1. K-Ras and Beyond Josep Tabernero, MD Vall d’Hebron University Hospital Barcelona, Spain

2. Disclosures Participated in Advisory Boards of Merck, Amgen, Imclone, Sanofi-Aventis, Onyx, and Roche

3. K-Ras and B-Raf in CRC Constitutive mutations of K-Ras predict resistance to anti-EGFR MoAbs in CRC: –refractory 1 setting –first-line 2-3 setting –basis for regulatory approval (EMEA) & national guidelines (NCCN) Role of mutations of other signal transducer proteins is being evaluated: –i.e. B-Raf: refractory setting 4 1 Lièvre, A. Cancer Res; 66:3992-3995, 2006 2 Van Cutsem, E. et al. N Engl J Med; 360:1408-1417, 2009 3 Bokemeyer, C. et al. J Clin Oncol; 27:663-671, 2009 4 Di Nicolantonio, F. et al. J Clin Oncol; 26:5702-5712, 2008 EGFR RAS RAF MEK MAPK Akt PI3K Cell Proliferation Cell Survival

4. K-Ras, B-Raf, N-Ras and PIK3CA mutations and cetuximab efficacy A4020 – Poster Board #: 11; Diether Lambrechts et al. The role of KRAS, BRAF, NRAS, and PIK3CA mutations as markers of resistance to cetuximab in chemorefractory metastatic colorectal cancer.

5. Lambrechts: Patients and Methods EndpointPerformance of 4 tumor based tests: K-Ras, B- Raf, N-Ras and PIK3CA mutation status UtilityPredictive biomarker SpecimenTumor specimens (paraffin-embedded) Patients Sample size Refractory mCRC treated with Irinotecan + Cetuximab 276 tumors  580 tumors (European consortium) AssaySequenom MALDI TOF MassArray system

6. Lambrechts: Results (1) Mutations included% coverage of potential mutations (Cosmic) Mutation rate detected KRAS G12S, G12R, G12C, G12D, G12A, G12V, G13D, A146T, G13A, G13V, A59T, Q61K, Q61E, Q61P, Q61R, Q61L, Q61H 99.2% 36.5% ( 622 samples) BRAF V600E,K601E, D594G,V600M97% 5% (589 samples) NRAS Q61P,Q61L,Q61H,Q61H,Q61Q,Q61E,G13S,G13C,G13R,Q61K,Q61R, G12D,G12S,G12C 97% 6% (261 samples worked) PI3K H1047R, H1047L, K179T, P539R,Q546K,Q546E, E81K, R88Q,G106V,N345K, R93W, S158L, H160N,R38H,E542K, E542Q,E545K,E545Q, G118D, G12D,K567R,H1047Y, P134S, R108H, C420R,H701P,K184E, C901F,M1004I, G1049R, G1007R, G1049S 86% 13% (578 samples)

7. K-Ras, B-Raf and N-Ras mutually exclusive 17.7% K-Ras mt and 10.4% K-Ras wt had a PIK3CA mutation (p= 0.009 Pearson Chi square) 6% B-Raf mutants and 13% B-Raf wt had a PIK3CA mutation (p= 0.412 Fisher’s Exact test) Representative series: outcomes in accordance with the literature –mPFS 18 wks, mOS 38 wks (≈BOND) Lambrechts: Results (1)

8. Lambrechts: Results (2) - RR KRASCR + PRSD + PDtotalp WT 130 (36%)226 (64%) 356p<.001 Mut 11 (5%)192 (95%) 203 BRAFCR + PRSD + PDtotalp WT 141 (26%)399 (74%) 540p=.035 Mut 2 (8%)24 (92%) 26 NRASCR + PRSD + PDtotalp WT 50 (21%)179 (79%) 239p=.317 Mut 1 ( 6%)14 (94%) 15 PI3KCR + PRSD + PDtotalp WT 128 (27%)357 (73%) 485p=.028 Mut 10 (14%)60 (86%) 70 PI3K In KRAS wt CR + PRSD + PDtotalp WT 117 (38%)195 (62%) 312p=0.107 Mut 8 (24%)26 (76%) 34

9. Lambrechts: Results (3) – PFS & OS KRASWTMUT N=369N=212 Median PFS24 weeks12 weeks HR (95% CI)0.542 (0.452-0.650) P value (log rank)<0.001

10. Lambrechts: Results (3) – PFS & OS KRASWTMUT N=369N=212 Median PFS24 weeks12 weeks HR (95% CI)0.542 (0.452-0.650) P value (log rank)<0.001 BRAFWTMUT N= 561N= 28 Median PFS19 weeks7.8 weeks HR (95% CI)0.410 (0.275-0.610) P value (log rank)<0.001

11. Lambrechts: Results (3) – PFS & OS KRASWTMUT N=369N=212 Median PFS24 weeks12 weeks HR (95% CI)0.542 (0.452-0.650) P value (log rank)<0.001 BRAFWTMUT N= 561N= 28 Median PFS19 weeks7.8 weeks HR (95% CI)0.410 (0.275-0.610) P value (log rank)<0.001 PI3KWTMUT 50573 Median PFS19 weeks12.5 HR (95% CI)0.772 (0.601-0.991) P value (log rank)0.036

12. Lambrechts: Results (3) – PFS & OS KRASWTMUT N=369N=212 Median PFS24 weeks12 weeks HR (95% CI)0.542 (0.452-0.650) P value (log rank)<0.001 BRAFWTMUT N= 561N= 28 Median PFS19 weeks7.8 weeks HR (95% CI)0.410 (0.275-0.610) P value (log rank)<0.001 PI3KWTMUT 50573 Median PFS19 weeks12.5 HR (95% CI)0.772 (0.601-0.991) P value (log rank)0.036 All KRAS wt PI3KWTMUT 32336 Median PFS24 weeks23 weeks HR (95% CI)0.848(0.599-1.201) P value (log rank)0.338

13. Lambrechts: Results (3) – PFS & OS KRASWTMUT N=369N=212 Median PFS24 weeks12 weeks HR (95% CI)0.542 (0.452-0.650) P value (log rank)<0.001 BRAFWTMUT N= 561N= 28 Median PFS19 weeks7.8 weeks HR (95% CI)0.410 (0.275-0.610) P value (log rank)<0.001 PI3KWTMUT 50573 Median PFS19 weeks12.5 HR (95% CI)0.772 (0.601-0.991) P value (log rank)0.036 All KRAS wt pi3KWTMUT 32336 Median PFS24 weeks2 3 weeks HR (95% CI)0.848(0.599-1.201) P value (log rank)0.338 Any PI3K, KRAS, BRAFWTMUT 298272 Median PFS26 weeks12 weeks HR (95% CI)0.538 (0.451-0.642) P value (log rank)<0.001

14. Lambrechts: Results (4) – Multivariate PFS Cox regresionHR95%CIP value KRAS0.5230.434 – 0.631p<.001 BRAF0.3280.217 – 0.497p<.001 Pi3K0.7980.620 – 1.027p=.079 OS Cox regresionHR95%CIP value KRAS0.5490.452 – 0.667p<.001 BRAF0.3780.250 – 0.572p<.001 Pi3KNot retainedp=.187 OR Logistic regresionOR95%CIP value KRAS0.0930.048 – 0.177p<.001 BRAF0.1400.032 – 0.604p=.008 Pi3KNot retainedp=.136

15. K-Ras impact ≈ literature 1 N-Ras impact: not mature, full series to be analyzed, currently mt incidence 6% B-Raf ≈ literature 2. Most powerful negative predictor PIK3CA: little effect, no effect if restricted to K-Ras wt, not retained in multivariate analysis  Discrepancy with the literature 3,4 (although limited number of patients) Lambrechts: Conclusions 1 Lièvre, A. Cancer Res; 66:3992-3995, 2006 2 Di Nicolantonio, F. et al. J Clin Oncol; 26:5702-5712, 2008 3 Sartore-Bianchi, A et al Cancer Res; 69:1851-7, 2009 4 Ann Oncol ;20:84-90, 2008

16. Lambrechts: Implications Strengths: –Unique and consistent population –Large database –Not influenced by other treatments

17. Lambrechts: Implications Weakness: –Not all the mutations have the same addictive role –Other possible deregulations not considered so far: PTEN mutations, PTEN loss of function, Src mutations, p53 mutations, … –Other potential predictors: Role of the ligands Polymorphisms 1-3 : –EGFR, EGF, … –Fc receptors (ADCC): FcgammaRIIa-H131R and FcgammaRIIIa-V158F 1 Lurge, J et al. Clin Cancer Res 1;14:7884-95,2008 2 Zhang, W wt al. J Clin Oncol 20;25:3712-8,2007 3 Bibeau, F et al. J Clin Oncol; 27:1122-9,2009

18. Amphiregulin/Epiregulin A4016 – Poster Board #: 7; Derek J Jonker et al. High epiregulin (EREG) gene expression plus K-ras wild-type (WT) status as predictors of cetuximab benefit in the treatment of advanced colorectal cancer (ACRC): Results from NCIC CTG CO.17—A phase III trial of cetuximab versus best supportive care (BSC). A4019 – Poster Board #: 10; Hans Prenen et al. Use of amphiregulin and epiregulin mRNA expression in primary tumors to predict outcome in metastatic colorectal cancer treated with cetuximab. A4021 – Poster Board #: 12; Fotios Loupakis et al. Amphiregulin (AR) expression in the prediction of benefit from cetuximab plus irinotecan in KRAS wild-type metastatic colorectal cancer (mCRC) patients.

19. 1 Singh, AB et al. Cell Signal; 17:1183-1193,2005 2 Shelly, M et al. J Biol Chem; 273:10496-10505,1998 3 Khambata-Ford, S. et al. J Clin Oncol; 25:3230-3237, 2007 Amphiregulin/Epiregulin EGFR ligands: –1 in C. Elegans –4 in Drosophila –7 in mammals: EGF, TGF-α, HB-EGF, amphiregulin (AREG), betacellulin, epiregulin (EREG) and epigen 1 –EREG and AREG bind more weakly to EGFR than EGF but much more potently and prolonged –EREG preferentially activates heterodimers 2 High gene expression levels of EREG and AREG predict response to cetuximab 3

20. Jonker: Patients and Methods EndpointThree tumor based tests: K-Ras mutation status and EREG & AREG (not shown) expression UtilityPredictive biomarker SpecimenTumor specimens (paraffin-embedded material) – Study NCIC CTG CO.17 Patients Sample size Refractory mCRC treated with Cetuximab or BSC K-Ras 394/572 (69%); EREG 385/572 (67%) AssayEREG gene expression by quantitative RT-PCR

21. Jonker: Background NCIC CTG CO.17: mCRC Cetuximab vs BSC HR OS: ITT 0.7  K-Ras wt 0.55 1 Jonker, DJ et al. NEJM; 357:2040-8,2007 2 Karapetis, CS. et al. NEJM;359:1757-65,2008

22. Jonker: Results (1) EREG in K-Ras wt as a continuous variable: prognostic and predictive Study arm Adjusted HR (95% CI) for 1 unit increase in EREG normCT (toward normal) P value Test for treatment / biomarker interaction (adjusted p value) CET/BSC1.17 (1.04-1.32)0.01 HR 1.03 (0.88-1.20) p=0.75 BSC1.13(1.01-1.27)0.04 EREG and OS in patients with K-Ras wild-type EREG and PFS in patients with K-Ras wild-type Study arm Adjusted HR (95% CI) for 1 unit increase in EREG normCT (toward normal) P value Test for treatment / biomarker interaction (adjusted p value) CET/BSC1.13 (1.01-1.26)0.03 HR 1.14 (0.98-1.33) p=0.08 BSC0.96 (0.87-1.07)0.48

23. Jonker: Results (2) EREG in K-Ras wt as a categorical variable (high vs low): predictive but not prognostic –In K-Ras wt patients on BSC, high EREG expression did not correlate with OS using: pre-specified threshold: adjusted HR 0.82 [0.58-1.15], p=0.24 minimum p threshold: adjusted HR 0.85 [0.59- 1.22], p=0.38

24. Jonker: Results (3) Combimarker: K-Ras wt and high EREG –Pre-especified threshold 1 –Minimum threshold: 169/384 (44%) response rate was 15.5 vs 0% for cetuximab vs BSC median PFS was 5.1 vs 1.9 months for cetuximab vs BSC (HR, 0.33; p<0.0001) median OS was 9.9 vs 5.0 months for cetuximab vs BSC (HR, 0.46; p<0.001) Implications in patients to be treated: –All comers  394 (100%)HR: 0.7 –K-Ras wt  230 (58%) HR: 0.55 –Combimarker  169 (44%)HR: 0.46 1 Khambata-Ford, S. et al. J Clin Oncol; 25:3230-3237, 2007

25. Jonker: Results (4) Combimarker: K-Ras wt and high EREG –Minimum threshold: 169/384 (44%)

26. Prenen: Patients and Methods EndpointThree tumor based tests: K-Ras mutation status and EREG and AREG expression UtilityPredictive biomarker SpecimenTumor specimens (paraffin-embedded) Patients Sample size Irinotecan refractory mCRC treated with Irinotecan + Cetuximab 220 tumors + 67 tumors (external validation) AssayEREG and AREG gene expression by quantitative RT-PCR

27. Prenen: Results (1) EREG expression is higher in K-Ras wt than in K-Ras mut tumors (p=0.0002)

28. Prenen: Results (2) EREG and AREG expression as a continuous variable is predictive of response in K-Ras wt but not in mut tumors EREG AREG p=.0005p=.0017

29. Prenen: Results (3) EREG and AREG expression as a categorical variable is predictive of RR, DCR, PFS, OS in K-Ras wt tumors However, the cut-offs points are different by ROC- analysis for each end-point Odd ratio EREGRR5.04 DCR20.7 AREGOR5.46 DCR6.86

30. Prenen: Results (3) Combination of K-Ras wt and EREG or AREG and OS EREG HR OS: 0.42 (95% CI 0.28 – 0.63) p<.001

31. Strengths: –Large series One randomized study: 394 pts. One multicentric cohort series: 287 pts. –Not influenced by other treatments –Proof of concept of AREG & EREG well established, beyond K-Ras Jonker & Prenen: Implications

32. Weakness: –Do not discriminate between AREG & EREG –Underestimate other relevant mutations –Reproducibility: magnitude and cut-off –Variability in the categorization and loss of power Jonker & Prenen: Implications

33. Loupakis: Patients and Methods EndpointThree tumor based tests: K-Ras and B-Raf mutation status and AREG expression UtilityPredictive biomarker SpecimenTumor specimens (paraffin-embedded) Patients Sample size Refractory mCRC treated with Irinotecan + Cetuximab 87 tumors (4 centers in Italy) AssayAREG expression by IHC (Mo Ab cl 31221, RD) H-Score (0-300) Mutations K-Ras & B-Raf (not described)

34. RR: - ITT: 16% - K-Ras wt: 25%; K-Ras wt + B-Raf wt: 30% AREG: High expression associated with B-Raf wt (p=.0005) but not with K-Ras wt AREG in K-Ras wt and B-Raf wt: no relation with RR, PFS and OS In the multivariate analysis only B-Raf status keep the prognostic value  Difficult to conciliate with the literature due the low frequency of B-Raf mut (5-10%) AREG by IHC not standardized Loupakis: Results - Implications

35. Polymorphisms A4022 – Poster Board #: 13; Dongyun Yang et al. Pharmacogenetic analysis in metastatic colorectal cancer (mCRC) patients (pts) treated with second-line irinotecan (IR)+/- cetuximab (CB): The EPIC experience.

36. Yang: Methods and Results EndpointTwo tumor based tests: K-Ras mutation status and EGFR-CA repeats in Intron 1 UtilityPredictive biomarker SpecimenTumor specimens (paraffin-embedded) Patients Sample size Oxaliplatin-refractory mCRC treated with Irinotecan + Cetuximab 84 pts treated in the US (Ir/Cmab) - EPIC study AssayEGFR-CA repeats in Intron 1 (PCR) Mutations (method not defined)

37. Yang: Results - Methods K-Ras mutation status was not significantly associated with PFS or response EGFR-CA- repeat in intron 1 in arm be associated with PFS (p=0.031) Results difficult to interpret: few patients in variant  20/  20

38. Yang: Implications US patientsIr/Cmab (n=84)Ir (n=102)p RR13.15.9- mTTP (m)3.02.7- TotalIr/Cmab (n=84)Ir (n=102)p RR16.44.2<.05 mTTP (m)4.02.6<.05 Behavior of homozygous variants (  20/  20 & <20/<20) is different to the heterozygous (  20/<20) Biology? Sample size

39. Methodology in K-Ras mutations determination A4018 – Poster Board #: 9; Andreas Jung et al. The German quality assurance system for the molecular-pathological detection of KRAS-mutations in colorectal cancer.

40. Jung: Patients and Methods EndpointQuality audit of K-Ras mutation status test UtilityPredictive biomarker SpecimenTumor specimens (paraffin-embedded) Patients Sample size mCRC patients from German-speaking countries (Austria, Germany and Switzerland) 10 patients; 50 institutions AssayK-Ras mutation analysis by DDS (disesoxy sequencing – Sanger), ARMS (amplification refractory mutation sequencing) and MPA (melting point analysis, pyrosequencing)

41. 10 patients: 74 different K-Ras determinations Limited number of patients and analysis The authors raise concerns on the difficulties to establish quality assurance systems The authors state there is no technique/method superior to another? Delay in the result higher than expected (>14 days) 15% conflicting results: not disclosed SOP: critical step Jung: Results - Implications

42. IGF-1/IGF1R axis in the treatment with anti-EGFR MoAbs A4017 – Poster Board #: 8; Mario Scartozzi et al. Correlation of insulin-like growth factor 1 (IGF-1) expression and clinical outcome in K-RAS wild-type colorectal cancer patients treated with cetuximab-irinotecan.

43. Scartozzi: Methods and Results EndpointTwo tumor based tests: K-Ras mutation status and Insulin-like growth factor (IGF-1) expression UtilityPredictive biomarker SpecimenTumor specimens (paraffin-embedded) Patients Sample size Refractory mCRC treated with Irinotecan + Cetuximab 62 tumors (4 centers in Italy) AssayIGF-1 expression by IHC (Cell Signaling) Mutations (method not defined) Total 62 pts.IGF-1 -IGF-1 +p RR PR7 (50%)1 (5%).004 mTTP (m)113.2.03

44. Combined IGF-1 IHC expression and K-Ras mutation analysis may represent an effective strategy for a better selection of responding colorectal tumors for cetuximab treatment Caveats: IHC considered positive if  2 These results should be externally validated Reproducibility of IHC for IGF-1, IGFBPs and IGF-1R is cumbersome Potential role for anti-EGFR and anti-IGF1R combinations: Activation of IGF-1/IGF1R reduces sensitivity to EGFR TKI in cancer cells. IGF-1R inhibition restores sensitivity to EGFR TKIs 1,2 Scartozzi: Results - Implications 1 Jones, HE et al. Br J Cancer 95;172-180, 2006 2 Guix, M et al. J Clin Invest. 118:2609–2619, 2008

45. Conclusions Each of these studies constitute and Academic effort to personalize the treatment in patients with mCRC by tuning the target population beyond the standard of care (K- Ras status) In order to completely define the ultimate role of the different predictive factors an international collaboration is needed

46. Conclusions Predictive factors accepted: –K-Ras status Far advanced: –B-Raf status To be defined: –N-Ras, PIK3CA status –Loss of PTEN –Ligands: AREG, EREG –Polymorphisms: EGFR, EGF, Fc receptors (ADCC): FcgammaRIIa-H131R and FcgammaRIIIa-V158F –Others

47. Acknowledgements ASCO Program Committee Poster presenters for providing their presentations in a timely fashion Eduardo Vilar, MD and Javier Hernández, PhD for their thoughtful comments Audience