Bioinformatics analysis and validation of key genes in the pathogenesis and prognosis of hepatocellular carcinoma

Abstract

Abstract: Objective: To screen the key genes of hepatocellular carcinoma (HCC) and verify the prognostic genes of the key genes by bioinformatics.
Method: GSE112790 and GSE101685 data sets were downloaded from Gene Expression Omnibus (GEO) database to screen common differentially expressed genes in HCC tissues and paracancerous tissues. The biological processes and related signaling pathways of the differentially expressed genes (DEGs) were analyzed by gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Ten key genes were screened from the protein-protein interaction network constructed by DEGs through Cytoscape software, which were screened and verified involved in prognosis.
Result: A total of 344 DEGs were screened out in the two data sets, among which 104 were up-regulated and 240 were down-regulated. GO enrichment analysis showed that differentially expressed genes were mainly concentrated in cell cycle process, mitotic cell cycle process, organic acid metabolism process, carboxylic acid metabolism process and oxalic acid metabolism process. KEGG enrichment analysis showed that the differentially expressed genes were mainly concentrated in metabolism of xenobiotics by cytochrome P450, p53 signaling pathway, drug metabolism-cytochrome P450, metabolic pathways, linoleic acid metabolic pathway, CDK1, CCNB1, CCNA2, CCNB2, MAD2L1, AURKA, TTK, CDC20, NDC80 and BIRC5 may play a role in the development and progression of HCC. After tissue specimen verification, the mRNA expression levels of CDK1 and MAD2L1 in HCC tissues were higher than those in adjacent tissues, and the differences were statistically significant (P<0.001). Results of survival analysis showed that the survival time of CDK1 low expression group was significantly longer than that of the high expression group (P=0.030), and MAD2L1 was not correlated with the prognosis of HCC patients (P=0.481).
Conclusion: CDK1, CCNB1, CCNA2, CCNB2, MAD2L1, AURKA, TTK, CDC20, NDC80 and BIRC5 may play a role in the development and progression of HCC. CKD1 is associated with the prognosis of HCC and may become a new prognostic marker.

Key words: Hepatocellular carcinoma, Key genes, Pathogenesis, Prognosis, Bioinformatics analysis

Shi Wenwu, Chen Zhimin, Zhou Jinhua. Bioinformatics analysis and validation of key genes in the pathogenesis and prognosis of hepatocellular carcinoma[J]. Electronic Journal of Liver Tumor, 2022, 9(3): 1-6.

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