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The talk will focus on new concepts regarding the development and progression of breast cancer and the consequences and implications for clinical testing facilities.
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Tumor Heterogeneity in Breast Cancer, Concepts and Tools
Anthony M Magliocco MD FRCPC FCAP Chair of Anatomical Pathology and
Executive Director of Esoteric Laboratory Services H. Lee Moffitt Cancer Center
March 13, 2013
Disclosures
§ Ventana Medical Systems
Overview
§ Discussion of Tumor Heterogeneity § Tools for analysis
w IHC w Image analysis w Genomics w CTCs
§ Future directions
http://library.med.utah.edu/WebPath/jpeg3/BREST003.jpg
Geographic and Temporal Variation in Tumors
Estrogen Receptor
HER2
Basal Keratins
EGFR
Molecular Breast Classification
Tumor Evolution
Invasion
Morphology of Tumor Progression
Lympahtic Space
Invasive Ductal Cacinoma
http://www.flagshipbio.com/wp-content/uploads/2011/09/Heterogeneity-of-HER2-staining-in-breast-cancer.png
HER2 Heterogeneity
http://www.sciencedirect.com/science/article/pii/S0304419X09000742#gr1
TUMOR EVOLUTION
http://www.nature.com/nrg/journal/v13/n11/images/nrg3317-f2.jpg
§ Immunohistochemistry is a powerful analytical tool
Estrogen receptor
Estrogen Receptor
Copyright © American Society of Clinical Oncology
Harvey, J. M. et al. J Clin Oncol; 17:1474 1999
Fig 2. Univariate DFS curves for all possible total IHC scores in patients receiving any adjuvant endocrine therapy (almost always tamoxifen)
ACIS EVALUATION of Ki67
MAGLIOCCO LABORATORIES SABCS 2010
Finding the Cut Point
MAGLIOCCO LABORATORIES SABCS 2010
16.25%
MAGLIOCCO LABORATORIES SABCS 2010
16.25%
MAGLIOCCO LABORATORIES SABCS 2010
FLUORESCENT IMAGING
• Several Advantages over DAB – More markers – Greater Dynamic Range – Easier channel separation for imaging
PR DAPI CTK
Composite Magliocco Laboratory
DAB-‐IHC vs IF-‐IHC
AQUA = Average target pixel intensity/Area of the defined compartment
DAB / Pathologist HistoRx AQUA
AQUA Scoring is Reproducible
R² = 0.99502
0
2000
4000
6000
8000
10000
12000
0 2000 4000 6000 8000 10000 12000
Her
2 C
ytop
lasm
ic A
QU
A - 0
3Dec
10
Her2 Cytoplasmic AQUA - 30Nov10
Run to Run Variation: Her2 cAQUA (Serial Sections)
Spearman = 0.986
ER AQUA interlab
HistoRx Scoring vs Pathologist Scoring • ER scoring from serial secCons of an 18 TMA Breast Cancer series
• Stained by DAB-‐IHC and scored by a pathologist or Stained by IF-‐IHC and scored by AQUA
Pathologist Score
AQUA Score
ER: Pathologist vs AQUA (All PaCents)
DAB-‐IHC vs AQUA-‐IHC
Pathologist Score
X-tile analysis
AQUATM: ERCC1 Cervix
Magliocco
Created by Tex
0 2 4 6 8 10
Year of Study
0.0
0.2
0.4
0.6
0.8
1.0
Adj
uste
d Pr
opor
tion
Aliv
e (O
vera
ll)
p-value = 0.52
IHC = 0,1,2
IHC = 3
Overall survival by ERCC1, IHC score
Created by Tex
Overall survival by ERCC1, AQUA™ score
0 2 4 6 8 10
Year of Study
0.0
0.2
0.4
0.6
0.8
1.0
Adj
uste
d Pr
opor
tion
Aliv
e (O
vera
ll)
p-value = 0.031
AQUA < 975
AQUA > 975
ERCC1 8F1 ERCC1 FL297
ERCC1 8F1 vs FL297
AQUA measurment of ERCC1 expression in Nucleus of TMA specimens
Ki67
pS6
pS6 different antibody clones via AQUA analysis – Cervix Cancer
pS6 AQUA®
cytoplasmic
pS6 status and OS
High pS6 status was associated with better overall survival in the RT+chemo cohort
High
Low
EGFR Ki67 CTK DAPI
Masking EGFR High vs EGFR Low Tumour Areas
Low EGFR/Ki67 RaCo Predicts Poor Survival
Kaplan-‐Meier survival curves measuring the overall disease specific survival based on straCficaCon by EGFR/Ki67 RaCo. The average raCo for each paCent (from replicate histospots) was used and paCents were categorized as having a high raCo if they fell within the top 3 quarCles of expressers (n=68). Five year esCmates for overall survival are 78% for high RaCo paCents and 39% for low RaCo paCents.
RTOG 0128 cd34 vessel density
Core 20 1%
core 84: 459.4 core 50: 59.9 "
Cervical Carcinoma – CAIX (AQUA™) CAIX
Stromal Caix in HPV neg HN cancer
Developing a scoring method to examine the relationship between CAIX and Ki67
CAIX and Ki-67 CARO CERVIX COHORT OS
High Ki-67 within CAIX high tumor regions was associated with better OS [HR 0.83 (0.7-0.97), p=0.023]
Tonsil CD4 red CD8 blue
PCK=Green CD4=Red CD8=Blue
Two tumors with strong tumor and stroma CD4/CD8 cell staining
CD4/CD8 RaCo May Predict Treatment Response
CD4 RED
CD8 BLUE
FRACTAL GEOMETRY IN CANCER
Prostate Cancer: Gleason Grading System
Low Grade (Well
Differentiate) • Slow growing • Look similar to
normal cells • Less
aggressive
Schematic Diagram by Dr. D. F. Gleason http://www.cancer.prostate-help.org/cagleas.htm
High Grade (Poorly
Differentiated) • Fast growing • Look very
different from normal cells
• Very aggressive (spread quickly)
Fractal Geometry
Fractal Dimension • Can be used as a measure of the level of
structural complexity
FD = 1
FD = 1
FD = 1.5
Methods: Staining Example: Breast Cancer Specimens
Hematoxylin & Eosin Pan-keratin
Methods: Staining and Segmented Structures
75.1=BD
69.1=BD
H&E
Pan-keratin MAGLIOCCO LABORATORIES
Results: Effects of Staining (Prostate Cancer)
Tambasco, M. Magliocco. .Micron.2008
1.2
1.28
1.36
1.44
1.52
1.6
1.68
1.76
1.84
1.92
2
Benign HighGrade
Benign HighGrade
Frac
tal D
imen
sion
H&E Pan-Keratin
Sample Sizes 63 Benign 19 High Grade
Calgary Tamoxifen Cohort
• Retrospective annotated series Cases between 1980-1999
• Over 800 Cases enriched with 200 events • No chemotherapy • Tamoxifen given to many regardless of ER
status
Kaplan-Meier Estimate of Survival
FD < 1.71
FD ≥ 1.71
369 Breast Cancer Patients Optimal fractal dimension cut-point = 1.71
p = 0.002
MAGLIOCCO LABORATORIES
MAGLIOCCO LABORATORIES SABCS 2010
Validation: Fractal Map
1.8
1.8 1.8
1.8
1.5
1.5
1.5
1.5
1.4
1.4 1.4
1.4
1.7
1.7
1.7
1.7
1.2
1.2 1.2
1.2
1.3
1.3
1.3
1.6
1.6
Outline of Takagi Surface Fractal Map
MAGLIOCCO LABORATORIES
Local Fractal Dimension
Fractal Dimension Map
MAGLIOCCO LABORATORIES
Fractal Map: Breast Cancer
1
3
2
4
1
3
2
4
MAGLIOCCO LABORATORIES
OTHER SOURCES OF HETERGENEITY
Quebec probes flawed cancer tests Health officials compare faulty breast exam results to problems in Newfoundland, promise fast action
PROBLEMS WITH “ROUTINE” TESTING
National Standards Immuno cIQc
CA
SE
Laboratory
Pre-Analytic
Analytical
Post-Analytical
Understanding VariaCon in Biomarker Analysis
Specimen quality PreparaCons
Immunohistochemistry Use automated system
standardize scoring
http://www.nasa.gov/images/content/235791main_image_1098_946-710.jpg
http://news.nationalgeographic.co.uk/news/2009/06/photogalleries/fathers-day-2009-animal-dads-pictures/images/primary/090618-07-greatest-animal-dads-emperor-penguin_big.jpg
.
Rakha E A et al. JCO 2008;26:3153-3158
©2008 by American Society of Clinical Oncology
Grade and Outcome Breast Ca
Before 1989
After 1989
Grade Changes with Treatment
Next Generation Sequencing
Emerging Breast Cancer Biomarkers?
DC Koboldt et al. Nature 000, 1-10 (2012) doi:10.1038/nature11412
Intratumoral genetic heterogeneity in an advanced primary CRC. Three-dimensional reconstruction of a tumor (Table IV, case 4) that was divided into two parts (1 and 2) and then
serially sectioned into five slices (A–E) of ∼4.5 mm thickness.
Losi L et al. Carcinogenesis 2005;26:916-922
Carcinogenesis vol.26 no.5 © Oxford University Press 2005; all rights reserved.
Copyright ©2004 American Association for Cancer Research
Allard, W. J. et al. Clin Cancer Res 2004;10:6897-6904
Tumor Cells Circulate in the Peripheral Blood of All Major Carcinomas but not in Healthy Subjects or Patients With Nonmalignant Diseases W. Jeffrey Allard1, Jeri Matera1, M. Craig Miller1, Madeline Repollet1, Mark C. Connelly1, Chandra Rao1, Arjan G. J. Tibbe1, Jonathan W. Uhr2 and Leon W. M. M. Terstappen1
Circulating tumor cells are found in patients with metastasis, and predict survival in breast cancer
Summary
§ Tumors evolve in 4d § We need better assays and tools for
reproducible measurements § We need greater focus on reducing pre
analytical variation § We need better collections of tumours after
treatment and in metastatic setting
Future
§ Anatomical Pathology
w Integration of: ● Medical data ● Imaging ● Advanced Histology ● Genomics ● CTCs and biomarkers ● Huge amounts of multidimensional data requiring
systems biology aproaches
MAGLIOCCO LABORATORIES Tom Baker Cancer Centre 2010
Acknowledgements -‐ Funding