Genetic variants in RUNX3, AMD1 and MSRA in the methionine metabolic pathway and survival in nonsmall cell lung cancer patients.

Abnormal methionine dependence in cancer cells has led to methionine restriction as a potential therapeutic strategy. We hypothesized that genetic variants involved in methionine-metabolic genes are associated with survival in nonsmall cell lung cancer (NSCLC) patients. Therefore, we investigated associations of 16,378 common single-nucleotide polymorphisms (SNPs) in 97 methionine-metabolic pathway genes with overall survival (OS) in NSCLC patients using genotyping data from two published genome-wide association study (GWAS) datasets. In the single-locus analysis, 1,005 SNPs were significantly associated with NSCLC OS (p < 0.05 and false-positive report probability < 0.2) in the discovery dataset. Three SNPs (RUNX3 rs7553295 G > T, AMD1 rs1279590 G > A and MSRA rs73534533 C > A) were replicated in the validation dataset, and their meta-analysis showed an adjusted hazards ratio [HR] of 0.82 [95% confidence interval (CI) =0.75-0.89] and pmeta  = 2.86 × 10-6 , 0.81 (0.73-0.91) and pmeta  = 4.63 × 10-4 , and 0.77 (0.68-0.89) and pmeta  = 2.07 × 10-4 , respectively). A genetic score of protective genotypes of these three SNPs revealed an increased OS in a dose-response manner (ptrend  < 0.0001). Further expression quantitative trait loci (eQTL) analysis showed significant associations between these genotypes and mRNA expression levels. Moreover, differential expression analysis further supported a tumor-suppressive effect of MSRA, with lower mRNA levels in both lung squamous carcinoma and adenocarcinoma (p < 0.0001 and < 0.0001, respectively) than in adjacent normal tissues. Additionally, low mutation rates of these three genes indicated the critical roles of these functional SNPs in cancer progression. Taken together, these genetic variants of methionine-metabolic pathway genes may be promising predictors of survival in NSCLC patients.

Duke Scholars

Author Sheng Luo Biostatistics & Bioinformatics, Division of Biostatistics

Author Patricia Gripka Moorman Family Medicine and Community Health, Prevention Research

Author Qingyi Wei Population Health Sciences