Identification of Key Biomarkers in Pancreatic Cancer Via Bioinformatic Analysis
Given that pancreatic cancer(PC)has insidious clinical symptoms and is difficult to diagnose and treat,this study aimed to identify differentially expressed genes(DEGs)that may be involved in the occur-rence or development of PC using bioinformatics technology to provide theoretical support for the early di-agnosis and prevention of this disease.Three PC-related mRNA microarray datasets(GSE41368,GSE91035,GSE43795)were downloaded from the GEO database,and DEGs were screened by GEO2R with adjusted P value＜0.05 and|log2 fold change|＞1.5.GO and KEGG pathway enrichment analyses,construction of protein-protein interaction network and modular analysis were performed for DEGs.The hub genes were identified using Cytoscape's MCODE plugin,and survival analysis was performed.In addi-tion,component expression and oncomine analyses of hub genes of interest were performed in different da-tabases to explore and validate the relationship between gene expression and disease.A total of 236 DEGs were identified and revealed the biological functions and processes involved.20 genes were identified as hub genes.Survival analysis showed that PC patients with high expression of PSAT1,CYB5A,GMNN,DDX60,CCL20,ALB,PDIA2 and low expression of F8 had poorer overall survival,and PC patients with high expression of CTRC,CLPS,DDX60,CCL20,SYCN,CELA2A,PNLIPRP1 and CELA2B had worse relapse free survival.Analysis of the differential expression of DDX60 and CCL20 between cancerous and normal tissues showed significant correlations in both overall and relapse free survival analyses,suggesting that they may play an important role in the development or progression of PC.The identified DEGs and hub genes in this study may provide insight into the molecular mechanisms of PC,which could be useful for early diagnosis and treatment of PC.
万方数据
维普
