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K-Ras and Beyond

K-Ras and Beyond

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K-Ras and Beyond

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  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. EGFR RAS RAF PI3K MEK MAPK Akt Cell Survival Cell Proliferation K-Ras and B-Raf in CRC • Constitutive mutations of K-Ras predict resistance to anti-EGFR MoAbs in CRC: • refractory1 setting • first-line2-3 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 setting4 1Lièvre, A. Cancer Res; 66:3992-3995, 2006 2Van Cutsem, E. et al. N Engl J Med; 360:1408-1417, 2009 3Bokemeyer, C. et al. J Clin Oncol; 27:663-671, 2009 4Di Nicolantonio, F. et al. J Clin Oncol; 26:5702-5712, 2008

  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

  6. Lambrechts: Results (1)

  7. Lambrechts: Results (1) • 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)

  8. Lambrechts: Results (2) - RR

  9. Lambrechts: Results (3) – PFS & OS

  10. Lambrechts: Results (3) – PFS & OS

  11. Lambrechts: Results (3) – PFS & OS

  12. Lambrechts: Results (3) – PFS & OS

  13. Lambrechts: Results (4) – Multivariate

  14. Lambrechts: Conclusions • K-Ras impact ≈ literature1 • N-Ras impact: not mature, full series to be analyzed, currently mt incidence 6% • B-Raf ≈ literature2. Most powerful negative predictor • PIK3CA: little effect, no effect if restricted to K-Ras wt, not retained in multivariate analysis  Discrepancy with the literature3,4 (although limited number of patients) 1Lièvre, A. Cancer Res; 66:3992-3995, 2006 2Di Nicolantonio, F. et al. J Clin Oncol; 26:5702-5712, 2008 3 Sartore-Bianchi, A et al Cancer Res; 69:1851-7, 2009 4Ann Oncol ;20:84-90, 2008

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

  16. 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 • Polymorphisms1-3: • EGFR, EGF, … • Fc receptors (ADCC): FcgammaRIIa-H131R and FcgammaRIIIa-V158F 1Lurge, J et al. Clin Cancer Res 1;14:7884-95,2008 2Zhang, W wt al. J Clin Oncol 20;25:3712-8,2007 3Bibeau, F et al. J Clin Oncol; 27:1122-9,2009

  17. 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.

  18. 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 epigen1 • EREG and AREG bind more weakly to EGFR than EGF but much more potently and prolonged • EREG preferentially activates heterodimers2 • High gene expression levels of EREG and AREG predict response to cetuximab3 1Singh, AB et al. Cell Signal; 17:1183-1193,2005 2Shelly, M et al. J Biol Chem; 273:10496-10505,1998 3Khambata-Ford, S. et al. J Clin Oncol; 25:3230-3237, 2007

  19. Jonker: Patients and Methods

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

  21. Jonker: Results (1) • EREG in K-Ras wt as a continuous variable: prognostic and predictive EREG and OS in patients with K-Ras wild-type EREG and PFS in patients with K-Ras wild-type

  22. 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

  23. Jonker: Results (3) • Combimarker: K-Ras wt and high EREG • Pre-especified threshold1 • 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 1Khambata-Ford, S. et al. J Clin Oncol; 25:3230-3237, 2007

  24. High EREG by minimum-p threshold Low EREG by minimum-p threshold Cetuximab + BSC 100 Cetuximab + BSC 80 60 Proportion alive 40 BSC alone BSC alone 20 HR 0.46 [0.32-0.65], p<0.0001 HR 0.93 [0.51-1.71], p=0.81 0 0 2 4 6 8 10 30 25 16 13 8 5 26 18 15 10 5 3 Time from randomization (months) Jonker: Results (4) • Combimarker: K-Ras wt and high EREG • Minimum threshold: 169/384 (44%) 100 80 60 Proportion alive 40 20 0 0 2 4 6 8 10 12 14 84 80 76 66 43 28 18 8 85 73 54 26 19 14 10 5 Time from randomization (months)

  25. Prenen: Patients and Methods

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

  27. 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=.0005 p=.0017

  28. 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

  29. 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

  30. Jonker & Prenen: Implications • 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

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

  32. Loupakis: Patients and Methods

  33. Loupakis: Results - Implications • 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

  34. 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.

  35. Yang: Methods and Results

  36. 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

  37. Yang: Implications • Behavior of homozygous variants (20/20 & <20/<20) is different to the heterozygous (20/<20) • Biology? • Sample size

  38. 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.

  39. Jung: Patients and Methods

  40. Jung: Results - Implications • 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

  41. 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.

  42. Scartozzi: Methods and Results

  43. Scartozzi: Results - Implications • 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 TKIs1,2 1Jones, HE et al. Br J Cancer 95;172-180, 2006 2Guix, M et al. J Clin Invest. 118:2609–2619, 2008

  44. 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

  45. 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

  46. 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