Impact of polymorphisms within genes involved in regulating DNA methylation in patients with metastatic colorectal cancer enrolled in three independent, randomised, open-label clinical trials: a meta-analysis from TRIBE, MAVERICC and FIRE-3

Background: CpG island DNA hypermethylation and global DNA hypomethylation are hallmark characteristics of colorectal cancer (CRC). Therefore, we aim to explore the effect of genetic variations within the genes that regulate the DNA methylation and demethylation pathways on outcomes in patients with metastatic CRC (mCRC) treated with first-line therapy and enrolled in three independent, randomised, open-label clinical trials. Methods: A total of 884 patients with mCRC enrolled in TRIBE, MAVERICC and FIRE-3 trials were included. Single-nucleotide polymorphisms (SNPs) within genes involved in DNA methylation and demethylation pathways were analysed. The prognostic value of each SNP across all treatment arms was quantified using the inverse-variance-weighted effect size, a meta-analysis approach implemented in the METASOFT software. Results: In the meta-analysis, DNMT3A rs11681717 was significantly associated with overall survival (hazard ratio = 1.26; 95% confidence interval [CI] 1.08-1.46; P = 0.002; false discovery rate [FDR] = 0.016), accounting for seven tests in the DNA methylation pathway. In addition, there was suggestive evidence of association for ten-eleven translocation (TET) genes variance with tumour response (TET1 rs3814177, odds ratio [OR] = 0.76, 95% CI 0.59-0.97, P = 0.025, FDR = 0.087; TET3 rs7560668, OR = 1.44; 95% CI 1.10-1.89; P = 0.009; FDR = 0.062). Conclusions: We showed that polymorphisms within the genes responsible for the DNA methylation and demethylation machineries are correlated with outcomes in patients with mCRC who were enrolled in three independent, randomised, open-label, phase II/III clinical trials. In addition, we demonstrated the feasibility of a meta-analysis approach to identify stronger and more convincing association between gene polymorphisms and outcome, potentially leading the way to a new method of analysis for similar data set. (C) 2019 Elsevier Ltd. All rights reserved.