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GI ASCO 2012 Non-colon update

GI ASCO 2012 Non-colon update. Dr. Delilah Lisa Topic, MD, FRCPC Clinical Fellow – St. Michael’s Hospital Supervisor: Dr. Brezden-Masley. GI ASCO 2012 – Jan 19-21 st , 2012 San Francisco, CA. GI ASCO 2012. Non-colon Esophagogastric Pancreatic Hepatobiliary. ESOPHAGOGASTRIC.

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GI ASCO 2012 Non-colon update

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  1. GI ASCO 2012Non-colon update Dr. Delilah Lisa Topic, MD, FRCPC Clinical Fellow – St. Michael’s Hospital Supervisor: Dr. Brezden-Masley

  2. GI ASCO 2012 – Jan 19-21st, 2012 San Francisco, CA

  3. GI ASCO 2012 • Non-colon • Esophagogastric • Pancreatic • Hepatobiliary

  4. ESOPHAGOGASTRIC

  5. Esophagogastric • Phase III trial of everolimus in previously treated patients with advanced gastric cancer (AGC): GRANITE-1 • Survival analysis according to disease subtype in AVAGAST: First-line capecitabine and cisplatin, plus bevacizumab or placebo, in patients with AGC

  6. Phase III trial of everolimus (EVE) in previously treated patients with advanced Gastric Cancer: GRANITE-1 Eric Van Cutsem, MD, PhD University Hospital Leuven/Belgium

  7. Background • Gastric cancer is aggressive and difficult to treat • 5 year survival for advanced/metastatic is <5% • Limited options upon failure of first-line chemotherapy

  8. PI3k/Akt/mtor pathway Key regulator of cell proliferation, growth, survival, metabolism, and angiogenesis Disregulated in 50-60% of gastric cancersEverolimus -Oral mTor inhibitor, efficacy in preclinical models of gastric cancer -Promising efficacy and tolerability in small phase II study (n=53) OS 10.1 mos, PFS 2.7mos

  9. Phase 3 GRANITE-1 Study Design • Confirmed advanced gastric cancer • Progression after 1 or 2 lines of previous systemic chemotherapy • Stratification by region: Asia vs rest of world • Stratification by number of lines of previous systemic chemotherapy (1 vs 2) Everolimus 10 mg PO daily+ BSC* (n = 439) RANDOMIZE 2:1 (N = 656) SCREEN Safety follow-up: EOT + 28 d Treatment until disease progression or intolerable toxicity Survival follow-up: every 3 mo Placebo PO daily + BSC (n = 217) BSC, best supportive care; EOT, end of treatment; PO, orally. ClinicalTrials.gov identifier: NCT00879333. Van Cutsem E et al. GI Cancer Symposium 2012 (Abstr LBA3).

  10. Eligibility criteria • Inclusion criteria • Age >18yrs • Confirmed gastric adenocarcinoma • Documented progression after 1-2 lines of chemo • ECOG ≤2 • Adequate bone marrow, renal, and hepatic function • Exclusion criteria • >2 lines of systemic treatment for advanced disease • Anticancer treatment within 3 wks or major surgery within 2 weeks of study randomization • Chronic treatment with steriods or immunosuppressive agents • Enteral feeding • CNS metastases • Any severe/uncontrolled medical condition

  11. Study Endpoints • Primary: • OS • Secondary: • PFS • ORR • AEs • Time to definitive deterioration of ECOG • Time to 5% deterioration in global health/QOL • Exploratory: • Correlation between biomarkers and clinical endpoints

  12. Participating Countries • North America • Canada • United States • Central and South America • Argentina • Colombia • Mexico • Peru • East Asia • China • Hong Kong • Japan • Korea • Taiwan • Other Asia and Pacific Region • Australia • New Zealand • Thailand • Europe and Middle East • Belgium • France • Germany • Israel • Italy • Netherlands • Russia • Spain • United Kingdom

  13. Baseline Patient Characteristics

  14. Baseline Disease Characteristics

  15. Overall Survival 100 Censoring Times Everolimus + BSC (n/N = 352/439) Placebo + BSC (n/N = 180/217) 80 Kaplan-Meier medians Everolimus + BSC: 5.39 months Placebo + BSC: 4.34 months 60 Hazard ratio: 0.90 (95% CI, 0.75-1.08) Probability of overall survival (%) Log-rank P value = 0.1244 40 20 0 0 2 4 6 8 10 12 14 16 18 20 22 24 Time (months) No. of patients still at risk Time (months) 0 2 4 6 8 10 12 14 16 18 20 22 24 Everolimus 439 355 253 195 139 87 52 30 13 6 3 1 0 217 172 1 17 82 60 35 28 16 12 8 4 1 0 Placebo CI, confidence interval. Van Cutsem E et al. GI Cancer Symposium 2012 (Abstr LBA3).

  16. Overall Survival by Stratification Factors Hazard Ratio (95% CI) All (N = 656) 0.90 (0.75-1.08) Prior chemotherapy 1 (n = 313) 0.94 (0.73-1.23) 2 (n = 343) 0.90 (0.70-1.15) Region Asia (n = 363) 0.96 (0.75-1.23) ROW (n = 293) 0.85 (0.65-1.10) 1 prior chemo & Asia (n = 146) 0.94 (0.63-1.39) Cross-class. of strata 2 prior chemo & Asia (n = 217) 0.98 (0.71-1.35) 1 prior chemo & ROW (n = 167) 0.91 (0.64-1.31) 2 prior chemo & ROW (n = 126) 0.74 (0.50-1.09) 0.6 0.8 1.0 1.2 1.4 Everolimus 10 mg/d Placebo In favor of ROW, rest of world. Van Cutsem E et al. GI Cancer Symposium 2012 (Abstr LBA3).

  17. Progression-Free Survival 100 Censoring Times Everolimus + BSC (n/N = 386/439) Placebo + BSC (n/N = 206/217) 80 Kaplan-Meier medians Everolimus + BSC: 1.68 months Placebo + BSC: 1.41 months 60 Hazard ratio: 0.66 (95% CI, 0.56-0.78) Probability of progression-free survival (%) Log-rank P value < 0.0001 40 20 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Time (months) No. of patients still at risk Time (months) 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Everolimus 439 367 179 117 92 60 44 37 27 20 13 10 6 5 3 3 2 1 1 0 0 0 217 168 55 28 23 17 8 7 6 3 2 2 2 2 2 2 2 2 2 2 1 0 Placebo Van Cutsem E et al. GI Cancer Symposium 2012 (Abstr LBA3).

  18. Tumour Response

  19. Best Percentage Change From Baseline in Tumor Size 160% 160% 140% 140% 120% 120% 100% 100% 80% 80% Everolimus 10 mg/day (n = 304) Placebo (n = 154) 60% 60% Best % change from baseline (measurable lesions) 40% 40% 20% 20% 0% 0% –20% –20% –40% –40% –60% –60% –80% –80% –100% –100% Van Cutsem E et al. GI Cancer Symposium 2012 (Abstr LBA3).

  20. Adverse Events

  21. Most Common AEs

  22. GRANITE-1Conclusions • Everolimusmonotherapy did not significantly improve OS in patients with AGC as second/third line therapy • Everolimus did reduce the risk of progression, compared with BSC • Median PFS 1.411.68, HR 0.66, p<0.001 • Disease control 22%43%

  23. GRANITE-1 Conclusions • Safety profile was similar to that observed with everolimus in other malignancies • Disease control signal worth further study? • Biomarkers to identify those who benefit

  24. Survival analysis according to disease subtype in AVAGAST: First-line capecitabine and cisplatin plus bevacizumab or placebo in pts with advanced gastric cancer Manish Shah, MD

  25. Gastric cancer: not one disease! • Clinical/epidemiological data suggest there are three subtypes: • Type 1: proximal, non-diffuse • Type 2: diffuse • Type 3: distal, non-diffuse • Each subtype has different gene expression profile

  26. Gastric cancer: 3 subtypes

  27. AVAGAST • Global, randomized, phase III study • Bevacizumab + chemo vs. placebo + chemo (first-line treatment for AGC) • Primary endpoint: OS • Was not met (12 mosvs 10 mos, p=0.1002) • Regional efficacy differences were noted • Patients from Europe/Americas did better

  28. Regional differences • Several analyses have been performed to better understand regional differences • Analysis has revealed: • It is the ‘high risk’ pts from Europe/Americas that derive more benefit from bevacizumab

  29. Objectives • To examine the OS data according to gastric cancer subtype and region • To identify if disease subtype was: • Prognostic • Predictive of bevacizumab benefit (Europe/Americas) • To examine the distribution of angiogenic biomarkers across subtypes • Do gastric cancer subtypes have different biomarker expression profiles?

  30. AVAGAST: trial design Placebo + capecitabine + cisplatin (n=387) Locally advanced or metastatic gastric cancer(n=774) R Bevacizumab + capecitabine + cisplatin (n=387) Stratification factors: 1. Geographic region 2. Fluoropyrimidine backbone 3. Disease status Endpoints Primary: Overall survival Secondary: Progression-free survival Exploratory: Changes in candidate biomarkers: pVEGFA, NRP-1, VEGFA, VEGFR1, VEGFR2 5-FU allowed if capecitabine contraindicated Maximum of 6 cycles of cisplatin Capecitabine and bevacizumab / placebo until PD

  31. Disease subtype: distribution by region All patients (n=733) Europe/Americas (n=378) Asia-Pacific (n=355)

  32. Biomarker distribution • There appears to be differences in biomarker distribution amongst gastric cancer subtypes

  33. Disease subtype: prognostic effect (overall survival in non-Asian patients) Survival rate (%) Proximal Diffuse Distal 100 90 80 70 60 50 40 30 20 10 0 0 3 6 9 12 15 18 21 24 Studymonth No. at risk Type 1 Type 2 Type 3 30 91 72 28 72 62 22 47 47 18 28 35 14 22 21 7 13 12 3 5 4 1 1 0 0 0 0

  34. Overall survival by disease subtype

  35. Does disease subtype predict response to Bevacizumab? (Europe/Americas only)

  36. Overall survival in pts with diffuse/distal disease (Europe/Americas only) Population: Europe/Americas with type 2/3 disease 100 90 Survival rate (%) Pla + chemo Bev + chemo 80 70 60 50 Hazard ratio 0.67 (95% CI 0.52–0.88) 40 30 20 10 00 0 3 6 9 12 15 18 21 24 Study month No. at risk Pla + chemo Bev + chemo 43 63 94 119 25 28 163 159 0 0 9 10 134 144 1 3 63 94

  37. Predictive biomarkers with bevacizumab

  38. Biomarker distribution according to subtypes

  39. Biomarker distribution (summary) • Proximal (type 1) gastric cancer appears to have the ‘worst’ profile for bevacizumab • High NRP-1, low pVEGF-A • Diffuse (type 2) and distal (type 3) appear to have at least one biomarker that may support benefit to an antioangiogenic strategy • Diffuse (type 2)  low NRP-1 • Distal (type 3)  high pVEGF-A

  40. AVAGAST Conclusions • Gastric cancer is more than one disease! • Gastric cancer subtypes have different prognoses • In all regions, diffuse (type 2) did worse • The addition of bev to chemo appears to improve outcomes in pts from Europe/Americas with diffuse and distal disease • Biomarkers NRP-1 and plasma pVEGF-A provide a rationale for subtype-specific outcomes with bevacizumab • Additional evaluation warranted

  41. Pancreatic

  42. Malignant progression in intraductal papillary mucinousneoplasms (IPMN) of the pancreas: Results of 157 patients selected for radiographic surveillance Jennifer Lafemina, MD Memorial Sloan-Kettering

  43. “Its just a cyst – don’t worry!”

  44. Intraductal papillary mucinousneoplasms (IPMN) – not “just a cyst” • Represents a field defect of ductal instability • Main and branch duct IPMN carry a risk of malignancy intarget cyst itself • 57-95% for MD-IPMN • 6-46% for BD-IPMN • Risk of developing malignancy in region other than target cyst is poorly defined

  45. Objectives • Identify patients with IPMN who underwent resection • Define: • Pathologic characteristics of target cyst • Risk of developing a PDAC in a region separate from the target cyst

  46. Methods • Retrospective review • Pts evaluated at MSKCC from Feb ‘89-Aug ‘10: • Radiologic confirmation of target cyst • Pathologic confirmation of IPMN and/or cyst fluid CEA level ≥200ng/mL • Time from IPMN diagnosis to resection ≥6 mos

  47. Patient demographics

  48. Objectives • Identify patients with IPMN who underwent resection • Define pathologic characteristics of target cyst • Define the risk of developing a PDAC in a region separate from the target cyst

  49. Target cyst characteristics

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