Screening and verification of key genes for colon cancer based on GEO database

doi:10.16352/j.issn.1001-6325.2023.11.1685

Abstract

Abstract: Objective To screen the potential key genes associated with colon cancer(CC) by bioinformatics analysis based on Gene Expression Omnibus (GEO) database, and verify them through in vitro experiments to explore potential colon cancer molecular markers. Methods The human CC data sets GSE10950 and GSE74602 were obtained from GEO database. The differentially expressed genes (DEGs) in colon cancer and adjacent tissues were screened by GEO2R tool and Venn diagram software. DEGs were used to perform by Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The Protein-Protein Interaction (PPI) network of DEGs was constructed by STRING database, then the key genes were screened with Cytoscape software. GEPIA database was used to validate expression and prognostic value of key genes. Finally, the functions of key genes were further verified by cell transfection and CCK8 assays. Results 515 DEGs were obtained from two datasets, of which 223 were up-regulated and 292 were down-regulated. GO enrichment analysis showed that up-regulated DEGs were mainly involved in negative regulation of cell cycle, transcriptional control. KEGG signaling pathways analysis showed that up-regulated DEGs were mainly enriched in cell cycle signaling pathways. A total of 33 hub genes were screened through the PPI. UCLCAN analysis was implemented and 7 of 33 genes were relative to lower survival rate of CC patients. The expression levels of 7 genes by GEPIA analysis (P＜0.05).It was verified by GEPIA database that CCNB1,CCNA2,CDC20,CDKN3,DLGAP5,HMMR and NCAPG were highly expressed in colon cancer tissues. KEGG pathway enrichment and found that three critical genes (CCNB1, CDC20 and CCNA2) enriched in cell cycle pathway. The inhibition of CCNB1,CDC20 or CCNA2 significantly promoted proliferation of colon cancer cells. Conclusions A total of 7 key genes were identified to be involved in the occurrence of CC. The expression of CCNB1,CDC20 and CCNA2 is potentially related to the poor prognosis in CC, which may be potential targets of clinical treatment and prognostic markers for CC patients.

Key words: colon cancer, bioinformatics analysis, differentially expressed genes, protein-protein interaction network

CLC Number:

R735.7

YAN Wen, LI Nan, GU Tongnan, KONG Xiangzhao. Screening and verification of key genes for colon cancer based on GEO database[J]. Basic & Clinical Medicine, 2023, 43(11): 1685-1692.

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