Exploration of new therapeutic targets for viral hepatic fibrosis, alcoholic hepatic fibrosis, and non-alcoholic hepatic fibrosis

BACKGROUND: Hepatic fibrosis is a widespread disease worldwide. Millions of people lose their lives due to hepatic fibrosis every year. The main causes of hepatic fibrosis include viral infection, alcoholism, and obesity. Many studies have been conducted on the single factors that cause hepatic fibrosis; however, no studies have examined whether hepatic fibrosis caused by multiple factors has concomitant expression molecules and signaling pathways. In this study, we sought to analyze the common differentially expressed messenger ribonucleic acids (mRNAs) of hepatic fibrosis caused by different factors, including hepatitis B virus (HBV) hepatic fibrosis, alcoholic hepatic fibrosis, and non-alcoholic hepatic fibrosis, and identify potential preventive and therapeutic targets. METHODS: The GSE171294, GSE142530, and GSE126848 datasets from the Gene Expression Omnibus (GEO) public database were used in this study. A |log fold change| >0.5 and a P value <0.05 were defined as differentially expressed mRNAs via R software screening. To further screen the target mRNAs, the differential mRNAs were subjected to a functional enrichment analysis based on the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Finally, the relationships between differentially expressed mRNA-encoded proteins were analyzed by a protein-protein interaction (PPI) analysis. RESULTS: A total of 54 differentially expressed mRNAs were identified. The KEGG analysis showed that the functions of different mRNAs mainly focused on Gonadotropin Releasing Hormone (GnRH) secretion, bile secretion and insulin secretion. The GO enrichment analysis showed that the differential mRNAs were mainly present in the cytoplasmic membrane region and exerted biological functions, such as activating channels and binding proteins by regulating biological processes (BPs), such as cells, cytoskeleton and heparin. The PPI network analysis revealed 16 nodes with 12 pairs of interactions. The 16 critical nodes included BCL6, CD4, CD24, IL32, CALD1, TRAF3, SOX9, KANSL3, MRGBP, PKD2, PKHD1, SYT1, ANXA4, KCNMA1, KCNN2, and CACNA1H. CONCLUSIONS: KCNN2, CD4, CD24, BCL6, KCNMA1, and other molecules obtained by the bioinformatics analysis of the RNA-sequencing data can be used as new research targets for hepatic fibrosis induced by different causes. Our findings could provide novel ideas for the treatment of hepatic fibrosis.