USC/Norris Comprehensive Cancer Center Mechanisms of Resistance to EGFR Inhibitors: Is It Time to Start Selecting Patients? Heinz-Josef Lenz, MD Professor of Medicine and Preventive Medicine Director, GI Oncology Program USC/Norris Comprehensive Cancer Center Eilat, January 10, 2008

What Patients Expect Today and More So In The Future Drugs that work Drugs that are safe Doses that are right for them

How to Use Predictive or Prognostic Markers When (Prognostic) With what (Predictive) How much (Predictive) What combination (Predictive)

Overview of potential biomarkers predicting efficacy EGFR IHC detection FISH detection mutations gene levels/polymorphisms EGFR ligands (EGF, heregulin, epiregulin, amphiregulin) K-ras COX-2

EGF Receptor: A Rational Target for CRC Therapy Ligand Target for EGFR-cetuximab Target for EGFT-TK inhibitor EGFR-TK pY GRB2 pY P13K SOS RAS RAF pY STAT MEK PTEN AKT MAPK The human epidermal growth factor receptor (HER-1/EGFR) signaling pathway is thought to play a key role in tumor growth and the progression of numerous cancers, including CRC. The HER-1/EGFR transmembrane proteins consist of an extracellular ligand-binding domain, an intracellular tyrosine-kinase (TK) domain, and a transmembrane region. Numerous ligands bind to the EGFR extracellular domain, which promotes receptor homo- or heterodimerization with another EGFR receptor or other HER family members. This induces activation of the receptor’s TK activity and initiates a downstream signaling cascade that ultimately leads to tumor cell proliferation, migration, adhesion and angiogenesis, and cell death inhibition (apoptosis). In CRC, HER-1/EGFR signaling is dysregulated. HER-1/EGFR overexpression has also been correlated with disease progression, poor prognosis, and reduced sensitivity to chemotherapy. Therefore, several agents have been developed to target HER-1/EGFR, including small-molecule TK inhibitors and monoclonal antibodies (mAbs). Currently, cetuximab is the most advanced mAb in develpoment for CRC. References Meyerhardt JA, Mayer RJ. Systemic therapy for colorectal cancer. N Engl J Med. 2005;352:476-487; Venook A. Critical evaluation of current treatments in metastatic colorectal cancer. Oncologist. 2005;10:250-261. Gene transcription Cell-cycle progression P P Cyclin D1 MYC JUN FOS Proliferation/ maturation MYC Cyclin D1 Survival (anti-apoptosis) Chemotherapy/ radiotherapy resistance Invasion and metastasis Angiogenesis Meyerhardt JA, Mayer RJ. N Engl J Med. 2005;352:476-487; Venook A. Oncologist. 2005;10:250-261.

Objective Response N (%) Reference Treatment (panitumumab or cetuximab) No of patients (WT:MT) MT WT A. Liévre, et al. (AACR Proceedings, 2007) cmab ± CT 76 (49:27) 0 (0) 24 (49) S. Benvenuti, et al. (Cancer Res, 2007) pmab or cmab or cmab + CT 48 (32:16) 1 (6) 10 (31) W. De Roock, et al. (ASCO Proceedings, 2007) cmab or cmab + irinotecan 113 (67:46) 27 (40) D. Finocchiaro, et al. (ASCO Proceedings, 2007) 81 (49:32) 2 (6) 13 (26) F. Di Fiore, et al. (Br J Cancer, 2007) cmab + CT 59 (43:16) 12 (28) S. Khambata-Ford, et al. (J Clin Oncol, 2007) cmab 80 (50:30) 5 (10)

Objective Tumor Response (Central Radiology) KRAS All Evaluable n (%) Mutant Wild-type Response Pmab (N = 208) BSC (N = 219) (N = 84) (N = 100) (N = 124) (N = 119) CR 0 (0) PR 21 (10) 21 (17) SD 52 (25) 22 (10) 10 (12) 8 (8) 42 (34) 14 (12) PD 104 (50) 149 (68) 59 (70) 60 (60) 45 (36) 89 (75) CR, PR, SD 73 (35) 63 (51) Pmab, panitumumab; BSC, best supportive care; CR, complete response; PR partial response; SD, stable disease; PD, disease progression

Primary diagnosis, n (%) Colon cancer 286 (67) 118 (64) 168 (69) KRAS Evaluable Mutant KRAS Wild-type KRAS Total (N = 427) Total (N = 184) Total (N = 243) Sex, n (%) Men 270 (63) 111 (60) 159 (65) Baseline age, years Median (min, max) 62.0 (27, 83) 63.0 (29, 82) Primary diagnosis, n (%) Colon cancer 286 (67) 118 (64) 168 (69) Months since primary diagnosis Median 25.1 24.1 ECOG performance status, n (%) 0-1 366 (86) 155 (84) 211 (87) ≥ 2 61 (14) 29 (16) 32 (13) Prior adjuvant chemotherapy, n (%) Yes 149 (35) 67 (36) 82 (34) Cells with EGFr membrane staining, n (%) 1% to < 10% 103 (24) 43 (23) 60 (25) 10% to 100% 322 (75) 140 (76) 182 (75) ECOG, Eastern Cooperative Oncology Group; EGFr, epidermal growth factor receptor

Distribution of KRAS Mutations Panitumumab + BSC BSC alone Total Mutation n % 12 Ala 8 9.5 7 7.0 15 8.2 12 Asp 34 40.5 36 36.0 70 38.0 12 Arg 0.0 3 3.0 1.6 12 Val 17.9 25 25.0 40 21.7 12 Cys 8.3 14 7.6 12 Ser 5 6.0 9 9.0 13 Asp 14.0 29 15.8

K-RAS mutation status trends with Progression Free Survival Patients Free of Tumor Progression (%) Wildtype Mutant (days) Hazard ratio = 1.3972 95% CI = 0.8728 to 2.5907 Ford et al AACR 2007

Mutant KRAS Subgroup: PFS by Treatment Median In Weeks Mean In Weeks 1.0 Events/N (%) 0.9 Pmab + BSC 76/84 (90) 7.4 9.9 0.8 BSC Alone 95/100 (95) 7.3 10.2 0.7 HR = 0.99 (95% CI: 0.73–1.36) 0.6 Proportion with PFS 0.5 0.4 0.3 0.2 0.1 0.0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 Patients at Risk Weeks Pmab + BSC 84 78 76 72 26 10 8 6 5 5 5 5 4 4 4 4 2 2 2 2 2 2 2 1 1 1 BSC Alone 100 91 77 61 37 22 19 10 9 8 6 5 5 4 4 4 4 4 4 3 3 3 2 2 2 2

Wild-type KRAS Subgroup: PFS by Treatment p < 0.0001 for quantitative-interaction test comparing PFS log-HR (pmab/BSC) between KRAS groups . 1 2 3 4 5 6 7 8 9 10 12 14 16 18 Weeks 124 115/124 (93) 12.3 19.0 114/119 (96) 7.3 9.3 Pmab + BSC BSC Alone Events/N (%) Median In Weeks Mean HR = 0.45 (95% CI: 0.34–0.59) Stratified log-rank test, p < 0.0001 Patients at Risk 119 112 106 80 69 63 58 50 45 44 33 25 21 20 17 13 109 91 81 38 15 11 Proportion with PFS

Overall Survival by Treatment and KRAS Median In Months Events/N (%) 1.0 Pmab–Wild-type 107 / 124 (86) 8.1 0.9 BSC–Wild-type 110 / 119 (92) 7.6 0.8 Pmab–Mutant 79 / 84 (94) 4.9 0.7 BSC–Mutant 95 / 100 (95) 4.4 0.6 Survival Probability 0.5 0.4 HR = 0.67 (95% CI: 0.55–0.82) (adjusted for treatment and randomization factors; ECOG, region) 0.3 0.2 0.1 0.0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 Months

Why more effective in refractory patients? First Line FOLFORI Second Line CPT-11 Third Line Benefit 8% 12% 23% No Cetuximab 36% 4% NA Cetuximab 44% 16%

Is it Patient or Tumor Selection? Patient Selection Patients who are being able to receive more than three lines of therapy are overall doing better (less ras mutations?) Tumor Selection Tumor biology changes with increasing exposure to chemotherapy Exposure to specific cytotoxic changes EGFR status EGFR expression associated with Metastatic Potential and Poor Prognosis Addiction to EGFR with more tumor progression

Prediction or Prognosis?

Rak, J. et al. Cancer Res 2000;60:490-498 Copyright ©2000 American Association for Cancer Research

Kras mutations don’t come alone! Kras mutations associated with braf mutations which itself with CIMP Kras mutations associated with PI3K mutations

EGFR mutations Biopsy samples from 110 patients with mCRC enrolled in a ERBITUX monotherapy trial revealed no mutations in EGFR (exons 18–21) Khambata-Ford S, et al. J Clin Oncol 2007;25:3230–3237

EGFR inhibitors: EGFR expression (FISH) EGFR expression determined by FISH may have predictive value for ERBITUX therapy1,2 and panitumumab therapy 2,3 BUT – no association with response was noted in another recent study4 1.0 1.0 0 10 20 p=0.05 EGFR FISH+ EGFR FISH- TTP (months) Cumulative distribution function Cumulative survival function 0 10 20 30 p=0.7 Survival time (months) 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0.0 0.0 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)

EGFR gene levels: Effect on survival 95% CI: 4.4–13.5 months 8 7.3 months 95% CI: 1.7–4.5 months 6 Median survival (months) 4 2.2 months 2 p=0.09 Low High mRNA levels There was no significant correlation between EGFR gene expression level and response to ERBITUX (small sample size) 39 patients with mCRC refractory to irinotecan and oxaliplatin treated with ERBITUX monotherapy Vallböhmer D, et al. J Clin Oncol 2005;23:3536–3544

Progression-free survival (months) EGFR gene copy number and efficacy of Cetuximab There was no relationship between EGFR gene copy number and either response or PFS  Ct values were related to survival using  Ct as a fixed covariate in a Cox model of survival (Wald 2 P=0.03) 3.0 2.0 1.0 0.0 -1.0 -2.0 3.0 2.0 1.0 0.0 -1.0 -2.0  Ct value (dCt)  Ct value (dCt) PR SD PD Progression-free survival (months) Best response 0 1 2 3 4 5 6 7 8 9 10 Ct = threshold cycle; = censored patients Lenz, H.-J. et al. J Clin Oncol 2006;24:4914–4921

Mechanisms of gene amplification Double minutes Amplified chromosome regions Distributed across genome Albertson DG. Trends Genet 2006;22:447–453

EGFR ligand expression: a predictor for increased PFS? 140 P=0.0002 EREG 120 115.5 days AREG 100 103.5 days 80 Median PFS (days) P=0.0002 60 57 days 57 days 40 20 High Low EGFR ligand expression A similar, significant relationship was also noted between ligand expression and disease control n=110, ERBITUX monotherapy Khambata-Ford S, et al. J Clin Oncol 2007;25:3230-3237

EGFR pathway gene polymorphisms EGFR codon R497K EGFR CA dinucletide repeat in intron 1 EGF A61G COX-2 G-765C Interleukine-8(IL-8) T-251A VEGF C936T Cyclin D1 A870G

Germline Polymorphisms Translation Splicing exon 1 exon 2 3’UTR 5’UTR promoter Transcription SNP in untranslated region or promoter region SNP in coding region of exon RNA stability SNP at splice site 26

Response to Cetuximab COX2 Polymorphisms PR SD PD 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% G/G G/C C/C (n=78) (n=30) (n=4) Response to Cetuximab by COX-2 765 GC polymorphism P value = 0.097

COX2 Polymorphisms associated with PFS in mCRC treated with cetuximab 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 3 6 9 12 Months Since Start of Cetuximab Treatment Estimated Probability of Progression-Free Survival Log-rank P value = 0.031 COX2 765GC Polymorphism and PFS G/G (n=87) G/G (n=34) C/C (n=4)

Antibody-dependent cell-mediated cytotoxicity (ADCC) Courtesy of Dr. Arteaga

Polymorphisms of FCGamma 2a and 3a associated with PFS Zhang et al JCO 2007

Fc Gamma Receptor 3a polymorphism associated with response to Cetuximab and Bevacizumab (BOND 2) Lenz et al ASCO GI 2007 abstract 401

Mechanisms of Resistance Kras a marker of resistance, but also prognostic marker? Kras patient/tumor selection? Associated with PI3K mutations? Horizontal and vertical inhibition to further increase efficacy and overcome resistance Cox2 a promising target for combination with EGFR inhibitors ADCC a mechanism of efficacy of IgG1 AB

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 MSKCC: Len Saltz, M Shah