Objective:This study analyzes the expression level of miR-1180-3p and constructs the regulatory network of relevant ceRNA by integrating the DNA methylation and gene expression profile of hepatocellular carcinoma from the Cancer Genome Atlas (TCGA).Methods:Firstly, the expression level of miR-1180-3p in hepatocellular carcinoma and adjacent tissues was analyzed by TCGA database, and the differential expression of lncrna and mRNA was screened. Secondly, the LncBase database and the TargetScan database were used to predict the relationship between miR-1180-3p and lncRNA and mRNA, and the DNA methylation-mediated lncRNA was screened by the DNA methylation profile of lncRNA. Finally, Cytoscape software was used to construct miR-1180-3p relevant ceRNA network, and WebGestalt website was used to perform GO and KEGG analysis of related mRNA in ceRNA.Results:Compared with patients with low expression of miR-1180-3p (mean overall survival duration, 5.69 ± 0.35 years), patients with high expression of miR-1180-3p had shorter overall survival time (mean overall survival duration, 3.99 ± 0.47 years), indicating that the high expression of miR-1180-3p was hepatocellular carcinoma risk factor affecting the prognosis ( HR = 1.28, 95% CI = 1.1 ~ 1.5, P < 0.01). A miR-1180-3p related ceRNA regulatory network was constructed in this study, which contained 2 lncRNAs (F11-AS1 and LINC01511) and 37 mRNAs. Conclusion:This study has successfully constructed miR-1180-3p relevant ceRNA regulatory network, and DNA methylation-mediated F11-AS1 and F11-AS1/miR-1180-3p/C11of54 ceRNA regulatory axis has played an important role in the occurrence and development of hepatocellular carcinoma.

Objective:To screen and analyze the differentially-expressed genes (DEGs) in primary hepatocellular carcinoma tissues and adjacent tissues using bioinformatics methods to explore the molecular mechanism of the occurrence and prognosis of primary hepatocellular carcinoma.Methods:GSE76427 data set was collected through GEO database, and DEGs were identified using GEO2R online analysis. Go and KEGG databases were used for enrichment and functional annotation of DEGs. Protein interaction network was built based on the STRING database and Cytoscape software to analyze the key genes of hepatocellular carcinoma, and the survival curve of these key genes were analyzed using the GEPIA database.Results:A total of 74 hepatocellular carcinoma DEGs were screened, of which 3 and 71 were up-and-down-regulated genes. The results of GO enrichment analysis showed that the down-regulated DEGs were mainly involved in cell response to cadmium and zinc ions, negative growth regulation, heterologous metabolic processes and hormone-mediated signaling pathways. KEGG pathway enrichment analysis results showed that the down-regulated DEGs pathway were mainly involved in retinol metabolism, chemical carcinogenesis, drug metabolism-cytochrome P450, cytochrome P450 metabolizing xenobiotics, tryptophan metabolism and caffeine metabolism. Protein interaction network had screened out 10 down-regulated core genes: MT1G, MT1F, MT1X, MT1E, MT1H, insulin-like growth factor 1, FOS, CXCL12, EGR1, and BGN. Among them, the insulin-like growth factor 1 was related to the prognosis of primary hepatocellular carcinoma.Conclusion:Bioinformatics analysis results of HCC chip data showed that 10 key genes may play a key role in the occurrence and development of HCC and the insulin like growth factor 1 is associated with the prognosis of primary hepatocellular carcinoma.