ArticleMolecular carcinogenesis2019
Genetic variants in glutamine metabolic pathway genes predict cutaneous melanoma-specific survival.
Article in Molecular carcinogenesis, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Identification and evaluation of glutamine-related gene characteristics based on multi-omics to predict the prognosis of patients with colorectal cancer.Journal of translational medicine · 2026Article
- Identification of key genes related to glutamine metabolism in diabetic nephropathy by machine learning methods.Scientific reports · 2025Article
- A metabolic perspective on nitric oxide function in melanoma.Biochimica et biophysica acta. Reviews on cancer · 2024Review
- 17β‑estradiol‑induced mitochondrial dysfunction and Warburg effect in cervical cancer cells allow cell survival under metabolic stress.International journal of oncology · 2020Article
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Authors and funding
9 authors at 5 institutions in 2 countries.
Funding
Abstract
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
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