Identification of potential biomarkers for colorectal cancer by bioinformatics analysis and analysis of associated survival by Kaplan-Meier curves

Abstract

Abstract Background: Colorectal cancer (CRC) is one of the most common cancers worldwide. A large number of studies have been carried out to elucidate its pathogenesis, but the pathogenesis and molecular mechanisms of CRC remain unclear. Due to the poor clinical outcomes, it is indispensable to investigate novel biomarkers for the diagnosis and prognosis of CRC.Objective: The aim of this study is to explore key genes as potential biomarkers for the diagnosis and prognosis of CRC for clinical utility.Methods: In order to identify and screen candidate genes in CRC carcinogenesis and disease progression, we downloaded microarray datasets GSE89076, GSE73360, GSE32323 from the GEO database, identified differentially expressed genes (DEGs), and performed functional enrichment analysis. A protein-protein interaction network (PPI) was constructed, and correlated module analysis was performed using STRING and Cytoscape. Results: 329 DEGs were identified, including 264 up-regulated genes and 65 down-regulated genes. DEGs' rich functions and pathways include the mitotic cell cycle, DNA damage and replication, chromosome correction, replication fork formation, protein recruitment, and meiosis-related processes. 47 Hub genes were identified, and biological process analysis showed that these genes were mainly enriched in the re-cell division, and during the cell cycle, survival analysis showed that CDK1, PCNA and CCNB1 might be involved in CRC carcinogenesis invasion and recurrence. Conclusion: The hub genes identified in this study contribute to our understanding of the molecular and pathogenic mechanisms of CRC carcinogenesis and progression and provide possible candidate targets for the diagnosis and treatment of CRC.