Individualizing Adjuvant Therapy on the Basis of Molecular Markers Charles S. Fuchs, MD Dana-Farber Cancer Institute Harvard Medical School Boston, MA

Conflict of Interest Disclosure Consultant or Advisory Role Adolor Alnylam Amgen Genentech Imclone Pfizer Roche Sanofi-Aventis

Adjuvant Therapy for Stage II/III Colon Cancer Fluorouracil-based therapy significantly improves survival in stage III disease. Optimal use of adjuvant therapy in stage II remains controversial. Growing interest in biomarkers to tailor therapy for each patient.

Biomarkers in Colorectal Cancer Management Predictive Factor Predicts the likelihood of response to therapy Prognostic Factor Correlates with clinical outcome regardless of treatment

Despite a growing list of biomarkers in CRC, few have entered into clinical practice. Biomarkers in Colorectal Cancer

Studies of Biomarkers in CRC: Potential Issues Assay standardization & reproducibility Small sample size Inadequate data on patient, disease, and treatment characteristics Lack of standardized statistical analysis No adequate validation

Assessing a Predictive Marker Statistical test for interaction:  Assess whether the presence of a biomarker significantly modifies the effect of a specific therapy

Prognostic Biomarkers Cannot guide the choice of a specific therapy Can place patients into distinct risk categories where different treatment options may be deemed appropriate

Potential Poor Prognostic Factors in Stage II Colon Cancer Bowel perforation Bowel perforation Bowel obstruction Bowel obstruction Tumor adherence/invasion (T 4 ) Tumor adherence/invasion (T 4 ) Lymphatic vessel invasion Lymphatic vessel invasion Venous invasion Venous invasion Poorly differentiated histology Poorly differentiated histology <10-12 lymph nodes examined <10-12 lymph nodes examined

Risk Stratification by Prognostic Markers: INT-0035 Survival at 7 years (%) CovariateObservation5-FU/Levamisole Adhesion to adjacent organs 7082 Invasion to adjacent organs 6486 Obstruction5870 Perforation5167 Moertel et al J Clin Oncol All stage II patients (N = 318) 7272

Use of Prognostic Markers in Stage II: MOSIAC DeGramont et al, ASCO year DFS (%) FOLFOX4LV5FU2HR [95% CI] All Stage II Pts [ ] High-risk Stage II* (N=576) [ ] Low-risk Stage II (N=323) [ ] *One of the following: T4, perforation, obstruction, poorly differentiated, venous invasion, <10 nodes examined.T4, perforation, obstruction, poorly differentiated, venous invasion, <10 nodes examined.

Microsatellite Instability in Colon Cancer Measure of deficient DNA mismatch repair Occurs in 10% to 18% of colon cancers Predicted better prognosis --- but lack of benefit to 5-FU- based adjuvant therapy –Ribic et al. NEJM 2003 –Sargent et al. ASCO 2008

S. Tejpar, F. Bosman, M. Delorenzi, R. Fiocca, P. Yan, D. Klingbiel, D. Dietrich, E. Van Cutsem, R. Labianca, A. Roth Microsatellite instability (MSI) in stage II and III colon cancer treated with 5FU-LV or 5FU-LV and irinotecan (PETACC 3- EORTC SAKK 60/00 trial). Abst. ID: 4001

PETACC 3: MSI in Colon Cancer MSI conferred improved survival – most apparent in stage II vs. III pts (P for interaction = 0.058) Benefit of MSI noted in both treatment arms MSI did not predict a benefit for adding irinotecan All patients received adjuvant chemotherapy  Stage II – MSI-H: cannot assess outcome for surgery alone

18q Loss of Heterozygosity Associated with chromosomal instability, inversely associated with MSI. Long arm of chromosome 18 contains several genes including: DCC, SMAD-4, SMAD-2, CABLES1.

18q LOH in Stage III Colon Cancer (N= 279) Watanabe et al. N Engl J Med. 2001;344: q LOH not associated with survival in stage II patients

. Molecular markers in colon cancer have a stage specific prognostic value. Results of the translational study on the PETACC 3 - EORTC SAKK trial. A. D. Roth, S. Tejpar, P. Yan, R. Fiocca, D. Dietrich, M. Delorenzi, R. Labianca, D. Cunningham, E. Van Cutsem, F. Bosman

18qLOH in PETACC [ ]18qLOH [ ]MSI-H v. MSS [ ]T4 v. T3 18q LOH was not associated with outcome in stage III patients Stage II patients:

Large Studies Assessing 18qLOH in CRC (N>250) Author (Year) No. of Patients Finding Watanabe, HR=2.75 (P=0.006) Halling, Null Barratt, Null Roth, Null Ogino, Null

ECOG 5202: Stage II Colon Cancer RANDOMIZE High-risk: MSS and 18q LOH Low-risk: MSI or No 18q LOH observe FOLFOX + Bevacizumab FOLFOX + Placebo

Studies of 18q LOH Could methodology explain discrepancy between studies?  Individual markers & criteria do differ  However, rates of 18q LOH are similar  18q LOH inversely associated with MSI Do we have the right locus on 18q?  Need to identify specific gene(s) responsible Predictive role for 18q LOH remains uncertain

Multi-gene expression assays to define cancer recurrence and therapy

Paik et al N Eng J Med 351:2817, 2004 Gene Expression and Recurrence in Node-Negative, ER-Positive Breast Cancer 7%14%31%

Paik, S. et al. J Clin Oncol; 24: Gene Expression and Benefit from Chemotherapy in Node- Negative, ER-Positive Breast Cancer P, interaction = 0.038

David Kerr 1, Richard Gray 2, Philip Quirke 3, Drew Watson 4, Greg Yothers 5, Ian Lavery 6, Mark Lee 4, Michael O'Connell 5, Steven Shak 4, Norman Wolmark 5 and the Genomic Health & QUASAR Colon Teams A quantitative multi-gene RT-PCR assay for prediction of recurrence in stage II colon cancer: Selection of the genes in 4 large studies and results of the independent, prospectively-designed QUASAR validation study

Colon Cancer Technical Feasibility Development Studies Surgery Alone NSABP C-01/C-02 (n=270) Cleveland Clinic (n = 765) Selection of Final Gene List & Algorithm Development Studies Surgery + 5FU/LV NSABP C-04 (n=308) NSABP C-06 (n=508) Clinical Validation Study – Stage II Colon Cancer QUASAR (n=1,436) Test Prognosis and Treatment Benefit Development and Validation of a Multi-Gene RT-PCR Colon Cancer Assay Standardization and Validation of Analytical Methods

22% (16%-29%) 18% (13%-24%) 12% ( 9% -16%) Kaplan-Meier Estimates (95% CI) of Recurrence Risk at 3 years QUASAR Results: Recurrence Risk in Pre-specified Recurrence Risk Groups (n=711) Comparison of High vs. Low Recurrence Risk Groups using Cox Model: HR = 1.47 (p=0.046) Years Recurrence Risk Group High Intermediate Low Proportion Event Free Recurrence Risk Group Range of RS Proportion of patients Low<3043.7% Intermediate % High≥4125.6%

Results Recurrence Score significantly associated with DFS, OS Recurrence and Treatment Scores did not predict benefit from FU/LV

Questions How did FU/LV vs. control arms compare within each risk strata? How did Recurrence and Treatment Scores perform in the development dataset? Could heterogeneity between the development and validation datasets affected assay performance in validation? 3-year recurrence ranged from 12% (low risk) to 22% (high risk)  Is assay sufficiently discriminative?