Identify liver fibrosis associated hub genes using integrated bioinformatics analysis

IF 1 Q4 GENETICS & HEREDITY

Gene Reports Pub Date : 2024-08-10 DOI:10.1016/j.genrep.2024.102001

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引用次数: 0

Abstract

Background

Cirrhosis is defined as diffuse liver fibrosis (LF) caused by various chronic liver diseases and characterized by excessive deposition of extracellular matrix in liver tissue. However, the molecular mechanism of cirrhosis has not been well understood. This study aimed to identify significant gene expression profiles that participate in cirrhosis pathogenesis using bioinformatics and to discover novel biomarkers.

Methods

Two LF datasets (GSE14323 and GSE139602), both consisted of cirrhosis patients and healthy individuals, were obtained from the Gene Expression Omnibus (GEO) database and used for further analysis. Firstly, differential expression analyses were conducted to discover overlapping differentially expressed genes (DEGs) using the limma package. Next, the clusterProfiler function was adopted to carry out the Gene Ontology (GO) and Kyoto Encyclopedia of Genes as well as Genomes (KEGG) enrichment analyses. Furthermore, protein-protein interaction (PPI) network of the DEGs was constructed in the STRING database. In addition, hub genes were extracted through the cytoHubba plug-in. To verify the results we observed from the bioinformatics analysis, mouse models were established by receiving Carbon tetrachloride (CCl₄) injections or 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) diet.

Results

A total of 81 upregulated and 21 downregulated overlapping DEGs were identified in cirrhosis tissues compared to healthy controls. 9 hub genes included SPP1, SOX9, THBS2, LUM, LAMA2, PECAM1, VIM, COL1A2, and COL3A1 were identified by the PPI analysis from the 81 upregulated overlapping DEGs. RT-PCR of the fibrotic liver tissues from the mouse model showed that the mRNA levels of Spp1, Sox9, Col1a2 and Col3a1 were up-regulated in mice treated with CCl₄, while Spp1, Thbs2, Lum, Pecam1, Vim, Col1a2, and Col3a1 were up-regulated in mice treated with DDC. Predictive analyses provided drug compounds that are associated with LF.

Conclusion

The present study identified hub genes that were associated with the occurrence of LF may provide reference for future studies to better explore the pathogenesis of cirrhosis, and play a possible role for developing drugs for LF.

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利用综合生物信息学分析确定肝纤维化相关枢纽基因

背景肝硬化是指由各种慢性肝病引起的弥漫性肝纤维化（LF），其特征是肝组织中细胞外基质的过度沉积。然而，人们对肝硬化的分子机制还不甚了解。方法从基因表达总库（Gene Expression Omnibus，GEO）数据库中获得两个肝硬化数据集（GSE14323和GSE139602），用于进一步分析。首先，使用 limma 软件包进行差异表达分析，以发现重叠的差异表达基因（DEGs）。接着，利用 clusterProfiler 功能进行了基因本体（GO）和京都基因组百科全书（KEGG）富集分析。此外，还在 STRING 数据库中构建了 DEGs 的蛋白-蛋白相互作用（PPI）网络。此外，还通过 cytoHubba 插件提取了枢纽基因。为了验证我们从生物信息学分析中观察到的结果，通过注射四氯化碳（CCl4）或3,5-二乙氧基羰基-1,4-二氢可待因（DDC）饮食建立了小鼠模型。通过PPI分析，从81个上调的重叠DEGs中确定了9个中心基因，包括SPP1、SOX9、THBS2、LUM、LAMA2、PECAM1、VIM、COL1A2和COL3A1。对小鼠模型的纤维化肝组织进行的 RT-PCR 分析表明，Spp1、Sox9、Col1a2 和 Col3a1 的 mRNA 水平在接受 CCl4 治疗的小鼠中上调，而 Spp1、Thbs2、Lum、Pecam1、Vim、Col1a2 和 Col3a1 的 mRNA 水平在接受 DDC 治疗的小鼠中上调。本研究发现了与肝纤维化发生相关的枢纽基因，为今后更好地探索肝硬化的发病机制提供了参考，并为开发治疗肝纤维化的药物提供了可能。

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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来源期刊

Gene Reports Biochemistry, Genetics and Molecular Biology-Genetics

CiteScore

3.30

自引率

7.70%

发文量

246

审稿时长

49 days

期刊介绍： Gene Reports publishes papers that focus on the regulation, expression, function and evolution of genes in all biological contexts, including all prokaryotic and eukaryotic organisms, as well as viruses. Gene Reports strives to be a very diverse journal and topics in all fields will be considered for publication. Although not limited to the following, some general topics include: DNA Organization, Replication & Evolution -Focus on genomic DNA (chromosomal organization, comparative genomics, DNA replication, DNA repair, mobile DNA, mitochondrial DNA, chloroplast DNA). Expression & Function - Focus on functional RNAs (microRNAs, tRNAs, rRNAs, mRNA splicing, alternative polyadenylation) Regulation - Focus on processes that mediate gene-read out (epigenetics, chromatin, histone code, transcription, translation, protein degradation). Cell Signaling - Focus on mechanisms that control information flow into the nucleus to control gene expression (kinase and phosphatase pathways controlled by extra-cellular ligands, Wnt, Notch, TGFbeta/BMPs, FGFs, IGFs etc.) Profiling of gene expression and genetic variation - Focus on high throughput approaches (e.g., DeepSeq, ChIP-Seq, Affymetrix microarrays, proteomics) that define gene regulatory circuitry, molecular pathways and protein/protein networks. Genetics - Focus on development in model organisms (e.g., mouse, frog, fruit fly, worm), human genetic variation, population genetics, as well as agricultural and veterinary genetics. Molecular Pathology & Regenerative Medicine - Focus on the deregulation of molecular processes in human diseases and mechanisms supporting regeneration of tissues through pluripotent or multipotent stem cells.