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Identification of key genes related to immune infiltration in cirrhosis via bioinformatics analysis

Cirrhosis is the most common subclass of liver disease worldwide and correlated to immune infiltration. However, the immune-related molecular mechanism underlying cirrhosis remains obscure. Two gene expression profiles GSE89377 and GSE139602 were investigated to identify differentially expressed gen...

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Autores principales: Du, Tong-Yue, Gao, Ya-Xian, Zheng, Yi-Shan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9892033/
https://www.ncbi.nlm.nih.gov/pubmed/36725885
http://dx.doi.org/10.1038/s41598-022-26794-8
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author Du, Tong-Yue
Gao, Ya-Xian
Zheng, Yi-Shan
author_facet Du, Tong-Yue
Gao, Ya-Xian
Zheng, Yi-Shan
author_sort Du, Tong-Yue
collection PubMed
description Cirrhosis is the most common subclass of liver disease worldwide and correlated to immune infiltration. However, the immune-related molecular mechanism underlying cirrhosis remains obscure. Two gene expression profiles GSE89377 and GSE139602 were investigated to identify differentially expressed genes (DEGs) related to cirrhosis. Enrichment analysis for DEGs was conducted. Next, the immune infiltration of DEGs was evaluated using CIBERSORT algorithm. The hub DEGs with tight connectivity were identified using the String and Cytoscape databases, and the expression difference of these hub genes between normal liver and cirrhosis samples was determined. Moreover, in order to evaluate the discriminatory ability of hub genes and obtained the area under the receiver operating characteristic curve values in the GSE89377 and GSE139602 datasets. Finally, the association between hub DEGs and immune cell infiltration was explored by Spearman method. Among the 299 DEGs attained, 136 were up-regulated and 163 were down-regulated. Then the enrichment function analysis of DEGs and CIBERSORT algorithm showed significant enrichment in immune and inflammatory responses. And four hub DEGs (ACTB, TAGLN, VIM, SOX9) were identified, which also showed a diagnostic value in the GSE89377 and GSE 139,602 datasets. Finally, the immune infiltration analysis indicated that, these hub DEGs were highly related to immune cells. This study revealed key DEGs involved in inflammatory immune responses of cirrhosis, which could be used as biomarkers for diagnosis or therapeutic targets of cirrhosis.
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spelling pubmed-98920332023-02-03 Identification of key genes related to immune infiltration in cirrhosis via bioinformatics analysis Du, Tong-Yue Gao, Ya-Xian Zheng, Yi-Shan Sci Rep Article Cirrhosis is the most common subclass of liver disease worldwide and correlated to immune infiltration. However, the immune-related molecular mechanism underlying cirrhosis remains obscure. Two gene expression profiles GSE89377 and GSE139602 were investigated to identify differentially expressed genes (DEGs) related to cirrhosis. Enrichment analysis for DEGs was conducted. Next, the immune infiltration of DEGs was evaluated using CIBERSORT algorithm. The hub DEGs with tight connectivity were identified using the String and Cytoscape databases, and the expression difference of these hub genes between normal liver and cirrhosis samples was determined. Moreover, in order to evaluate the discriminatory ability of hub genes and obtained the area under the receiver operating characteristic curve values in the GSE89377 and GSE139602 datasets. Finally, the association between hub DEGs and immune cell infiltration was explored by Spearman method. Among the 299 DEGs attained, 136 were up-regulated and 163 were down-regulated. Then the enrichment function analysis of DEGs and CIBERSORT algorithm showed significant enrichment in immune and inflammatory responses. And four hub DEGs (ACTB, TAGLN, VIM, SOX9) were identified, which also showed a diagnostic value in the GSE89377 and GSE 139,602 datasets. Finally, the immune infiltration analysis indicated that, these hub DEGs were highly related to immune cells. This study revealed key DEGs involved in inflammatory immune responses of cirrhosis, which could be used as biomarkers for diagnosis or therapeutic targets of cirrhosis. Nature Publishing Group UK 2023-02-01 /pmc/articles/PMC9892033/ /pubmed/36725885 http://dx.doi.org/10.1038/s41598-022-26794-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Du, Tong-Yue
Gao, Ya-Xian
Zheng, Yi-Shan
Identification of key genes related to immune infiltration in cirrhosis via bioinformatics analysis
title Identification of key genes related to immune infiltration in cirrhosis via bioinformatics analysis
title_full Identification of key genes related to immune infiltration in cirrhosis via bioinformatics analysis
title_fullStr Identification of key genes related to immune infiltration in cirrhosis via bioinformatics analysis
title_full_unstemmed Identification of key genes related to immune infiltration in cirrhosis via bioinformatics analysis
title_short Identification of key genes related to immune infiltration in cirrhosis via bioinformatics analysis
title_sort identification of key genes related to immune infiltration in cirrhosis via bioinformatics analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9892033/
https://www.ncbi.nlm.nih.gov/pubmed/36725885
http://dx.doi.org/10.1038/s41598-022-26794-8
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