Screening Of Biomarkers For Hepatocellular Carcinoma Based On Bioinformatics

Objective:The GEO database was used to mine gene chips,and the differential genes(DEGs)of hepatocellular carcinoma(HCC)and normal tissue were screened to explore the signaling pathways involved in the occurrence and development of HCC,and to find biomarkers with higher sensitivity and specificity for HCC diagnosis.Methods:Three HCC microarray data sets GSE84402,GSE101685 and GSE62232,all from the GPL570 platform,were downloaded from GEO database,including 109 HCC samples and 32 normal tissue samples,use the GEO2 R to analyse three microarray data sets,and use P<0.05 and︱log2FC︱>2 as the standard to screen out DEGs,DEGs of cancerous and non-cancerous tissues can be obtained,Co-expressed DEGs were screened from three datasets.DAVID database was used for gene ontology(GO)functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis.Protein-protein interaction(PPI)networks are mapped using the STRING database.Cytoscape software is used to perform graphic visualization and network modularization on the selected network maps,and score each gene according to its connectivity using MMC(maximum centrality)scoring criteria.Pick the top 10 core genes.For the selected core genes,Survival analysis of the core gene was conducted through Kaplan-Meier Plotter database,and the survival curve was drawn.GEPIA database was used for expression analysis,and the box pattern of expression of each core gene in cancer tissue and normal tissue was drawn.KEGG pathway enrichment analysis was performed on the final obtained core genes through the DAVID database to further analyze the signaling pathways involved in the core genes.Results: Data sets GSE101685,GSE84402 and GSE62232 screen out 459,471 and292 DEGs,respectively.Venn diagram show that 169 DEGs are co-expressed in GSE101685,GSE84402 and GSE62232 data sets,among which 43 DEGs are upregulated and 126 DEGs are down-regulated.GO functional enrichment analysis show that biological processes of DEGs mainly play a role in cellular response to cadmium ion,detoxification of copper ion,cellular response to copper ion,negative regulation of growth,epoxygenase P450 pathway,exogenous drug catabolic process,cellular response to zinc ion,xenobiotic metabolic process,cellular zinc ion homeostasis,and xenobiotic catabolic process.KEGG pathway enrichment analysis mainly plays a role in retinol metabolism,drug metabolism-cytochrome P450,metabolic pathway,metabolism of xenobiotics by cytochrome P450,caffeine metabolism,mineral absorption,chemical carcinogenic-DNA adduct,progesterone-mediated soft blast maturation,tryptophan metabolism,and blie secretion.Ten core genes DLGAP5,BIRC5,CCNB1,CCNA2,TTK,NDC80,NCAPG,MAD2L1,BUB1 B and RRM2 were selected by MMC(maximum centrality)score for each core gene in the network diagram through Cyto Hubba plugin of Cytoscape software.By comparing and analyzing the survival curves of 10 core genes,it was found that the abnormal expression of 10 core genes was associated with poor survival prognosis,and the overall survival rate showed a downward trend with the prolongation of the disease course.The expression levels of 10 core genes were analyzed by GEPIA database,and the expression levels of 9 core genes(DLGAP5,BIRC5,CCNB1,CCNA2,NDC80,NCAPG,MAD2L1,BUB1 B,RRM2)are statistically significant(P<0.05).KEGG pathway enrichment analysis of 9 core genes was performed using DAVID database,and found that core genes BUB1 B,CCNA2,CCNB1,MAD2L1 and RRM2 were mainly enriched in p53 signaling pathway and cell cycle.Conclusion: BUB1 B,CCNA2,CCNB1,MAD2L1 and RRM2 are highly expressed in HCC,and their high expression is associated with poor survival rate of HCC,which can be used as prognostic biomarkers of HCC and provide theoretical basis for the treatment of HCC patients.DLGAP5,BIRC5,NDC80 and NCAPG are worthy of further exploration in HCC diagnosis and prognosis assessment.