Breast cancer classification: beyond the intrinsic molecular subtypes Britta Weigelt, PhD Signal Transduction Laboratory CRUK London Research Institute
Summary Breast cancer heterogeneity Molecular classification of breast cancer Prognostic gene signatures Outlook
Breast cancer patient management Size Grade Type Lymph node metastasis Vascular invasion HER2 HER2 ER, PR and HER2 Breast cancer Individualised breast patient cancer therapy patient therapy
Intrinsic molecular subtypes of breast cancer Normal Breast Luminal B Basal-like HER2 ER-negative! Perou et al, Nature, 2000; Sorlie et al, PNAS 2003 Luminal A ER-positive! Intrinsic gene set
Intrinsic subtypes are associated with outcome Normal! Breast! Luminal B! HER2+! Luminal A! Basal-like! Perou et al, Nature 2000; Sorlie et al, PNAS 2001; Hu et al, BMC Genomics 2006
Cancer Invest 2008
Identification of intrinsic molecular subtypes Hierarchical clustering Intrinsic gene lists Normal Breast Basal-like HER2 Centroids Single sample predictors Luminal B Luminal A - Large number of samples - Retrospective assignment - Centroid: mean expression profile for each of the five subtypes - Classification of individual samples - Prospective assignment
Intrinsic molecular subtype evolution Intrinsic genes Single sample predictor genes Perou CM et al, Nature 2000 496 Sørlie T et al, PNAS 2001 Sørlie T et al, PNAS 2003 456 534 500 Hu Z et al, BMC Genomics 2006 1300 306 Parker JS et al, J Clin Oncol 2009 1906 50
Hierarchical cluster analysis
Limitations hierarchical clustering Clustering algorithms always detect clusters, also in random data Stability of clusters identified by hierarchical clustering analysis Number of clusters is unknown
Aim To determine the objectivity and inter-observer reproducibility of the assignment of molecular subtype classes by hierarchical cluster analysis 3 2 1 3 2 2 1 2
Material and Methods 1 3 publicly available datasets NKI-295 dataset (n=295) Wang dataset (n=286) TransBig dataset (n=198) 5 intrinsic gene lists Perou et al, 2000 Sorlie et al, 2001 Sorlie et al, 2003 Hu et al, 2006 Parker et al, 2009 5 observers
Material and Methods 2 1. Inter-observer agreement (%) 2. Free-marginal Kappa scores for the whole classification for each molecular subtype separately Kappa scores Slight: 0.01-0.20 Fair: 0.21-0.40 Moderate: 0.41-0.60 Substantial: 0.61-0.80 Almost perfect: 0.81-0.99
Molecular subtype assignment based on dendrogram analysis is subjective Mackay A*, Weigelt B* et al, JNCI 2011
Basal-like and HER2 intrinsic subtypes are reproducibly identified Mackay A*, Weigelt B* et al, JNCI 2011
Molecular subtype evolution Intrinsic genes Single sample predictor genes Perou CM et al, Nature 2000 496 Sørlie T et al, PNAS 2001 Sørlie T et al, PNAS 2003 456 534 500 Hu Z et al, BMC Genomics 2006 1300 306 Parker JS et al, J Clin Oncol 2009 1906 50
Do different SSPs consistently classify the same patients into the molecular subtypes?
Agreement between different SSPs performed by Sorlie and Perou Sorlie s SSP Chang et al (Sorlie s group) NKI-295 cohort Hu s SSP Fan et al (Perou s group) Agreement: moderate Kappa score: 0.527 (95% CI 0.456-0.597) Kappa scores Slight: 0.01-0.20 Fair: 0.21-0.40 Moderate: 0.41-0.60 Substantial: 0.61-0.80 Almost perfect: 0.81-0.99
Material and Methods 3 publicly available datasets NKI-295 dataset (n=295) Wang dataset (n=286) TransBig dataset (n=198) 1 in-house dataset Grade III invasive ductal carcinomas, microdissected (n=53) 3 SSPs Sorlie et al, 2003 Hu et al, 2006 Parker et al, 2009 Agreement between molecular subtype assignment - Kappa scores Weigelt et al, Lancet Oncol 2010
Reproducibility of intrinsic molecular subtypes NKI-295 dataset 295 cases Wang dataset 286 cases TransBig dataset 198 cases GIII IDC dataset 53 cases Sorlie SSP, 2003 Hu SSP, 2006 Parker SSP, 2009 Sorlie SSP, 2003 Hu SSP, 2006 Parker SSP, 2009 Sorlie SSP, 2003 Hu SSP, 2006 Parker SSP, 2009 Sorlie SSP, 2003 Hu SSP, 2006 Parker SSP, 2009 - Agreement moderate to substantial (κ=0.40-0.79) - Classification of each patient is dependent on the SSP - Only basal-like form a stable group
Outcome prediction using distinct SSPs Weigelt et al, Lancet Oncol 2010
Outcome prediction using distinct SSPs Weigelt et al, Lancet Oncol 2010
5715 breast tumours Haibe-Kains B et al, JNCI 2012
Assignment of luminal subtypes 1 Hierarchical clustering Single sample predictors Sorlie SSP, 2003 Hu SSP, 2006 Parker SSP, 2009 Weigelt et al, Lancet Oncol 2010; Mackay A*, Weigelt B* et al, JNCI 2011
Assignment of luminal subtypes 2 Luminal A: ER Luminal B: ER Proliferation Proliferation??? Reis-Filho & Pusztai, Lancet 2011
12 years of molecular subtyping ER-positive and ER-negative tumours Fundamentally different diseases Breast cancer molecular subtypes Not stable Only basal-like is robust Limited clinical application No validated/ standardised methodology PAM50?
Additional molecular subtypes" Interferon-rich Molecular apocrine Claudin-low Molecular subtypes of triple negative breast cancer METABRIC subtypes Hu et al, BMC Genomics 2006; Farmer et al, Oncogene 2005; Doane et al, Oncogene 2006; Prat et al, Breast Cancer Res 2010;" Lehmann et al, JCI 2011; Curtis et al, Nature 2012 "
Prognostic gene signatures
Mammaprint
Oncotype DX (21-gene signature) ER+/ LN-/ Tamoxifen-treated patients Proliferation Ki67 STK15 Survivin CCNB1 MYBL2 HER2 GRB7 HER2 GSTM1 Oestrogen ER PGR BCL2 SCUBE2 Recurrence score Low risk RS 18 Intermediate risk 18>RS<31 High risk RS 31 CD68 Invasion MMP11 CTSL2 BAG1 Reference ACTB GAPDH RPLPO GUS TFRC
A signature to rule them all?
Fan et al. NEJM 2006; Sotiriou et al. JNCI 2006 A signature to rule them all
Meta-analysis gene signatures Proliferation Proliferation Blue dots: good prognosis Red dots: poor prognosis Wirapati et al. Breast Cancer Res 2008;10:R65
What do prognostic signatures offer? ER-positive disease: good discriminatory power Limited value for ER-negative disease Correlate with proliferation (and grade!) Ki-67?
Immune response related signatures are prognostic in TNBC
but the good prognosis group still has a high number of events Rody et al. Breast Cancer Res 2010; Karns et al. PLoS One 2011
What do prognostic signatures offer? ER positive disease - good discriminatory power Limited value for ER negative disease Correlate with proliferation (and grade!) Ki-67? Immune response-related signatures Prognostic in ER-/HER2- and HER2+ disease Potential predictive of response to chemotherapy
Take home messages Molecular classification not ready yet for use in clinical practice standardised methods/ definitions required (PAM50?) First generation prognostic signatures complementary to histopathology determined by proliferation discriminatory power only in ER-positive disease Second generation immune-related prognostic signatures discriminatory power in ER-negative disease not yet sufficient for clinical decision-making
Outlook survival Good Poor = treat Current classification: descriptive and prognostic time Weigelt et al, Nat Rev Clin Oncol 2011
Outlook survival Good Poor = treat Current classification: descriptive and prognostic time Future: predictive sub-classification Mutation X? Amplification Y? Sensitive drug A Resistant drug B Weigelt et al, Nat Rev Clin Oncol 2011
Acknowledgements Julian Downward Alan Mackay Rachael Natrajan Maryou Lambros Anita Grigoriadis Alan Ashworth Jorge Reis-Filho Bas Kreike Roger A Hern Mitch Dowsett
Immune response may predict pathological complete response following neoadjuvant chemo All breast cancers ER-/HER2- HER2+ ER+/HER2- statistically significant not statistically significant Ignatiadis et al. J Clin Oncol 2012
PAM50 vs Ki67 103 ER+/HER2- breast cancers profiled with PAM50 and Ki67 IHC Ki67 Luminal A (n=76) Luminal B (n=27) <13.25% 64 (84%) 10 (37%) 13.25% 12 (16%) 17 (63%) Kappa score = 0.4607 (0.2609 to 0.6605) Kelly et al. Oncologist 2012
OncotypeDx vs PAM50 Is low RS synonymous with luminal A? 108 ER+/ HER2- breast cancers profiled with GHI OncotypeDx and ARUP labs PAM50 Low (n=59) 90% 8% 2% Intermediate (n=39) 59% 33% 8% High (n=10) 90% 10% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Lum A Lum B HER2-enriched Basal-like Kelly et al. Oncologist 2012
PAM50 vs OncotypeDx Is luminal A synonymous with low RS? 108 ER+/ HER2- breast cancers profiled with GHI OncotypeDx and ARUP labs PAM50 Lum A (n=76) 70 30 Lum B (n=27) 19 48 33 HER2-enriched (n=4) 25 75 Basal-like (n=1) 100 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Low Intermediate High Kelly et al. Oncologist 2012