Chk1 and Chk2 have been shown to phosphorylate p5318

.

ATM-mediated phosphorylation of Ser15, as a result of DNA-double strand breaks, is

particularly noteworthy because of its role in facilitating the dissociation of MDM2 from p5319

.

Phosphorylation of Ser20 by Chk2 is also known to achieve the same end20

. As such,

phosphorylation at these sites is well-correlated with increased p53 levels; other commonly

phosphorylated sites occur at Ser33 and Ser4617

.

Another common mode of p53 stabilization involves the acetylation of several lysine

residues in its C-terminus. Transfer of an acetyl group by histone acetyltransferases (HATs) such

as p300 alters the folding of the C-terminal region of p53 and helps to expose its important

DNA-binding domain. These acetylated residues can also block MDM2-mediated ubiquitination

and degradation21

. In addition, evidence suggests that specific modifications, such as the

4

previously described Ser15 phosphorylation, are necessary first steps that facilitate further post-

translational modifications22

. Thus, the interplay of various modifications adds yet another layer

of complexity to the stress-induced stabilization of the p53 protein. It is important to note

however, that p53 retains its transcriptional activity even when all phosphorylation sites are

mutated, highlighting a level of redundancy in the p53 stabilization process, as well as perhaps

the supremacy of MDM2 regulation over other modes of p53 stabilization.

1.1.1.2 MDM2 Inhibition

In light of its critical functions, p53 activity is tightly regulated by several cellular factors,

but most importantly by MDM2. The Mdm2 gene, initially identified in mouse double minute

chromosomes, encodes a protein product that exerts tight control over p53 activity. Binding of

MDM2 to the N-terminus of p53, a region important for p53’s transactivational potential,

directly blocks its transcriptional activity23

. Fulfilling its role as a E3 ubiquitin ligase, MDM2

can also target p53 for degradation through its ubiquitin-mediated proteosomal pathway24

.

Furthermore, MDM2 is also known to promote the nuclear export of p53 and its cytoplasmic

accumulation as a result of mono-ubiquitination. Thus, MDM2 controls p53 activity at multiple

levels. Not surprisingly, conditional removal of the Mdm2 gene in adult tissues leads to cell

lethality as a result of elevated and hyperactive p53 signaling25

. Further evidence for the

intricate relationship between MDM2 and p53 comes from the observation that while

constitutive Mdm2 knockout mice are embryonic lethal, mice lacking both genes are viable26

.

Adding to this complexity, Mdm2 is also a transcriptional target of p5327

; therefore, MDM2

regulates p53 through an autoregulatory negative feedback system. The purpose of this

regulatory loop is to prevent p53 activation in unstressed cells and to reduce the severity of the

p53 response once activated28

. Consequently, the p53 response can only be activated once this

5

regulatory loop is broken. In response to stress, a variety of signals act to destabilize and inhibit

MDM2 activity29

. For example, ATM-mediated phosphorylation of MDM2 at Ser395 occurs

frequently in response to stress, helping to block the ability of MDM2 to degrade p53 and

promote its nuclear export30

. Furthermore, MDM2 activity can also be inhibited by increased

acetylation31

. Finally, decreased sumoylation of MDM2 can further inhibit its activity by

increasing its self-ubiquitination32

.

It is evident that post-translational modifications to both p53 and MDM2 play a role in

breaking the auto-regulatory loop controlling these two proteins; however, these modifications

are not the only factors involved in liberating p53 from MDM2 control. In this respect, the ARF

protein (p14 ARF) also plays a crucial role. ARF activates p53 by inhibiting the ubiquitin

activity of MDM2 as well as promoting its sequestration in the nucleolus33

. MDMX is yet

another potent modulator of the MDM2-p53 regulatory loop. In a manner similar to MDM2,

MDMX can also bind and inactivate p53 through its N-terminal domain but unlike MDM2, it has

no ubiquitin activity of its own34

. Paradoxically, MDMX can also activate p53 by binding

MDM2 through its RING finger domain35

. More recently, a number of small non-coding

regulatory RNAs (miR-192, -194, -215 and -605) have been shown to negatively regulate the

feedback loop controlling p53 and MDM2 function36,37

.

1.1.2 TP53 Program

The p53 protein acts primarily as a sequence-specific transcription factor. Not

surprisingly, the majority of TP53 mutations target the DNA-binding domain of p5338

. Target

genes that are activated by p53 typically contain at least one Response Element (RE) within their

promoter regions. In some instances, p53 RE sites may also be located in intronic or even exonic

regions39

. These canonical sites are usually made up of two half sites (5-RRRCWWGYYY-3)

6

separated by a variable number of nucleotides40

; however, non-canonical p53 RE are also known

to exist41,42

. Once bound to these REs through its DNA-binding domain, the N-terminal domain

of p53 facilitates transcription by attracting several members of the transcriptional machinery. In

this way, p53 activates genes involved in a variety of cellular processes, especially cell cycle

arrest and apoptosis.

1.1.2.1 Cell Cycle Arrest

The cell cycle is composed of four distinct stages (G1, S, G2 and M phase), and each cell

must pass through two important checkpoints (G1/S and G2/M checkpoints) before completing

cellular division, or mitosis43

. Normal cells, unlike those lacking p53, arrest during these critical

checkpoints in order to monitor the state of the cell and engage in DNA repair if needed44

. By

controlling the expression of multiple cell-cycle genes, p53 plays a pivotal role in dictating

whether a cell will progress through the cell cycle and undergo mitosis45

. The protein encoded by

the p21 gene (CDKN1A) represents the most prominent mediator of TP53-induced G1/S arrest46

.

Studies show that ectopic expression of the N- and C-terminal regions of p21 alone is sufficient

to induce cell-cycle arrest. Under conditions of stress, p53 up-regulates the transcription of p21,

leading to the inhibition of its most important cellular target: the Cyclin-Dependent-Kinase 2

(CDK2)47

. Importantly, activated p21 blocks CDK2 from phosphorylating and inactivating the

pRb protein, thus helping maintain pRb-mediated repression of the E2F family of transcription

factors. As a result, E2F-target genes responsible for facilitating the G1/S transition remain

transcriptionally silent and the cell cycle is temporarily arrested at G148

. Once checkpoint

requirements have been met and DNA repair has occurred, p53 levels drop and inhibition of

CDK2 by p21 is removed, allowing the cell to replicate its DNA in the S phase and proceed

towards the G2 phase. The final G2/M checkpoint is also similarly regulated by p53. In cancers

7

with a mutated TP53, the appropriate cell cycle response to DNA damage is impaired. Instead,

p53 dysfunction and thus deficient p21 activation empowers cancer cells to proceed through cell

cycle checkpoints despite the presence of oncogenic lesions in its DNA.

1.1.2.2 Apoptosis

In cases where the DNA is damaged beyond repair, apoptosis is needed in order to

safeguard the cell against oncogenic transformation49

. Apoptosis or programmed cell death is a

complex biochemical event that leads to specific morphological changes which culminate in

cellular death. Apoptotic cells are typically identified by the following morphological features:

formation of protrusions in the plasma membrane called ‘blebs’, cell shrinkage, nuclear

fragmentation, condensation of chromatin known as pyknosis, and finally DNA fragmentation.

Normally, apoptosis is a tightly regulated developmental and homeostatic process. For example,

the normal self-renewal of the gut epithelium depends on an intricate balance between cellular

proliferation and apoptosis while in the developing human embryo, apoptosis is necessary for the

proper separation of digits. Cancer cells will often evade this program by turning off apoptotic

signals. In fact, evasion of apoptosis is a major hallmark of cancer50

and abrogation of the TP53

response, typically through mutations in the DNA binding domain of TP53, a common

mechanism through which cancer cells can counter cell death. While TP53-induced apoptosis

can occur through transcription-independent pathways51

, this process is primarily dependent on

the transactivation of multiple components of the extrinsic and intrinsic apoptotic pathways (see

below)45

.

The extrinsic apoptosis pathway involves the ligand-induced activation of specific

“death” receptors belonging to the tumor necrosis factor receptor (TNF-R) family. Once

engaged, these cell surface receptors form a death-inducing-signaling-complex (DISC), in which

8

two important initiator caspases (caspase-8 and -10) are recruited and activated. These initiator

caspases in turn promote the maturation of the zymogenic form of the effector caspases

(caspases-3, -6 and -7), which finally cleave their own set of cellular targets in order to trigger

apoptosis52

. The p53 protein activates this important pathway by upregulating the expression of

its component parts in a tissue and stress-specific manner53

. Specifically, p53 augments the

activation of genes encoding three trans-membrane “death” receptors (Fas, DR5, PERP)54,55

, as

well as the expression of specific pro-apoptotic ligands such as TRAIL56

.

In the intrinsic pathway, apoptosis is triggered by the depolarization of the mitochondria

and the subsequent release of cytochrome C (cyt C) from the mitochondrial intermembrane space

into the cytoplasm. As a result, cyt C combines with apoptotic protease-activating factor 1

(APAF-1) and procaspase-9 to form a wheel-like molecule, termed the apoptosome. This “death

machine” serves to activate caspase-9, and with it the rest of the caspase cascade 57

. TP53-

mediated induction of the intrinsic pathway revolves around its transcriptional control over a

subset of the Bcl-2 family of proteins. The Bcl-2 family is composed of both pro-survival and

pro-apoptotic members which can associate with the mitochondria and which can be further

divided into three classes: pro-survival proteins (Bcl-2 and Bcl-Xl); pro-apoptotic proteins that

structurally resemble Bcl-2 (Bax and Bak); and finally pro-apoptotic BH3-only proteins (Puma,

Noxa, Bid)58

. In addition to Bax, all BH3-only proteins are transcriptional targets of TP5359,60,61

.

Following p53 induction, these genes help shift the balance of Bcl-2 family members at the

mitochondria towards the pro-apoptotic members. As a result, the mitochondria depolarize and

cyt C is released triggering the formation of the apoptosome and ultimately apoptosis.

9

1.2 Li-Fraumeni Syndrome

In addition to being the most mutated gene in sporadic cancers (>50%), TP53 dysfunction

is also implicated in the etiology of a peculiar familiar cancer syndrome, called Li-Fraumeni

Syndrome (LFS)4,62

. LFS was first described by Drs. Frederick Li and Joseph F. Fraumeni Jr in

1969 whilst studying families of children diagnosed with a rare soft-tissue tumor called

rhabdomyosarcoma63

. Upon retrospective analysis, they discovered that five of these families

had a second child who had also been diagnosed with a soft-tissue sarcoma. These families also

had a higher than usual prevalence of a number of different cancer types (soft-tissue sarcoma,

premenopausal breast cancer, adrenocortical carcinoma and brain tumors) amongst first- and

second-degree relatives from the same parental lineage. This observed inheritance pattern

coupled with the unusual clustering of early-onset tumors in these families was indicative of a

previously unknown autosomal dominant cancer predisposition syndrome.

1.2.1 Clinical Diagnosis

Prospective analysis of 24 similar families further defined this newly described syndrome

by the presence of all of the following criteria: a proband with a sarcoma diagnosed before age

45 years who has a first-degree relative with any cancer before age 45 years, as well as a first- or

second-degree relative with any cancer before age 45 years or a sarcoma at any age64

. Families

which fit this clinical criterion were defined as “classic” LFS (LFS-C). As the observed

component tumors of LFS expanded beyond the previously described “classic LFS tumors” to

include choroid plexus carcinoma, colorectal cancer, melanoma, lymphoma, gastric cancer,

Wilms tumor and germ cell tumor, the clinical definition of LFS similarly expanded65

. Today,

families that do not precisely fit the LFS-C criteria are termed “LFS-like” (LFS-L) and are

defined by a less stringent criterion in terms of the tumor types included and the age cut-offs66

.

10

The LFS-L criteria were further refined first by the “Chompret criteria” and later by the “revised

Chompret criteria” in order to account for those individuals with early-onset tumors who are

highly suggestive of LFS even in the absence of a clear family history of cancer67,68

.

1.2.2 Cancer Risk

The diagnosis of LFS carries a devastating prognosis: TP53 mutation carriers have up to

a 90% lifetime risk of developing cancer. A hospital-based analysis that investigated cancer risk

among LFS mutation carriers estimated that for males the lifetime probability of developing

cancer was approximately 73%, whereas for females it was nearly 100%. This marked difference

in lifetime cancer risk primarily resulted from the high risk of female breast cancer. In addition

to lifetime risk, probabilities of developing cancer were also examined in different age groups.

For male mutation carriers, the risk of developing cancer before the age of 15 was 19%, which

was higher than the probability in females (12%). However, in the age groups of 16 to 45, and 45

or older, the risk in females was 82% and 100% respectively; which was higher than the

probabilities observed for males (27% and 54%, respectively)69

. A subsequent study by Hwang

et al, where both TP53 mutation carriers and control non-carriers were followed for 20 years,

confirmed the results from the earlier hospital-based studies70

. This report also highlighted the

point that despite the similar distribution of TP53 mutations between males and females, the

cancer risks conferred by these mutations were significantly higher in females (p<0.001).

An important clinical feature of LFS that distinguishes it from other cancer susceptibility

syndromes is that LFS predisposes individuals towards a wide variety of cancer types. However,

the most common LFS tumors tend to include breast cancers, brain tumors, soft-tissue sarcomas,

adrenocortical carcinomas and bone sarcomas. These five cancer types account for 30.6%

(breast), 17.8% (soft-tissue), 14% (brain), 13.4% (bone) and 6.5% (adrenal gland) of LFS

11

malignancies71

. Furthermore, each tumor type also has a distinct profile in terms of the mean age

at presentation72

. For instance, brain tumors in LFS follow a bimodal distribution with two

peaks, one in childhood, and another in the 20s and 30s. On the other hand, tumors such as

osteosarcomas and soft-tissue sarcomas occur most frequently during the period of childhood

and adolescence. In addition to the disparate ages of cancer onset, multiple synchronous or

metachronous LFS tumors may also develop in the same patient73

.

1.2.3 The p53 Connection

In 1990, Malkin et. al employed a candidate gene approach in order to identify the

vertically transmitted susceptibility allele suspected of causing LFS. TP53 was chosen as a

promising candidate because of its widespread dysfunction in sporadic human cancers (>50%)

as well as evidence from transgenic mice linking mutant p53 overexpression to the development

of multiple cancers62,74

. All five of five LFS families studied in the initial report tested positive

for heterozygous point mutations spanning exons 5-9 of the TP53 gene75

. Since then, TP53

mutations have been shown to underlie 60% to 80% of “classic” LFS families, whilst on the

other hand contributing little to the etiology of LFS-L families76

. The spectrum of germline TP53

mutations in LFS closely mirrors the distribution of sporadic TP53 lesions, with the majority of

mutations manifesting as missense mutations in the highly-conserved DNA binding domain of

TP5338

. Specifically, these point mutations tend to cluster at specific “hotspots”; namely, codons

175, 245, 248, 249, 273, and 282. Due to their location either at or near the p53-DNA interface,

these recurrent “hotspot” lesions have a detrimental effect on the ability of p53 to act as a

sequence-specific transcription factor.

Furthermore, the predominance of missense mutations as the most common mode of

TP53 inactivation (>70%) is a particularly striking example of tumor evolutionary fitness62

. It is

12

thought that cancer cells acquire a distinct selective survival advantage when they retain the full

length mutant p53 protein as opposed to completely removing it. Studies show that mutant TP53

not only acquires a new oncogenic role but that it also sequesters the wild-type gene product of

TP5377,78

. For example, while overexpressing normal p53 can have profound anti-cancer effects,

overexpression of mutant p53 is sufficient to transform normal cells and increase the resistance

of cancer cells to chemotherapeutics and apoptosis79,80

. TP53 knock-in mice (+/mut) in which the

wild-type TP53 allele is swapped for a hotspot mutant also develop a more aggressive and

metastatic tumor profile when compared with TP53 knock-out mice (-/-)81

. In addition, since

mutated p53 becomes expressed at very high nuclear levels compared to its normal counterpart,

the mutant protein can also bind and inactive its close relatives, the tumor suppressors p63 and

p73, whilst also inactivating the remaining wild-type gene product of p53 by forming

dysfunctional mixed tetramers82,83

. Thus, the ubiquitous missense p53 mutants can promote

tumorigenesis through both a gain-of-function, and a dominant negative mechanism.

1.2.4 TP53 Genotype: Phenotype Correlations

Through site-directed mutagenesis of almost every single TP53 codon (>2000 mutants),

Kato et al were able to demonstrate that a patchwork of transcriptional activity defined different

p53 mutant genotypes84

. Following this revelation, multiple studies began dissecting

genotype:phenotype correlations in LFS. For example, in a study examining French LFS

families, the mean age of cancer onset was 9 years earlier for individuals carrying the more

oncogenic missense TP53 mutants85

. This suggested that earlier age of cancer onset in LFS was

directly related to the severity of the TP53 mutation. Additionally, these correlations also seem to

extend to the types of tumors that LFS patients develop. For example, LFS patients with early-

onset cancers such as brain tumors are more likely to carry nonsense, frameshift and splice TP53

13

mutations. Patients with adrenocortical cancers, on the other hand, are more likely to harbor

mutations in the non-DNA binding loops of p5371

.

Despite these advances, however, genotype:phenotype do not yet fully account for the

multitudes of tumors and the disparate ages of cancer onset typically observed in LFS patients.

Furthermore, functional differences in p53 activity cannot account for interfamilial variations in

LFS given that all affected members carry the same defective copy of the TP53 gene. Instead,

secondary genetic factors have been posited to be responsible for an important spectrum of these

clinical differences. Given the central importance of the p53 network in the etiology of LFS,

members of this signaling pathway have received particular scrutiny. To date, functional

polymorphisms in TP53 (Arg72Pro)/(PIN3), MDM2 (SNP 309), as well as DNA copy number

variations (CNVs) and telomere attrition, have been associated with cancer risk in LFS86,87,88,89,90

.

1.2.5 Secondary Modifiers in Li-Fraumeni Syndrome

The TP53 PEX4 polymorphism, which results in an Arginine to Proline substitution at

codon 72, was one of the first common variants to be implicated as an age of onset modifier in

LFS89

. Studies showed that the Pro72 and Arg72 variants of TP53 are functionally distinct. In

fact, not only does the Arg72 variant bind MDM2 with higher affinity and is thus degraded by it

faster, but as a result of greater mitochondrial localization, it can also induce apoptosis more

efficiently than the Pro72 variant91

. In LFS, carriers of the TP53 codon 72Arg allele develop

cancer at earlier ages compared to individuals who are homozygous for the 72Pro allele

(Pro:Pro)89

. The other modifier variant to be associated with cancer risk in LFS is the SNP309

polymorphism in intron 1 of the Mdm2 gene89,88

. This common genetic variation, which results

in a T to G transition, results in increased binding affinity for the Sp1 transcription factor; thus,

leading to higher basal levels of MDM2. As a result of elevated MDM2 levels, tumor cell lines

14

which are homozygous for the SNP309 (G/G) are unable to stabilize p53, and have an impaired

response to DNA damage92

. LFS patients who carry at least one copy of the SNP309 G-allele

have been shown to develop tumors at earlier ages compared to mutation carriers who are

homozygous for the T-allele89,88

. Intriguingly, the tumor accelerating effects of the Mdm2

SNP309 polymorphism seem to be amplified when present alongside the TP53 PEX4 variation93

.

Finally, a 16 base-pair duplication in intron 3 of TP53, which was reported to be associated with

lower levels of p53 mRNA in lymphoblastoid cells, has also shown age modifying activity in a

unique Brazilian LFS population carrying the R337H mutation87

. Thus, it seems that genetic

factors which impact p53 activity are plausible modifier events in patients with Li-Fraumeni

syndrome.

More recently, Shlien et. al uncovered higher levels of CNV enrichement in TP53

mutation carriers compared to controls90

. Accelerated telomere attrition has also been suggested

as a plausible mechanism for the observed reduction in the age of cancer onset through

successive generations of LFS families. Specifically, telomere length was shorter in affected

carriers compared to their non-affected and non-carrier family members86,94.

Today, it is clear

that individual LFS phenotypes are defined not only by the underlying germline TP53 mutation

but also by an important interplay of different modifier genes. Acting in tandem, different

combinations of these low-penetrance susceptibility loci could account for the wide spectrum of

different susceptibilities that characterize LFS95

. Thus, developing useful biomarkers for the

future clinical monitoring of LFS patients will require a more thorough and complete

understanding of all p53 modifying events.

15

1.3 MicroRNAs

MicroRNAs (miRNAs) are 19-25 nucleotide non-coding regulatory RNAs, that

participate in a variety of developmental pathways and whose deregulation has been implicated

in the etiology of human cancers96,97

. In 1993, Ambros et al discovered the very first miRNA

whilst screening for mutations that could block developmental stages in the worm

Caenorhabditis elegans98

. A mutant, called Lin-4, proved particularly interesting given that its

gene product was not a protein. Instead, Lin-4 produced a single stranded 22-nucleotide long

RNA molecule, which could bind with anti-sense complementarity to several sites in the

3’untranslated region (3’UTR) of lin-14. In the process, lin-4 could block the translation of the

lin-14 mRNA. It was not until 2000 that a second miRNA, named let-7, was discovered99

. More

important was the discovery that the let-7 sequence was evolutionarily conserved across

species100

. Thus, for the first time, miRNAs were recognized as an ancient and ubiquitous

eukaryotic program for regulating gene expression. Since then, more than 1000 microRNA genes

have been identified in humans 101

.

1.3.1 Biogenesis and Function

Functionally, miRNAs behave primarily as sequence-specific post-transcriptional

regulators of gene expression, affecting >60% of human genes102

. The seed sequence, typically

comprising nucleotides 2-7 of the mature miRNA sequence, is thought to specify the targeting

repertoire of each miRNA. By binding to the 3’ UTR of the complementary mRNA, each

miRNA can lead either to the degradation or translational repression of about 100 different

transcripts103

. The biogenesis of miRNAs is a multi-step process that involves numerous cellular

factors. miRNAs are first transcribed by RNA polymerase II as a primary miRNA (pri-miRNA)

transcript, that is capped and polyadenylated104

. This hairpin structure is recognized and cleaved

16

by the nuclear RNAse III endonuclease DROSHA and its partner DGCR8, leading to the

production of a 60-70 nucleotide stem-loop structure, called precursor miRNA (pre-miRNA)105

.

Alternatively, pre-miRNAs may also be produced from splicesome processing of intragenic

miRNA sequences. However they are generated, the next step involves the nuclear export of the

pre-miRNA structure by Exportin-5 and GTP-bound RAN106

. Once in the cytoplasm, the pre-

miRNA is processed by yet another endonuclease, Dicer. Dicer, along with TRBP cleaves the

pre-miRNA into a short RNA duplex. This duplex then dissociates into two single-stranded RNA

molecules (ssRNAs), namely the guide and the passenger strands. Generally, the passenger

strand is degraded while the guide strand is loaded into the RNA-induced Silencing Complex

(RISC). Within RISC, the guide strand binds with anti-sense complementarity to sites in the

sequence of its target mRNA. Depending on the extent of complementarity, RISC binding can

lead to either the degradation or translational repression of target sequences107

.

1.3.2 The MicroRNA-TP53 Network

Recently, several microRNAs have emerged as major players in the TP53 network. In

2007, the miR-34 genes (miR-34a and miR-34b/c) emerged as the first miRNA transcriptional

targets of TP53108

. In response to stress, activated p53 induces the transcriptional upregulation of

the miR-34 gene family. When ectopically expressed, miR-34 genes negatively regulate the

expression of multiple oncogenic genes, leading to cell cycle arrest and apoptosis. Importantly, a

majority of these genes, such as CDK4, CDK6, Cyclin D1 and c-MYC are known targets of

TP53-mediated repression109,110,111,112

. Thus, it seems that the miR-34 gene family represents the

missing link that controls TP53-meditated target repression. In addition to miR-34, numerous

other miRNAs, including miR-107, miR-145, miR-15a/16-1, miR-192, miR-194 and miR-215,

have been identified as TP53 transcriptional targets113,114,115,116

. Similar to miR-34, these p53-

17

induced miRNAs play an important role in negatively regulating protein repressors of the TP53

pathway.

Intriguingly, the p53 protein has also been shown to play a role in miRNA maturation117

.

Specifically, the wild-type p53 protein, but not its mutant version, was found to directly bind the

DROSHA complex and facilitate the processing of specific pri-miRNA transcripts. As a result of

enhanced p53-mediated processing, the levels of several miRNAs such as miR-16-1, miR-143

and miR-145 are increased, leading to the repression of their target genes. Thus, the proper

maturation of miRNA transcripts represents yet another important p53 function, which is lost in

the context of TP53 mutant cells. Furthermore, p53 has also been found to impact the selection

of miRNA targets by upregulating the expression of a natural molecular competitor of

miRNA:mRNA, called RNA-binding-motif protein 38 (RBM38)118

.

Not surprisingly, the TP53 mRNA transcript itself has emerged as a major target of

miRNA regulation. Multiple miRNAs such as miR-125b, miR-504, miR-33 and miR-1285

negatively regulate TP53 expression by binding to complementary sequences in the 3’UTR of

the TP53 mRNA119,120,121,122

. Indeed, activation of these oncogenic miRNAs is associated with

anti-p53 functions such as deficient cell cycle arrest, decreased cell death, and increased

stemness. The MDM2 transcript, as the most important controller of TP53 levels, is similarly

regulated by multiple miRNAs. Direct inhibition of MDM2 translation by p53-inducible

miRNAs (miR-192, miR-194, miR-215 and miR-605) promotes the activation of the p53

pathway123,36,37

. Thus, it is evident that miRNAs are not only regulated by p53, but in turn they

play important roles in regulating p53 itself, as well as its most important regulator, MDM2.

18

1.3.3 Genetic Variations in MicroRNAs

In cancer, miRNAs are often aberrantly expressed as a result of different mechanisms,

including genomic rearrangements, mutations, DNA copy number and epigenetic changes.

Recently, common point variations (SNPs) within miRNA genes have emerged as yet another

potent mechanism for miRNA deregulation. To date, more than 757 SNPs have been identified

in 440 pre-miRNA sequences. Amongst this, 178 SNPs map to the mature sequence of miRNAs

and only 50 SNPs are located in the important seed regions124

. Carlos et al were amongst the first

to demonstrate that variations in miRNA genes could cause cancer125

. In this study, they

discovered that a kindred with familial chronic lymphocytic leukemia had inherited a germ line

mutation in pri-miR-16-1, which led to lower levels of miR-16-1 expression. Subsequently,

several groups began reporting SNP-mediated miRNA dysfunction for several individual

miRNAs. For example, a SNP in the 3p strand of miR-146a was found to reduce the amount of

pre- and mature miR-146a levels by 1.9- and 1.8-fold, respectively; predisposing these patients

to papillary thyroid carcinoma126

. As a result of lower miR-146a levels, the variant C allele was

also less efficient at inhibiting its target genes. Moreover, tumors from heterozygote carriers of

this SNP had a markedly different apoptotic expression profile compared to homozygotes127

. In

other studies, SNPs in the pre-miRNA region of miR-196a-2, miR-499, miR-423, miR-492,

miR-27a, miR-631, and the pri-miRNA region of miR-26a-1, miR-124-1, miR-219-1 have also

been implicated with increased susceptibility to multiple cancer types128,129,130,125

. Based on those

studies, a SNP in a miRNA gene can be predicted to alter the function of its host miRNA in one

of three different ways: a) it can alter the transcriptional activation of the pri-miRNA; b) the

post-transcriptional processing of the pri- and pre-miRNA transcripts; and finally, c) the

interactions between miRNAs and their target mRNAs.

19

1.3.4 miR-605 and its variant: A role in Li-Fraumeni Syndrome?

Intriguingly, some miRNA regulators of the TP53 network are also known to contain

common genetic variations, which have previously been tested in cancer association studies. One

particular member of this family, miR-605 has been shown to liberate p53 from the control of the

MDM2-p53 negative feedback loop36

. These effects were shown to be mediated by miR-605

regulation of MDM2. In response to stress, Wang et al showed that miR-605 levels accumulated

in the cell, leading to lower levels of MDM2. As a result, p53 escapes MDM2 control and its

target genes are activated. miR-605 is thus a potent modulator of p53 signaling, and its

deregulation another potential mechanism through which cancer cells can escape p53-mediated

tumor suppression. This specific miRNA is also known to host a common genetic variant

(rs2043556) in its pre-miRNA sequence, which is located 74 base pairs (bps) downstream of the

5’ end of the pre-miRNA. The A>G polymorphism has a Minor Allele Frequency (MAF) of

0.344 and an energy change (ΔΔG) of 2.6 kcal/mol. In a recent study, the miR-605 SNP was

associated with gastrointestinal cancer risk131

. Furthermore, the authors showed that tumors from

patients who are homozygous for the variant allele contained lower levels of mature miR-605

compared to patients who were homozygous for the common allele. Due to its location in the

precursor structure of miR-605, this SNP could impact the post-transcriptional processing of

miR-605 by Dicer. Given the TP53 regulatory role of this miRNA, its potential deregulation by

this SNP could modulate LFS cancer risk by causing important transcriptional changes in the

levels of p53 and/or MDM2. Additional functional features of miR-605, such as its association

with cancer and its capacity to target multiple gene products, render miR-605 and its variant as

promising candidate modifiers in Li-Fraumeni Syndrome.

20

CHAPTER 2

METHODS

Study Subjects The study population consists of 55 individuals from Caucasian families with

a germline TP53 mutation who had provided informed consent to participate in the research

study. These patients fit at least one of the published LFS, LFL and revised Chompret criteria. In

cases where patients developed more than one tumor, including a benign tumor, we chose the

age at which the first malignant tumor was diagnosed.

Nucleic Acid Extraction DNA was extracted from peripheral leukocytes using standard

methods and DNA quantification was performed on a NanoDrop Spectrophotometer (NanoDrop,

Wilmington, DE). Total RNA was extracted from cell lines with TRIzol solution (Invitrogen).

miR-605 SNP Genotyping The rs2043556 variant was genotyped by Restriction Fragment

Length Polymorphism (SNP-RFLP). First, a 284-bp DNA fragment containing the pre-miR-605

region and its polymorphism was amplified by PCR: 5’-CGCCTCTTTTTGCTCATTCT-3’ and

5’-AGAGCAGTTACGCCACATGA-3’. Following amplification, genomic samples were

digested by the HinfI enzyme (New England Biolabs) and fragment lengths were assayed on a

2% w/v agarose gel. In homozygote carriers of the miR-605 A-allele, a HinfI enzyme recognition

site was created in the 284-bp PCR fragment resulting in two equal 142-bp fragments (1 band

total). In contrast, HinfI-digested PCR fragments from patients carrying the G-allele produce

three fragments: 1 uncut 284-bp DNA fragment, and 2 equal 142-bp DNA fragments (2 bands

total). To further validate the genotyping calls, 20% of our genomic samples were confirmed by

Sanger sequencing.

miR-605 Expression Vectors and RD Cell Nucleofection CMV promoter-driven

microRNA expression vectors (pCMV-MIR) containing genomic fragments (639-bp)

21

corresponding to pre-miR-605-G and pre-miR-605-A along with a control vector (no miRNA

insert) were purchased from OriGene (Rockville, MD). The sequence of both vectors was

confirmed by Sanger sequencing. These expression plasmids were transiently transfected into

RD cells by nucleofection (Amaxa Inc.). Briefly, 1 × 10^6 (confluent) cells were harvested,

centrifuged and slowly resuspended in a 100ul nucleofection solution (Amaxa) containing 2.5ug

of plasmid DNA. After transfer to the electroporation cuvette, this reaction mixture was inserted

into the Nucleofector device (Amaxa), and the T20 program was used. This nucleofection

program was chosen because it achieved the highest nucleofection efficiency in RD cells as

determined by GFP fluorescence. Total RNA was extracted 6 hours after nucleofection for real-

time RT-PCR.

Quantitative RT-PCR of mature miR-605 To evaluate expression levels of mature miR-

605, total RNA (200ng) from pre-miR-605-A- and pre-miR-605-G-nucleofected cells was

reverse transcribed into cDNA using specific stem-loop RT primers for mature miR-605 and U6

(Applied Biosystems). Subsequently, the PCR levels of these miRNAs were quantified using the

corresponding TaqMan miRNA Assays (Applied Biosystems). The amount of mature miR-605

relative to the negative control (no miRNA insert) was calculated using the 2-ΔΔCt method and

normalized to the U6 endogenous control. Results represent fold-change over control and are

shown as mean ± SEM; each experiment was conducted at least 4-times (n=4).

Quantitative RT-PCR of precursor miR-605 Similarly to our mature miR-605

quantification procedure, pre-miR-605 levels were determined by TaqMan qRT-PCR analysis.

First, total RNA (200ng) from transfected cells was reverse transcribed into cDNA using random

hexamer primers from the iScript cDNA Synthesis Kit (Bio-Rad Laboratories). In the qPCR step,

22

a custom TaqMan gene expression assay was used to measure the level of pre-miR-605. The

amount of pre-miR-605 was calculated, and results presented as described previously.

Cell Lines and Transfection Human embryonal (RD) and alveolar (Rh30)

rhabdomyosarcoma cell lines (both from Dr. A. Thomas Look of Dana-Farber Cancer Institute,

Boston, MA) were maintained in Dulbecco's Modified Eagle Medium (Wisent) with 10% Fetal

Bovine serum (Wisent). On the day of transfection, 60,000 (confluent) cells were added to a 12-

well tissue culture dish containing pre-plated transfection complexes: 2ul of Lipofectamine 2000

(Invitrogen) and 25nM of miR-605 or control miRNA mimics (Ambion). Cells were maintained

in culture at 37°C in a sealed humidified chamber (w/ 5% C02) for 24 hours before assay use.

Cell Viability Assay The viability of cells was measured by the colorimetric MTS assay

(Promega). Briefly, 3,500 RD and Rh30 transfected cells were seeded into a 96-well plate, and

maintained in culture for 96 hours. The MTS reagent was then added to each well and the cells

incubated at 37°C for a period of 2 hours. To quantify the resulting absorbance changes, a

spectrophotometer (490nm) was used. Background absorbance levels were adjusted by

subtracting the average absorbance values of negative control wells (i.e empty) from the raw

absorbance values of each experimental well. Results were normalized to control-transfected

cells and represent mean cell viability ± SEM; each experiment was conducted at least 3-times

(n=3).

Drug Sensitization Studies For the drug synergy studies, cells were transfected and replated

into a 96-well plate as described previously. On the following day, the cells were treated for 24

hours with separate doses of Actinomycin D (A1410), Doxorubicin hydrochloride (44583) and

Etoposide (E1383), all purchased from Sigma. The combinatorial treatment regimens for both

RD and Rh30 cells were as follows: 1) miR-605 mimic + vehicle; 2) miR-605 mimic + drug; 3)

23

control mimic + vehicle; and 4) control mimic + drug. After 24 hours of drug treatment, the

culture media was replaced, and the cells were allowed to recover for 72 hours before cell

viability was measured by the MTS assay. Results were normalized to control-transfected cells

and represent mean cell viability ± SEM; each experiment was conducted at least 3-times (n=3).

Colony Formation Assay The capacity of single cells to form colonies was examined using

the colony formation assay. Twenty-four hours following transfection by a miR-605 or control

mimic, RD and Rh30 cells were harvested and seeded (1,500 cells) into a 100mm culture plate.

Cells were allowed to attach and grow for 2 weeks at 37°C before their colonies were fixed,

stained by crystal violet, and counted. Results were normalized to control-transfected cells,

representing the mean number of colonies ± SEM; each experiment was conducted at least 3-

times (n=3).

Migration Assay Cell migration following miR-605 transfection was assessed using a

transwell assay. Twenty-four hours post-transfection, RD and Rh30 cells were trypsinized,

centrifuged, and resuspended in serum-free DMEM medium (60,000 cells/reaction). Transfected

cells were then placed in the upper chamber of a 8-μm polyethylene terephthalate cell culture

insert (BD Bioscience, Franklin Lakes, NJ), and allowed to migrate for 48 hours at 37°C towards

the serum-rich chemo-attractant in the lower compartment (DMEM with 20% FBS). Following

the incubation period, the cells on the lower surface of the insert membrane were washed, fixed

and then stained. One representative field at 5X magnification was counted for each insert.

Results were normalized to control-transfected cells, representing the mean number of migrated

cells ± SEM; each experiment was conducted at least 3-times (n=3).

Western Blotting miR-605- and control-transfected cells were washed with PBS, and lysed in

EBC lysis buffer (120 mM NaCl, 50 mM Tris pH 8, 0.5% NP-40) containing a cocktail of

24

protease and phosphatase inhibitors (Roche). Following protein quantification by Bradford (Bio-

Rad Laboratories), cell lysates were electrophoresed through 10% SDS-PAGE gels and

transferred to a PVDF membrane (Millipore). The membrane was blocked in Odyssey Blocking

Buffer (LI-COR Biosciences) for 1 hour, then incubated overnight at 4°C with MDM2 antibody

(Calbiochem), p53 antibody (Calbiochem), Thr202/Try204-phosphorylated ERK1/2 antibody

(Cell Signaling), total ERK1/2 antibody (Cell signaling), Thr183/Tyr185-phosphorylated JNK

antibody (Cell signaling), total JNK antibody (Cell signaling), Thr180/Try182-phosphorylated

p38 antibody (Cell signaling), total p38 antibody (Cell signaling), or Vinculin antibody

(Millipore). Signals from infrared dye-labeled anti-rabbit (680 nm) or anti-mouse (800 nm)

secondary antibodies were detected using the Odyssey Infrared Imaging System (LI-COR

Biosciences, Lincoln, NE, USA). For the MAPK protein blots (JNK, ERK and p38), the Odyssey

Infrared Imaging System Application Software (LI-COR Biosciences) was used for densitometric

analysis. Densitometry values show the average ratio of phosphorylated MAPKs over total

MAPKs of three independent blots, normalized to control-transfected RD cells at 24 hours.

Statistical Analysis Data were analyzed using Graphpad Prism 3.0 (Graphpad Software Inc.).

For functional studies, statistical analyses were performed using the unpaired two-tailed

Student’s t-test. The non-parametric Mann-Whitney test was used to compare the age of cancer

onset between the different SNP genotypes. A p value of less than 0.05 was considered to be

statistically significant.

25

CHAPTER 3

RESULTS

3.1 Functional impact of the miR-605 SNP

3.1.1 The miR-605 SNP modifies the age of cancer onset in LFS patients

Since miR-605 is an important regulator of the p53-MDM2 loop, and its variant is

predicted by RNAfold to impact the stability of its precursor structure (Supp. Figure 1), we

analyzed the association of this polymorphism with the age of cancer onset in Caucasian LFS

patients carrying germline TP53 mutations. Genotyping of blood-derived DNA samples from 55

patients was performed using SNP-RFLP. Briefly, a 284-bp DNA fragment corresponding to the

miR-605 gene was amplified by PCR (Supp. Figure 2), with the resulting product digested using

the HinfI restriction enzyme. Samples containing the G-allele of miR-605 were partially digested

compared to samples containing the A-allele (Figure 1). Randomly chosen samples were further

genotyped by direct sequencing in order to confirm the RFLP data (Supp. Figure 3).

Interestingly, results revealed that the G-allele of the miR-605 SNP was associated with a

significantly earlier age of cancer onset (p<0.05). The mean and median age of cancer onset for

LFS carriers of the G-allele (n= 17) was 12.8 years and 4 years, respectively; compared to 22.9

years and 23.5 years for carriers of the common homozygous A/A genotype (n=38) (Figure 2a).

Figure 1: Representative SNP-RFLP genotyping of the miR-605 SNP. In homozygote carriers of the

miR-605 A-allele, a HinfI enzyme recognition site is created in the 284-bp PCR amplified DNA fragment

26

resulting in two equal 142-bp fragments. PCR fragments from heterozygote carriers of the G-allele

contain one allele which is uncut and one allele which is cut, leading to the production of 1 uncut 284-bp

DNA fragment and 2 equal 142-bp DNA fragments

Figure 2. (2a): Age of cancer onset in TP53 mutation carriers according to miR-605 genotype.

Germline DNA samples from 55 Caucasian TP53 mutation carriers were genotyped for the miR-605

variant (rs2043556) using SNP-RFLP. Samples were divided according to the presence of the G-allele.

TP53 mutation carriers with the A/G and G/G genotypes developed cancer at earlier ages compared to

individuals with the A/A genotype. (2b): Percentage of unaffected TP53 mutation carriers for each

miR-605 genotype as a function of age of cancer onset.

p-value < 0.05

2a

2b

27

3.1.2 The miR-605 SNP affects the processing efficiency of pre-miR-605

To determine the functional consequences of the miR-605 SNP, microRNA plasmids

(pCMV-MIR) containing genomic fragments (639-bp) corresponding to pre-miR-605-G and pre-

miR-605-A were nucleofected into the rhabdomyosarcoma cell line (RD) (Figure 3); these

plasmids were sequence confirmed (Figure 4a). By qRT-PCR, RD cells transfected with pre-

miR-605-A expressed 2.6 times more mature miR-605 compared to cells transfected with pre-

miR-605-G (Figure 4b). In contrast, the precursor form of miR-605 (pre-miR-605) was

expressed at similar levels in both pre-miR-605-A and pre-miR-605-G transfected cells,

indicating a defect in miR-605 processing from its pre- to mature form (Figure 4c). To compare

the efficiency of Dicer processing between the two variants, the expression level of mature miR-

605 was divided by that of pre-miR-605. The processing efficiency of the pre-miR-605-G

plasmid was 65% lower than the processing efficiency of the pre-miR-605-A plasmid (Figure

4d).

Figure 3: Schematic representation of SNP expression experiment

28

Figure 4. (4a): Sanger sequencing of the pre-miR-605-A and pre-miR-605-G vectors. Results

confirm the correct sequence with the only difference being in the SNP. (4b): Impact of the miR-605

SNP on mature miR-605 levels. Three different miRNA expression plasmids containing the following

constructs were used: pre-miR-605-A, pre-miR-605-G, no miRNA insert. RD cells were nucleofected and

total RNA was isolated 6 hours post-nucleofection. Compared to the empty vector, mature miR-605

levels were upregulated 137.1 fold in RD cells transfected with pre-miR-605-A vector compared to 52.4

fold upregulation in RD cells transfected with pre-miR-605-G. Results are normalized to the negative

control and represent mean ± SEM. n=4. * p< 0.05. (4c): Impact of the miR-605 SNP on precursor

miR-605 levels. Precursor levels of miR-605 were quantified using the same methodology and the same

RNA samples as our mature miR-605 expression results. (4d): Processing efficiency of pre-miR-605

according to genotype. The levels of mature miR-605 were divided by the levels of precursor miR-605

in order to calculate the processing efficiency of each variant.

*

*

4a

4b

4c

4d

*

29

3.2 Role of miR-605 in TP53 mutant cells

3.2.1 miR-605 affects cell viability and colony formation in TP53 mutant cells

Although miR-605 has been shown to have potent tumor suppressive activity in TP53

wild-type type cells, its effects on TP53 mutant cells have never been tested. To directly assess

the function of miR-605 in TP53 mutant cells, we overexpressed a commercial miR-605 mimic

into two RMS cell lines carrying homozygous and heterozygous TP53 mutations (RD and Rh30).

The effects of miR-605 expression on cellular function were examined by the MTS and colony

formation assays. Overexpression of miR-605 resulted in a significant reduction in cell viability

and clonogenicity (Figure 5a-c). Western blotting revealed that while MDM2 protein levels

were down regulated, p53 levels were not affected as a result of miR-605 overexpression

(Figure 5d). These data suggest a tumor suppressive role for miR-605 even in the absence of an

activated p53 response.

Figure 5. (5a): Effect of miR-605 overexpression on cell viability in TP53 mutant cells. RD and

Rh30 cells were transfected with either a miR-605 mimic or a control mimic; 96 hours post-transfection,

the MTS assay was performed to measure levels of cell viability. Compared to controls, both cell types

demonstrated lower levels of viability following miR-605 overexpression. Results are normalized to

control-transfected cells and represent mean ± SEM. n=3. * p< 0.05. (5b): Effect of miR-605

overexpression on colony formation in TP53 mutant cells. RD and Rh30 cells were transfected as

described previously. Two weeks post-transfection, colonies from miR-605- and control-transfected cells

were fixed, stained and counted. miR-605-transfected RD and Rh30 cells contained lower numbers of

RD Rh30

* *

5a

5b

RD Rh30

* *

30

colonies compared to control cells. Results are normalized to control-transfected cells and represent mean

± SEM. n=3. * p< 0.05.

(5c): Representative plates from colony formation assay. (5d): Western Blot of MDM2, p53 and

Vinculin in RD cells. Analysis reveals MDM2 downregulation at 24hrs and 48hrs following miR-605

transfection. Interestingly, miR-605 overexpression had no effect on p53 protein levels.

3.2.2 miR-605 affects the chemosensitivity and migration of TP53 mutant cells

Since our hypothesis suggested that SNP-mediated miR-605 deregulation could result in a

more aggressive cancer phenotype, we further sought to investigate the role of miR-605 in the

chemo-resistance and migratory potential of TP53 mutant cell lines. Similarly to our previous

experiments, overexpression of miR-605 was accomplished by transiently transfecting cells with

a commercial miR-605 mimic, along with the appropriate controls. Following our transfection,

these TP53 mutant RMS cells were then treated with one of three different chemotherapy agents;

Actinomycin D, Doxorubicin or Etoposide. Our combinatorial regimens were as follows: 1) drug

Control miR-605

RD

Rh30

5c

5d

31

+ miR-605; 2) drug + miRNA control; 3) Vehicle + miR-605; and 4) Vehicle + miRNA control.

Our MTS results showed a significant attenuation in the chemosensitivity of both RD and Rh30

cells following miR-605 overexpression. Specifically, treated cells showed a significant loss in

cell viability when combined with miR-605 as compared to treated cells that were control

transfected (Figure 6a-c). To measure the effects of miR-605 on cell migration, a classic

chemotactic transwell assay was employed. miR-605- and control-transfected cells were allowed

to migrate to the lower chamber for 48 hours before they were fixed, stained and counted.

Significantly fewer RD and Rh30 cells were attracted to the chemo-attractant (20% FBS) in the

miR-605-transfected group as compared to the control (Figure 7a-b). Taken together, these data

suggest that higher miR-605 expression was associated with a less aggressive cancer phenotype.

RD Rh30 6a

*

*

32

Figure 6: Effect of miR-605 on RD and Rh30 chemosensitivity. A miR-605 commercial mimic

was used to transfect RD and Rh30 cells, followed by the addition of a single chemotherapeutic (6a:

Eto=Etoposide, 6b: Dox=Doxorubicin, 6c: Act=Actinomycin). An MTS assay, measuring levels of cell

viability was employed to assess the chemosensitizing effects of miR-605 overexpression. In each case,

miR-605-transfected cells treated with a chemotherapeutic agent measured lower levels of cell viability

RD

RD

Rh30

Rh30

** *

***

**

6c

6b

33

compared to control cells treated with the same drug. Results are normalized to control-transfected +

vehicle-treated cells and represent mean ± SEM. n=3. * p< 0.05, ** p <0.01, *** p<0.001.

Figure7. (7a): Effect of miR-605 overexpression on cell migration in TP53 mutant cells. RD and

Rh30 cells were transfected as described previously. Twenty-four hours post-transfection, miR-605- and

control-transfected cells were seeded into serum-free media and allowed to migrate for forty-eight hours.

Migrated cells were then fixed, stained and counted. miR-605-transfected RD and Rh30 cells migrated at

lower levels compared to control cells. Results are normalized to control-transfected cells and represent

mean ± SEM. n=3. * p< 0.05, ** p <0.01, *** p<0.001. (7b): Representative inserts from migration

assay.

3.2.3 miR-605 overexpression activates the MAPK pathway in TP53 mutant cells

Since the tumor suppressive effects of miR-605 did not seem to be dependent on p53

activation, we hypothesized that miR-605 acted through alternative signalling pathways. The

MAP kinase family was probed because of previous work in our lab implicating these pathways

in RMS biology. At the same conditions as the aforementioned cell transfections, an increase in

the phosphorylated forms of p38, ERK and JNK were detected, whereas total level of these

proteins remained relatively constant (Figure 8).

RD Rh30

* ***

7a

7b

34

Figure 8: Western Blot of MAPK proteins in Rd cells. Western Blot analysis reveals an increase in

the phosphorylated forms of JNK, ERK and p38 at 24hrs, 48hrs and 72hrs following miR-605

transfection. Densitometry values show the average ratio of phosphorylated/total MAPKs of three

independent blots and are normalized to control-transfected RD cells at 24hrs.

Densitometry (RU) 1.0 5.4 2.7 10.3 1.9 10.9

Densitometry (RU) 1.0 2.0 1.6 2.3 2.0 4.2

Densitometry (RU) 1.0 1.6 1.3 1.9 1.4 2.5

35

CHAPTER 4

DISCUSSION

4.1 miR-605 SNP and LFS Cancer Risk

To our knowledge, this is the first report describing an association between a common

SNP in a pre-miRNA gene and cancer risk in Li-Fraumeni Syndrome. In this work, we showed

that the G-allele of the miR-605 SNP was associated with a significant reduction in the age of

cancer onset in a cohort of Caucasian germ-line TP53 mutation carriers. Functionally, the G-

allele of miR-605 appeared to cause a defect in the processing efficiency of its host miRNA,

leading to a 2.6 fold reduction in the amount of mature miR-605 as compared to the more

common A-allele. Significantly, no such difference was detected in the precursor levels of miR-

605. These findings are consistent with a recent report in which mature miR-605 expression

levels were shown to be attenuated in patients with colorectal cancers carrying the G/G

genotype131

. Expanding on those findings, our work establishes cytoplasmic miRNA processing

by Dicer as a potential mechanism for miR-605 SNP-mediated dysfunction. Thus, the miR-605

SNP adds to a growing list of pre-miRNA polymorphisms which can impact the post-

transcriptional processing of their host miRNA and which in the process predispose patients to

increased cancer risk.

As previously discussed, SNP-mediated defects in miRNA processing have become a

well-established feature of many human cancers such as breast, esophagus, bladder, lung, and

thyroid carcinomas132,128,133,134,135,126

. Changes in RNA duplex stability represent one particular

mechanism through which SNPs can impact miRNA biogenesis and function. Such changes can

alter the kinetics of several miRNA processes such as RNA unwinding, cleavage, strand

36

selection and RNA-protein interactions, all of which play a critical role in miRNA

maturation136,137,138

. The miR-605 SNP, similar to other pre-miRNA SNPs, is known to alter the

conformational stability of its pre-miRNA (Supp. Figure 1). Specifically, the secondary

structure of pre-miR-605 containing the wild base pairing G:U is calculated to be less stable than

the one with the SNP base pairing G:C (∆∆G=-2.6 kcal/mol). Importantly, this difference in

Gibbs free energy is comparable to that of previously-reported functional pre-miRNA SNPs

(Supp. Table 1). Given that the unwinding of pre-miRNAs is an important miRNA processing

step, less stable RNA duplexes such as the pre-miR-605-A variant would be predicted to be

processed faster and more efficiently as compared to the more stable pre-miR-605-G variant.

This mechanism could potentially explain the observed overexpression of mature miR-605 from

the A-allele as well as the lack of such difference in the precursor levels of miR-605 between

these two variants.

Because each miRNA is thought to regulate >100 different gene products, SNP-mediated

deregulation of miR-605 can be predicted to have widespread biological effects. Specifically,

transcripts normally regulated by miR-605, including MDM2, could be less efficiently regulated

as a result of lower miR-605 expression. In LFS patients carrying a mutant TP53 gene, higher

levels of MDM2 have been consistently shown to be associated with younger ages of tumor

onset. Functionally, these events have been linked to either deregulated MDM2 and/or p53

function87,93,88

. It is possible that LFS patients carrying copies of the G-allele produce lesser

amounts of miR-605, and thus have higher levels of its target transcripts. As a result of elevated

MDM2 levels, these cells would be predicted, as has been shown in some studies, to have an

impaired p53 response to DNA damage and other forms of genetic insults92

. Because LFS

patients already lack a functional copy of p53, further impairment of the p53 pathway could

37

render them at an even greater risk of developing cancer. Thus, from this work, we add yet more

evidence that regulators of the p53 pathway are promising genetic modifiers in LFS and that

their SNPs remain an important consideration in attempting to predict cancer risk in these

patients.

4.2 miR-605 Action and Signaling in TP53 Mutant Cells

Previously, miR-605 had been shown to exhibit potent tumor suppressive functions in

TP53 wild-type cells, but not in isogenic cell lines lacking the TP53 gene (TP53 -/-). Given these

findings, miR-605 was assumed to be dependent on p53 signaling for its biological effects37

. In

this report, we show for the first time that miR-605 behaves as a tumor suppressor, despite the

presence of TP53 mutations. Overexpressing miR-605 significantly reduced cell viability, colony

formation, cell migration and chemo-sensitivity in two RMS cell lines with differing TP53

mutant status. These findings suggest that miR-605 deregulation is a plausible modifier of cancer

phenotypes in TP53 mutation carriers, and they strengthen our hypothesis that expression

changes caused by the miR-605 SNP could be partly responsible for an accelerated tumor onset

in LFS. Importantly, the cytotoxic effects of miR-605 overexpression do not seem to rely on p53

activation. Following miR-605 overexpression in RD cells carrying a homozygous R248W

mutation, no changes in p53 protein levels were detected. Instead, our results suggest the

involvement of the Mitogen Activated Protein Kinase (MAPK) family as a potential mechanism

for miR-605-mediated tumor suppression.

The MAPK family of protein kinases are serine-threonine kinases that include c-Jun N-

terminal kinase (JNK), p38, and extracellular signal-regulated kinase (ERK), each with a well-

established role in carcinogenesis. The classical MAPK pathways form a multi-tier linear

signalling cascade that involves the sequential phosphorylation and activation of MAP3K,

38

MAP2K and finally MAPK itself. Upon activation by a number of different stimuli, including

mitogenic factors, cytokines, and cellular stress, the MAPK proteins lead to the phosphorylation

and activation of an important class of transcription factors that control cellular proliferation,

differentiation, survival and apoptosis. Interestingly, all three MAPKs (JNK, p38 and ERK) have

been shown to be regulated by numerous miRNAs, including miR-497, -101, and -143 139,140,141

.

However, this is the first reported instance of MAPK activation as a result of miR-605 signaling.

At this point, it remains unclear as to whether MAPK activation is directly related to miR-605’s

tumor-suppressive activities. From work in our lab as well as others, we know that MAPK

activation can lead to tumor suppression in the form of increased apoptosis and cell cycle arrest

but in order to establish a direct link with miR-605 activation, combinatorial treatments with

MAPK inhibitors/MAPK siRNAs and miR-605 mimics need to be performed. Understanding

whether MAPK inhibition/depletion can protect against miR-605-mediated tumor suppression

will help in our understanding of miR-605 function and its potential role in cancer and LFS.

Furthermore, the molecular link between miR-605 overexpression and MAPK activation

remains unknown. So far, miR-605 has only two validated targets: MDM2 and Sec24D, a protein

involved in cellular trafficking142,37

. While MDM2 has a well-established role in cancer, little is

known about the cancer role if any, of Sec24D. Furthermore, neither MDM2 nor Sec24D seem to

control MAPK activation. In the case of MDM2, the opposite is in fact true: JNK activation leads

to the phosphorylation of MDM2 and the inhibition of the MDM2-p53 interaction. In order to

explore further signalling pathways that may be regulated by miR-605 and thus potentially

involved in MAPK activation, we performed an in-silico analysis of predicted miR-605 targets.

Using a combinatorial miRNA target prediction approach, we screened the UTR sequences of all

known protein-coding genes for complementarity to the seed sequence of miR-605. A list of 12

39

putative miR-605 targets was generated from the common predictions of six microRNA

prediction algorithms (DIANA, PITA, TargetScan, MicroCosm, miRDB, TargetScan_cons).

From this initial list, PubMed searches with the keywords “<gene name> MAPK” and “<gene

name> p53” was performed to identify targets that had an established role in these signalling

pathways (Supp. Table 2). Probing for the biological relevance of these interactions and their

effects on MAPK and/or p53 signalling would be a starting point to expand our understanding of

miR-605-mediated MAPK activation and tumor suppression.

List of predicted miR-605 targets: ADAMTS6, CDH2/N-Cad, COPS2, DGKG, DHX8,

HIVEP2, IER5, MTMR8, SLAIN2, SLITRK2, TSN, VAPB

4.3 Study Limitations

In this study, we relied on two specific cell line models: RD and Rh30. These cell lines

were selected because of their mutant TP53 status as well as the fact that RMS is an important

component tumor of LFS. However certain limitations do arise; for one, we only tested the

effects of miR-605 overexpression on TP53 mutant cells carrying the R273C and R248W

hotspot missense mutants. Although these two mutations are some of the most commonly

occurring sites of TP53 lesions, it is possible that the effects of miR-605 could be dependent on

other types of TP53 mutations. Future experiments examining cell lines with different TP53

mutant status should be carried out to further delineate the role of this miRNA in the context of

TP53 mutations.

Secondly, since we used transient transfections as our method for transducing miR-605,

we were not able to examine the effect of these two SNP variants on the tumor suppressive

functions of miR-605. Future experiments in which the two variants are stably transfected into

RD cells or another cell type would offer a more powerful system of dissecting the functional

40

differences between these two variants. It remains possible that more sustained MDM2 inhibition

by miR-605 could activate parts of the p53 pathway. Again, a stably-expressed miR-605 system

would be most useful in clarifying this possibility. Thirdly, we were unable to perform knock-

down experiments because none of these cell lines express miR-605 at high levels. Lastly, even

though our results are strengthened by our SNP expression analyses, the rarity of this syndrome,

and thus our low sample size remains another important limitation of this study. Larger

independent cohorts of LFS patients would be necessary to further verify these results.

41

CHAPTER 5

CONCLUSION/FUTURE PERSPECTIVES

In summary, our results identified a miR-605 SNP as a potential modifying event in TP53

mutation carriers. The rs2043556 SNP was associated with a lower age of cancer onset in LFS

patients, and caused a decrease in the expression levels of its mature miRNA, indicating a SNP-

mediated processing defect in miR-605 maturation. In addition to defining a novel MAPK

signalling role for miR-605, our findings further implicate miR-605 overexpression in

attenuating cell viability, colony formation, cell migration and chemosensitivity in TP53 mutant

cells. Future work should focus on elucidating the functional consequences of the miR-605 SNP

on p53 and MAPK pathway signaling whilst also pursuing a more general understanding of miR-

605 tumor suppression. Finally, the role of miR-605 in suppressing MDM2 expression, and its

association with cancer risk in LFS suggests that modulating miR-605 might represent a novel

therapeutic strategy for the successful treatment of both TP53 wild-type and mutated tumors.

42

APPENDIX 1

SUPPLEMENTARY FIGURES

Supplementary Figure 1: Secondary structures of wild-type and variant pre-miR-605. RNAfold was

used to predict the RNA secondary structures and the Gibbs free energy of (A) pre-miR-605-A, (B) pre-

miR-605-G.

Minimum Free Energy: -52.3 kcal/mol

|∆∆G|: 2.6kcal/mol

pre-miR-605-A

Minimum Free Energy: -54.9 kcal/mol

pre-miR-605-G

43

CGCCTCTTTTTGCTCATTCTTTAAAGTAGGAACTTTGGTAGAACTTTCACAGCCTGTAACATAT

GTCTCTAGCCCTAGCTTGGTTCTAAATCCCATGGTGCCTTCTCCTTGGGAAAAACAGAGAAGGC

ACTATGAGATTTAGAAT/CCAAGTTAGGACTGCAGATACAGGTTACCTATGTTACAGGCTGACA

GCCACAGGTATATTGCTCTCTGCACATGTGTTTTTTCCTGGCCTCTCAATGACATTATAAGCTT

CTATTATACCTCATGTGGCGTAACTGCTCT

-Primer_Forward: CGCCTCTTTTTGCTCATTCT (Tm: 59.6 ° C, GC content: 45.0 %)

-Primer_Reverse: AGAGCAGTTACGCCACATGA (Tm: 59.5 °C, GC content: 50.0 %)

Supplementary Figure 2: Sequence of DNA primers (in blue) used to amplify a 284-bp PCR product

containing the pre-miR-605 gene (in red) and its rs2043556 SNP (in green).

Supplementary Figure 3. Representative Sanger sequencing of miR-605 PCR amplified product from

a) a patient sample with the homozygous A/A genotype and b) a patient sample with the heterozygous

A/G genotype

a

b

44

APPENDIX 2

SUPPLEMENTARY TABLES

Supplementary Table 1: Validated functional pre-miRNA SNPs with similar |∆∆G| to rs2043556 SNP

Supplementary Table 2: Predicted miR-605 targets in MAPK and/or p53 signaling

Gene Symbol

Gene Name

p53

Signaling

MAPK

Signaling

Reference(s)

(Pubmed ID)

CDH-2/N-CAD Cadherin-2/Neuronal

Cadherin

✓ 12213839

17409417

COPS2/ALIEN COP9 Signalosome

Subunit 2

✓

11285227

DHX8 DEAH Box Protein 8

✓

21460037

Gene

SNP ID

Variation

|∆∆G|

(kcal/mol)

Effect on

mature miR

levels

Reference(s)

(Pubmed ID)

miR-890 rs138166791 G/C 3.4 Downregulated 19617315

miR-149 rs2292832 T/C 2.2 Upregulated 23272122

miR-140 rs7205289 C/A 2.4 Downregulated 20358594

miR-146a rs2910164 G/C 2.8 Downregulated 18474871

miR-27a rs11671784 G/A 0.8 Downregulated 23246964

miR-34a rs72631823 C/T 0.87 Upregulated 23828613

miR-612 rs12803915 C/A 0.2 Upregulated 23077621

45

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