Identification of Hub Genes Associated With Development and Microenvironment of Hepatocellular Carcinoma by Weighted Gene Co-expression Network Analysis and Differential Gene Expression Analysis - Bai, Qingquan; Liu, Haoling; Guo, Hongyu; Lin, Han; Song, Xuan; Jin, Ye; Liu, Yao; Guo, Hongrui; Liang, Shuhang; Song, Ruipeng; Wang, Jiabei; Qu, Zhibo; et al. (Frontiers in Genetics, 2020)
A further understanding of the molecular mechanism of hepatocellular carcinoma (HCC) is necessary to predict patients' prognosis and develop new targeted gene drugs. This study aims to identify essential genes related to HCC. We used Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis to analyze the gene expression profile of GSE45114 in the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas database (TCGA). A total of 37 overlapping genes were extracted from four groups of results Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway and Gene Ontology (GO) enrichment analysis were performed on the 37 overlapping genes. Then, we used the STRING database to map the protein interaction (PPI) network of 37 overlapping genes. Ten hub genes were screened according to the Maximal Clique Centrality (MCC) score using the Cytohubba plugin of Cytoscape(Including FOS, EGR1, EPHA2, DUSP1, IGFBP3, SOCS2, ID1, DUSP6, MT1G, and MT1H). Most hub genes show a significant association with immune infiltration types and tumor stemness of microenvironment in HCC. According to Univariate Cox expression analysis and Kaplan-Meier survival estimation, SOCS2 was positively correlated with overall survival(OS), and IGFBP3 was negatively correlated with OS. Moreover, the expression of IGFBP3 increased with the increase of the clinical-stage, while the expression of SOCS2 decreased with the increase of the clinical stage. In conclusion, our findings suggest that SOCS2 and IGFBP3may play an essential role in the development of HCC and may serve as a potential biomarker for future diagnosis and treatment.