Tumour heterogeneity in breast cancer. Leticia De Mattos-Arruda, MD, M.Sc Memorial Sloan Kettering Cancer Center Vall d Hebron Institute of Oncology

Tumour heterogeneity in breast cancer Leticia De Mattos-Arruda, MD, M.Sc Memorial Sloan Kettering Cancer Center Vall d’Hebron Institute of Oncology ...
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Tumour heterogeneity in breast cancer

Leticia De Mattos-Arruda, MD, M.Sc Memorial Sloan Kettering Cancer Center Vall d’Hebron Institute of Oncology

Outline  Introduction  Intra-tumour heterogeneity: spatial and temporal  Inter-tumour heterogeneity  How can tumour heterogeneity be overcome?

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Breast tumours are heterogeneous  Breast cancer is a complex disease characterised by inter- and intra-tumoral heterogeneity at the morphologic and molecular levels. Morphology

Gene expression

Genetics

Luminal A Luminal B HER2-enriched Basal like Normal breast Claudin low

Reprinted by permission from Macmillan Publishers Ltd: Weigelt B and Reis-Filho JS. Nat Rev Clin Oncol 2009;6(12):718-730 © 2009; Reprinted by permission from Macmillan Publishers Ltd: 15.12.14 3 Perou CM et al. Nature 2000;406(6797):747-752 © 2000; Sørlie T et al. Proc Natl Acad Sci U S A 2001 98(19):10869-10874 copyright (2001) National Academy of Sciences, U.S.A; The Cancer Genome Atlas Network. Nature 2012;490:61-70

Breast tumours are morphologically heterogeneous  Tumour morphologic heterogeneity Mucinous

Micropapillary

Papillary

Metaplastic

Secretory

Lipid-rich

Apocrine

Acinic cell

15.12.14 Reprinted by permission from Macmillan Publishers Ltd: Weigelt B and Reis-Filho JS. Nat Rev Clin Oncol 2009;6(12):718-730 © 2009

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Breast tumours can be immunophenotypically heterogeneous  Immunophenotypic heterogeneity: HER2 overexpression

HER2-negative

HER2-positive

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Reprinted by permission from Macmillan Publishers Ltd: De Mattos-Arruda L et al. Nat Rev Clin Oncol 2013;10(7):377-389 (Micrograph Dr. Reis-Filho, Dr. Vicent-Salomon) © 2013

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Breast tumours are heterogeneous within and between subtypes  Molecular heterogeneity: the collection of genetic alterations differ within and between breast cancer intrinsic subtypes

Luminal A

Luminal B HER2enriched

Basal like

15.12.14 The Cancer Genome Atlas Network. Nature 2012;490:61-70 Creative Commons license

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Breast tumour heterogeneity is important in the clinic  Tumour heterogeneity may affect clinical diagnosis, treatment, and disease recurrence / progression.  Clinical and therapeutic decisions based on individual biopsies:  not representative of the entire tumour burden  not real-time assessment  Understanding tumour heterogeneity:  to characterise patients’ cancers and guide their treatment  to monitor the emergence of drug resistance and select tailored therapy http://www.shongjog.files.wordpress.com/2011/01/kaleidoscope-image-created-at-sumopaint.png

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Intra-tumour genetic heterogeneity

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Spatial heterogeneity: leading to sample bias?  Spatial heterogeneity: genetic variation across different locations within a single tumour  Biopsies of different areas may produce different results

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Gerlinger M et al. N Engl J Med 2012;366(10):883-892. Reproduced with permission of MASSACHUSETTS MEDICAL SOCIETY in the format Use in an e-coursepack via Copyright Clearance Center

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Temporal heterogeneity: ESR1 mutation as an example  Temporal heterogeneity: evolution may occur during the course of breast cancer progression

Toy W et al. Nat Genet 2013;45(12):1439-1445; Robinson DR et al. Nat Genet 2013;45(12):1446-1451; Reprinted by permission from Macmillan Publishers Ltd: Polyak K. Nat Med 2014;20(4):344-346 © 2014

Massively Parallel Sequencing (MPS) identifies intra-tumour genetic heterogeneity in breast cancer  Genetic diversity of breast cancer:  Few cancer genes are commonly mutated  A large number of genes are rarely mutated  Some tumours don’t seem to have any of these mutations/copy number changes  Constellation of mutations in ER+ and ER- tumours is distinct

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ER-positive

Reprinted by permission from Macmillan Publishers Ltd: Stephens PJ et al. Nature 2012;486(7403):400-404 © 2012; Shah SP et al. Nature 2012;486(7403):395-399

ER-negative 11

Intra-tumour genetic heterogeneity and clonal evolution  Clonal evolution and the tree model:  Tumour cells divide and acquire mutations, upon a selective pressure (treatment) the fittest clone (s) prevails

Clonal Evolution

Acquirement of additional mutations

Founder clone (e.g.TP53 somatic mutation in triple negative breast cancer) 15.12.14

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Intra-tumour genetic heterogeneity may affect driver genetic events  Triple negative breast cancers vary widely in their clonal frequencies at the time of diagnosis  Intra-tumour heterogeneity may affect driver genetic events  TP53 and PIK3CA somatic mutations are clonally dominant  Some tumours: clonal frequencies incompatible with founder status

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Reprinted by permission from Macmillan Publishers Ltd: Shah SP et al. Nature 2012;486(7403):395-399 © 2012; Turner NC and Reis-Filho JS. Clin Cancer Res 2013;19(23):6380-6388

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Summary: Intra-tumour genetic heterogeneity  Breast tumours have considerable intra-tumour genetic heterogeneity:  spatial  temporal  Darwinian rules seem to govern the somatic changes that occur within a tumour Clinical impact: Analysis of biopsies of different areas within tumours may produce distinct results. Tumours may evolve over time (biomarker discordance / therapeutic resistance). Challenges for clinical management. 15.12.14

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Inter-tumour heterogeneity

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Inter-tumour heterogeneity

Inter-tumour heterogeneity: - Heterogeneity between tumours in different patients

Note: Inter-lesion heterogeneity: - Heterogeneity between primary tumour and metastasis (or between metastases) of the same patient

Seoane J and De Mattos-Arruda L. J Intern Med 2014;276(1):41-51 © 2014 The Association for the Publication of the Journal of Internal Medicine

Inter-lesion heterogeneity: primary vs. metastasis Basal-like primary breast tumour

Selective pressure

Metastasis

Treatment/ environment

17 Reprinted by permission from Macmillan Publishers Ltd: Ding L et al. Nature 2010;464(7291):999-1005 © 2010

Inter-lesion heterogeneity: metastasis vs. metastasis  Cellular genotypes and phenotypes at the single cell level per immuno FISH.  Genetic diversity is different between two distant metastases in the same patient.  The quantification of genetic diversity between distant metastases of the same patient may help explain therapy resistance.

18 Reprinted from Almendro V et al. Cancer Res 2014;74(5):1338-1348, with permission from AACR

Applying heterogeneity to the clinics: the HER2 example  Discordance in the expression of ER, PR and HER2 receptors has been reported

HER2-negative HER2-positive

 Anti-HER2 agents effective in only a subset of patients with HER2-positive tumours:  Role of heterogeneity for HER2 within tumours and between tumours in the same patient

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De Mattos-Arruda L et al. Nat Rev Clin Oncol 2013;10(7):377-389; Wolff AC et al. J Clin Oncol 2013;31(31):3997-4013

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Applying heterogeneity to the clinics: the HER2 example  Discordance in the expression of ER, PR and HER2 receptors has been reported

HER2-negative HER2-positive

 Anti-HER2 agents effective in only a subset of patients with HER2-positive tumours:  Role of heterogeneity for HER2 within tumours and between tumours in the same patient Clinical impact: For HER2, ASCO/CAP has guidelines for scoring / reporting HER2 copy number. HER2 should be tested in all patients (early stage, metastatic disease, recurrence) Importance for stratifying patients and guiding treatment decision-making. 15.12.14

De Mattos-Arruda L et al. Nat Rev Clin Oncol 2013;10(7):377-389; Wolff AC et al. J Clin Oncol 2013;31(31):3997-4013

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Summary: inter-lesion / inter-tumour heterogeneity

 Primary breast tumours and their metastases, and metastases at different sites of the same patients display genetic heterogeneity.  Tumour heterogeneity in the clinics remains challenging:  Importance of offering individualised treatments to more patients.

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How can tumour heterogeneity be overcome?

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Sampling heterogeneity in breast cancer patients  Goal: patient selection for therapy based on the presence of molecular markers and/or driver / actionable genomic alterations

Biopsies at relapse / progression Biopsies at multiple tumor sites

Heterogeneity

Liquid Biopsies

Sampling heterogeneity in breast cancer patients  Goal: patient selection for therapy based on the presence of molecular markers and/or driver / actionable genomic alterations

Biopsies Not at relapse always/ progression possible Biopsies at Not multiple feasible tumor sites

Heterogeneity

Liquid Biopsies

Liquid biopsies are potential tools to assess tumour heterogeneity  Circulating tumour DNA (ctDNA) and circulating tumour cells (CTCs) are potential valuable sources to assess tumour heterogeneity:  Capturing repertoire of genetic alterations from discordant primary tumour and/or metastases (all clones are potentially mixed in blood)  Longitudinal monitoring of disease  Predicting targeted therapy response  Tracking secondary resistance (emergence of resistant clones)

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Reprinted by permission from Macmillan Publishers Ltd: De Mattos-Arruda L et al. Nat Rev Clin Oncol 2013;10(7):377-389 © 2013; De Mattos-Arruda L et al. Annals Oncol 2014;25(9):1729-1735

0

100

MAF > 50%

MAF 20 - 50%

60

40

Baseline

100

Plasma 1

80

60

40

20 0

2 months

KN AK 2A p TP T 1 .S 1 53 p.E 2* J p 17 TS AK3 . K13 K C1 p. 2N T N CD F 1 p. S1 21M H1 p. 04 p V2 6C M .15 420 CT LL 9_ fs 3 1 PI NNB p.G 71P K3 1 2 C p 92 GA 2G .A52 E TA p. K 2G EP 1 97 H p. K 8N E S B1 315 R1 p.I3 N P M AK p.E 32M AP 7 38 2K p. 0Q E F L 2 p. 49 T 4 E2 4* p. 07 R2 Q 82 Q

80

Mutant Allele Fraction (%)

100

CD

KN AK 2A p TP T 1 .S 1 53 p.E 2* J p 17 TS AK3 . K13 K C1 p 2N .T CD NF 1 p. S1 21M H1 p.V 04 p.1 24 6C M CT LL 59_ 20f s N 3 1 PI NB p.G 71P K3 1 2 C p 92 GA 2G . A52 E T p. 2 EP A1 K97 G H p.K 8N E S B 1 31 R1 p.I3 5N 3 MA PAK p. E 2M P 2 7 p 380 K .E Q FL 2 p 49 T 4 . E2 4* p.R 07Q 28 2Q

Mutant Allele Fraction (%)

80

60

40

20

Mutant Allele Fraction (%)

Primary Tumor

Mutant Allele Fraction (%)

Metastasis CD

Pa cli ta xe l-b An as th ed ra cy cl Ca in epe ba ci ta se bi d ne -b as e

DK N 2 AK A p T P T1 .S1 53 p. E 2* J A p.K 17K T S K3 13 C1 p 2N . p T CD NF1 .S1 21M H p. 04 1 p V2 6C M . 15 420 CT LL 9_ fs N 3 1 PI NB p.G 71P K3 1 2 C p. 92 G 2G A 5 E AT p 22 . EP A1 K97 G H p.K 8N ES B1 31 R p.I 3 5N 1 3 M PA p.E 2M AP K7 38 2K p. 0Q E F L 2 p 49 T4 .E 2 4* p.R 07 28 Q 2Q

C

Primary tumour

CD KN 2 AK A p T P T1 .S1 53 p. E 2* JA p.K 17K T S K3 13 C1 p. 2N T CD NF1 p.S1 21M H1 p. 04 p V 2 6C M .1 4 CT LL 59_ 20fs N 3 1 PI NB p.G 71P K3 1 2 C p 92 GA 2G .A 52 E T p. 2 EP A 1 K97 G H p.K 8N ES B1 31 R1 p.I 3 5N 3 M A PA K p.E 2M P2 7 p 380 K .E Q F L 2 p. 49 T4 E 2 4* p. R 07 28 Q 2Q

20 Mutant Allele Fraction (%)

40

KN AK 2A p TP T 1 . S1 53 p.E 2* J p 17 T S AK3 . K13 K C1 p 2N .T CD NF 1 p.S1 21M H1 p.V 04 p. 24 6C 1 CT MLL 59_ 20fs N 3 1 P I NB p.G 71P K3 1 2 C2 p.A 92 GA G 52 E T p. 2 E P A1 K97 G H p.K 8N E S B1 31 R1 p.I3 5N 3 MA PAK p.E 2M P2 7 p 380 K .E Q F L 2 p. 49 T4 E2 4* p.R 07Q 28 2Q

Mutant Allele Fraction (%) 60

CD

KN A K 2A p T P T1 .S1 53 p. E 2* J p 17 TS AK3 .K13 K C1 p. 2N T CD NF1 p.S 1 21M H1 p. 04 p V2 6C M . 15 420 CT LL 9_ f s 3 1 PI NNB p. G 71P K3 1 2 C p 92 GA 2G .A 52 E TA p.K 2G EP 1 97 H p.K 8N ES B1 31 R1 p. I3 5N M PAK p. E 32M AP 7 38 2K p. 0Q E FL 2 p. 49 T 4 E2 4* p. 07 R2 Q 82 Q

CD

Capturing intra-tumour genetic heterogeneity by de novo mutation profiling of ctDNA Plasma ctDNA

100 100

0

De Mattos-Arruda L et al. Annals Oncol 2014;25(9):1729-1735 by permission of Oxford University Press 80

60

40

20 20 0

6 months

Liver Metastasis

100

Plasma 3 Disease progression

80 80

60

40

0 20

0

MAF 5 - 20%

MAF: Mutant Allele Fraction MAF < 5%

Not all mutations identified in the metastasis were reliably identified in the primary breast tumour. All mutations present in the primary tumour and/ or liver metastasis were found in ctDNA.

Conclusions

 In breast cancers, single biopsies may differ:  according to the area of the tumour sampled  between primary tumours and their distant metastases  between different metastatic sites  Genetic analyses of breast cancers have provided direct evidence of spatial and temporal intra-tumour genetic heterogeneity.  The study of tumour heterogeneity may provide answers to:  patient stratification  guide treatment decision-making

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Acknowledgments

 Dr. Britta Weigelt and Dr. Jorge Reis-Filho (MSKCC)  Dr. Javier Cortes and Dr. Joan Seoane (Vall d’Hebron Institute of Oncology)

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THANK YOU!

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