Random survival forests identify pathways with polymorphisms predictive of survival in KRAS mutant and KRAS wild-type metastatic colorectal cancer patients

• Main Authors: Madiha Naseem, Shu Cao, Dongyun Yang, Joshua Millstein, Alberto Puccini, Fotios Loupakis, Sebastian Stintzing, Chiara Cremolini, Ryuma Tokunaga, Francesca Battaglin, Shivani Soni, Martin D. Berger, Afsaneh Barzi, Wu Zhang, Alfredo Falcone, Volker Heinemann, Heinz-Josef Lenz
• Format: Article
• Language: English
• Published: Nature Publishing Group 2021-06-01
• Series: Scientific Reports
• Online Access: https://doi.org/10.1038/s41598-021-91330-z

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.