Bioinformatics identification of key genes associated with the prognosis of gastric cancer - LIU Zhao, LIU Rui, FAN Haijing, SUN Hui, LYU Jing, ZHANG Zhen (精准医学杂志)
Objective To screen and identify key genes and pathways associated with the prognosis of gastric cancer, and to investigate the mechanisms of the development and progression of gastric cancer. Methods Microarray datasets (GSE2685, GSE29272) of gastric cancer gene expression profile were downloaded from the gene expression omnibus, and the online analytical tool GEO2R was used to screen for differentially expressed genes (DEGs) between gastric cancer tissue and normal tissue. The Database for Annotation, Visualization, and Integrated Discovery was used for functional enrichment analysis. The Search Tool for the Retrieval of Interacting Genes and Cytoscape software were used to analyze the interaction network of the proteins encoded by the DEGs. The online survival analysis database (KM-plotter) was used to investigate the association between core candidate genes and the prognosis of gastric cancer patients. Immunohistochemical staining was used to verify the expression of candidate genes in gastric cancer tissue and analyze their association with the clinicopathological parameters and prognosis of gastric cancer. The Cox proportional hazards regression model was used to analyze the influencing factors for the overall survival of patients. Results Database screening obtained five DEGs that were associated with tumor staging and prognosis, i.e., COL1A1, COL1A2, COL3A1, COL5A1, and TFF2, and immunohistochemical staining showed that the expression level of COL3A1 was associated with tumor differentiation and staging, vascular tumor thrombus, lymph node metastasis, and vascular invasion (χ2=5.480-13.830,P<0.05). The increase in the expression of COL3A1 in gastric cancer tissue was significantly associated with the prognosis (overall survival rate) of gastric cancer patients (P<0.05). The univariate analysis showed that vascular tumor thrombus, the degree of pathological differentiation, staging, and the expression level of COL3A1 were significantly associated with the overall survival rate of patients (P<0.05). The indicators with statistical significance in the univariate analysis were included in the multiva-riate analysis, and the results showed that the high expression of COL3A1 was significantly associated with the overall survival rate of patients (P<0.05). Conclusion COL3A1 can serve as a potential biomarker for diagnosis and prognosis of gastric cancer.