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

Abstract

Stomach adenocarcinoma is a major contributor to worldwide mortality and poses a substantial challenge to improving life expectancy. The main objective of the current work was to identify diagnostic and prognostic biomarkers in stomach adenocarcinoma in order to advance translational medicine and patient outcomes. By accomplishing this objective, the research seeks to provide significant insights into the field of translational medicine. Seven novel unfavourable prognosis-associated genes (NALCN, CALCR, CPT1C, ELAVL3, FLJ16779, MYOZ3, and TPST1) were first identified. Additionally, 41 potential miRNAs were predicted. ELAVL3-hsa-mir-29a-3p and CALCR-hsa-mir-29a-3p axes were identified as two critical pathways in the carcinogenesis of stomach adenocarcinoma via a bioinformatics analysis. Following that, lncRNAs binding to hsa-mir-29a-3p were predicted via starBase and miRNet databases for predicting lncRNA binding sites. After conducting both expression and survival analyses for these predicted lncRNAs, we found that only one lncRNA (KCNQ1OT1) was markedly overexpressed in stomach adenocarcinoma, and its elevated expression was associated with an unfavourable prognosis. Next, we established a comprehensive mRNA-miRNA-lncRNA triple ceRNA network linked to the prognosis of patients with stomach adenocarcinoma. In summary, the current study provides an extensive ceRNA network that highlights novel diagnostic and prognostic biomarkers for stomach adenocarcinoma.