Identification Of Key Genes In Pancreatic Cancer Using Bioinformatics Analysis

Objective: The bioinformatics method was used to find the differentially expressed genes in pancreatic cancer,analyze the biological role of differentially expressed genes in pancreatic cancer,and explore the relationship between differentially expressed genes and the prognosis of pancreatic cancer.Methods: Using the data in the GEO database subset finding genetic differences.Biological analysis of differential genes was performed using DAVID database.The STRING database was used for protein interaction analysis,and Cytoscape software was used to identify the most important modules in the protein interaction network,and the key genes were screened out for DAVID analysis.The survival of key genes was analyzed using the clinical data of tumor patients in the cBioPortal database.Meanwhile,the Oncomine database was used to verify the expression of key genes and analyze the relationship between key genes and tumor classification,staging,molecular markers and drug sensitivity.Result: In the present study,to identify the candidate genes that play a role in the carcinogenesis and progression of PC,microarray datasets GSE28735,GSE15471,and GSE62452 were downloaded from the Gene Expression Omnibus(GEO)database.Initially,a total of 219 differentially expressed genes(DEGs)were identified in the three GEO datasets,which included 161 upregulated and 58 downregulated DEGs.The function and pathway of these genes were determined by enrichment analysis.The results showed that DEGs were involved in cell adhesion,extracellular matrix organization,proteolysis,calcium ion binding,serine-type endopeptidase activity,extracellular exosome,plasma membrane,extracellular region,and extracellular space.Furthermore,a protein-protein interaction network was constructed,and the 219 DEGs were filtered into the network.Ten hub genes were identified in the network.The most significant modules were selected for the function and pathway analysis.Survival analysis showed that FN1 and POSTN may be involved in the carcinogenesis or invasion of PC.In conclusion,DEGs and hub genes identified in the present study can serve as candidate targets for the prognosis and treatment of PC.Conclusion: A total of 219 DEGs and 10 hub genes were identified.Furthermore,high expression of FN1 and POSTN may be a predictor of poor survival.These key genes may open up new possibilities for the detection and treatment of PC.