Li Jin , Zhuo Cheng , Hanfei Huang , Lin Deng , Meidiao Ma , Siming Qu , Bo Yuan , Yuan Fang , Youzhi Ye , Zhong Zeng
{"title":"利用综合生物信息学分析确定肝纤维化相关枢纽基因","authors":"Li Jin , Zhuo Cheng , Hanfei Huang , Lin Deng , Meidiao Ma , Siming Qu , Bo Yuan , Yuan Fang , Youzhi Ye , Zhong Zeng","doi":"10.1016/j.genrep.2024.102001","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>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.</p></div><div><h3>Methods</h3><p>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 (CCl<sub>4</sub>) injections or 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) diet.</p></div><div><h3>Results</h3><p>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 CCl<sub>4</sub>, 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.</p></div><div><h3>Conclusion</h3><p>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.</p></div>","PeriodicalId":12673,"journal":{"name":"Gene Reports","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452014424001249/pdfft?md5=f80f0fec23a1a219bb039dad2fa12822&pid=1-s2.0-S2452014424001249-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Identify liver fibrosis associated hub genes using integrated bioinformatics analysis\",\"authors\":\"Li Jin , Zhuo Cheng , Hanfei Huang , Lin Deng , Meidiao Ma , Siming Qu , Bo Yuan , Yuan Fang , Youzhi Ye , Zhong Zeng\",\"doi\":\"10.1016/j.genrep.2024.102001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>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.</p></div><div><h3>Methods</h3><p>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 (CCl<sub>4</sub>) injections or 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) diet.</p></div><div><h3>Results</h3><p>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 CCl<sub>4</sub>, 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.</p></div><div><h3>Conclusion</h3><p>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.</p></div>\",\"PeriodicalId\":12673,\"journal\":{\"name\":\"Gene Reports\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2024-08-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2452014424001249/pdfft?md5=f80f0fec23a1a219bb039dad2fa12822&pid=1-s2.0-S2452014424001249-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Gene Reports\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2452014424001249\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Gene Reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2452014424001249","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Identify liver fibrosis associated hub genes using integrated bioinformatics analysis
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.
Gene ReportsBiochemistry, 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.