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Predictive Biomarkers of EGFR Targeted Therapy: Beyond KRAS

Predictive Biomarkers of EGFR Targeted Therapy: Beyond KRAS. Josep Tabernero, MD PhD Vall d ’ Hebron University Hospital and Vall d ’ Hebron Institute of Oncology (VHIO) Barcelona, Spain. EGFR inhibitors: beyond KRAS. NCIC CTG CO.17: mCRC Cetuximab vs BSC HR OS: ITT 0.7  KRAS wt 0.55.

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Predictive Biomarkers of EGFR Targeted Therapy: Beyond KRAS

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  1. Predictive Biomarkers of EGFR Targeted Therapy: Beyond KRAS Josep Tabernero, MD PhD Vall d’Hebron University Hospital and Vall d’Hebron Institute of Oncology (VHIO) Barcelona, Spain

  2. EGFR inhibitors: beyond KRAS NCIC CTG CO.17: mCRCCetuximabvs BSC HR OS: ITT 0.7  KRASwt 0.55 1Jonker, DJ et al. NEJM; 357:2040-8,2007 2Karapetis, CS. et al. NEJM;359:1757-65,2008

  3. Baseline Predictive Biomarkers MUTATIONS • KRAS mut • NRASmut, BRAFmut • PIK3CAmut • TP53mut, PTEN mut RECEPTOR EXPRESSION • EGFR (HER1), HER-2/neu, HER-3, HER-4, IGF1R LIGAND EXPRESSION • EGF, TGF-α, HB-EGF, amphiregulin (AREG), betacellulin, epiregulin (EREG) and epigen DOWNSTREAM EFECTORS EXPRESSION • MPK-1 (DUSP-1), DUSP-4, DUSP-6

  4. BRAF mutations mCRC patients treated with panitumumab or cetuximab, n=114 KRAS mutational status (evaluable patients n=113) BRAF mutational status on wild-type KRAS tumours (n=79) *p<0.05 (p=0.011)‡p<0.05 (p=0.029) Di Nicolantonio, et al. J Clin Oncol 2008;26:5705-12

  5. BRAF mutations aCochran–Mantel–Haenszel test Van Cutsem E, et al. J Clin Oncol 2011; 29:2011-9

  6. BRAF, NRAS, PIK3CA mutations • European Consortium: • Refractory CRC patients treated with irinotecan + cetuximab • 1022 tumour samples • 773 samples of quality De Roock, W et al. Lancet Oncol 2010;11:753-62

  7. BRAF, NRAS, PIK3CA mutations Response Rate Overall Survival De Roock, W et al. Lancet Oncol 2010;11:753-62

  8. BRAF, NRAS mutations PICCOLO study target total n = 1200 (including 494 accrued under previous design) eligibility as before KRAS mutated or unknown KRAS-wt (c.12/13 & 61) IrCs irinotecan + c’sporin IrPan irinotecan + pan’mab Ir irinotecan alone Ir irinotecan alone Ir vs IrCs non-inferior efficacy primary endpoint PFS at 12 wks Ir vs IrPan superior efficacy primary endpoint OS Seymour et al. Proc ASCO 2011:A3523

  9. BRAF, NRAS mutations OS KRAS wt: 460 pts, 312 events HR=0.91 (0.73, 1.14), p=0.44 Double wt : 348 pts, 230 events; HR=0.87 (0.67, 1.13), p=0.30 All wt: 264 pts, 171 events; HR=0.86 (0.63, 1.16), p=0.32 BRAF mut: 63 pts, 53 events; HR=2.03 (1.13, 3.64) NRAS mut: 21 pts, 15 events HR=4.59 (1.19, 17.67) KRAS146mut: 17 pts, 14 events HR=1.32 (0.30, 5.81) Anymut: 99 pts, 80 events HR=2.03 (1.26, 3.28) *Adjusted HRs, 95% CIs IrPan betterIr better Seymour et al. Proc ASCO 2011:A3523

  10. BRAF, NRAS mutations PRIME study: FOLFOX +/- Panitumumab Overall Survival Oliner et al. Proc ASCO 2013:A3511 Presented by:

  11. HER-2 amplification Normal HER2 amplification FISH - HER2 HER2 Quadruple* wt non-responders (n=11 xenopatients) *KRAS/NRAS/ BRAF/PIK3CA mCRC treated with cetuximab (DFCI) 36.4% (P<0.001) Bertotti A et al. Cancer Discov 2011;1:508-23 Yonesaka K et al. Sci Transl Med 2011;3:99ra86

  12. HER-3 overexpression mCRC treated with irinotecan + cetuximab OS PFS Scartozzi M et al. Oncologist 2011;16:53-60 Scartozzi M et al. Ann Oncol 2012;23:1706-1712

  13. EGFR Ligands • 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 more prolonged • EREG preferentially activates heterodimers2 • High gene expression levels of EREG and AREG predict response to cetuximab3-5 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 4Tabernero J et al, J Clin Oncol 2010;28:1181-1189 5Jacobs B et al, J Clin Oncol 2009;27:5068-5074

  14. Ligands: AREG, EREG, TGFalpha mCRC 1st-line treatment Cetuximab (window) + FOLFIRI Tabernero J et al, J Clin Oncol 2010;28:1181-1189 Presented by:

  15. Ligands: AREG, EREG, TGFalpha • Combimarker: K-Raswt and high EREG • Pre-especified threshold1 • Minimum threshold: 169/384 (44%) • All comers  394 (100%) HR: 0.7 • K-Raswt 230 (58%) HR: 0.55 • Combimarker 169 (44%) HR: 0.46 100 High EREG by minimum-p threshold Low EREG by minimum-p threshold 80 Cetuximab + BSC 100 60 Cetuximab + BSC Proportion alive 80 40 60 20 Proportion alive 40 BSC alone 0 BSC alone 0 2 4 6 8 10 12 14 20 84 80 76 66 43 28 18 8 85 73 54 26 19 14 10 5 HR 0.46 [0.32-0.65], p<0.0001 HR 0.93 [0.51-1.71], p=0.81 Time from randomization (months) 0 0 2 4 6 8 10 30 25 16 13 8 5 26 18 15 10 5 3 Time from randomization (months) 1Khambata-Ford, S. et al. J Clin Oncol; 25:3230-3237, 2007 2Jonker, D et al. Proc ASCO 2009

  16. On-treatment Predictive Biomarkers(“under pressure”) MUTATIONS • KRAS mut • EGFR mut RECEPTOR EXPRESSION • HER-2/neu, HER-3, IGF1R RECEPTOR AMPLIFICATION • C-Met

  17. KRAS mut/ampl under pressure Misale S, et al. Nature 2012 Diaz E, et al. Nature 2012

  18. KRAS mut/ampl under pressure Initial response to cetuximab followed by PD Quantitative analysis of KRAS(Q61H) mutant DNA in plasma, as assessed by BEAMing Misale S, et al. Nature 2012 Diaz E, et al. Nature 2012

  19. C-Met amplification Bardelli A, et al. Cancer Discov 2013;e

  20. EGFR mutations EGFR ectodomain mutation (S492R) that prevents Cetuximab binding, but retain binding to panitumumab S492R EGFR mutation was detected in 4 (7%) out of 55 pts (MDACC) KRAS wt after treatment with cetuximab Montagut C, et al. Nature Med 2012;18:221-223 Morelli MP et al. Proc ASCO 2013:A3512

  21. CD73 – 5’nucleotidase (5’-NT) • The release of extracellular ATP in response to cell death or stress activates immune responses • The hydrolysis of extracellular ATP into adenosine acts as a negative feedback mechanism to prevent excessive inflammation and tissue damage • CD73 converts AMP to adenosine and is considered as a an immunosuppressor inducer • Anti-CD73 mAb therapy delays tumor growth in immune-competent mice and inhibits the development of metastasis, through the induction of adaptive immune response Mizumoto N et al, Nat Med 2002;8:358-365 Stagg J et al, PNAS 2010;107:1547-1552

  22. CALGB80203Study Design – Biomarker program A: FOLFIRI 1st line Metastatic Colorectal Cancer n = 238 B: FOLFIRI + Cetuximab C: FOLFOX D: FOLFOX + Cetuximab Total patients for biomarker analysis (n=103) Key inclusion criteria: EGFR positive Ras status not required Accrual: 01/21/2004-12/03/2004 Hurwitz H, et al. Proc ASCO 2013

  23. Prognostic Analyses: Chemotherapy only population 52 patients Hurwitz H, et al. Proc ASCO 2013

  24. Prognostic Analyses: Chemotherapy only, WT KRAS population 29 patients Hurwitz H, et al. Proc ASCO 2013

  25. Predictive Analyses: CD73 and Her3Overall Population Population: 52 w/o + 51 w Cetuximab Hurwitz H, et al. Proc ASCO 2013

  26. Predictive Analyses: CD73 and Her3Wild type KRAS Population Population: 29 w/o + 26 w Cetuximab Hurwitz H, et al. Proc ASCO 2013

  27. Author’s Conclusions & Personal Comments • Multiple Her axis members and CD73 were identified as candidate prognostic markers for patients treated with FOLFOX/FOLFIRI chemotherapy • CD73 and Her3 were identified as candidate predictive markers for benefit/lack of benefit from cetuximab • Candidate markers were selected from the literature and confirmed –only as candidates- in the study

  28. + Predictive Genes & outcomeKRAS wt population • 144 KRAS wt mCRC treated with cetuximab • 4-gene predictive classifier (AREG, EREG, DUSP6, SLC26A3) constructed using multivariate analysis with two-layer five-fold cross-validation • Patients below the classifier cutpoint had PFS and disease control rates similar to those of patients with KRAS mutant mCRC. Khambata-Ford, S. et al. J Clin Oncol 2007;25:3230-3237. Baker JB, et al. Br J Cancer 2011;104:488-495

  29. Author’s Conclusions & Personal Comments • These results • Merit confirmation in other randomized studies • Suggest potentially intersecting roles for tumor inflammation, Her family cross talk, and Ras signaling • Suggest potential novel patient selection and combination treatment approaches • Important correlative translational study: • Negative, prematurely closed study, poor recruitment • In this circumstances, high tumor acquisition rate (43%) • Hypothesis generating study • No power to confirm any previous finding… • …but raises new potential prognostic/predictive biomarkers to be explored in the future

  30. What’s next? • Reproduce these results in large cohorts datasets, especially for the new candidates, i.e. CD73 • Evaluate these proposed candidates in trials with Panitumumab, in order to address the class-effect or the Ig subtype-effect (IgG1 vs IgG2) • Integrate different correlative studies into large datasets • Make the results open access

  31. Acknowledgements • ASCO Scientific & Educational Committee • The authors, especially Herb Hurwitz, for the very constructive interaction • Special claim for implementing more correlative studies and for data sharing for the best interest of our patients

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