Identification of hub genes and potential inhibitory compounds in the process of liver transplantation through transcriptome sequencing

Abstract

Liver transplantation (LT) is the best choice for patients with end-stage liver diseases. In order to better understand pathophysiological alterations in LT, we aimed to identify potential hub genes and inhibitory compounds involved in the LT process. Four pairs of peripheral blood mononuclear cell (PBMC) samples of the LT recipients before and after surgery were collected and taken for transcriptome sequencing. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed for the screened differentially expressed genes (DEGs) between pre- and post-operation groups. Common DEGs were obtained from GO and KEGG enriched pathways, followed by protein-protein interaction (PPI) network construction, hub gene identification, module analysis, and structure-based virtual screening process (SBVS). Compared to the pre-operation stage, 4745 genes were down-regulated and 798 up-regulated after LT. GO analysis showed that the DEGs were enriched in ribosome-related translation regulation, and KEGG analysis indicated that infection and immune-related pathways and diseases were largely enriched. A large number of down-regulated DEGs were not only associated with ribosome-related pathways but also with the alterations of epigenetic modifications, in particular ubiquitination. Moreover, through the PPI network of 29 common genes from GO and KEGG-enriched pathways, 7 hub genes were identified, including PTEN, MYC, EIF2S1, EIF4EBP1, HSP90AB1, TP53, and HSPA8, which were mainly involved in the PI3K-AKT signaling pathway. SBVS of the seed molecule PTEN (PDB code: 1D5R) predicted top hits compounds that may serve as potential inhibitors of PTEN, of which the compound ZINC4235331 had the lowest binding affinity of -10 kcal/mol. The significance of screened hub genes and potential inhibitors involved in the process of LT provides novel therapeutic strategies for improving the outcomes of LT recipients during surgery.

Keywords

• Liver transplantation
• Bioinformatics
• Epigenetic modification
• Differentially expressed genes
• Protein–protein interaction network