long noncoding rna magi2-as3 in the tumorigenesis of stomach adenocarcinoma

Background: gastric cancer is among the most prevalent and fatal malignancies worldwide. although radical surgical resection, radiotherapy, and chemotherapy are standard treatment strategies, the accurate diagnosis and effective management of gastric cancer remain challenging. therefore, identifying reliable biomarkers is of great importance. increasing evidence has highlighted the critical role of long noncoding rnas (lncrnas) in the pathogenesis of gastric cancer. in this study, we explored interactions among lncrnas, mirnas, and mrnas using the cancer genome atlas (tcga) data and identified novel candidate biomarkers with significant diagnostic and prognostic potential.materials and methods: rnaseq, mirnaseq, and corresponding clinical data were obtained from the tcga database. differential expression analysis was performed using the limma package in r. a competing endogenous rna (cerna) network was constructed based on the star database. gene ontology (go) and kyoto encyclopedia of genes and genomes (kegg) pathway analyses were conducted to explore functional enrichment. the diagnostic and prognostic significance of candidate biomarkers was evaluated using the kaplan–meier survival analysis with the log-rank test and receiver operating characteristic (roc) curve analysis.results: differential expression analysis identified 2127 differentially expressed mrnas in gastric cancer, of which 935 were upregulated, and 1192 were downregulated. go and kegg pathway analyses revealed that these mrnas were significantly enriched in key biological processes and cancer-related signaling pathways. construction of the cerna network demonstrated that the lncrna magi2as3 plays a pivotal role in gastric cancer initiation and progression. moreover, survival and roc analyses indicated that magi2as3 has strong potential as a diagnostic and prognostic biomarker for patients with gastric cancer.conclusion: in summary, this study elucidates the interactions among lncrnas, mirnas, and mrnas and identifies regulatory networks that may serve as promising therapeutic targets and biomarkers in gastric cancer.