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Axel Grothey Mayo Clinic College of Medicine Rochester, MN

Have We Made Progress in Pharmacogenomics and in the Implementation of Molecular Markers in Colorectal Cancer ?. Axel Grothey Mayo Clinic College of Medicine Rochester, MN. Definitions. Pharmacogenomics:

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Axel Grothey Mayo Clinic College of Medicine Rochester, MN

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  1. Have We Made Progress in Pharmacogenomics and in the Implementation of Molecular Markers in Colorectal Cancer ? Axel Grothey Mayo Clinic College of Medicine Rochester, MN

  2. Definitions • Pharmacogenomics: • Assessment of influence of genetic variation on drug response by correlating gene expression or single-nucleotide polymorphisms (SNPs) with a drug's efficacy or toxicity • Whole genome application of pharmacogenetics, which examines single gene interactions with drugs • Biomarker: • Property of the tumor or the host associated with clinical outcome • Either single trait or grouping of traits (signature)

  3. To Distinguish… • Predictive vs prognostic markers • Some biomarkers are predictive AND prognostic • Biomarkers can be used to predict efficacy and/or toxicity • Somatic vs germline markers (mutations) • Single marker analysis vs genome-wide approach

  4. Single marker analysis - Chemotherapy

  5. 5-FU: Predictive Markers RNA DPD FU FUH2 FUrd FUMP FUDP FUTP TP FUdR FUPA FdUMP FdUDP FdUTP LV FBAL TS DNA dTMP dUMP 5,10-CH3THF DHF

  6. DPD, TS and TP Gene Expression vsResponse to 5-FU/LV in Colorectal Cancer 1.2 Response Non response 1 DPD 0.8 TS Danenberg Tumor Profile Scale TP 0.6 0.4 0.2 0 7 91 583 135 137 150 154 165 204 289 361 374 574 438 121 152 164 189 196 217 220 270 278 288 359 396 401 458 526 559 582 585 105m Patient ID Number Salonga et al. Clin Cancer Res 2000

  7. Irinotecan-Metabolism Irinotecan CH3 CH2 O N O N Inhibition of topoisomerase I O N C O O N HO CH2CH3 Carboxylesterase CH3 SN-38 (=active agent) CH2 O HO O N O N HO CH2CH3 UGT1A1*1 (TA)6 UGT Glucuronidation(Detoxification) UGT1A1*28 (TA)7

  8. UGT1A1 Polymorphism Predicts Severe Neutropenia on Irinotecan: 7/7 vs 6/7 + 6/6 Genotypes From Parodi et al, FDA Subcommittee presentation, November, 2004

  9. N9741 - Rates of Grade 4 Neutropenia for Genotype by Treatment. *Based on test of trend McLeod et al. ASCO GI 2006

  10. Glutathione-S-Transferase P1 I105V Polymorphism • GSTP1 = detoxifying enzyme that catalyzes the conjugation of glutathione to an electrophilic center in the toxic compound • Single-nucleotide polymorphism (SNP) at residue 105 (C or T) determines enzymatic activity • T (Isoleucine)  C (Valine) substitution leads to • Lower enzymatic activity • Lower thermal stability  Reduced detoxicating properties of GSTP1 Johansson et al., J Mol Biol 1998

  11. GST-P1 I105V (TC) Polymorphism Predicts Early Onset of Oxaliplatin-mediated Neurotoxicity % Grade 2/3 Neurotoxicity P=0.030 mg/m2 cum. oxaliplatin-dose Grothey et al., ASCO 2005

  12. XPD, ERCC1, TS, GSTP1 17.4 mo 5.4 mo Multifactor Analysis 5-FU/Oxaliplatin-Treated Patients Stoehlmacher et al. BJC 2004

  13. Only a subgroup of patients benefits from EGF-R targeted therapy 1.0 0.9 0.8 0.7 Event-free Probability 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Panitumumab vs. BSC: PFS Panitumumab BSC Hazard ratio=0.54 (95% CI: 0.44, 0.66) Stratified log-rank test P < .000000001 0 8 16 24 32 40 48 56 Weeks from Randomization Van Cutsem et al., JCO 2007

  14. Selected Potential Predictors of Anti-EGFR Therapy in CRC • Tumor-related factors • EGFR mutations • EGFR expression levels • Alterations in EGFR signaling pathway • Patient-related factors • Intensity of skin rash • Genetic polymorphism in, e.g. components of EGFR pathway, ADCC activation

  15. Cetuximab + Irinotecan n/N (%) Cetuximab n/N (%) Percentage of EGFR-expressing cells ≤10% 25/109 22.9 4/56 7.1 >10 - ≤20% 4/20 20.0 5/16 31.3 >20 - ≤35% 6/27 22.2 0/7 0.0 >35% 15/62 24.2 3/32 9.4 EGFR-staining intensity Faint 11/53 20.8 1/21 4.8 Weak/moderate 22/89 24.7 7/55 12.7 Strong 17/75 22.7 4/34 11.8 No Correlation of Response Rate and EGFR Expression Cunningham et al. NEJM 2004

  16. Gene Copy Number of EGFR and Response to EGFR Antibodies FISH • 31 pts with CRC treated with cetuximab- or panitumumab-based therapy • Increased EGFR copy number in • 8/9 pts with response • 1/21 pts without response(p<0.0001) Dual color FISH assays for probes of EGFR (red) and Chr 7 (CEP7, green) Moroni et al., Lancet Oncol 2005

  17. KRAS Mutation Status Predictive of Response to Cetuximab? • 30 patients with CRC on cetuximab • PR: 11/30 patients (37%) • KRAS mutation in • 0/11 responders • 13/19 non-responders (68%) • p=0.0003 • Increased EGFR gene copy number in 10% • significantly associated with response (p=0.04) 16.3 mo 6.9 mo Lievre et al. Cancer Res 2006

  18. COX-2, IL-8 and EGFR Gene Expression Levels Associated with Survival on Cetuximab 1.00 Adjusted log-rank p value = 0.028 0.90 0.80 0.70 0.60 Estimated probability of survival All low expressions (n = 12) 0.50 0.40 0.30 0.20 0.10 Any high expression (n = 16) 0.00 0 3 6 9 12 15 18 21 24 Months since start of cetuximab treatment Vallböhmer et al., JCO 2005

  19. Genome-Wide Approaches • Potential to obtain comparative gene expression profiles and genetic fingerprints • Can lead to identification of novel biomarkers and potential therapeutic target • Different technologies applied: • Expression profiling microarrays • SNP arrays • Array-based comparative genomic hybridization (CGH)

  20. Genome-Wide Approaches 32,000 gene microarray 78 tumors (Dukes B/C) 53 prognostic genes identified Eschrich et al. JCO 2005

  21. Gene Signatures: Limitations and Challenges • Fresh Frozen Tissue versus Formalin-Fixed Paraffin-Embedded Tissue • Tissue Specific Array versus Non Tissue Specific Arrays • Quantitative Gene Expression Profiles versus Arrays

  22. Candidate Gene Approach Genomic Health • Expert selection of genes of interest • 142 genes exhibited a significant linear relationship with RFI (p<0.05) in NSABP C-01/02 • 78 genes exhibited a significant linear relationship with RFI (p<0.05) after controlling for important covariates • The prognostic genes in colon cancer are different from those in breast cancer • Preliminary analysis of NSABP C-04 indicate that many genes are confirmed to be prognostic in colon cancer O’Connell et al. ASCO 2006

  23. Candidate Gene Approach O’Connell et al. ASCO 2006

  24. Challenges • Combination therapy complicates choice of appropriate biomarkers • Identification of biomarkers lags behind standard of care and agents used in clinical trials • Most biomarkers identified in retrospective analysis without (or pending) prospective validation • Complex, step-wise trial designs to validate usefulness of biomarkers • Large sample size

  25. Trial Designs:1. Marker by Treatment Interaction Treatment A Marker + R Treatment B Register Test Marker Treatment A Marker - R Treatment B Validation of marker as predictor for response to specific treatment No proof yet that marker-based treatment strategy is superior Sargent et al. JCO 2005

  26. Trial Designs (Example):1. Marker by Treatment Interaction 5-FU/Irino TS low R Oxali/Irino Register Test TS 5-FU/Irino TS high R Oxali/Irino Validation of marker as predictor for response to specific treatment No proof yet that marker-based treatment strategy is superior Sargent et al. JCO 2005

  27. Trial Designs:2. Marker-Based Strategy Marker + Treatment A Marker-basedstrategy Marker - Treatment B Register R Test Marker Treatment A Non-marker-based strategy R Treatment B Validation that marker-based treatment strategy is superior to random choice of therapy Sargent et al. JCO 2005

  28. Phase II Trial Designs (Example):2. Marker-Based Strategy TS low 5-FU/Irino Marker-basedstrategy TS high Oxali/Irino Register R Test TS 5-FU/Irino Non-marker-based strategy R Oxali/Irino Validation that marker-based treatment strategy is superior to random choice of therapy Sargent et al. JCO 2005

  29. Phase II NCCTG/ECOG ProposalMarker-driven First-Line CRC KRAS wt or EGFR ampl. FOLFOX + EGFR-mAb KRAS analysis EGFR gene amplification KRAS mut andno EGFR ampl FOLFOX + Bevacizumab • Statistical calculations: • Primary Endpoint: RR • FOLFOX+Cetuximab 70% • FOLFOX+BEV 50% • N=200 • =0.10 (two-sided) • 90% power

  30. Conclusions • Biomarker-driven treatment strategies hold promise of individualized, tailored therapeutic approaches with • Higher efficacy • Lower toxicity • Improved cost-effectiveness • Biomarkers are can be derived from retrospective analysis of single/multiple factors or from comparative genomic screening • Prospective validation of biomarkers in clinical trials are challenging, but necessary

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