Objective: To search for potential biomarkers and available medicines for gastric adenocarcinoma.
Study design: Experimental study. Place and Duration of the Study: Scientific Research Section, Shenzhen Longhua District Central Hospital, Shenzhen, China, from January to April 2023.
Methodology: Datasets were retrieved from the Gene Expression Omnibus (GEO). Differential gene expression analysis between gastric adenocarcinoma and normal samples was conducted using GEO2R. Subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed via the Enrichr website. Protein-protein interaction (PPI) networks were established using the STRING website. The central hub genes were identified using the cytoHubba plugin integrated within Cytoscape. Finally, the GEPIA2 and QuartataWeb websites were employed to validate the expression levels of the hub genes and to identify potential medicines for gastric adenocarcinoma.
Results: In total, 133 DEGs were identified. GO analysis revealed that these DEGs predominantly participate in processes such as cell adhesion, positive regulation of cell proliferation, and extracellular matrix organisation. In the KEGG pathways, DEGs were significantly enriched in gastric acid secretion, protein digestion and absorption, and ECM-receptor interaction. Following the construction of the PPI network, 10 central hub genes were identified and validated using GEPIA2. Notably, among these hub genes, SERPINE1 demonstrated a significant association with the prognosis of gastric adenocarcinoma, and potential therapeutic agents were subsequently predicted.
Conclusion: SERPINE1 and potential therapeutic agents hold promise to enhance personalised diagnosis and treatment for gastric adenocarcinoma patients in the future.
Key words: Biomarkers, Gastric adenocarcinoma, Bioinformatics, Differentially Expressed Genes (DEGs).