Gastric cancer (GC) is one of the most commonly occurring cancers, and metabolism-related genes (MRGs) are associated with its development. Transcriptome data and the relevant clinical data were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases, and we identified 194 MRGs differentially expressed between GC and adjacent nontumor tissues. Through univariate Cox and lasso regression analyses we identified 13 potential prognostic differentially expressed MRGs (PDEMRGs). These PDEMRGs (CKMT2, ME1, GSTA2, ASAH1, GGT5, RDH12, NNMT, POLR1A, ACYP1, GLA, OPLAH, DCK, and POLD3) were used to build a Cox regression risk model to predict the prognosis of GC patients. Further univariate and multivariate Cox regression analyses showed that this model could serve as an independent prognostic parameter. Gene Set Enrichment Analysis showed significant enrichment pathways that could potentially contribute to pathogenesis. This model also revealed the probability of genetic alterations of PDEMRGs. We have thus identified a valuable metabolic model for predicting the prognosis of GC patients. The PDEMRGs in this model reflect the dysregulated metabolic microenvironment of GC and provide useful noninvasive biomarkers.
Aim: To explore the mechanism of gastric carcinogenesis by mining potential hub genes and to search for promising small-molecular compounds for gastric cancer (GC). Materials & methods: The microarray datasets were downloaded from Gene Expression Omnibus database and the genes and compounds were analyzed by bioinformatics-related tools and software. Results: Six hub genes ( MKI67, PLK1, COL1A1, TPX2, COL1A2 and SPP1) related to the prognosis of GC were confirmed to be upregulated in GC and their high expression was correlated with poor overall survival rate in GC patients. In addition, eight candidate compounds with potential anti-GC activity were identified, among which resveratrol was closely correlated with six hub genes. Conclusion: Six hub genes identified in the present study may contribute to a more comprehensive understanding of the mechanism of gastric carcinogenesis and the predicted potential of resveratrol may provide valuable clues for the future development of targeted anti-GC inhibitors.
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