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通过加权基因共表达网络分析(WGCNA)建立的非酒精性脂肪性肝病与肝细胞癌之间的共享基因和分子机制

Shared Genes and Molecular Mechanisms between Nonalcoholic Fatty Liver Disease and Hepatocellular Carcinoma Established by WGCNA Analysis.

作者信息

He Juan, Zhang Xin, Chen Xi, Xu Zongyao, Chen Xiaoqi, Xu Jiangyan

机构信息

Traditional Chinese Medicine (ZHONG JING) School, Henan University of Chinese Medicine, Zhengzhou, Henan, People's Republic of China.

First School of Clinical Medicine, Henan University of Chinese Medicine, Zhengzhou, Henan, People's Republic of China.

出版信息

Glob Med Genet. 2023 Jul 10;10(3):144-158. doi: 10.1055/s-0043-1768957. eCollection 2023 Sep.

Abstract

Hepatocellular carcinoma (HCC) is one of the leading causes of death from cancer worldwide. The histopathological features, risk factors, and prognosis of HCC caused by nonalcoholic fatty liver disease (NAFLD) appear to be significantly different from those of HCC caused by other etiologies of liver disease.  This article explores the shared gene and molecular mechanism between NAFLD and HCC through bioinformatics technologies such as weighted gene co-expression network analysis (WGCNA), so as to provide a reference for comprehensive understanding and treatment of HCC caused by NAFLD.  NAFLD complementary deoxyribonucleic acid microarrays (GSE185051) from the Gene Expression Omnibus database and HCC ribonucleic acid (RNA)-sequencing data (RNA-seq data) from The Cancer Genome Atlas database were used to analyze the differentially expressed genes (DEGs) between NAFLD and HCC. Then, the clinical traits and DEGs in the two disease data sets were analyzed by WGCNA to obtain W-DEGs, and cross-W-DEGs were obtained by their intersection. We performed subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) enrichment analyses of the cross-W-DEGs and established protein-protein interaction networks. Then, we identified the hub genes in them by Cytoscape and screened out the final candidate genes. Finally, we validated candidate genes by gene expression, survival, and immunohistochemical analyses.  The GO analysis of 79 cross-W-DEGs showed they were related mainly to RNA polymerase II (RNAP II) and its upstream transcription factors. KEGG analysis revealed that they were enriched predominantly in inflammation-related pathways (tumor necrosis factor and interleukin-17). Four candidate genes (JUNB, DUSP1, NR4A1, and FOSB) were finally screened out from the cross-W-DEGs.  JUNB, DUSP1, NR4A1, and FOSB inhibit NAFLD and HCC development and progression. Thus, they can serve as potential useful biomarkers for predicting and treating NAFLD progression to HCC.

摘要

肝细胞癌(HCC)是全球癌症死亡的主要原因之一。非酒精性脂肪性肝病(NAFLD)所致HCC的组织病理学特征、危险因素和预后似乎与其他肝病病因所致HCC有显著差异。 本文通过加权基因共表达网络分析(WGCNA)等生物信息学技术探索NAFLD和HCC之间共享的基因和分子机制,以便为全面了解和治疗NAFLD所致HCC提供参考。 利用来自基因表达综合数据库的NAFLD互补脱氧核糖核酸微阵列(GSE185051)和来自癌症基因组图谱数据库的HCC核糖核酸(RNA)测序数据(RNA-seq数据)分析NAFLD和HCC之间的差异表达基因(DEG)。然后,通过WGCNA分析两个疾病数据集中的临床特征和DEG以获得W-DEG,并通过它们的交集获得交叉W-DEG。我们对交叉W-DEG进行了后续的基因本体论(GO)和京都基因与基因组百科全书(KEGG)富集分析,并建立了蛋白质-蛋白质相互作用网络。然后,我们通过Cytoscape识别其中的枢纽基因并筛选出最终的候选基因。最后,我们通过基因表达、生存和免疫组织化学分析验证候选基因。 对79个交叉W-DEG的GO分析表明,它们主要与RNA聚合酶II(RNAP II)及其上游转录因子有关。KEGG分析显示,它们主要富集于炎症相关途径(肿瘤坏死因子和白细胞介素-17)。最终从交叉W-DEG中筛选出四个候选基因(JUNB、DUSP1、NR4A1和FOSB)。 JUNB、DUSP1、NR4A1和FOSB抑制NAFLD和HCC的发生发展。因此,它们可作为预测和治疗NAFLD进展为HCC的潜在有用生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d3f/10370469/f300a4eafd3e/10-1055-s-0043-1768957-i2300012-1.jpg

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