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
...
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
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
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
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
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
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
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)
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)