Genetic variants in glutamine metabolic pathway genes predict cutaneous melanoma-specific survival.

Glutamine dependence is a unique metabolic defect seen in cutaneous melanoma (CM), directly influencing the treatment and prognosis. Here, we investigated the associations between 6025 common single-nucleotide polymorphisms (SNPs) in 77 glutamine metabolic pathway genes with CM-specific survival (CMSS) using genotyping datasets from two published genome-wide association studies (GWASs). In the single-locus analysis, 76 SNPs were found to be significantly associated with CMSS (P < .050, false-positive report probability < 0.2 and Bayesian false discovery probability < 0.8) in the discovery dataset, of which seven SNPs were replicated in the validation dataset and three SNPs (HAL rs17676826T > C, LGSN rs12663017T > A, and NOXRED1 rs8012548A > G) independently predicted CMSS, with an effect-allele attributed adjusted hazards ratio of 1.52 (95% confidence interval = 1.19-1.93) and P < .001, 0.68 (0.54-0.87) and P = .002 and 0.62 (0.46-0.83) and P = .002, respectively. The model including the number of unfavorable genotypes (NUGs) of these three SNPs and covariates improved the five-year CMSS prediction (P = .012) than the one with other covariates only. Further expression quantitative trait loci (eQTL) analysis found that the LGSN rs12663017 A allele was significantly associated with increased messenger RNA (mRNA) expression levels (P = 8.89 × 10 -11 ) in lymphoblastoid cell lines of the 1000 Genomes Project database. In the analysis of the genotype tissue expression (GTEx) project datasets, HAL rs17676826 C and NOXRED1 rs8012548 G alleles were significantly associated with their mRNA expression levels in sun-exposed skin of the lower leg (P = 6.62 × 10-6 and 1.37 × 10-7 , respectively) and in sun-not-exposed suprapubic skin (P < .001 and 1.43 × 10-8 , respectively). Taken together, these genetic variants of glutamine-metabolic pathway genes may be promising predictors of survival in patients with CM.

Duke Scholars

Author Qingyi Wei Population Health Sciences