Identification of target genes and prognostic evaluation for colorectal cancer using integrated bioinformatics analysis

Abstract

The underlying molecular mechanisms of colorectal cancer (CRC) has attracted great attention from the scholarly community. The aim of our study is to identify pivotal genes related to the pathogenesis and prognosis of CRC. We integrated five microarray datasets from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were analyzed with the limma package. DAVID and OmicShare tools were used for Gene Ontology (GO) and KEGG enrichment analysis. The protein–protein interaction (PPI) network of DEGs was constructed. The prognostic analysis of hub genes was performed through Kaplan Meier-plotter. Finally, potential drugs were predicted in the CMap database. Through five microarray datasets, a total of 90 DEGs were detected including 54 up-regulated and 36 down-regulated genes. Biological process analysis showed DEGs were mainly enriched in positive regulation of neutrophil chemotaxis, chemokine-mediated signaling pathway, and bicarbonate transport. Signaling pathway analysis indicated that DEGs played a vital in proximal tubule bicarbonate reclamation, cell cycle and progesterone-mediated oocyte maturation. The GEPIA database confirmed that overexpression levels of hub genes were significantly associated with better survival of patients. Finally, the 20 most significant small molecules were obtained based on the CMap database. Our study has identified novel candidate biomarkers, pathways, and kinases associated with CRC prognosis.

Keywords

• bioinformatics analysis
• colorectal cancer
• candidate small molecules
• differentially expressed genes
• hub genes