Background: Worldwide, gastric cancer (GC) is a common lethal solid malignancy with a poor prognosis. Cuproptosis is a novel type of cell death mediated by protein lipoylation and may be related to GC prognosis.
Aim: To offer new insights to predict GC prognosis and provide multiple therapeutic targets related to cuproptosis-related genes (CRGs) for future therapy.
Methods: We collected data from several public data portals, systematically estimated the expression level and prognostic values of CRGs in GC samples, and investigated related mechanisms using public databases and bioinformatics.
Results: Our results revealed that FDX1, LIAS, and MTF1 were differentially expressed in GC samples and exhibited important prognostic significance in The Cancer Genome Atlas (TCGA) cohort. We constructed a nomogram model for overall survival and disease-specific survival prediction and validated it via calibration plots. Mecha-nistically, immune cell infiltration and DNA methylation prominently affected the survival time of GC patients. Moreover, protein-protein interaction network, KEGG pathway and gene ontology enrichment analyses demonstrated that FDX1, LIAS, MTF1 and related proteins play key roles in the tricarboxylic acid cycle and cuproptosis. Gene Expression Omnibus database validation showed that the expression levels of FDX1, LIAS, and MTF1 were consistent with those in the TCGA cohort. Top 10 perturbagens has been filtered by Connectivity Map.
Conclusion: In conclusion, FDX1, LIAS, and MTF1 could serve as potential prognostic biomarkers for GC patients and provide novel targets for immunotarget therapy.
Keywords: Bioinformatics; Biomarker; Cuproptosis; Gastric cancer; Nomogram; Prognosis.
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