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2006 European Breast Cancer Meeting Stockholm, Sweden 20–21 May 2006 USING PROGNOSTIC & PREDICTIVE FACTORS IN BREAST CANCER Fatima Cardoso, MD Jules Bordet Institute & TRANSBIG PROGNOSTIC FACTOR % Treat. A Treat. B + - PREDICTIVE FACTOR Case 1 Case 2 Treat. B % Treat. B % Treat. A Treat. A + - + - WHY DO WE NEED PROGNOSTIC AND PREDICTIVE FACTORS PROGNOSTIC FACTORS PREDICTIVE FACTORS Who needs a treatment? Which treatment is best? THERAPEUTIC CHOICES AVOID UNDER AND OVER TREATMENT INDIVIDUALIZE TREATMENT BC GENE EXPRESSION PATTERNS and OUTCOME Molecular (re-)classification of BC ER- ER+ HER-2-like Basal-like Basal-like 1 2 Luminal 1 Luminal 2 Luminal 3 RFS Adapted from Sotiriou et al, PNAS, 2003 PROGRESS IN ADJUVANT CHEMOTHERAPY FOR BREAST CANCER Average treatment effect +++ ++ + ± Financial toxicity d) 20.000 $ c) 13.800 $ b) 7.400 $ a) 800 $ TAC x 6 FEC docetaxel +++ AC paclitaxel dose-dense FAC FEC x 6 ++ A(E) CMF CMF x 6 AC x 4 Paclitaxel x 4 + AC x 4 L-PAM, MF ± 1970’s 1980’s 1990’s 2000’s Successive generations of adjuvant CT regimens +++ ADJUVANT TRASTUZUMAB +++ Adapted with permission from G. Hortobagyi St Gallen 2005 Consensus: What’s new? • New prognostic factors accepted: HER-2, vascular invasion • Node+ 1-3: in average risk group, if HER-2– and no vascular invasion Beyond St Gallen 2005 … uPA, PAI-1 Cyclin E Oncotype DX* (predictive & Px) Genomic signatures Topo-II- *Genomic Health uPA-PAI-1 CLINICAL RELEVANCE OF uPA & PAI-1 IN PRIMARY BREAST CANCER uPA and PAI-1: first novel tumor biological factors in breast cancer with clinical relevance validated at highest level of evidence (LOE I) Standardized quality assured ELISA tests: Sweep et al, Br J Cancer 78: 1434-41, 1998 Prospective multi-center therapy trial („Chemo N0“): Jänicke et al, JNCI 93: 913-20, 2001 EORTC RBG meta analysis (n=8,377): Look et al, JNCI 94:116-28, 2002 Recommended for clinical risk assessment: AGO Therapy Guidelines „breast cancer“ (since 2002):www.ago-online.de N. Harbeck – used with permission uPA AND PAI-1 FIRST NOVEL TUMOR BIOLOGICAL FACTORS IN BC WITH LEVEL 1 OF EVIDENCE WHY ARE THEY NOT WIDELY USED? 1. ELISA not commonly used in pathological practice a. Biochemistry lab required b. Further personnel training required c. €€££$$ required 2. Frozen tumor specimen required 3. Large quantity (100 µg) required Target population = small tumors – feasible ? 4. Population used in validation studies: Interaction with ER status not well defined (?) uPA AND PAI-1 FIRST NOVEL TUMOR BIOLOGICAL FACTORS IN BC WITH LEVEL 1 OF EVIDENCE HOW CAN THEY BECOME WIDELY USED? 1. Refining ELISA test – less tissue 2. Alternative techniques – other protein assays – gene expression 3. Further validation according to ER status ALL ONGOING GENOMIC SIGNATURES IMPROVED RISK ASSESSMENT OF EARLY BREAST CANCER THROUGH GENE EXPRESSION PROFILING microarray Gene-expression profile Good signature ~4% die of breast cancer ~96% survive breast cancer Poor signature ~50% die of breast cancer ~50% survive breast cancer N Engl J Med, Vol 347 (25), Dec. 2002 BIG-TRANSBIG Secretariat– Used with permission TRANSLATING MOLECULAR KNOWLEDGE INTO EARLY BREAST CANCER MANAGEMENT INDEPENDENT VALIDATION : DESIGN Target n = 400 Amsterdam RNA Achieved n = 307 Tissue samples UK (Guy’s, Oxford) : 1984 => 1996 France (IGR, CRH) : 1978 => 1998 Sweden (Karolinska) : 1980 => 1990 • Node negative, untreated • < 60 years old • > 5 years follow-up • T1, T2 • Tumor cell % > 50% Gene expression profiling • Agilent platform • 70-gene prognostic custom designed chip Clinical data « Local » pathological data Audited clinical data Centrally reviewed path data (Milan) High or low gene signature risk Brussels Comparison of clinical vs gene signature assessment of prognostic risk Endpoints 1. TDM 2. OS 3. DMFS, DFS BIG-TRANSBIG Secretariat– Used with permission OVERALL SURVIVAL by GENE SIGNATURE RISK Amsterdam/Agendia Signature 0.6 10-year OS 70% (62%-76%) 0.4 Probability 0.8 1.0 10-year OS 89% (81%-94%) 0.2 Patients Events Risk group 16 Genetic low risk 66 Genetic high risk 0.0 113 194 0 2 4 6 8 10 12 14 98 130 82 110 69 90 45 53 Year 113 194 112 185 105 168 101 147 Number at risk 38 CLR 39 CHR Average Survival HR 2.66 M. Buyse et al. JNCI 2006. In press BIG-TRANSBIG Secretariat– Used with permission TRANSBIG INDEPENDENT VALIDATION The best signature? Amsterdam’s Signature 70 genes Rotterdam’s Signature 76 genes Brussels’ GGI signature Only few genes in common … But similar biological pathways TEST ALL IN VALIDATION SERIES & DECIDE BIG-TRANSBIG Secretariat– Used with permission 1.0 OVERALL SURVIVAL by GENE SIGNATURE RISK Rotterdam/Veridex Signature 0.6 low risk group: 0.98 (0.88-1.00) 0.4 high risk group: 0.84 (0.77-0.89) 10 year survival: PatientsEvents Risk group 0.2 Probability 0.8 5-year survival: 55 143 6 39 low risk group: 0.87 (0.73-0.94) Good signature Poor signature 0.0 HR (95% CI): 2.87 (1.21-6.82) 0 2 high risk group: 0.72 (0.63-0.78) Logrank P= 0.0126 4 6 8 10 46 98 38 89 Year Good signature 55 Poor signature 143 55 138 C. Desmedt et al. Presentated at: EBCC 2006 52 51 124 106 Number at risk BIG-TRANSBIG Secretariat– Used with permission CONCLUSIONS VALIDATION PHASE • The Amsterdam 70-gene signature has been independently validated • The Rotterdam 76-gene & Genomic Grade signatures have been independently validated using the same TRANSBIG validation series • The performances of the signatures are similar • There is a strong time dependency of all signatures (better predictors of EARLY RELAPSE), which was not seen for the clinical risk • The Amsterdam 70-gene test is robust (laboratory reproducibility) and available for patient diagnostic testing • GREEN LIGHT FOR MINDACT TRIAL! EORTC-BIG MINDACT TRIAL DESIGN 6,000 Node negative women Evaluate Clinical-Pathological risk and 70-gene signature risk 55% 32% N=3300 Clinical-pathological and 70-gene both HIGH risk Discordant cases Clin-Path HIGH 70-gene LOW 13% N=780 Clinical-pathological and 70-gene both LOW risk Clin-Path LOW 70-gene HIGH N=1920 Use Clin-Path risk to decide Chemo or not R1 Use 70-gene risk to decide Chemo or not Chemotherapy Endocrine therapy Potential CT sparing in 10-15% pts GENOMIC GRADE Sotiriou et al., ASCO 2005 Histologic Grade Genomic Grade G1 GG1 G2 GG2 G3 GG3 • Poor inter observer reproducibility • G2: difficult treatment decision making, under- or over treatment likely C. Sotiriou – used with permission • Findings consistent across multiple data sets and microarray platforms • More objective assessment • Easier treatment decision-making • High proportion of genes involved in cell proliferation ! GENOMIC GRADE IN EACH OF THE HISTOLOGIC GRADE SUBGROUPS Histological Grade 1 Histological Grade 2 HG1 Genomic Grade 1 C. Sotiriou et al. JNCI 2006 Histological Grade 3 HG3 HG2 Genomic Grade 3 C. Sotiriou – used with permission Oncotype DX NSABP & Genomic Health MULTI GENE RT-PCR ASSAY FOR PREDICTING RECURRENCE IN NODE NEGATIVE BC PATIENTS Tested using RT-PCR Three studies 250 candidate genes 21 GENE PREDICTOR low Recurrence score intermediate high THREE BREAST CANCER STUDIES USED TO SELECT CANDIDATE GENES FOR A RECURRENCE SCORE UNDER TAMOXIFEN TREATMENT PROLIFERATION Ki-67 STK15 Survivin Cyclin B1 MYBL2 INVASION Stromolysin 3 Cathepsin L2 Best RT-PCR performance and most robust predictors Recurrence score for TAM-treated pts established and subsequently validated HER2 GRB7 HER2 ESTROGEN ER PGR Bcl2 SCUBE2 GSTM1 CD68 BAG1 REFERENCE Beta-actin GAPDH RPLPO GUS TFRC Paik et al, N Engl J Med 2004 B14-RESULTS DRFS—Low, Intermediate, High RS Groups 100% 90% 338 pts 80% 149 pts 70% 181 pts 60% 50% DRFS 40% 30% 20% Low Risk (RS <18) Intermediate Risk (RS 18 - 30) High Risk (RS 31) 10% 0% 0 2 4 6 8 10 12 14 16 Years Paik et al, N Engl J Med 2004 PREDICTIVE MARKERS Oxford Overview 2000 NIH Consensus Panel 2000 ASCO Guidelines 2001 St Gallen Consensus Panel 2003 Accepted Predictive Markers In Breast Cancer HER-2 neu 95% Negative predictive value ER/PgR 30-70% Positive predictive value <5% chances of responding to TRASTUZUMAB (HER-2) or to HT (ER) 30%-70% chances of responding to HT (ER) & 40%-50% of responding to TRASTUZUMAB (HER-2) PREDICTIVE MARKERS FOR CHEMOTHERAPY ADJUVANT SETTING CMF vs. ANTHRA-BASED TOPO II RESULTS All pts with HER-2 amplification FISH Topo II non-amplified Topo II amplified 0.9 Anthra-Based 0.9 CMF 0.8 0.7 0.6 CMF % EFS 0.8 % EFS IHC 1.0 1.0 0.7 0.5 0.5 0.4 0.4 0.3 0.3 0 12 24 36 Time (Months) 8 15 7 14 4 11 48 Anthra-Based 0.6 Topo II pos. 1.0 0 12 4 CMF 15 9 Anthra 23 24 36 1.0 0.8 48 0.8 0.6 12 17 12 16 11 12 % HEC 0.4 0.4 HR=0.66 (0.32-1.36) p=0.25 0.2 Di Leo A et al, Clin Cancer Res, 2002 0.6 CMF % 15 21 CMF HEC Time (Months) No pts at risk: 4 11 Topo II neg. HR=1.26 (0.63-2.50) p=0.51 0.2 0.0 0.0 0 12 24 36 48 60 72 84 0 Time to first event (months) CMF 52 HEC 52 48 50 39 47 30 37 24 29 19 24 12 24 36 48 60 72 84 Time to first event (months) CMF 64 HEC 56 62 51 53 47 41 37 31 23 23 14 p-value interaction test: 0.13 Di Leo A et al, Ann Oncol 2001 BCIRG 006 4 x AC 4 x Docetaxel 60/600 mg/m2 100 mg/m2 4 x AC 4 x Docetaxel ACT Her2+ (Central FISH) N+ or high risk N- 60/600 mg/m2 100 mg/m2 ACTH 1 Year Trastuzumab 6 x Docetaxel and Carboplatin N=3,222 Stratified by Nodes and Hormonal Receptor Status 75 mg/m2 AUC 6 TCH Slamon D., SABCS 2005 1 Year Trastuzumab 1.0 Disease Free Survival 0.8 91% 86% 86% 80% 77% 84% 80% AC->TH TCH 73% 0.7 AC->T Patients Events 0.6 1073 1074 1075 147 77 98 AC->T AC->TH TCH HR (AC->TH vs AC->T) = 0.49 [0.37;0.65] P<0.0001 HR (TCH vs AC->T) = 0.61 [0.47;0.79] P=0.0002 0.5 % Disease Free 0.9 93% 0 1 2 3 Year from randomization 4 5 Slamon D., SABCS 2005 1.0 DFS CO-AMPLIFIED TOPO II BY ARM 0.8 AC->T TCH Patients AC->T AC->TH TCH 23 13 21 Logrank P= 0.24 0.6 227 265 252 Events Treatment 0.5 % Disease Free AC->TH 0 6 12 18 24 30 36 42 48 54 Months Slamon D., SABCS 2005 0.8 AC->TH TCH 0.6 Patients Events Treatment 458 472 446 92 45 54 AC->T AC->TH TCH Logrank P= <0.001 AC->T 0.0 % Disease Free 1.0 DFS NON CO-AMPLIFIED TOPO II BY ARM 0 6 12 18 24 30 36 42 48 54 Months Slamon D., SABCS 2005 HER-2 AND TOPOISOMERASE-II PROMISING POTENTIAL PREDICTIVE MARKERS OF ANTHRACYCLINE EFFICACY HOW TO OBTAIN LEVEL 1 EVIDENCE LARGE PROSPECTIVE TRIALS META-ANALYSIS HER-2 AND TOPOISOMERASE-II AS POTENTIAL PREDICTIVE MARKERS OF ANTHRACYCLINE EFFICACY: A META-ANALYSIS DANISH TRIAL FEC vs CMF BELGIAN TRIAL EC vs CMF UK TRIAL ECMF vs CMF NCIC-CTG TRIAL CEF vs CMF Tampere University Laboratory Central evaluation of HER-2/TOPO II gene amplification by FISH Correlation with outcome of CMF or anthracycline-based therapy with 4,500 tumor samples TOP TRIAL OR « TRIAL OF PRINCIPLE » Operable tumors, > 2 cm ER-negative Inflammatory or LABC Incisional biopsy ER-negative EPIRUBICIN 100 mg/m² x 4 EPIRUBICIN 100 mg/m² x 6 dose dense / 2w + G-CSF Snap frozen sample SURGERY Docetaxel x 4 Radiotherapy ± HT HER2/Topo2 FISH analysis (Vysis probe) Hypothesis : pCr in HER-2 / Topo2 co-amplified tumors pCr in HER-2 - / basal-like 1 tumors Gene expression analysis Genomic signature of response to anthracyclines EORTC-BIG-p53 TRANSLATIONAL RESEARCH TRIAL: STUDY DESIGN . Loc. adv. . Infl. . Large Operable R A N D Non Taxane arm FEC100 or Canadian FEC Local ± TAM therapy Taxane arm T-T-T-ET-ET-ET Local ± TAM therapy Sample 1: standard fixation Incisional biopsy Sample 2: snap frozen P53 analysis P53 pathway Target accrual= 1300 (872 p53-, 436 p53+) Hypothesis: ↑ DFS at 3 y by 5% in p53- and by 20% in p53+ Postmenopausal patients (no age limits) Non-candidates for CT T 2 cm Stages I, II & III ER and/or PgR+ 15 days FRAGRANCE trial 4 - 6 months Letrozole Genomic signature of de novo AI resistance Microarray Analysis Microarray Analysis Microarray Analysis INTEGRATING TRANSLATIONAL RESEARCH IN CLINICAL RESEARCH & PRACTICE INDISPENSABLE and already ongoing • Multidisciplinarity • Collaboration (between specialties, between centers…) • Bench-to-bedside-to-bench • Biological material collection (unethical not to do it!) • Patient selection & treatment tailored to the individual • New technologies, new statistical methods… • Costs ?? MINDACT & TRANSBIG FUNDING - 1 OTHER: National Funding Pharmaceutical Industry Biotechnology companies (Agendia) Other grants EU funding €7,000,000 NATIONAL FUNDING FOR NATIONAL PATIENTS (indispensible) EU funding Other Total expected costs: €35, 000,000 ACKNOWLEDGEMENTS BIG-TRANSBIG Team M. Piccart Bordet Fellows Translational Research Team