30 years of progress in cancer research

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1 Breast Cancer Molecular Knowledge Integrated in Clinical Practice Personalized Medicine Laura J. Esserman UCSF Comprehensive Cancer Center Retreat Breast Cancer Management Advances 80-90s 1) Screening programs for early detection have been introduced with the ultimate goal to reduce mortality 2) Adjuvant Chemotherapy has been proven to be beneficial Observations 1) 25 years of screening: what do we detect? 2) Chemotherapy standard of care: do we treat those who benefit? 30 years of progress in cancer research? Recent advances in molecular knowledge give biological insight Normal cell Cancer The GENOMICS ERA 21st century - Personalized Medicine

2 Single gene, little information Comprehensive set shows the picture 476 Molecular portraits of breast cancer Perou & Sorlie et al, Nature 2000 Breast Cancer RNA Gene Expression Profiling Recurrence Score Oncotype; 70 gene prognosis signature - MammaPrint; H/ITM (HOXB13/IL17BR); Genomic Grade; 76 gene Rotterdam signature Survival analysis was done on the 51 doxorubicin treated patients only 70 Gene Prognosis Signature MammaPrint Screen detected cancers Tumor samples 70 significant prognosis genes van t Veer et al., Nature 415, p , 2002 Majority of cancers detected by screening are biologically low risk Majority of clinical high risk cancers are biologically high risk and not screen detected Current screening programs increase the burden of low risk cancers and will have limited impact on reduction of mortality New screening strategies needed for early detection of high risk cancers threshold set with 10% false negatives 91 % sensitivity, 73% specificity 2

3 Breast Cancer - Adjuvant Treatment Kaplan-Meier Survival Curves Current Clinical Management lymph node negative breast cancer adjuvant treatment selection criteria: e.g., age, diameter, grade, ER (US or EU) consensus criteria: > 80% 1) Who to treat 2) How to treat As only 30-40% of these patients develop distant metastases, some 40-60% of patients are over-treated The Problem For Using Chemotherapy (Most Common Presentation Of Breast Cancer Today: T1 N0 ER+ Grade 2) Need To Treat 100 Women CLINICAL RISK ASSESSMENT ADJUVANT! ONLINE FOR BREAST CANCER And Only One Benefits! 10-30% suffer from side-effects 1) Who has the risk 2) Who shows benefit 3

4 Absolute Prerequisites for Prognostic and Predictive Assays Accuracy and reproducibility o Does the assay measure what it says it does? o Will the same value result if run twice? Clarity o Is the result unambiguous? Utility o Is the prognostic and predictive information useful? o Does it alter management uniquely and lead to improved outcomes or efficiencies of therapy? Potential Advantages of Multi-Gene Assays Better pattern recognition o Linking profile/pattern to outcome is likely to be better than a single or a few protein or gene measurements o Discovers marker genes/proteins in an unbiased manner Automated reading o Lack of subjectivity of immunohistochemistry and cell morphology Evaluates tumor and stroma Basic Elements of Multi-Gene Assays Amplification of mrna (whole or fragments) o Specific mrna using gene-specific primers o All mrna Labeling of RNA (or crna) with fluorescent probes Direct measurement or RNA or crna Real-time (quantitative RT-PCR) hybridization of labeled crna to an array of ~45,000 genes Regulatory Status of Clinical Utilized Assays Oncotype DX o Homebrew Exemption o CLIA certified MammaPrint o FDA Clearance, Class2, 510(k) o CLIA certified 4

5 21-Gene Recurrence Score (RS) Assay Oncotype DX (Genomic Health) 16 Cancer and 5 Reference Genes From 3 Studies PROLIFERATION Ki-67 STK15 Survivin Cyclin B1 MYBL2 INVASION Stromolysin 3 Cathepsin L2 HER2 GRB7 HER2 ESTROGEN ER PR Bcl2 SCUBE2 CD68 REFERENCE Beta-actin GAPDH RPLPO GUS TFRC GSTM1 BAG1 RS = x HER2 Group Score x ER Group Score x Proliferation Group Score x Invasion Group Score x CD x GSTM x BAG1 Category RS (0 100) Low risk RS < 18 Intermediate risk High risk RS 31 RS 18 and < 31 Recurrence Score (RS) as a Continuous Predictor Distant Recurrence at 10 Years 40% 35% 30% 25% 20% 15% 10% 5% Low Risk Group Intermediate Risk Group 95% CI 0% Recurrence Score High Risk Group Paik S et al NEJM 2005 B14-Results: Outcome by RS Multivariate Analysis of 10y DDFS Distant Disease-Free 10 Yr 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Low Risk (RS <18) Intermediate Risk (RS 18-30) High Risk (RS 31) Years 338 pts (51%) 149 pts (22%) 181 pts (27%) Paik S et al NEJM 2005 Variable p-value Hazard Ratio (95% CI) Paik S et al NEJM

6 21-Gene Assay: MD Anderson Study Results Selection criteria: Surgery at MDACC ; 5 years follow-up, node, ER+ or ER, no adjuvant tamoxifen or chemotherapy, tissue available (N = 149) DRFS 95% CI for Variable Hazard P Value Hazard Ratio Ratio Age 0.99 (0.96, 1.02) 0.33 Tumor Size 1.23 (0.93, 1.63) 0.14 Recurrence Score 0.99 (0.98, 1.00) 0.10 *Esteva FJ et al. Esteva Clin Cancer FJ et al. Res. Clin 2005;11:3315. Cancer Res Year Recurrence Rates by RS & Nodes: Analysis of E2197 (AC vs AT for 0-3 Nodes) N=465 HR+ subset with available tissue (out of 2885 enrolled) p= p= Goldstein L et al ASCO 2007 Abstr #526 RS and Adjuvant! in Proportional Hazards Model Hazard Ratio Local Grade RS 2.64 (p<0.001) Adjuvant! 1.34 (p=0.11) Hazard Ratio Central Grade 2.51 (p<0.001) 1.51 (p=0.02) RS by Adjuvant! interaction term added to either model not significant (p=0.94 local grade, p=0.56 central grade) Confirms their independence Goldstein L et al, SABCS 2007, Abstract #63 RS vs Adjuvant!: Risk of Recurrence by RS Group in Adjuvant! Risk Groups with Low RS as the Referent RS Risk Group Adjuvant! Low Inter. vs. Low* RS High vs. Low Adjuvant! Intermed* Inter. vs. Low RS High vs. Low Adjuvant! High* Inter. vs. Low RS High vs. Low Ratio 95% Conf Int 2.55 (1.11, 5.85) (1.73, 9.25) (3.01, 29.19) (1.70, 19.64) (0.30, 2.63) 2.62 (1.05, 6.51) *Adjuvant! risk using central grade Hazard Ratio Goldstein L et al, SABCS 2007, Abstract #63 6

7 B-20: Absolute % Increase in DRFS with CMF over Tam at 10 Years Comparison of CAF-T to Tamoxifen Alone by RS RS n = 353 (54%) DFS hazard ratios adjusted for nodal status Low RS < 18 Overall trial Int RS High RS > 30 n = 134 n = 164 (25%) Trial Subset Entire RS sample Low RS Interm. RS High RS 40% of patients 28% of patients 32% of patients Chemotherapy benefit No chemotherapy benefit 0 10% 20% 30% 40% % Increase in DRFS at 10 Yrs (mean ± SE) Paik S et al. J Clin Oncol Hazard Ratio Albain K et al. SABCS 2007, Abstract 10 Supervised Classification on Prognostic Signatures on 78 Tumors Independent Validation of 70-Gene Signature MammaPrint (Agendia) 295 Patients, Stage I/II, Age < 53 Years, No Systemic Therapy Requires fresh tissue (with FDA-cleared RNA preservative solution) Prognostic Reporter Genes Differentiating Between 2 Groups Expression Data Matrix of 70 Prognostic Genes van't Veer LJ et al. Nature 2002 Van de Vijver MJ et al. NEJM

8 Multivariate Proportional Hazards Analysis: Risk of Distant Metastasis as First Event Independent Validation of 70-Gene Signature 295 Patients, Stage I/II, Age < 53 Years Variable Hazard Ratio p-value (95% CI) Poor vs. good prognosis signature 4.6 ( ) <0.001 Age (10-year increments) 0.72 ( ) 0.10 Lymph node status (per + node) 1.13 ( ) 0.01 Tumor diameter (per cm) 1.56 ( ) <0.001 Tumor Grade 2 vs ( ) Tumor Grade 3 vs ( ) 0.54 Vascular invasion 1-3 vs. 0 vessels 0.66 ( ) Vascular invasion >3 vs. 0 vessels 1.65 ( ) 0.05 ER expression (per point/log normalized) 0.86 ( ) 0.48 Mastectomy vs. breast conservation 1.27 ( ) 0.32 Chemotherapy vs. no Chemo Rx 0.37 ( ) <0.001 Hormonal therapy vs. no Horm Rx 0.62 ( ) 0.23 Van de Vijver MJ et al. NEJM 2002 Van de Vijver MJ et al. NEJM 2002 Independent Validation of 70-Gene Signature 295 Patients, Stage I/II, Age < 53 Years Is a 70-gene "good profile" sufficiently lowrisk to forego chemotherapy? 1-3 positive nodes All patients (n = 241) 8-year OS Good profile (n = 99) 95% 5 Poor profile (n = 142) 73% 34 No. of events Chemotherapy (n = 128) 8-year OS Good profile (n = 39) 95% 2 Poor profile (n = 89) 69% 24 No. of events No chemotherapy (n = 101) 8-year OS Good profile (n = 57) 94% 3 Poor profile (n = 44) 77% 10 No. of events Van de Vijver MJ et al. NEJM 2002 Conclusions: 70-gene profile is a significant prognostic marker for patients with 1-3 positive nodes This profile improves risk assessment compared to Adjuvant! and identifies a low risk group who could be spared chemotherapy Mook, S et al. SABCS 2007 Abstract 50 8

9 70 gene profile identifies Adjuvant!online identifies High risk 63% Risk assessment Breast Cancer TransBIG - 5 European Hospitals 302 patients but also: Concordant cases 65% Low risk 37% High risk 74% Reduces high risk population! Buyse, JNCI, % Discordant cases Low risk 26% Adjuvant! Clinical low risk defined as 10-year survival probability 88% for ER+ patients 92% for ER- patients Probability Patients Risk assessment Breast Cancer TransBIG - 5 European Hospitals 302 patients 70 gene profile Adjuvant! Events Risk group Gene signature low risk Gene signature high risk Year 10-year DMFS 90% (85%-96%) 10-year DMFS 71% (65%-78%) Number at risk Buyse, JNCI, 2006 Low risk signature High risk signature Probability Patients Events Risk group Low clinical risk High clinical risk Year 10-year DMFS 85% (77%-94%) 10-year DMFS 76% (70%-82%) Number at risk Discordant cases better predicted by 70 gene prognosis signature Low risk Adjuvant! High risk Adjuvant! Response to neo-adjuvant chemotherapy and 70 gene MammaPrint Signature Adjuvant therapy decided by risk of relapse and benefit of therapy Biological stratification in low and high risk of relapse pcr Some benefit more then others! overall survival Low risk: no chemotherapy, ERpos endocrine therapy High risk: chemotherapy and endocrine therapy (they show the chemo benefit!) MammaPrint low risk signature -> no benefit of chemotherapy MammaPrint high risk signature -> benefit of chemotherapy time (years) Straver, Rodenhuis et al 2008, unpublished 9

10 Clinical Utility 70 gene signature Discordant cases 70 gene MammaPrint versus Guidelines The Netherlands and Adjuvant-0n-line Prospective study implementing 70 gene signature , ~800 patients Sponsor: Dutch Health Insurance Council ~30 % discordant cases led in ~20% to in treatment advice Bueno et al, Lancet Oncol, 2007, Knauer et al, SABCS 2008 #1084 Bueno et al, Lancet Oncol, 2007, Knauer et al, SABCS 2008 #1084 Other Multi-Gene or Protein Assays in Commercially Available* or in Development Gene Expression Signature Assay Name Manufacturer # of Genes Microarray Platform Amsterdam Signature* MammaPrint Agendia 70 Agilent Recurrence Score* Oncotype DX Genomic Health 16 (21) RT-PCR H/I TM (HOXB13/IL17BR)* H/I AviaraDX 2 RT-PCR Sensitivity to Endocrine Therapy (SET) SET/TFAC Nuvera 200 Rotterdam Signature GeneSearch Veridex 76 Affimetrix 5-protein assay ProEx TM Br TriPath 5 IHC 5-protein assay* Mammastrat Applied Genomics 5 IHC Key 2 BC Prognostic Test exagen BC exagen Diagnostics 3 FISH Invasiveness Gene Signature IGS Oncomed 186 Affimetrix Wound-Response Signature 512 cdna (Custom) Genomic Grade 97 Affimetrix p53 Signature 32 Affimetrix Cancer Death Signature 11 Affimetrix Molecular Predictors of pathologic Complete Response (pcr) in I SPY Predictor P Value NKI 70 genes (Van t Veer) GHI Recurrence Score (Paik) T-FAC 30 gene set (MDACC) 0.02 TP53 (Perou) 0.01 Molecular Subtypes (Sorlie) 0.02 ER, Phospho ER (-) Her-2, Phospho Her MRI Volume significant 10

11 Comparison of Assay Reliability Standard Pathology Nodal Status, T Stage, Margins Grade ER, PR, Her2 Adjuvant! For a population, within 2% of outcome As an individual predictor, 35% discrepant with molecular assays (good vs. poor outcome) 70 gene NKI assay (array) Prognostic for all, predictive Requires frozen tissue 21 gene assay (RT-PCR) predictive and prognostic for ER positive, node negative Can be performed on slides made from paraffin blocks Molecular Markers in Guidelines Oncotype NCCN St. Gallens (as of March 13, 2009) Mammaprint NCCN St. Gallens (as of March 13, 2009) The GENOMICS ERA 21 st century - Personalized Medicine Main goals of today s cancer management & research RISK STRATIFICATION by GERMLINE VARIATION Who needs SCREENING, when Influence of environmental and lifestyle RISK FACTORS TREATMENT INDIVIDUALIZATION OR TAILORING TUMOR BIOLOGY, risk of recurrence, response to therapy PROGNOSTIC & PREDICTIVE TOOLS NEW SCREENING OPTIONS and TREATMENTS Molecular TRACERS New DRUG TARGETS QUALITY OF LIFE & SURVIVORSHIP How to make best use of these new developments? 11