Breast Cancer Heterogeneity Breast Cancer Molecular Subtypes Patients and Tumors Between Patients: subtypes How to use Molecular Diagnostic Tests in Breast Diseases Laura J. van ‘ t Veer Within Tumors: subclones University of California, San Francisco Helen Diller Family Comprehensive Cancer Center Nature Rev Cancer, 2012 The Opportunity of Today Breast Cancer - Survival Tailoring Treatment Kaplan-Meier Survival Curves • Breast Cancer local and systemic treatment is tailored • Integrative Biospecimen Diagnostics – breast cancer morphological type – breast cancer molecular subtype – prognosis, prediction, follow-up monitoring – activated pathways, individual targets Which Breast Cancers Return? After surgery and Radiotherapy: 1) Who to treat, 2) How to treat 1
Histology of breast cancer • Invasive breast cancer is a clinically and histologically • ‘ WHO Classification of Breast Tumors ’ distinguishes heterogeneous disease more than 30 morphologic types Type of Breast Cancer how to use understand: risk of recurrence tailor: choice of systemic-targeted treatment • The classification is based on the growth pattern and cellular features of the invasive tumor cells Histological types of breast cancer Prognosis of histological types The phenotypic variation suggests differences in the etiology, genetics and behavior of breast cancers. ‘ special types ’ est. 90% Weigelt B et al, Nature Rev Cancer 2005 2
The Opportunity of Today Diagnostics of Cancer from micro-scope to micro-array Tailoring Treatment • Breast Cancer local and systemic treatment is tailored • Integrative Biospecimen Diagnostics – breast cancer morphological type – breast cancer molecular subtype – prognosis, prediction, follow-up monitoring Micro-scope Micro-array – activated pathways, individual targets Comprehensive set shows the picture Single gene, little information Microarray test of Breast Cancer Tumor Detection of gene activity RNA Red=active Green=inactive Yellow=neutral Patient DIAGNOSIS Gene activity pattern TREATMENT Gene Microarrays and Sequencers 3
‘ Invasive Ductal Carcinoma ’ Multi Gene Expression Profiles Molecular Intrinsic Subtypes in Clinical Practice Perou & Sorlie et al, Nature 2000 70 Gene Prognosis Signature Breast Cancer Gene Expression MammaPrint: ‘ 07 FDA cleared IVDMIA for prognosis assessment Profiling Prognostic Tests Lymph node negative, adjuvantly untreated 1. OncotypeDX Recurrence Score (Paik et al., NEJM, 2004) 70 significant prognosis genes 2. MammaPrint (van de Vijver et al., NEJM, 2002) Tumor samples 3. The PAM50 Intrinsic Subtypes: LumA, LumB, Basal-like, HER2-enriched, Normal-like (Parker et al., JCO 2009) 4. The PAM50 Risk of Recurrence (ROR) (Parker et al., JCO 2009) 1. Genomic Grade Index (Sotiriou et al. JNCI 2006) 5. Breast Cancer Index: 2-gene ratio plus 5-gene proliferation (Ma et al., CCR 2008) Van ’ t Veer et al, Nature 2002 6. EndoPredict (Filipits et al., CCR 2011) 4
International Treatment Recommendations Reproducibility IHC, Grade and Molecular testing Endocrine Therapy (chemo in selected cases) Endocrine + Chemo (most) Endocrine+ Chemo + anti-HER2 Chemo + anti-HER2 Chemo Quote: “IHC-based classification will be more widely applicable at lesser cost, notwithstanding its limited validation” => Multigene Assays more accurate Goldhirsch et al. Ann Oncol 2013; NCCN 2014 Prat et al. Nature Rev Clin Oncol 2011 TCGA: comprehensive subtype analysis Diagnostics of Cancer from micro-scope to micro-array to nextgen sequencing Consensus clustering over 4 platform technologies Highest hierarchy: 4 groups, roughly Luminal A, Luminal B, Basal, Her2 type The Cancer Genome Atlas Micro-scope Micro-array NextGen Sequencers Many authors and Christina Yau Nature. 2012;490:61-70 5
Genomic and transcriptomic architecture -> 10 subtypes High risk for recurrence Biology guides choice of (targeted) drugs Trans-acting copy number aberrations and subgroup-specific gene networks associated with outcome. Metabric dataset (includes a TCellReceptor deletion-mediated adaptive immune response and a basal-specific chromosome 5 deletion- associated mitotic network) Nature. 2012;486:346-352 TCGA Pan-Cancer Effort Hallmarks of Cancer Evasion of immune system - TCGA network position paper in Nature Pan-Cancer focus - Describes effort and highlight findings from ‘basket’ of papers stemming from the Pan-Cancer effort - Basket of 18 accepted Papers - TCGA network acknowledged but not listed as author Adapted from submitted position paper Figure 1 6
Though most subtype assignments were nearly identical to their pathological classification, Pathway Characteristics of Integrative Subtypes several distinct cancer types were found to merge into a common subtype. Convergent subtypes: C2-Squamous-like subtype combines head and neck and lung squamous cancers and a subset of bladder cancers. C1-LUAD-enriched combines lung adenocarcinoma and a subset of bladder cancers. Pathway Implications (supported by both enrichment and sub-network) Tissue 1 2 3 4 5 6 7 8 9 10 13 COCA 1-LUAD enriched Activated Pathways : AP1, RAC1, Immune, p53, HIF1A, CDC42, p38 � � � � � � Silhouette width Repressed Pathways: E2F � � � � � � � � � � � � � � � � � � � � � � � � 2-Squamous Activated Pathways: p63, p53, MYC, FOXM1, RAC, RHO, XBP1, Immune, HIF1A, AP1, p38 � � � � � � �� � � �� � � Repressed Pathways: FOXA1/ER �� � � �� � � COCA LUAD 1 - LUAD-enriched 3-BRCA Luminal Activated Pathways: FOXA1/ER, PI3K, p63, MYB, CDC42 2 - Squamous-like LUS C Repressed Pathways: MYC, E2F, FOXM1, RAC, RHO, Immune, p53, p38 3 - BRCA/Luminal 4 - BRCA/Basal 5 - KIRC 4-BRCA Basal Activated Pathways: p63, MYC, PLK1, Immune, XBP1, MYB, p73 HNS C 6 - UCEC Repressed Pathways: FOXA2, p53 7 - COAD/READ BR C A 8 - BLCA 9 - OV 5-KIRC Activated Pathways: HIF1A, Immune KIR C 10 - GBM Repressed Pathways: Caspase, MYC, FOXM1, p63 11 - small-various Divergent 12 - small-various UC E C cancers: 6-UCEC Activated Pathways: E2F, XBP1, p53 13 - AML Tissue Type Repressed Pathways: HIF1A, RAC, Immune, AP1, p38, MAP kinase C OAD/R E AD BLCA BRCA 7-Colorectal Activated Pathways: MYC, E2F, p53, p38, (PKC) BLC A COAD Repressed Pathways: IL12, IL27, AP-1, HIF1A, CDC42, PI3K GBM HNSC OV KIRC 8-BLCA Activated Pathways: p63, p53 LAML GBM Repressed Pathways: HIF1A, il23 LUAD LUSC AML OV 9-OV Activated Pathways: E2F, MYC, CDC42, XBP1 READ Repressed Pathways: p53, immune UCEC C OAD 10-GBM Activated: AKT, (PKC) LUAD LUS C HNS C BR CA KIR C UC E C - cn R E AD BLC A OV GBM AML Repressed Pathways: p53, immune, MYC, PI3K, ARF6 Bronchioid Primitive Atypical Luminal A m1 1 MSI/CIMP I Differentiated G-CIMP 1 Magnoid Classical Classical Luminal B m2 2 Invasive II Immunoreactive Proneural 2 13-LAML Activated: MYC, p38, RHO, ERK/MAPK, caspase Squamoid Secretory Mesenchymal HER2-enriched m3 3 CIN III Mesenchymal Neural 3 Basal Basal Normal-like m4 4 IV Proliferative Classical 4 Repressed: PI3K, p53, RAC Basal-like Mesenchymal 5 6 7 TCGA Pan-Cancer-12 project Therapeutic targeting of the hallmarks of cancer Based on this study, one in ten cancer patients would be classified differently by this new Cell. 2011;144:646-6 molecular taxonomy versus our current tissue-of-origin tumor classification system. 7
"Here are my genes..." The New Yorker 8
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