WGCNA分析证实非酒精性脂肪肝与肝细胞癌的基因共享及分子机制

IF 1.2 Q4 GENETICS & HEREDITY Global Medical Genetics Pub Date : 2023-09-01 DOI:10.1055/s-0043-1768957
Juan He, Xin Zhang, Xi Chen, Zongyao Xu, Xiaoqi Chen, Jiangyan Xu
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引用次数: 0

摘要

肝细胞癌(HCC)是世界范围内癌症死亡的主要原因之一。非酒精性脂肪性肝病(NAFLD)引起的HCC的组织病理学特征、危险因素和预后与其他肝病病因引起的HCC明显不同。目的通过加权基因共表达网络分析(weighted gene co-expression network analysis, WGCNA)等生物信息学技术探讨NAFLD与HCC之间的共享基因和分子机制,为全面认识和治疗NAFLD所致HCC提供参考。方法采用来自基因表达图谱数据库的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与HCC之间的差异表达基因(DEGs)。然后,通过WGCNA对两种疾病数据集中的临床特征和deg进行分析,得到w - deg,并通过它们的交集得到交叉w - deg。我们对交叉w - degs进行了基因本体(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。然后利用Cytoscape对其中心基因进行鉴定,筛选出最终候选基因。最后,我们通过基因表达、存活和免疫组织化学分析验证候选基因。结果79个交叉w - deg的氧化石墨烯分析显示,它们主要与RNA聚合酶II (RNAP II)及其上游转录因子相关。KEGG分析显示,它们主要富集于炎症相关通路(肿瘤坏死因子和白细胞介素-17)。最终从交叉w - deg中筛选出4个候选基因JUNB、DUSP1、NR4A1和FOSB。结论JUNB、DUSP1、NR4A1和FOSB抑制NAFLD和HCC的发生发展。因此,它们可以作为预测和治疗NAFLD进展为HCC的潜在有用的生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

Background  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. Objective  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. Methods  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. Results  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. Conclusion  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.

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来源期刊
Global Medical Genetics
Global Medical Genetics GENETICS & HEREDITY-
自引率
11.80%
发文量
30
审稿时长
14 weeks
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