Identification of functional genes in liver fibrosis based on bioinformatics analysis of a lncRNA-mediated ceRNA network.

BACKGROUND: Liver fibrosis is a major global healths problem; nevertheless, its molecular mechanism are not completely clear. This study aimed to build a lncRNA-miRNA-mRNA network, identify potentially related lncRNAs, and explore the pathogenesis of liver fibrosis. MATERIALS AND METHODS: We used the Gene Expression Omnibus databases and bioinformatics analysis to identify differentially expressed genes (DEGs) between liver fibrosis and normal tissues. The ceRNA network was constructed according to the interactions between DElncRNA, miRNA, and DEmRNA. Then, these DEGs were identified using functional enrichment analysis, and a protein-protein interaction (PPI) network was established. The critical lncRNAs were verified using the quantitative real-time polymerase chain reaction (qRT-PCR). RESULTS: The ceRNA network was composed of three lncRNAs, five miRNAs, and 93 mRNAs. Gene Ontology functional enrichment analysis revealed significant enhancement in cell components, molecular function, and biological process. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed pathways associated with transcriptional misregulation in cancer, including the Rap1 signaling pathway, proteoglycans in cancer, mineral absorption, HTLV-l infection, and central carbon metabolism in cancer. According to the PPI network and the GSE84044 database, seven hub genes associated with liver fibrosis were identified. In addition, qRT-PCR revealed that lncRNA AC100861 (lncRNA TNFRSF10A-DT) was explicitly decreased in liver fibrosis tissues and activated hepatic stellate cells. CONCLUSIONS: In summary, this study preliminarily found that lncRNA TNFRSF10A-DT may be a biomarker for the diagnosis and outcome of liver fibrosis. We uncovered a novel lncRNA-mediated ceRNA regulatory mechanism in the pathogenesis of liver fibrosis.