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USING PROGNOSTIC & PREDICTIVE FACTORS IN BREAST CANCER

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. %. %.

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USING PROGNOSTIC & PREDICTIVE FACTORS IN BREAST CANCER

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  1. 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

  2. PROGNOSTIC FACTOR % Treat. A Treat. B + -

  3. PREDICTIVE FACTOR Case 1 Case 2 Treat. B % % Treat. B Treat. A Treat. A - + + -

  4. WHY DO WE NEED PROGNOSTIC AND PREDICTIVE FACTORS PROGNOSTIC FACTORS Who needs a treatment? PREDICTIVE FACTORS Which treatment is best? THERAPEUTIC CHOICES INDIVIDUALIZE TREATMENT AVOID UNDER AND OVER TREATMENT

  5. BC GENE EXPRESSION PATTERNS and OUTCOME Molecular (re-)classification of BC ER- ER+ HER-2-like Luminal 2 Luminal 3 Basal-like 1 Basal-like 2 Luminal 1 RFS Adapted from Sotiriou et al, PNAS, 2003

  6. 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 AC x 4  Paclitaxel x 4 ++ ++ CMF x 6 AC x 4 + + L-PAM, MF ± ± 1970’s 1980’s 2000’s 1990’s Successive generations of adjuvant CT regimens +++ ADJUVANT TRASTUZUMAB +++ Adapted with permission from G. Hortobagyi

  7. 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 Oncotype DX* (predictive & Px) Genomic signatures Cyclin E Topo-II- *Genomic Health

  8. uPA-PAI-1

  9. 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

  10. uPA AND PAI-1 FIRST NOVEL TUMOR BIOLOGICAL FACTORS IN BC WITH LEVEL 1 OF EVIDENCE WHY ARE THEY NOT WIDELY USED? • ELISA not commonly used in pathological practice • Biochemistry lab required • Further personnel training required • €€££$$ required • Frozen tumor specimen required • Large quantity (100 µg) required • Target population = small tumors – feasible ? • Population used in validation studies: Interaction with ER status not well defined (?)

  11. uPA AND PAI-1 FIRST NOVEL TUMOR BIOLOGICAL FACTORS IN BC WITH LEVEL 1 OF EVIDENCE HOW CAN THEY BECOME WIDELY USED? • Refining ELISA test • less tissue • Alternative techniques • other protein assays • gene expression • Further validation according to ER status ALL ONGOING

  12. GENOMIC SIGNATURES

  13. 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

  14. TRANSLATING MOLECULAR KNOWLEDGE INTO EARLY BREAST CANCER MANAGEMENT

  15. INDEPENDENT VALIDATION : DESIGN Target n = 400 • Amsterdam • Gene expression profiling • Agilent platform • 70-gene prognostic • custom designed • chip RNA High or low gene signature risk 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% Brussels Comparison of clinical vs gene signature assessment of prognostic risk Endpoints 1. TDM 2. OS 3. DMFS, DFS Clinical data « Local » pathological data Centrally reviewed path data (Milan) Audited clinical data

  16. OVERALL SURVIVAL by GENE SIGNATURE RISK Amsterdam/Agendia Signature 10-year OS 89% (81%-94%) 10-year OS 70% (62%-76%) Average Survival HR 2.66 • M. Buyse et al. JNCI 2006. In press

  17. TRANSBIG INDEPENDENT VALIDATION The best signature? Rotterdam’s Signature 76 genes Brussels’ GGI signature Amsterdam’s Signature 70 genes Only few genes in common … But similar biological pathways TEST ALL IN VALIDATION SERIES & DECIDE

  18. OVERALL SURVIVAL by GENE SIGNATURE RISK Rotterdam/Veridex Signature 5-year survival: low risk group: 0.98 (0.88-1.00) high risk group: 0.84 (0.77-0.89) 10 year survival: low risk group: 0.87 (0.73-0.94) high risk group: 0.72 (0.63-0.78) • C. Desmedt et al. Presentated at: EBCC 2006

  19. 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!

  20. EORTC-BIG MINDACT TRIAL DESIGN 6,000 Node negative women Evaluate Clinical-Pathological risk and 70-gene signature risk 55% 32% 13% N=780 N=3300 Discordant cases Clinical-pathological and 70-gene both LOW risk Clinical-pathological and 70-gene both HIGH risk Clin-Path HIGH 70-gene LOW Clin-Path LOW 70-gene HIGH R1 N=1920 Use Clin-Path risk to decide Chemo or not Use 70-gene risk to decide Chemo or not Chemotherapy Endocrine therapy Potential CT sparing in 10-15% pts

  21. GENOMIC GRADE

  22. Sotiriou et al., ASCO 2005 • Poor inter observer reproducibility • G2: difficult treatment decision making, under- or over treatment likely • Findings consistent across multiple data sets and microarray platforms • More objective assessment • Easier treatment decision-making • High proportion of genes involved in cell proliferation ! C. Sotiriou – used with permission

  23. Histological Grade 1 Histological Grade 2 HistologicalGrade 3 HG3 HG1 HG2 Genomic Grade 3 Genomic Grade 1 GENOMIC GRADE IN EACH OF THE HISTOLOGIC GRADE SUBGROUPS C. Sotiriou et al. JNCI 2006 C. Sotiriou – used with permission

  24. Oncotype DX NSABP & Genomic Health

  25. 21 GENE PREDICTOR Recurrence score low intermediate high MULTI GENE RT-PCR ASSAY FOR PREDICTING RECURRENCE IN NODE NEGATIVE BC PATIENTS Tested using RT-PCR Three studies 250 candidate genes

  26. THREE BREAST CANCER STUDIES USED TO SELECT CANDIDATE GENES FOR A RECURRENCE SCORE UNDER TAMOXIFEN TREATMENT PROLIFERATION Ki-67 STK15 Survivin Cyclin B1 MYBL2 ESTROGEN ER PGR Bcl2 SCUBE2 HER2 GRB7 HER2 GSTM1 REFERENCE Beta-actin GAPDH RPLPO GUS TFRC CD68 INVASION Stromolysin 3 Cathepsin L2 BAG1 Best RT-PCR performance and most robust predictors Recurrence score for TAM-treated pts established and subsequently validated Paik et al, N Engl J Med 2004

  27. B14-RESULTS DRFS—Low, Intermediate, High RS Groups 338 pts 149 pts 181 pts Paik et al, N Engl J Med 2004

  28. PREDICTIVE MARKERS

  29. NIH Consensus Panel 2000 St Gallen Consensus Panel 2003 ASCO Guidelines 2001 Oxford Overview 2000 Accepted Predictive Markers In Breast Cancer HER-2 neu ER/PgR 95% Negative predictive value 30-70% Positive predictive value 30%-70% chances of responding to HT (ER) & 40%-50% of responding to TRASTUZUMAB (HER-2) <5% chances of responding to TRASTUZUMAB (HER-2) or to HT (ER)

  30. PREDICTIVE MARKERS FOR CHEMOTHERAPY

  31. ADJUVANT SETTING CMF vs. ANTHRA-BASED TOPO II  RESULTS All pts with HER-2 amplification FISH IHC Di Leo A et al, Clin Cancer Res, 2002 Di Leo A et al, Ann Oncol 2001

  32. BCIRG 006 4 x Docetaxel 100 mg/m2 4 x AC60/600 mg/m2 ACT Her2+ (Central FISH) N+ or high riskN- 4 x Docetaxel 100 mg/m2 4 x AC60/600 mg/m2 ACTH 1 Year Trastuzumab 6 xDocetaxel and Carboplatin 75 mg/m2 AUC 6 N=3,222 TCH Stratified by Nodes and Hormonal Receptor Status 1 Year Trastuzumab Slamon D., SABCS 2005

  33. Disease Free Survival 1.0 93% 0.9 AC->TH 91% 86% 84% 86% 80% 80% TCH 0.8 77% 73% % Disease Free AC->T 0.7 Patients Events 1073 147 AC->T 0.6 HR (AC->TH vs AC->T) = 0.49 [0.37;0.65] P<0.0001 1074 77 AC->TH 1075 98 TCH HR (TCH vs AC->T) = 0.61 [0.47;0.79] P=0.0002 0.5 0 1 2 3 4 5 Slamon D., SABCS 2005 Year from randomization

  34. DFS CO-AMPLIFIED TOPO II BY ARM 1.0 AC->TH AC->T 0.8 % Disease Free TCH Patients Events Treatment AC->T 227 23 Logrank P= 0.24 265 13 AC->TH 252 21 TCH 0.6 0.5 0 6 12 18 24 30 36 42 48 54 Months Slamon D., SABCS 2005

  35. DFS NON CO-AMPLIFIED TOPO II BY ARM 1.0 0.8 % Disease Free AC->TH TCH Patients Events Treatment 0.6 458 92 AC->T 472 45 AC->TH Logrank P= <0.001 AC->T 446 54 TCH 0.0 0 6 12 18 24 30 36 42 48 54 Months Slamon D., SABCS 2005

  36. HER-2 AND TOPOISOMERASE-II PROMISING POTENTIAL PREDICTIVE MARKERS OF ANTHRACYCLINE EFFICACY HOW TO OBTAIN LEVEL 1 EVIDENCE LARGE PROSPECTIVE TRIALS META-ANALYSIS

  37. HER-2 AND TOPOISOMERASE-II AS POTENTIAL PREDICTIVE MARKERS OF ANTHRACYCLINE EFFICACY: A META-ANALYSIS DANISH TRIAL FEC vs CMF UK TRIAL ECMF vs CMF BELGIAN TRIAL EC vs CMF NCIC-CTG TRIAL CEF vs CMF Tampere University Laboratory Central evaluation of HER-2/TOPO II gene amplificationby FISH Correlation with outcome of CMF or anthracycline-based therapy with  4,500 tumor samples

  38. TOP TRIAL OR « TRIAL OF PRINCIPLE » Operable tumors, > 2 cm ER-negative Incisional biopsy Inflammatory or LABC ER-negative Snap frozen sample EPIRUBICIN 100 mg/m² x 4 EPIRUBICIN 100 mg/m² x 6 dose dense / 2w + G-CSF SURGERY Gene expression analysis HER2/Topo2 FISH analysis (Vysis probe) Docetaxel x 4 Radiotherapy ± HT Genomic signature of response to anthracyclines Hypothesis :  pCr in HER-2 / Topo2 co-amplified tumors  pCr in HER-2 - / basal-like 1 tumors

  39. Local ± TAM therapy . Loc. adv. . Infl. . Large Operable Non Taxane arm FEC100 or Canadian FEC R A N D Local ± TAM therapy Taxane arm T-T-T-ET-ET-ET Sample 1: standard fixation Incisional biopsy Sample 2: snap frozen P53 analysis P53 pathway EORTC-BIG-p53 TRANSLATIONAL RESEARCH TRIAL: STUDY DESIGN Target accrual= 1300 (872 p53-, 436 p53+) Hypothesis: ↑ DFS at 3 y by 5% in p53- and by 20% in p53+

  40. Postmenopausal patients (no age limits) Non-candidates for CT T 2 cm Stages I, II & III ER and/or PgR+ FRAGRANCE trial 15 days 4 - 6 months Letrozole Genomic signature of de novo AI resistance Microarray Analysis Microarray Analysis Microarray Analysis

  41. 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 ??

  42. 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) Total expected costs: €35, 000,000

  43. ACKNOWLEDGEMENTS BIG-TRANSBIG Team Bordet Fellows M. Piccart Translational Research Team

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