The Prognostic Value of Metabolic Genes in Gastric Adenocarcinoma

Background: A great number of metabolic genes have been discovered in gastric cancer (GC); however, their prognostic roles remain incompletely clear so far. Methods: : The Cancer Genome Atlas-stomach adenocarcinoma, and GSE84437 dataset collected via the Gene Expression Omnibus (GEO) database were utilized for retrieving those clinicopathological data and RNA expression patterns. Besides, the signature was obtained through the lasso Cox regression model and univariate Cox regression analysis. A novel 13-gene metabolic signature (including GSTA2, POLD3, GLA, GGT5, DCK, CKMT2, ASAH1, OPLAH, ME1, ACYP1, NNMT, POLR1A, and RDH12) was constructed for predicting the prognosis for gastric adenocarcinoma. Results: : The results suggested that, the survival in high risk group was remarkably dismal compared with that in low risk group. In addition, that as-constructed signature had been identified as a factor to independently predict the prognosis for gastric adenocarcinoma patients. Moreover, the signature-based nomogram showed certain benefits in predicting the overall survival (OS). Besides, results of gene set enrichment analysis (GSEA) suggested that some pathways were markedly enriched, which help to illustrate the possible mechanisms. Conclusions: : The new 13-gene metabolic model is constructed in this study to predict the prognosis for GC. It probably reflects dysregulation in the metabolic microenvironment, in the meantime of providing metabolic treatment biomarkers, and predicting the treatment response to gastric adenocarcinoma.