Pharmacogenomics in Colon Cancer: Fantasy or Reality? Heinz-Josef Lenz, MD Professor of Medicine and Preventive Medicine Director, GI Oncology Program USC/Norris Comprehensive Cancer Center ASCO/ONS Highlights 2008 Potential Predictive Markers for Colon Cancer Treatment Drug Marker Fluoropyrimidines TS, DPD*, TP, MSI, MTHFR expression /polymorphisms Irinotecan UGT polymorphisms*, MSI, transporter polymorphisms Oxaliplatin ERCC1, GST P1, XPD expression, transporter polymorphisms EGFR Antibodies gene amplification/polymorphism, RAS mutation, BRAF mutation, ligand expression, PTEN expression, VEGF levels VEGF inhibitors VEGF polymorphisms, ICAM polymorphisms/levels, E-selectin levels, HIF1, Glut-1, VEGFr gene expression General Circulating tumor cells *FDA-recognized Meropol ASCO 2008 1
How to Use Predictive or Prognostic Markers When (Prognostic) With what (Predictive) How much (Predictive) What combination (Predictive) 2
3
Molecular Predictors of EGFR Inhibitors EGF Receptor: A Rational Target for CRC Therapy Ligand: AREG, EREG Target for EGFT-TK inhibitor P13K PTEN P AKT P py py STAT MYC JUN FOS Proliferation/ maturation Chemotherapy/ radiotherapy resistance Gene transcription Cell-cycle progression MYC Angiogenesis GRB2 SOS Cyclin D1 Cyclin D1 Invasion and metastasis RAS RAF MEK MAPK Survival (antiapoptosis) Meyerhardt JA, Mayer RJ. N Engl J Med. 2005;352:476-487; Venook A. Oncologist. 2005;10:250-261. py EGFR-TK 4
KRAS mutations: 40% of colorectal cancer an Early Event Reference:Fodde R et al Nature Rev cancer 2001 Reference A Liévre, et al. (JCO, 2007) Treatment (panitumumab or Certuximab) No. of patients (WT:MT) Objective response n (%) MT WT Cetuximab ± CT 76 (49:27) 0 (0%) 24 (49%) S Benvenuti, et al. (Cancer Res, 2007) Panitumumab or Cetuximab or Cetuximab + CT 48 (32:16) 1 (6%) 10 (31%) W De Roock, et al. (Annals of Oncology, 2007) Cetuximab or Cetuximab + irinotecan 113 (67:46) 0 (0%) 27 (40%) D Finocchiaro, et al. (ASCO Proceedings, 2007) Cetuximab ± CT 81 (49:32) 2 (6%) 13 (26%) F Di Fiore, et al. (Br J Cancer, 2007) Cetuximab + CT 59 (43:16) 0 (0%) 12 (28%) S Khambata-Ford, et al. Cetuximab 80 (50:30) 0 (0%) 5 (10%) WT = wild type; MT = mutant; CT = chemotherapy (J Clin Oncol, 2007) 5
Percent Decrease of Target Lesions in KRAS Evaluable Patients Pmab + BSC BSC Alone % Change % Change 160 140 120 100 80 60 40 20 0-20 -40-60 -80 160 140 120 100 80 60 40 20 0-20 -40-60 -80 PR (0%) Mutant SD (12%) PD (70%) Patient PR (0%) SD (8%) PD (60%) Patient 160 140 120 100 80 60 40 20 0-20 -40-60 -80 % Change 160 140 120 100 80 60 40 20 0-20 -40-60 -80 % Change PR (17%) Wild-Type SD (34%) PD (36%) Patient PR (0%) SD (12%) PD (75%) Patient BSC = Best supportive care; Pmab = panitumumab Amado 2008 ASCO GI abstract #278 Overall survival according to KRAS mutation and skin toxicity 1.00 2 good prognostic factors (wild type and grade 2-3 skin toxicity) 1good prognostic factors (wild type or grade 2-3 skin toxicity) 0 good prognostic factors (KRAS mutant and grade 0-1 skin toxicity) Survival probability 0.25 0.50 0.75 5.6 months (95%CI: 2.8-10.6) 15.6 months (95%CI, 10.9-22) 10.7 months (95%CI, 8.3-16.3) p = 0.0008 0.00 0 10 20 30 Months Uses colours from showfile part 1 in L:\Medi Cine International\Merck - NEW\Erbitux\Completed\Meetings\MK13677 6th EAN, Nov 07\Deliverables\Slides\SHOWFILES AND FINAL SLIDES 6
Response rate (%) 70 60 50 40 30 20 10 0 FOLFIRI CRYSTAL (n=540) 43 59 Cetuximab + FOLFIRI 1 Bokemeyer C et al, ASCO 2008 OPUS 1 (n=233) 37 FOLFOX 61 Cetuximab + FOLF0X PFS estimate PFS estimate 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 p=0.017 p=0.016 CRYSTAL - KRAS wild-type: HR=0.68 32% risk reduction for progression 0 2 4 6 8 10 12 14 16 18 Months OPUS - KRAS wild-type: HR=0.57 43% risk reduction for progression 0 2 4 6 8 10 12 Months a In the combination therapy group (mt vs wt): PFS=12 vs 34 weeks, p=0.016; OS=6.3 vs 10.3 months, p=0.003) Lièvre A, et al. Cancer Res 2006;66:3992 3995; Di Fiore F, et al. Br J Cancer 2007;96:1166 1169; De Roock W, et al. Ann Oncol 2007;Epub ahead of print; Lièvre A, et al. J Clin Oncol 2008;26:374 379 7
EGFR ligand expression: a predictor for increased PFS? Median PFS (days) 140 120 100 80 60 40 20 P=0.0002 103.5 days 115.5 days 57 days EREG AREG P=0.0002 57 days 0 High EGFR ligand expression Low n=110, Cetuximab monotherapy Khambata-Ford S, et al. J Clin Oncol 2007;25:3230-3237 Epiregulin Expression associated with PFS and OS in mut and wt kras KRAS Status Epiregulin Exp. Median PFS mos Median OS mos All < 0.5233 12 26 > 0.5233 30 45.9 Overall 18 36 Wildtype* < 0.5233 12 31.6 > 0.5233 36 65.4 Overall 24 44.3 Mutant < 0.5233 12 22.9 > 0.5233 12 29.1 Overall 12 24.3 P <.001 P <.001 Tejpar 2008 ASCO GI abstract #411 8
Germline Polymorphisms Translation Splicing 5 UTR promoter exon 1 exon 2 3 UTR Transcription SNP in untranslated region or promoter region SNP in coding region of exon RNA stability SNP at splice site 9
Why is Cetuximab more effective in refractory patients? First Line FOLFORI Crystal CALGB Second Line CPT-11 EPIC Third Line CPT-11 Bond Benefit 8% 12% 23% No Cetuximab 36% 4% NA Cetuximab 44% 16% 23% 10
Is it Patient or Tumor Selection? Patient Selection Patients are different who can receive two or three or four lines of therapy Tumor Selection Tumors are different who can receive two or three or four lines of therapy Tumor biology changes with increasing exposure to chemotherapy and targeted agents Exposure to specific cytotoxic changes pegfr status Possible increased addiction to EGFR with more tumor progression EGFR inhibitors: EGFR expression (FISH) 1.0 1.0 Cumulative distribution function 0.8 0.6 0.4 0.2 p=0.05 EGFR FISH+ Cumulative survival function 0.8 0.6 0.4 0.2 p=0.7 EGFR FISH- EGFR FISH- EGFR FISH+ 0.0 0 10 20 TTP (months) 0.0 0 10 20 30 Survival time (months) 1. Cappuzzo F, et al. Ann Oncol 2007 (Epub ahead of print); 2. Moroni M, et al. Lancet 2005;6:279 286; 3. Sartore-Bianchi A, et al. J Clin Oncol 2007;25:3238 3245; 4. Personeni N, et al. J Clin Oncol 2007;25:18S (Abstract No. 10569) 11
Mechanisms of gene amplification Double minutes Amplified chromosome regions Distributed across genome Albertson DG. Trends Genet 2006;22:447 453 Analysis of multiple markers which increase predictive value of Kras testing for EGFR inhibitors EGFR ligands PI3K mutations PTEN loss EGFR gene copy number Fcγ Receptors Cox2 12
The 4 good reasons for testing for K-RAS before anti EGFR 1. Significant gain benefit if wild 2. Avoid unnecesary toxicity 3. Avoid extra cost 4. Avoid potential harm if mutated CHMP recommended extended approval for cetuximab 29/5/08, but only for wild type K -RAS USA: all trials on hold to be amended or rewritten incorporating kras data Copyright 2000 American Association for Cancer Research Rak, J. et al. Cancer Res 2000;60:490-498 Rak, J. et al. Cancer Res 2000;60:490-498 13
AVF 2107: PFS by K-ras Status Proportion surviving 1.0 0.8 0.6 0.4 0.2 5.5 mos (6.2 mos*) Progression-free Survival by Kras Randomized Subjects in Arms 1 and 2 Group: Mutant (n=78 34/44) Group: Wild Type (n=152 67/85) 1.0 Treatment Group IFL + Placebo IFL + Bev 9.1 mos (10.6 mos*) Proportion surviving 0.8 0.6 0.4 0.2 7.2 mos (6.2 mos*) Treatment Group IFL + Placebo IFL + Bev 13.3 mos (10.6 mos*) 0.0 0 5 10 15 20 25 Duration of survival (months) 0.0 0 5 10 15 20 25 Duration of survival (months) *point estimates AVF2107 entire population Ince et al JCO 2005 AVF 2107: OS by K-ras Status Duration of Survival by Kras Randomized Subjects in Arms 1 and 2 1.0 Group: Mutant (n=78 34/44) Group: Wild Type (n=152 67/85) 1.0 Proportion surviving 0.8 0.6 0.4 0.2 0.0 13.6 mos (15.6 mos*) Treatment Group IFL + Placebo IFL + Bev 19.9 mos (20.3 mos) 0 5 10 15 20 25 30 Duration of survival (months) Proportion surviving 0.8 0.6 0.4 0.2 0.0 Treatment Group IFL + Placebo IFL + Bev 17.6 mos (15.6 mos*) >27.7 mos (20.3 mos*) 0 5 10 15 20 25 30 Duration of survival (months) *point estimates AVF2107 entire population Ince et al JCO 2005 14
Kras associated with PFS in patients treated with FOLFOX/Bevacizumab Wt 15 months Mut 7 months Response with IFL/Bev dependent on kras status Mutant (?) IFL 42% IFL/Bev 43% Wt kras (?) IFL 37% IFL/Bev 60% Caution may be different with FOLFOX and needs to validated 15
Molecular Predictors to Bevacizumab Therapy? Hypoxia Growth factors e.g. EGF EGFR HIf1α ARNT HIF1 DNA NFkb Tumor cell AM Leptin VEGF IL-8 IL-1 β CRLR LEPR NRP1 VEGFR CXCR IL-1R Endothelial cell Tumor associated angiogenesis 16
CONFIRM Trials Stratification Factors PS 0, 1-2 LDH, > 1.5 x ULN CONFIRM 1 1 ST Line 1168 Patients R an d o m iz e d FOLFOX4/Placebo 583 Patients FOLFOX4/PTK 585 Patients Progressed from irinotecan-based therapy CONFIRM 2 2 ND Line 855 Patients R an d o m iz e d FOLFOX4/Placebo 426 Patients FOLFOX4/PTK 429 Patients ULN Upper limit of normal; PS Performance status; LDH Lactate dehydrogenase Response to PTK/ZK Response (n=93) Multivariate Analysis: - Serum LDH - Age - Gender - Performance Status Confirm 1 Confirm 2 VEGFR1 (n=42) Hif1a (n=51) <3.85 3.85 1.21 <1.21 Group 1 Group 2 Group 1 Group 2 (10%) (61%) (13%) (53%) 17
PFS with PTK/ZK Confirm 1 PFS (n=95) Confirm 2 Multivariate Analysis: - Serum LDH - Age - Gender - Performance Status LDHA (n=43) Hif1a (n=52) 0.92 < 0.92 <0.85 0.85 Group 1 HR=1 (n=28) Group 2 HR=1.94 (n=49) Group 3 HR=1.25 (n=10) Glut1 (n=42) <3.25 Group 4 HR=3.02 (n=26) 3.25 Group 5 HR=7.96 (n=16) VEGFR2 CONFIRM1 Estimated Probability of Progression-Free Survival 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 VEGFR2 > 2.98 (n=7) w/o PTK/ZK for interaction between treatment and VEGFR2 <2.98 (n=34) with PTK/ZK VEGFR2 expression p= 0.001 VEGFR2 > 2.98 (n=8) with PTK/ZK VEGFR2 <2.98 (n=34) w/o PTK/ZK 0 5 10 15 20 25 30 35 40 Months since randomization 18
VEGFR2 Predicts OS in CONFIRM1 Estimated Probability of Survival 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 VEGFR2 > (n=45) 1.76 VEGFR2 < (n=38) 1.76 Adjusted P value = 0.012 VEGFR2 >1.76 35.8 mo v 20 mo 0.2 0.1 0.0 0 6 12 18 24 30 36 42 48 Months since randomization Sensitivity of Targeted linked to Sensitivity of Chemotherapy 19
Or how do we find our perfect Partner? 20
Collaborations Medical Oncology: Syma Iqbal, Anthony El-Khoueiry Surgery: Robert Beart, Richard Selby Danenberg Lab: Peter Danenberg ResponseGenetics: Kathy Danenberg Lenz Lab: Philipp Manegold Zhang Wu Anne Schultheiss Mizutomo Azuma Georg Lurje Alexandra Pohl Fumio Nagashima Mol Epidemiol: Chris Haiman, Robert Haile Statistics: Susan Groshen, Dongyun Yang Pathology: Robert Ladner, William Fazzone, Peter Wilson, Melissa LaBonte Novartis/Schering Patients and Investigators Confirm 21