Abstract

KRAS status serves as a predictive biomarker of response to treatment in metastatic colorectal cancer (mCRC). We hypothesize that complex interactions between multiple pathways contribute to prognostic differences between KRAS wild-type and KRAS mutant patients with mCRC, and aim to identify polymorphisms predictive of clinical outcomes in this subpopulation. Most pathway association studies are limited in assessing gene–gene interactions and are restricted to an individual pathway. In this study, we use a random survival forests (RSF) method for identifying predictive markers of overall survival (OS) and progression-free survival (PFS) in mCRC patients treated with FOLFIRI/bevacizumab. A total of 486 mCRC patients treated with FOLFIRI/bevacizumab from two randomized phase III trials, TRIBE and FIRE-3, were included in the current study. Two RSF approaches were used, namely variable importance and minimal depth. We discovered that Wnt/β-catenin and tumor associated macrophage pathway SNPs are strong predictors of OS and PFS in mCRC patients treated with FOLFIRI/bevacizumab independent of KRAS status, whereas a SNP in the sex-differentiation pathway gene, DMRT1, is strongly predictive of OS and PFS in KRAS mutant mCRC patients. Our results highlight RSF as a useful method for identifying predictive SNPs in multiple pathways.

Highlights

  • Kirsten Ras (KRAS) status serves as a predictive biomarker of response to treatment in metastatic colorectal cancer

  • In this study, we illustrate the utility of random survival forests (RSF) in integrating complex interactions and uncovering polymorphisms in multiple pathways predictive of survival in metastatic colorectal cancer (mCRC) patients based on their KRAS status

  • Published work from our lab using Cox-proportional hazard (CPH) models did not identify significant associations between Wnt pathway single nucleotide polymorphisms (SNPs) and overall survival (OS) or progression-free survival (PFS) in mCRC patients treated with FOLFIRI/bevacizumab in individual clinical ­trials[10,11]

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Summary

Introduction

KRAS status serves as a predictive biomarker of response to treatment in metastatic colorectal cancer (mCRC). Our previous work used genome-wide association studies and Cox-proportional hazard (CPH) models to identify significant differences in predicting survival outcomes in mCRC patients from individual clinical cohorts based on genetic polymorphisms in pathways regulating angiogenesis. In this study, we illustrate the utility of random survival forests (RSF) in integrating complex interactions and uncovering polymorphisms in multiple pathways predictive of survival in mCRC patients based on their KRAS status.

Results
Conclusion
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