Screening of differentially expressed genes for colorectal cancer and prediction of potential traditional Chinese medicine: based on bioinformatics / 中国中药杂志

ABSTRACT

This study screened and analyzed the differentially expressed genes(DEGs) between colorectal cancer(CRC) tissues and normal tissues with bioinformatics techniques to predict biomarkers and Chinese medicinals for the diagnosis and treatment of CRC. The microarray data sets GSE21815, GSE106582, and GSE41657 were downloaded from the Gene Expression Omnibus(GEO), and the DEGs were screened by GEO2 R, followed by the Gene Ontology(GO) tern enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis of the DEGs based on DAVID. The protein-protein interaction network was constructed by STRING, and MCODE and Cytohubba plug-ins were used to screen the significant modules and hub genes in the network. UCSC, cBioPortal, and Oncomine were employed for hierarchical clustering, survival analysis, Oncomine analysis, and correlation analysis of clinical data. Coremine Medical was applied to predict the Chinese medicinals acting on hub genes. A total of 284 DEGs were screened out, with 146 up-regulated and 138 down-regulated. The up-regulated genes were mainly involved in cell cycle, NLRs pathway, and TNF signaling pathway, and the down-regulated genes were related to mineral absorption, nitrogen metabolism, and bicarbonate reabsorption in proximal tubules. The 15 hub genes were CDK1, CDC20, AURKA, MELK, TOP2 A, PTTG1, BUB1, CDCA5, CDC45, TPX2, NEK2, CEP55, CENPN, TRIP13, and GINS2, among which CDK1 and CDC20 were regarded as core genes. The high expression of CDK1 and CDC20 suggested poor prognosis, and they significantly expressed in many cancers, especially breast cancer, lung cancer, and CRC. The expression of CDK1 and CDC20 was correlated with gender, tumor type, TNM stage, and KRAS gene mutation. The potential effective medicinals against CRC were Scutellariae Radix, Scutellariae Barbatae Herba, Arnebiae Radix, etc. The significant expression of CDK1 and CDC20 can help distinguish tumor tissues from normal tissues, and is related to survival prognosis. Thus, the two can be used as biomarkers for the diagnosis and treatment of CRC. This study provides a reference for related drug development.