Identification of Key Biomarkers Associated with Survival and Prognosis in Colon Adenocarcinoma
Abstract Background: Colorectal cancer (CRC) has a high rate of relapse and recurrence that result in poor prognosis and unsatisfactory outcomes. Colon adenocarcinoma (COAD) is the most prevalent type of CRC. It is crucial to identify novel molecular biomarkers for the early diagnosis, prognosis evaluation and disease monitoring of COAD.Methods: Three gene expression profile data were downloaded from the Gene Expression Omnibus(GEO), and the differential expression genes(DEGs) were identified by GEO2R. Gene Ontology (GO) and KEGG pathway enrichment analysis were conducted by WebGestalt online tool. String database and Cytoscape software were used for protein–protein interaction (PPI) network construction and module analysis. The top 20 Hub Genes were screened from the PPI network using MCC algorithm on CytoHubba app of Cytoscape software, and were verified by ONCOMINE database then. The core genes affecting CRC prognosis were screened by GEPIA2 survival analysis web tool. Finally, the expression level and clinical indicators including core genes was analyzed by TCGA-COAD dataset.Results: In total, 413 differentially expressed genes (DEGs) were identified, and the GO and KEGG enrichment analyses of DEGs were processed. After, the protein–protein interaction (PPI) network was constructed and 20 hub genes were identified. Furthermore, three core genes were selected via survival analysis . Finally, the diagnostic and prognostic value of these core genes was verified by clinical analysis of TCGA-COAD dataset.Conclusion: SPP1, GRP and GNGT1 were all over-expressed in COAD, and may be regarded as novel diagnostic and prognostic biomarkers for COAD.