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New Drugs in Pancreatic Cancer

New Drugs in Pancreatic Cancer. Manuel Hidalgo, M.D., Ph.D. CIO “Clara Campal” Madrid, SPAIN Johns Hopkins University Baltimore, MD, USA. Current situation. Promising new targets. Approaches to new drug development The “omis” of pancreatic cancer. Agenda. Significant Problem.

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New Drugs in Pancreatic Cancer

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  1. New Drugs in Pancreatic Cancer Manuel Hidalgo, M.D., Ph.D. CIO “Clara Campal” Madrid, SPAIN Johns Hopkins University Baltimore, MD, USA

  2. Current situation. Promising new targets. Approaches to new drug development The “omis” of pancreatic cancer. Agenda

  3. Significant Problem Jemal et al, Cancer Statistics 2007

  4. Pivotal Phase III Study of Gemcitabine in Pancreatic Cancer R ANDOM I Z E Gemcitabine (1000 mg/m2/wk) • Advanced pancreatic cancer • No prior chemotherapy • Pain, intensity scale > 20/100 • (MPAC) • Adequate Karnofsky PS 5-Fluorouracil (600 mg/m2/wk) Burris et al. JCO 1997

  5. Pivotal Phase III Study of Gemcitabine in Advanced Pancreatic Cancer * Clinical benefit measured as an improvement in pain, performance status, or weight gain with an algorithm using the Memorial Pain Assessment Card. Burris et al. JCO 1997

  6. Most Common Strategies to Develop Drug A in Pancreas Cancer Phase I Trial (s) Single R ANDOM I Z E Gemcitabine Phase I/II Trial in Combination with Gemcitabine RANDOMIZED Gemcitabine + A

  7. Taxanes. Topo I inhibitors. Platinum analogs. FTIs. VEGF antibodies. MMP. EGFR antibodies. Antimetabolites. Drug Tested that Failed

  8. Study Schema RANDOM I ZE Stratified by: - Center - PS (0/1 vs 2) - Stage of disease (locally advanced vs distant metastases) Gemcitabine 1000 mg/m2 IV + Erlotinib100/150 mg po daily Gemcitabine 1000 mg/m2 IV + Placebo 100/150 mg po daily Moore et al. JCO 2007

  9. RR = 0.81* 95% CI (0.67, 0.97) P = 0.025 Gemcitabina + Tarceva Mediana = 6.37 meses Supervivencia 1 año=24% Gemcitabina + Placebo Mediana = 5.91 meses Supervivencia 1 año=17% Supervivencia Global Annals Oncol 2007; 18 (suppl 7): vii 14 (abs O-0010)

  10. Adverse Events

  11. Serious Adverse Events * Pneumonitis, pulmonary infiltrate Moore MJ et al. J Clin Oncol 2007;25:1960–6

  12. Laboratory Abnormalities Worst Grade per Patient On Study Moore MJ et al. J Clin Oncol 2007;25:1960–6

  13. PA.3: Riesgo relativo en supervivencia con características basales (100mg cohorte) Factores n HR 95% CI Tarceva: placebo* 521 0.81 0.7–1.0 PS 0–1 PS 2 432 89 0.87 0.70 0.7–1.1 0.5–1.1 Localmente advanzado Metástasis a distancia 124 397 0.93 0.80 0.6–1.3 0.7–1.0 Intensidad del dolor £20 Intensidad del dolor >20 238 268 0.72 1.00 0.6–0.9 0.8–1.3 HER1/EGFR positivo HER1/EGFR negativo HER1/EGFR no analizado 70 66 385 0.82 0.75 0.86 0.5–1.3 0.5–1.2 0.7–1.1 Hombre Mujer 273 240 0.74 1.00 0.6–0.9 0.8–1.3 Edad <65 años Edad ³65 años 274 247 0.78 0.94 0.6–1.0 0.7–1.2 0 0.50 1.00 1.50 2.00 2.50 *Estratificación por PS y extensión de la enfermedad **no permitida quimioterapia previa, excepto radiosensibilizante HR Moore MJ et al. J Clin Oncol 2007;25:1960–6

  14. PA.3: Supervivencia global en pacientes con Cáncer de Páncreas metastásico* 1.00 0.75 0.50 0.25 0 RR=0.80 (0.66–0.98); p=0.029  25% mejora en SG  20% reducción del riesgo de muerte Probabilidad de supervivencia Gemcitabine + Tarceva Gemcitabine + placebo 0 6 12 18 24 30 36 Tiempo (meses) *Cohorte 100mg Annals Oncol 2007; 18 (suppl 7): vii 14 (abs O-0010)

  15. PA.3 Rash vs Supervivencia Riesgo relativo = 0.71 p<0.0001 Grado 2 Grado 1 Grado 0 Annals Oncol 2007; 18 (suppl 7): vii 14 (abs O-0010)

  16. Expresión K-ras y EGFR como factor predictivo* • *RR ajustados por supervivencia • Interacción entre tratamiento y mutación del K-ras = 1.71 (0.64 -4.63 ; p=0.29) • Interacción entre tratamiento y expresión de EGFR = 1.41 (0.60 –3.32 ; p=0.43) • RR ajustado por SLP • Interacción entre tratamiento y mutación del K-ras = 0.60 (0.22,- 1.62;p=0.31) • Interacción entre tratamiento y expresión de EGFR = 1.18 (0.52-2.6; p=0.69 ) Moore M, et al. JCO, 2007 ASCO Annual Meeting Proceedings Part I. Vol 25, No. 18S (June 20 Supplement), 2007: 4521

  17. Another drug for docs and patients to use. Data is weak but still best data. Need to continue exploring erlotinib in pancreas cancer: Adjuvant and neoadjuvant settings. Continue to explore biomarkers of activity. Exploit rash as a predictor of efficacy. Incorporate into other combinations Punch line of Erlotinib in Pancreatic Cancer

  18. Few single agent studies. Most studies have been done in combination with gemcitabine. Poor understanding of mechanism of action. MMPs Ras inhibitors. Lack of solid phase II data. Cetuximab. Factors that may be implicated in high failure rate

  19. Known Genetic Profile of Pancreatic Cancer Gene ■ p16 ■ K-ras(90%) (+ 5% BRAF) ■ p53 ■ DPC4 ■ BRCA2 (FANC C and G) ■ Mismatch repair genes ■ STK11 (Peutz-Jeghers) Rate of genetic alteration 98 95 70 55 7-10 4 5

  20. FA Complex Genes Physiology Genes and Develop, 2003

  21. Mitomycin C - Sensitivity Am J Pathol. 2004 Aug;165(2):651-7

  22. MMC Prospective Trial in BRCA2 mut Patients Standard therapy BRCA2 wild type Patient with pancreatic cancer Test for BRCA2 BRCA2 mutant Mitomycin C Mitomycin- C

  23. Poly (ADP-Ribose) Polymerase Pathway Ratnam et al, CCR 2007

  24. PARP Inhibitors Ratnam et al, CCR 2007

  25. Some Recently Discovered Potential Targets in Pancreatic Cancer

  26. SHH mutation Role of the Sonic Hedgehog Pathway in Tumorigenesis Hh ligand Smo Smo Cyclopamine Ptch Ptch Fu Cos2 SuFu Fu Cos2 SuFu Processing Stabilization Repress Gli Activates Gli Ptch Gli1 Pathway Off Pathway On

  27. Targeting Hedgehog Pathway in Pancreatic Cancer

  28. Targeting Hedgehog Pathway in Pancreatic Cancer

  29. Better understanding of what are the key targets. Drug development oriented preclinical models. More effective clinical trials design. Gene Newer Approaches for Drug Development in Pancreatic Cancer

  30. Genetic Mouse Models of Pancreas Cancer Hruban, et al. Can Res, 2007

  31. F0 Patient Phase F1 Engraftment Phase F2 Expansion Phase Treatment Phase Biologic studies Biomarker discovery F3 Fn Perpetual bank Design and dynamics Pancreas xenograft model: methodology Rubio et al, CCR 2007

  32. Diagnosis Gemcitabine Mitomycin C Example of a prospective patient

  33. The Complexity of Cancer Genome • Average of 90 mutated genes per case. • Average of 11 thought to be relevant for the neoplastic process. Sjoblom, et al. Science, 2006

  34. Gene mutations. Gene deletions and amplifications: CGH, MLPA, SNP analysis. Expression arrays. microRNAs. Methylation. Proteomics. More to come. The “omics” of pancreatic

  35. MLPA Assessment of Gene Changes in the EGFR Pathway

  36. KEGG Active Pathways in Pancreatic Cancers

  37. In Vivo Activity of Erlotinib, Cetuximab and the Combination in Direct Xenografts from Pancreas Cancer

  38. Baseline IHC Profile

  39. Baseline Mutation and Gene Amplification

  40. GSEA of EGFR Sensitive Tumors

  41. Figure 3D. Figure 3C.

  42. Potentially useful trials • Proof of mechanism studies. • Single agent phase II studies. • Window of opportunity • Second line • Randomized phase II studies. • Biomarker driven trials • Randomized discontinuation studies. • Novel exploratory endpoints • CA199 • PET

  43. Incorporating Biomarkers in Phase II Studies • Determine the clinical activity of PLK-1 inhibitor based on cyclin B1 ex vivo assay.

  44. Conclusions • Pancreatic cancer remains hard to beat. • Erlotinib is the only drug to demonstrate survival improvement in pancreatic cancer. • Significant number of new targets and new drugs. • Which are important? • How to develop them fast? • Better understanding and “big picture” of pancreas cancer starts to emerge. • Individualized treatment is the next step.

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