Background

1. Validation of four gene-expression risk scores in a large colon cancer cohort and contribution to an improved prognostic methodAntonio F. Di Narzo1, Sabine Tejpar3, Simona Rossi1, Pu Yan5, Vlad Popovici1, Pratyaksha Wirapati1, Eva Budinska1, Tao Xie6, Heather Estrella6, Adam Pavlicek6, Mao Mao6, Eric Martin6, Weinrich Scott6, Graeme Hodgson6, Eric Van Cutsem3, Fred Bosman5,Arnaud Roth4,7, Mauro Delorenzi1,21) Swiss Institute of Bioinformatics, Lausanne, Switzerland; 2) Département de formation et recherche, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland; 3) Digestive Oncology Unit and Center for Human Genetics, University Hospital Gasthuisberg, Leuven, Belgium; 4) Oncosurgery, Geneva University Hospital Geneva, Switzerland;5) Department of Pathology, Lausanne University, Lausanne, Switzerland; 6) Pfizer Inc., Worldwide Research and Development, Oncology Research Unit, 10777 Science Center Drive, La Jolla, CA 92121; 7) Swiss Group for Clinical Cancer Research (SAKK).

2. Background • Prognosis prediction for resected primary colon cancer is currently based on the tumor, nodes, metastasis (TNM) staging system • Different laboratories studied gene expression profiles and proposed distinct risk scoring systems • Each single scoring system has been internally validated. But how do they compare? Are them equivalent? • Four, well documented scoring systems were selected and tested on the PETACC-3 series

3. Aim • Assess the performance of the 4 scoring systems for: • Overall Survival (OS) • Relapse Free Survival (RFS) • Survival After Relapse (SAR) • Check agreement among them • Is there space for improvement in biomarker development?

4. Patients: the PETACC-3 trial N = 688 samples with gene expression microarray data Van Cutsem et al., 2009

5. The selected scoring systems

6. There is little overlap in thegenes lists

7. Results: Overall Survival The Combined Score is obtained as a geometric average of the rankings of the four scoring systems All HRs are relative to 1 Interquartile Range Variation of the risk score. Multivariate Cox model includes: Age, Gender, T-stage, N-stage, Grade, Location, Treatment Arm, Lymphovascular Invasion, Microsatellite Instability

8. Results:Relapse-Free Survival The Combined Score is obtained as a geometric average of the rankings of the four scoring systems All HRs are relative to 1 Interquartile Range Variation of the risk score. Multivariate Cox model includes: Age, Gender, T-stage, N-stage, Grade, Location, Treatment Arm, Lymphovascular Invasion, Microsatellite Instability

9. Results:Survival After Relapse The Combined Score is obtained as a geometric average of the rankings of the four scoring systems All HRs are relative to 1 Interquartile Range Variation of the risk score. Multivariate Cox model includes: Age, Gender, T-stage, N-stage, Grade, Location, Treatment Arm, Lymphovascular Invasion, Microsatellite Instability

10. There is weak agreement in the predictions of the four risk scoring systems The percentage of patients with the same predicted outcome according to 2 distinctscoring systems is rather smallThe VDS scoring systems is anti-correlated with GHS and MDA, and almost uncorrelated with ALM.

11. Conclusions • These four scoring systems are based on different gene populations with little overlap • These four scoring system have, in our hands, a confirmed prognostic value for OS but concur poorly on a per patient basis • There is a high variability in prognostic values depending on the endpoint  (OS, RFS, SAR) • A combined score based on these four scoring systems seems to lead to an improved prognosis prediction compared to each system separately