Identification of a candidate single-nucleotide polymorphism related to chemotherapeutic response through a combination of knowledge-based algorithm and hypothesis-free genomic data

Inter-individual variations in drug responses among patients are known to cause serious problems in medicine. Genome-wide association study (GWAS) is powerful for examining single-nucleotide polymorphisms (SNPs) and their relationships with drug response variations. However, no significant SNP has been identified using GWAS due to multiple testing problems. Therefore, we propose a combination method consisting of knowledge-based algorithm, two stages of screening, and permutation test for identifying SNPs in the present study. We applied this method to a genome-wide pharmacogenomics study for which 109,365 SNPs had been genotyped using Illumina Human-1 BeadChip for 119 gastric cancer patients treated with fluoropyrimidine. We identified rs2293347 in epidermal growth factor receptor (EGFR) is as a candidate SNP related to chemotherapeutic response. The p value for the rs2293347 was 2.19 × 10−5 for Fisher's exact test, and the p value was 0.00360 for the permutation test (multiple testing problems are corrected). Additionally, rs2293347 was clearly superior to clinical parameters and showed a sensitivity value of 55.0% and specificity value of 94.4% in the evaluation by using multiple regression models. Recent studies have shown that combination chemotherapy of fluoropyrimidine and EGFR-targeting agents is effective for gastric cancer patients highly expressing EGFR. These results suggest that rs2293347 is a potential predictive factor for selecting chemotherapies, such as fluoropyrimidine alone or combination chemotherapies.