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Identification of Hub Genes Associated With Development and Microenvironment of Hepatocellular Carcinoma by Weighted Gene Co-expression Network Analysis and Differential Gene Expression Analysis

A further understanding of the molecular mechanism of hepatocellular carcinoma (HCC) is necessary to predict a patient’s prognosis and develop new targeted gene drugs. This study aims to identify essential genes related to HCC. We used the Weighted Gene Co-expression Network Analysis (WGCNA) and dif...

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Autores principales: Bai, Qingquan, Liu, Haoling, Guo, Hongyu, Lin, Han, Song, Xuan, Jin, Ye, Liu, Yao, Guo, Hongrui, Liang, Shuhang, Song, Ruipeng, Wang, Jiabei, Qu, Zhibo, Guo, Huaxin, Jiang, Hongchi, Liu, Lianxin, Yang, Haiyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7783465/
https://www.ncbi.nlm.nih.gov/pubmed/33414813
http://dx.doi.org/10.3389/fgene.2020.615308
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author Bai, Qingquan
Liu, Haoling
Guo, Hongyu
Lin, Han
Song, Xuan
Jin, Ye
Liu, Yao
Guo, Hongrui
Liang, Shuhang
Song, Ruipeng
Wang, Jiabei
Qu, Zhibo
Guo, Huaxin
Jiang, Hongchi
Liu, Lianxin
Yang, Haiyan
author_facet Bai, Qingquan
Liu, Haoling
Guo, Hongyu
Lin, Han
Song, Xuan
Jin, Ye
Liu, Yao
Guo, Hongrui
Liang, Shuhang
Song, Ruipeng
Wang, Jiabei
Qu, Zhibo
Guo, Huaxin
Jiang, Hongchi
Liu, Lianxin
Yang, Haiyan
author_sort Bai, Qingquan
collection PubMed
description A further understanding of the molecular mechanism of hepatocellular carcinoma (HCC) is necessary to predict a patient’s prognosis and develop new targeted gene drugs. This study aims to identify essential genes related to HCC. We used the 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 analyses 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 regression 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 IGFBP3 may play an essential role in the development of HCC and may serve as a potential biomarker for future diagnosis and treatment.
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spelling pubmed-77834652021-01-06 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 Guo, Huaxin Jiang, Hongchi Liu, Lianxin Yang, Haiyan Front Genet Genetics A further understanding of the molecular mechanism of hepatocellular carcinoma (HCC) is necessary to predict a patient’s prognosis and develop new targeted gene drugs. This study aims to identify essential genes related to HCC. We used the 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 analyses 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 regression 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 IGFBP3 may play an essential role in the development of HCC and may serve as a potential biomarker for future diagnosis and treatment. Frontiers Media S.A. 2020-12-22 /pmc/articles/PMC7783465/ /pubmed/33414813 http://dx.doi.org/10.3389/fgene.2020.615308 Text en Copyright © 2020 Bai, Liu, Guo, Lin, Song, Jin, Liu, Guo, Liang, Song, Wang, Qu, Guo, Jiang, Liu and Yang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Bai, Qingquan
Liu, Haoling
Guo, Hongyu
Lin, Han
Song, Xuan
Jin, Ye
Liu, Yao
Guo, Hongrui
Liang, Shuhang
Song, Ruipeng
Wang, Jiabei
Qu, Zhibo
Guo, Huaxin
Jiang, Hongchi
Liu, Lianxin
Yang, Haiyan
Identification of Hub Genes Associated With Development and Microenvironment of Hepatocellular Carcinoma by Weighted Gene Co-expression Network Analysis and Differential Gene Expression Analysis
title Identification of Hub Genes Associated With Development and Microenvironment of Hepatocellular Carcinoma by Weighted Gene Co-expression Network Analysis and Differential Gene Expression Analysis
title_full Identification of Hub Genes Associated With Development and Microenvironment of Hepatocellular Carcinoma by Weighted Gene Co-expression Network Analysis and Differential Gene Expression Analysis
title_fullStr Identification of Hub Genes Associated With Development and Microenvironment of Hepatocellular Carcinoma by Weighted Gene Co-expression Network Analysis and Differential Gene Expression Analysis
title_full_unstemmed Identification of Hub Genes Associated With Development and Microenvironment of Hepatocellular Carcinoma by Weighted Gene Co-expression Network Analysis and Differential Gene Expression Analysis
title_short Identification of Hub Genes Associated With Development and Microenvironment of Hepatocellular Carcinoma by Weighted Gene Co-expression Network Analysis and Differential Gene Expression Analysis
title_sort identification of hub genes associated with development and microenvironment of hepatocellular carcinoma by weighted gene co-expression network analysis and differential gene expression analysis
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7783465/
https://www.ncbi.nlm.nih.gov/pubmed/33414813
http://dx.doi.org/10.3389/fgene.2020.615308
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