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Copyright (c) 2023 Bing Wang, Yiqing Zhang, Lin Gai, Yujie He, Hong Qiu, Ping Li
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The undersigned hereby assign all rights, included but not limited to copyright, for this manuscript to CMB Association upon its submission for consideration to publication on Cellular and Molecular Biology. The rights assigned include, but are not limited to, the sole and exclusive rights to license, sell, subsequently assign, derive, distribute, display and reproduce this manuscript, in whole or in part, in any format, electronic or otherwise, including those in existence at the time this agreement was signed. The authors hereby warrant that they have not granted or assigned, and shall not grant or assign, the aforementioned rights to any other person, firm, organization, or other entity. All rights are automatically restored to authors if this manuscript is not accepted for publication.Identification of Key Biomarkers in Hepatocellular Carcinoma Induced by Non-alcoholic steatohepatitis or Metabolic Syndrome via Integrated Bioinformatics Analysis
Corresponding Author(s) : Hong Qiu
Cellular and Molecular Biology,
Vol. 69 No. 7: Issue 7
Abstract
The burden of hepatocellular carcinoma (HCC) is steadily growing because obesity, type 2 diabetes, and nonalcoholic fatty liver disease (NAFLD) are replacing viral- and alcohol-related liver disease as major pathogenic promoters. The current study attempted to identify the key genes and pathways in the non-alcoholic steatohepatitis (NASH) induced development of HCC using integrated bioinformatics analyses. Two gene expression profiling datasets, GSE102079 and GSE164760 were downloaded. Differentially expressed genes (DEGs) from HCC and healthy control samples were screened. Functional enrichment analyses based on Gene Ontology (GO) resource, Kyoto Encyclopedia of Genes and Genomes (KEGG) resource. Then protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING). Expression and survival analysis of hub genes, methylation and genetic mutation analysis were explored with GEPIA2, UALCAN, GSCA, and TIMER2.0 databases. We identified 158 overlapping genes from the 2 datasets. Up-regulated genes were mainly related to the proliferation, adhesion and metastasis of tumors, while down-regulated genes were mainly related to oxidative stress and energy metabolism. CDKN2A, SPP1, CYP2C9 and CYP4A11 were associated with prognostic performance and were considered the potential crucial genes, which SPP1, CYP2C9 and CYP4A11 were identified as the DNA methylation-driven genes. In different mutation statuses of HCC, gene expression of CDKN2A, SPP1, CYP2C9 and CYP4A11 showed significant differences. CDKN2A and SPP1 were identified as risk genes, while CYP2C9 and CYP4A11 were identified as protective genes, which may affect the transformation of NASH into HCC.
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