A Genomic Approach to Active Surveillance
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1 A Genomic Approach to Active Surveillance Eric A. Klein, M.D. Chairman Glickman Urological and Kidney Institute Professor of Surgery Cleveland Clinic Lerner College of Medicine Cleveland Clinic
2 Disclosures Genomic Health provided research support to Cleveland Clinic for this study No individual employed by CC nor Cleveland Clinic itself has a financial stake in Genomic Health I serve as a consultant to Genomic Health GenomeDx Metamark
3 Outcomes with Surveillance Overall Survival Cancer Specific Survival Klotz et al, JCO 28:126, 2010
4 Barriers to Adopting Surveillance Economic/Professional Doctors get trained & paid to treat, not watch Legal Failure to diagnose or cure Anxiety Patient, family, doctors Uncertainties in clinical tools to predict True biologic potential at diagnosis True biologic progression after initiating surveillance ( when to pull the trigger ) If delayed intervention is too late for cure
5 Conventional Pre-Treatment Models Stratify Average Risks at the Population Level Clinical Risk Groups Very Low Low Intermediate AVERAGE RISK
6 But Individual Risk Varies Widely for Patients Within Each Clinical Risk Group Clinical Risk Groups Very Low Low Intermediate INDIVIDUAL RISK Biological heterogeneity and biopsy undersampling limit accuracy, precision, and confidence of current risk assessment
7 The Promise of Genomics Unfavorable Biology Intermediate Risk Clinical Risk Groups Very Low Low Intermediate Favorable Biology Very Low Risk INDIVIDUAL RISK
8 Goal Develop a biopsy based test that can more accurately stratify risk Identify tumors that are Indolent & suitable for surveillance or Aggressive & not suitable for surveillance At time of diagnosis On interval biopsy while on surveillance
9 Challenges Small Tissue Samples Heterogeneity
10 Oncotype DX Genomic Prostate Score (GPS): Test Development Prostate Cancer Technical Feasibility Prostatectomy Study (Cleveland Clinic) Two tumor foci per patient (n=441) 1º endpoint: Clinical Recurrence (metastasis) 2º endpoints: PCSS, BCR, Adverse Pathology at RP 727 candidate genes Biopsy Study (Cleveland Clinic) Needle biopsy specimens (n=167) 1º endpoint: Adverse Pathology at RP 81 genes selected from Prostatectomy Study Analytical Validation 17-Gene Genomic Prostate Score Assay 17 genes selected for final assay Klein et. al. ASCO GU 2011 Klein et. al. ASCO 2012
11 Methods Specimens re-reviewed for assignment of stage & grade (2005 Consensus) Manual microdissection Two tumor foci Primary Gleason pattern Highest Gleason pattern Gleason Pattern 3 Gleason Pattern 4 RNA extraction Quantitative RT- PCR (Oncotype Dx assay) for each gene in triplicate Data analysis Identify specific gene expression levels associated with outcome (cr, br, PCSS) Cox regression controlling the false discovery rate at 10%
12 Genes Associated With Clinical Outcome Cluster Into Gene Families with Related Biological Functions
13 Hazard Ratios for Genes Associated with Metastasis or Death Better Outcome Univariate Std. HRs for crfi Cox PH Regression Worse Outcome Stress DUSP1 FOS Migration GSTM2 PPAP2B Proliferation BIRC5 TOP2A ECM COL3A1 FAP Std. Hazard Ratio for Clinical Recurrence Stnd Hazard Ratio for Clinical Recurrence Highest Primary \\Lims\medical\Prostate\CCFProstateGI(09-002)\Analysis\AAGUS\Programs\g_ForestcRFIStdHR4GeneGrp_xGP.sas 30MAR2011:1226 SCL: jyue
14 Pattern genes Overcoming Heterogeneity 288 genes 288 genes that predict outcome whether their expression is assessed in pattern 3 or pattern 4 Pattern genes
15 Multiple Gene Groups Add Prognostic Value beyond Clinical and Pathological Covariates Better Outcome Worse Outcome Stress Migration DUSP1 FOS GSTM2 PPAP2B Unadjusted Adj. for path T-stage Adj. for surgical GS Adj. for Gleason pattern Proliferation ECM BIRC5 TOP2A COL3A1 FAP Adj. for CAPRA risk group Adj. for AUA risk group Std. Hazard HR Ratio (95% CI) AUA CAPRA
16 Biopsy Study Results Endpoint = Adverse RP Adverse Pathology High grade Non-organ confined Both
17 Oncotype DX Genomic Prostate Score (GPS): Independent Clinical Validation Prostate Cancer Technical Feasibility Prostatectomy Study (Cleveland Clinic) Two tumor foci per patient (n=441) 1º endpoint: Clinical Recurrence (metastasis) 2º endpoints: PCSS, BCR, Adverse Pathology at RP Biopsy Study (Cleveland Clinic) Needle biopsy specimens (n=167) 1º endpoint: Adverse Pathology at RP Study results to be presented at AUA 2013 by Cooperberg et al. Wed., May 8 th 8:00AM Prostate: Markers (I) Room 1 Abstract #2131 Analytical Validation 17-Gene Genomic Prostate Score Assay UCSF Clinical Validation Study Biopsy Specimens (n=395) GPS Predicts Adverse Pathology
18 Improved Risk Stratification Clinical Risk Groups Very Low Low Intermediate High GPS Unfavorable Biology Intermediate Risk Low GPS Favorable Biology Very Low Risk INDIVIDUAL RISK Combining GPS with clinical assessment more accurately identifies a larger population of patients who can confidently choose active surveillance
19 How will this help manage patients? Initial Biopsy Gene Signature good Gene Signature bad Surveillance Treatment Repeat Biopsy Gene Signature good Gene Signature bad
20 Acknowledgements Genomic Health Tara Maddala Carl Millward Rick Baehner Joff Baker Robert Pelham Diana Cherbavaz William Novotny Louise Polychronopoulos Mark Lee Steve Shak Cleveland Clinic Cristina Magi-Galluzzi Sara Falzarano Alwyn Reuther
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