Bioinformatics and pathway enrichment analysis identified hub genes and potential biomarker for gastric cancer prognosis - Darang, Elham; Pezeshkian, Zahra; Mirhoseini, Seyed Ziaeddin; Ghovvati, Shahrokh (Frontiers in Oncology, 2023)
Gastric cancer is one of the most common cancers in the world. This study aimed to identify genes, biomarkers, and metabolic pathways affecting gastric cancer using bioinformatic analysis and meta-analysis. Datasets containing gene expression profiles of tumour lesions and adjacent non-tumour mucosa samples were downloaded. Common differentially expressed genes between datasets were selected to identify hub genes and further analysis. Gene Expression Profiling and Interactive Analyses (GEPIA) and the Kaplan-Meier method were used to further validate the expression level of genes and plot the overall survival curve, respectively. KEGG pathway analysis showed that the most important pathway was enriched in ECM-receptor interaction. Hub genes including COL1A2, FN1, BGN, THBS2, COL5A2, COL6A3, SPARC and COL12A1 were identified. The top interactive miRNAs including miR-29a-3p, miR-101-3p, miR-183-5p, and miR-15a-5p targeted the most hub genes. The survival chart showed an increase in mortality in patients with gastric cancer, which shows the importance of the role of these genes in the development of the disease and can be considered candidate genes in the prevention and early diagnosis of gastric cancer.