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Journal Club Cremona 24 Maggio 2008 Genomica e proteomica: significato e utilità attuali Alberto Ballestrero Clinica di Medicina Interna a indirizzo Oncologico DIMI - Università di Genova Incorporation of genomic into breast cancer management Prognosis Gene expression analysis Who treat? Prediction Which therapy? Classification/ Gene discovery Improve biological knowledge Gene expression analysis assumptions 1) Expression analysis allows identifying the tumour transcriptional features (transcriptoma) 2) Transcriptoma contains the information required to predict tumour evolution and response to treatments Technologies used for high-throughput gene expression analysis Marchionni, L. et. al. Ann Intern Med 2008;148:358-369 Netherlands signature 70 significant prognosis genes in N- patients 78 tumors Good signature Poor signature Van’t Veer et al. Nature, 2002 Are results reproducible? September 2006 Median coefficient of variation for: within-laboratory replicates = 5-15% between-laboratory replicates = 10-20% Building a genomic classifier Patients of interest Testing set Internal validation Training set Classifier Esternal validation: • Retrospective Classifier gene selection: discriminant analysis linear or not linear • Prospective Independent patients 70-gene prognostic signature (“Netherlands signature”) 1st Validation Study van de Vijver et al. N Engl J Med, 2002 Van’t Veer et al. Nature, 2002 Mammaprint Agendia Netherlands signature: 151 N- patients Van de Vijver MJ et al. N Engl J Med 347:1999-2009, 2002 Netherlands signature: 144 N+ patients Van de Vijver MJ et al. N Engl J Med 347:1999-2009, 2002 Reclassify St. Gallen and NIH subgroups according to 70-gene signature: 151 N- patients Van de Vijver MJ et al. N Engl J Med 347:1999-2009, 2002 The gene-expression profile is a more powerful predictor of the outcome of disease in young patients with breast cancer than standard systems based on clinical and histologic criteria. Risk assessments for metastases and death: 70-gene signature vs Adjuvant 2nd Validation Study Buyse et al. J Natl Cancer Inst, 2006 N° of patients in risk groups Mts within 5 yrs Deaths within 10 yrs Risk classification High Low Sensitivity Specificity Sensitivity Specificity 70-gene signature 194 113 0.90 (0.78-0.95) 0.42 (0.36-0.48) 0.84 (0.73-0.92) 0.42 (0.36-0.48) Adjuvant! 222 80 0.87 (0.75-0.94) 0.29 (0.24-0.35) 0.82 (0.71-0.90) 0.29 (0.23-0.35) Both test correctly identify the high risk patients. Gene signature is superior in correctly identifying the low risk patients. 90% (CI 85%-96%) DMF 71% (CI 65%-78%) 30% discordant cases between 70-gene signature and Adjuvant Buyse et al. J Natl Cancer Inst 2006 MINDACT trial a testing hypotesis for a key question Key question for use of 70-gene to decide on chemotherapy. Evaluate the risk of undertreating patients who would otherwise get chemotherapy per clinical-pathological criteria. Testing hypotesis. The patients who have a low risk gene prognosis signature and high risk clinical-pathologic criteria, and who were randomized to receive no chemotherapy has a 5-year DMFS = 92% (null hypothesis). EORTC-BIG MINDACT TRIAL DESIGN 6,000 Node negative women Assess clinical risk and genomic risk Clinical and Genomic BOTH HIGH RISK DISCORDANT Clinical and Genomic Risks Clinical and Genomic BOTH LOW RISK RANDOMIZE decision-making Use clinical risk High risk Chemotherapy High risk Use genomic risk Low risk Low risk No chemotherapy Oncotype DX® 21-Gene Recurrence Score (RS) Assay 16 Cancer and 5 Reference Genes From 3 Studies PROLIFERATION Ki-67 STK15 Survivin Cyclin B1 MYBL2 ESTROGEN RS = ER PR Bcl2 SCUBE2 GSTM1 INVASION Stromelysin 3 Cathepsin L2 HER2 GRB7 HER2 BAG1 CD68 REFERENCE Beta-actin GAPDH RPLPO GUS TFRC + 0.47 x HER2 Group Score - 0.34 x ER Group Score + 1.04 x Proliferation Group Score + 0.10 x Invasion Group Score + 0.05 x CD68 - 0.08 x GSTM1 - 0.07 x BAG1 Category RS (0-100) Low risk RS <18 Int risk RS ≥18 and <31 High risk RS ≥31 Paik et al. N Engl J Med. 2004;351:2817-2826. 17 Prediction of recurrence in N0 ER positive patients (TAM treated) Paik et al. N Engl J Med. 2004;351:2817-2826 Prediction of chemotherapy benefit in Node-negative, ER-positive breast cancer: NSABP B-20 (Paik S et al. JCO 2006) TAM vs TAM + CT - 651 evaluable patients Patient reclassification Low risk 4.4 absolute benefit from TAM+CT RS Intermediate risk High risk RS predicts chemotherapy benefit Schema: TAILORx Node-Neg, ER-Pos Breast Cancer Oncotype DX® Assay RS <10 Hormone Therapy RS 11-25 Randomize Hormone vs Chemotherapy + Hormone RS >25 Chemotherapy + Hormone Primary study group To determine whether adjuvant hormonal therapy is not inferior to adjuvant chemohormonal for patients in the “primary study group” Oncologist treatment recommendations after RS: N- ER+ patients Others Genetic Element of Interest Chin L, Gray JW. Nature 2008 Why proteomic? Cellular signaling events are driven by protein-protein interactions, post-translational protein modifications and enzymatic activities that cannot be predicted accurately or described by transcriptional profiling methods alone. Proteomic analysis of human breast cancer J Proteome Res, 2008 EGFR family signaling, AKT/mTOR pathway activation, c-kit/abl growth factor signaling and ERK pathway Tumour as a system = organoid Tumour stem cells Tumour cell subpopulations Microenvironment Immune cells