A Bioinformatics-Driven ceRNA Network in Stomach Adenocarcinoma: Identification of Novel Prognostic mRNA-miRNA-lncRNA Interactions

Background: Stomach adenocarcinoma is a major contributor to worldwide mortality and significantly impacts life expectancy. The main objective of the current study was to identify a prognostic biomarker for stomach adenocarcinoma to advance translational medicine and improve patient outcomes. Method: various databases (GEPIA, UALCAN, miRNet, StarBase, and Kaplan Meier plotter) bioinformatics tools (cytoscape) and were used in this study. Results: Ten novel unfavorable prognosis-associated genes were identified. In addition, 41 potential miRNAs were predicted. ELAVL3-hsa-mir-29a-3p and CALCR-hsa-mir-29a-3p were identified as the two critical networks in the oncogenesis of stomach adenocarcinoma via bioinformatics analysis. Subsequently, the binding of lncRNAs to hsa-mir-29a-3p was predicted utilizing the starBase and miRNet databases. Following the execution of both expression and survival analyses for the predicted lncRNAs, it was determined that only one lncRNA, KCNQ1OT1, exhibited significant overexpression in stomach adenocarcinoma, and its elevated expression was associated with an unfavorable prognosis. Subsequently, we constructed a triple ceRNA network involving mRNA, miRNA, and lncRNA, which is associated with the prognosis of stomach adenocarcinoma. Conclusions: In summary, the current study provides an extensive ceRNA network that highlights novel prognostic biomarkers for stomach adenocarcinoma.