1. Personalized Therapy in Colorectal Cancers J. Randolph Hecht, MD Professor of Clinical Medicine Director, UCLA GI Oncology Program David Geffen School of Medicine at UCLA

2. What Does Personalized Therapy Mean? Right Treatment Right Patients

3. Biomarker NIH Definition: a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.NIH Definition: a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. Predictive: (Ex: HER-2, BRAF, cytogentic abnormalities)Predictive: (Ex: HER-2, BRAF, cytogentic abnormalities) Prognostic: (Ex: HER-2, KRAS)Prognostic: (Ex: HER-2, KRAS)

4. Biomarkers

5. Evaluating Predictive Biomarkers: Trial Design Patient Population R Biomarker positive Biomarker negative Receive treatment Do not receive treatment Receive treatment Do not receive treatment

6. Biology of Colorectal Cancers Subgroup Analysis –Breast cancer does it, is it time for CRC? CIN vs MSI vs CIMP+ –CIN: Majority of tumors MSS, APC mutation –MSI: Abnormal DNA mismatch repair ~15% Most Sporadic (BRAF mut); others HNPCC Molecular Subgroup Analysis

7. Tabernero, ASCO GI 2013

8. Uronis, ASCO GI 2013

9. Cancer Genome Atlas Network, Nature 2012

10. Biomarkers Histology: TNM Dukes, J Path Bacteriol, 1932

11. Survival Rates of by Stage of Adenocarcinoma of the Colon Edge SB, et al. AJCC cancer staging manual. 2010. Data from the SEER 1973-2005 Public Use File diagnosed in years 1998-2000. Survival Rate 0 20 0 40 60 80 100 1 2345 30 50 70 90 10 100 100 100 100 I IIA IIB IIC IIIA IIIB IIIC IV 91.4 89.9 85.4 66.0 98.3 83.4 71.9 39.9 87.0 83.4 77.8 52.5 88.0 70.8 50.3 19.7 82.6 77.8 69.1 45.3 83.6 59.3 39.0 11.3 78.2 72.0 62.9 41.5 79.1 51.7 32.9 7.6 74.0 66.5 58.6 37.3 73.1 46.3 28.0 5.7 Yrs From Diagnosis

12. Other Putative Biomarkers: Molecular pathology CTCs Molecular abnormalities –Mutations –microRNAs Gene expression profiles

13. Where Would Biomarkers Be Most Useful? Adjuvant –Treat those who would benefit –Don’t treat those that won’t Metastatic Disease –We have multiple agents. How can we choose for safety and efficacy?

14. Stage II Colon Cancer Which stage II colon cancer patients should be treated with adjuvant chemotherapy? –75% to 80% cured with surgery alone –Benefit of chemotherapy is small and no consensus on whom to treat or on how to identify whom to treat Decision to give chemotherapy based on –Clinical/pathologic markers of risk –Molecular biomarkers –Not informative for majority of patients

15. 1.0 0.8 0.6 0.4 0.2 0 Stage IIStage III Follow-up (Yrs) Surgery alone: 66.8% Surgery + FU-based chemotherapy: 72.2% Surgery alone: 42.7% Surgery + FU-based chemotherapy: 53.0% 012345678012345678 1.0 0.8 0.6 0.4 0.2 0 Sargent D, et al. J Clin Oncol. 2009;27:872-877. ∆ = 5.4% P =.026 012345678012345678 ∆ = 10.3% P <.0001 Adjuvant Therapy Increases OS: ACCENT Database of 20,898 Patients Probability of Survival

16. Determining Who Benefits From Adjuvant Therapy in CRC Risk assessment in stage II (III) CRC: prognostic factor(s) of recurrence of disease and predictive factor(s) to the treatment. –High-risk prognostic factors [1] Stage II: T4, tumor perforation, bowel obstruction, poorly differentiated tumor, venous invasion, or < 10 examined nodes Stage III: age, lymph node involvement, T stage, tumor obstruction, differentiation –Defective mismatch repair and microsatellite instability [2-5] 1. André T, et al. J Clin Oncol. 2009;27:3109-3116. 2. Hutchins G, et al. J Clin Oncol. 2011;29:1261-1270. 3. Sargent DJ, et al. J Clin Oncol. 2010;28:3219-3226. 4. Sinicrope FA, et al. J Natl Cancer Inst. 2011;103:863-875. 5. Ribic CM, et al. N Engl J Med. 2003;349:247-257.

17. MOSAIC: Exploratory Analysis of DFS and OS in “High-Risk” Stage II CRC André T, et al. J Clin Oncol. 2009;27:3109-3116. 0.40.60.81.01.21.41.6 Stage II High-risk stage II Stage III Stage II High-risk stage II Stage III OS at 6 Yrs DFS at 5 Yrs HR Favors FOLFOX4Favors LV5FU2

18. Missed Micrometastases IHC+ H&E LN“N0” RT-PCR+

19. MMR-D (MSI) Is a Favorable Prognostic Marker in Stage II (and III) Colon Cancer Study Stage Treatment Endpoint MMR-D vs MMR-P HR (95% CI; P Value) Ribic et al [1] II/III Surgery alone OS0.31 (0.14-0.72;.004) Roth et al (PETACC-3) [2] II 5-FU/LV ± irinotecan Relapse-free survival OS 0.27 (0.10-0.72;.0094) 0.14 (0.03-0.64;.011) Sargent et al [3] II/III Surgery alone DFS OS 0.46 (0.22-0.95;.03*) 0.51 (0.24-1.10;.06*) Gray et al (QUASAR) [4 ] II Surgery alone Recurrence-free interval 0.31 (0.15-0.63; <.001) 1. Ribic CM, et al. N Engl J Med. 2003;349:247-257. 2. Roth AD, et al. J Clin Oncol. 2010;28:466-474. 3. Sargent DJ, et al. J Clin Oncol. 2010;28:3219-3226. 4. Gray R, et al. J Clin Oncol. 2011;29:4611-4619.

20. 5-FU Not Beneficial and Survival Longer in Stage II Patients With MMR Deficiency Sargent DJ, et al. J Clin Oncol. 2010;28:3219- 3226. No Adjuvant 5-FU Chemotherapy Adjuvant 5-FU Chemotherapy HR for OS: 0.47 (95% CI: 0.26-0.83; P =.004) HR for OS: 0.78 (95% CI: 0.49-1.24; P =.28) Percent Alive and Progression Free Yrs 021345 0 20 40 60 80 100 MMR-d (n = 86) MMR-p (n = 426) HR: 0.79 (95% CI: 0.49-1.25; P =.30) Percent Alive and Progression Free Yrs 021345 0 20 40 60 80 100 MMR-d (n = 79) MMR-p (n = 436) HR: 0.51 (95% CI: 0.29-0.89; P =.009)

21. Gene signatures provide prognostic, not predictive, information 12-gene recurrence score assay validated for recurrence risk in stage II patients –QUASAR: 12% (low risk) vs 22% (high risk) 3-yr recurrence risk [1] –CALGB 9581: 13% (low risk) vs 21% (high risk) 5-yr recurrence in T3, MMR proficient disease [2] 1. Gray RG, et al. J Clin Oncol. 2011;29:4611-4619. 2. Venook AP, et al. ASCO 2011. Abstract 3518. Genomic Tests for CRC Risk Stratification

22. Personalized Therapy For Metastatic Disease Cytotoxics Anti-EGFR Antibodies Anti-VEGF Pathway Agents

23. Cytotoxic Agents Fluoropyrimidines –TS: A target. No clear evidence for choosing therapy –DPD: Dihydropyrimidine dehydrogenase deficiency associated with severe FP toxicity Testing only in patients with toxicity Irinotecan –UGT1A1*28 (10% of North Americans) Originally associated with diarrhea but later studies with neutropenia instead In package insert, but not used –Topo 1: Conflicting data Oxaliplatin –ERCC1: Unproven for efficacy

24. Anti-EGFR Agents

26. EGFR Signaling Pathway Extracellular Intracellular Ligand EGFR PI3K Akt Ras Raf MEK MAPK Cell motility Metastasis Angiogenesis Proliferation Cell survival DNA PTEN

28. KRAS as a Biomarker for Panitumumab Response in Metastatic CRC PFS log HR significantly different depending on KRAS status (p <.0001) Percentage decrease in target lesion greater in patients with wild-type KRAS receiving panitumumab Approved in EU in KRAS WT Patients With Mutant KRAS Mean in Wks Stratified log rank test: P <.0001 115/124 (93) Patients With Wild-Type KRAS 1.0 0.9 Proportion With PFS 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 024 6810 Events/N (%) Median in Wks Pmab + BSC BSC alone 114/119 (96) 12.3 7.3 19.0 9.3 HR: 0.45 (95% CI: 0.34–0.59) 12141618 20 2224262830 32 343638 40 42 44 46485052 Weeks Proportion With PFS 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 24 681012141618 20 2224262830 32 343638 40 42 44 464850 Weeks Pmab + BSC BSC alone Mean in Wks 76/84 (90) Events/N (%) Median in Wks 95/100 (95) 7.4 7.3 9.9 10.2 HR: 0.99 (95% CI: 0.73–1.36) 52 Amado et al., JCO 2008.

29. Tejpar et al., ASCO 2011 What About G13D (~20% mutations)

30. No Effect Of G13D in Larger Sample Peeters ASCO GI 2012

31. EGFR Signaling Pathway Extracellular Intracellular Ligand EGFR PI3K Akt Ras Raf MEK MAPK Cell motility Metastasis Angiogenesis Proliferation Cell survival DNA PTEN

32. BRAF –V600E mutation relatively common in CRC (5-15%) –Poor prognostic factor (Van Cutsem ASCO GI, 2010) FOLFIRI+cetuximab PFS: 25.1 vs 14.1 months –Inhibitors: sorafenib, PLX4032 (vemurafenib) –PLX4032: 70% RR in V600E melanoma, but 5% in CRC

33. CI, confidence interval; CT, chemotherapy; HR, hazard ratio; mt, mutant; OS, overall survival; wt, wild-type 32251612852220 3824146633100 0 0CT CT + cetuximab Probability of overall survival 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 18061224603036424854 Time (months) Number of patients 3493172682251631208063194 3813502832121491076346172 0 0CT CT + cetuximab KRAS wt/BRAF wt HR [95% CI]: 0.840 [0.710–0.993] p=0.041 FOLFIRI / FOLFOX4 + cetuximab: (n=349) median 24.8 months FOLFIRI / FOLFOX4: (n=381) median 21.1 months KRAS wt/BRAF mt HR [95% CI]: 0.633 [0.378–1.060] p=0.079 FOLFIRI / FOLFOX4 + cetuximab: (n=32) median 14.1 months FOLFIRI / FOLFOX4: (n=38) median 9.9 months Bokemeyer Pooled analysis of OS in patients with KRAS wt/BRAF mt tumors

34. Other Markers (Unknown Benefit) Rare KRAS mutations NRAS Ligands (amphiregulin, epiregulin) Copy Number

35. Anti-VEGF Pathway Drugs None!

36. Molecular Profiling Multiple Targets (Caris, Foundation Medicine) Sequencing Explants No Evidence of Clinical Benefit Hours of Physician Time

37. We are on the verge of truly personalized therapy for colorectal cancer We need to be able to identify subgroups by genetic alterations and activated pathways We need to validate molecular tests before selling them to the public We need to identify new targets for new drugs We may have to find ways to do trials in small subsets

38. BONUS New indications for anti-VEGF pathway agents!!

39. Agents Targeting the Vascular Endothelial Growth Factor (VEGF) Pathway VEGFR-2 VEGFR-1 P P P P P P P P Endothelial cell Small-molecule VEGFR inhibitors (PTK787, sunitinib, sorafenib, regorafenib, axitinib) Anti-VEGFR antibodies (IMC-1121b) Soluble VEGF receptors (VEGF-TRAP/ aflibercept) VEGF Anti-VEGF antibodies (bevacizumab)

40. Golden Age of CRC Therapeutics: Bevacizumab Hurwitz H et al. N Engl J Med. 2004;350:2335-2342. HR = 0.66, P <.001 Percent Surviving Duration of Survival (months) 1.0 0.8 0.6 0.4 0.2 0.0 010203040 IFL/bevacizumab IFL/placebo 20.315.6 10.6 100 80 60 40 20 0 0102030 Progression-free Survival (%) Progression-Free Survival (months) 6.2 (n = 402) (n = 411) HR = 0.54, P <.001

41. What About Angiogenesis Inhibition After First Line Therapy? Bevacizumab Aflibercept Regorafenib

42. E3200: Overall Survival P r o b a b i l i t y 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 OS (months) 0369121518212427303336 ALIVEDEADMEDIANTOTAL A:FOLFOX4 + bevacizumab 2892464312.9 B:FOLFOX42902573310.8 C:bevacizumab2432162710.2 HR = 0.76 A vs B: p = 0.0018 B vs C: p = 0.95 Giantonio BJ, et al. ASCO 2005 No first line bev!

43. BEV + standard first-line CT (either oxaliplatin or irinotecan-based) (n=820) Randomise 1:1 Standard second-line CT (oxaliplatin or irinotecan- based) until PD BEV (2.5 mg/kg/wk) + standard second-line CT (oxaliplatin or irinotecan- based) until PD PD ML18147 (TML) study design CT switch: Oxaliplatin → Irinotecan Irinotecan → Oxaliplatin CT switch: Oxaliplatin → Irinotecan Irinotecan → Oxaliplatin Study conducted in 220 centres in Europe and Saudi Arabia Primary endpointOverall survival (OS) from randomisation Secondary endpoints included Progression-free survival (PFS) Best overall response rate Safety Stratification factors First-line CT (oxaliplatin-based, irinotecan-based) First-line PFS (≤9 months, >9 months) Time from last BEV dose (≤42 days, >42 days) ECOG PS at baseline (0/1, 2) Arnold 2012

44. OS: ITT population OS estimate Time (months) 1.0 0.8 0.6 0.4 0.2 0 0612182430364248 No. at risk CT4102931625124732 0 BEV + CT40932818864291341 0 CT (n=410) BEV + CT (n=409) 9.8 mo 11.2 mo Unstratified a HR: 0.81 (95% CI: 0.69–0.94) p=0.0062 (log-rank test) Stratified b HR: 0.83 (95% CI: 0.71–0.97) p=0.0211 (log-rank test) a Primary analysis method; b Stratified by first-line CT (oxaliplatin-based, irinotecan-based), first-line PFS (≤9 months, >9 months), time from last dose of BEV (≤42 days, >42 days), ECOG performance status at baseline (0, ≥1)

45. PFS: ITT population PFS estimate Time (months) 1.0 0.8 0.6 0.4 0.2 0 06121824303642 No. at risk CT4101192064000 BEV + CT40918945125220 CT (n=410) BEV + CT (n=409) 4.1 mo 5.7 mo Unstratified a HR: 0.68 (95% CI: (0.59–0.78) p<0.0001 (log-rank test) Stratified b HR: 0.67 (95% CI: 0.58–0.78) p<0.0001 (log-rank test) a Primary analysis method; b Stratified by first-line CT (oxaliplatin-based, irinotecan-based), first-line PFS (≤9 months, >9 months), time from last dose of BEV (≤42 days, >42 days), ECOG performance status at baseline (0, ≥1)

46. What else does TML teach us? Affirms the limited utility of Registry studies regarding interventions and outcomes: –BRITE: 9.5 v. 19.2 OS beyond PD –TML: 9.8 v. 11.2 BRiTE findings not replicated; the publication* could be cited as an example of the pitfalls of Registry data * Grothey et al, JCO, 2008 Venook 2012

47. Aflibercept (VEGF-TRAP) Fully human fusion protein and soluble recombinant decoy VEGF receptor composed of Domain 2 of VEGFR1 and Domain 3 of VEGFR2 fused to the Fc of IgG1 Higher affinity for VEGF-A than bevacizumab and also blocks PlGF; T 1/2 17 days EFC10262 (VELOUR ) –Phase III Trial 2 nd Line FOLFIRI +/- VEGF-TRAP (Aflibercept) Where has it been?

48. VELOUR Study Design Primary endpoint: overall survival Sample size: HR=0.8, 90% power, 2-sided type I error 0.05 Final analysis of OS: analyzed at 863 rd death event using a 2-sided nominal significance level of 0.0466 (α spending function) Metastatic Colorectal Cancer RANDOMIZERANDOMIZE Aflibercept 4 mg/kg IV, day 1 + FOLFIRI q2 weeks Aflibercept 4 mg/kg IV, day 1 + FOLFIRI q2 weeks Placebo IV, day 1 + FOLFIRI q2 weeks Placebo IV, day 1 + FOLFIRI q2 weeks 1:1 Disease Progression Death 600 600 600 Stratification factors: ECOG PS (0 vs 1 vs 2) Prior bevacizumab (Y/N)

49. VELOUR: Results Van Cutsem, et al. WCGC 2011

50. VELOUR Study Overall results –Adding aflibercept to FOLFIRI in mCRC patients previously treated with an oxaliplatin-based regimen resulted in significant OS and PFS benefits Van Cutsem E et al. ESMO/WCGC 2011, Barcelona, Abstract O-0024. OS PFS

51. Overall Survival: Stratified by Prior Bevacizumab – ITT Population Allegra 2012

52. Progression-Free Survival: Stratified by Prior Bevacizumab – ITT Population Allegra 2012

53. TML/VELOUR Is aflibercept better than bevacizumab second-line? ? Differences in toxicity than bevacizumab What about anti-EGFR Ab? SPIRITT trial (KRAS WT) pending

54. Small Molecule TKIs Both Abs and TKIs may inhibit the “classic” VEGF-A/VEGFR-2 pathway Inhibition of multiple VEGF receptors may be important Inhibition of other receptors (Clean vs. Dirty) c-kit, PDGF-R, RET, FGF-R MAb TKI Godzilla vs. Mothra 1964

55. CRC: Graveyard of VEGFR TKIs Negative Randomized Trials: 6365+ pts SU5416719 CONFIRM 11168 CONFIRM 2855 HORIZON II/III1050/1614 SUN1122768 SUN1104 191 TKI

56. VEGFR TKIs: Take 2 Negative in combination with chemotherapy New studies with chemo free regimens Front-line vs salvage

57. Regorafenib: What A Difference a F Makes!

58. Regorafenib: Small molecule inhibitor of VEGFR and FGFR-1 CORRECT Trial Grothey et al. 760 pts 2:1 Chemorefractory mCRC vs BSC, interim analysis PFS: 1.9 v 1.7m (HR=0.493) p<0.000001 OS: 6.4 v 5.0m (HR=0.773) p=0.0051 Positive but is it clinically significant?

59. Overall survival (primary endpoint) Primary endpoint met prespecified stopping criteria at interim analysis (1-sided p<0.009279 at approximately 74% of events required for final analysis) 1.00 0.50 0.25 0 0.75 200100500150300250400350450 Days from randomization Survival distribution function Placebo N=255 Regorafenib N=505 Median 6.4 mos 5.0 mos 95% CI 5.9–7.3 4.4–5.8 Hazard ratio: 0.77 (95% CI: 0.64–0.94) 1-sided p-value: 0.0052 RegorafenibPlacebo Grothey 2012

60. 1.00 0.50 0.25 0 0.75 200100500150300250350 Days from randomization Survival distribution function Placebo N=255 Regorafenib N=505 RegorafenibPlacebo Median 1.9 mos 1.7 mos 95% CI 1.9–2.1 1.7–1.7 Hazard ratio: 0.49 (95% CI: 0.42–0.58) 1-sided p-value: <0.000001 Progression-free survival (secondary endpoint) Grothey 2012

61. Overall response and disease control rates (secondary endpoints) *DCR = PR + SD; p<0.000001 Grothey 2012

62. Why these results? Possibly benefit from long term anti-VEGF inhibition (BRITE) Can anti-VEGF therapy worsen post-therapy outcome? (Bevacizumab Addiction) –Bevacizumab only leads to modest improvement in OS –VEGF inhibition may up-regulate other parts of pathway and other pathways –Preclinical models of increased metastasis with VEGFR-2 inhibition (Rip- TAG Paez-Ribes, 2009 and sunitinib conditioning Ebos, 2009) –Differences between PFS and OS with PTK/ZK (Hecht JCO 2010)