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Identification of oxidative stress-related biomarkers associated with the development of acute-on-chronic liver failure using bioinformatics

Acute-on-chronic liver failure (ACLF) is a serious stage of chronic liver disease with high short-term mortality and no definitely effective treatment. Oxidative stress (OS) is involved in the development of ACLF. OS-related genes targeted therapy may provide additional assistance for the treatment...

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Autores principales: Zhu, Zongyi, Jiang, Huiqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10564851/
https://www.ncbi.nlm.nih.gov/pubmed/37816833
http://dx.doi.org/10.1038/s41598-023-44343-9
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author Zhu, Zongyi
Jiang, Huiqing
author_facet Zhu, Zongyi
Jiang, Huiqing
author_sort Zhu, Zongyi
collection PubMed
description Acute-on-chronic liver failure (ACLF) is a serious stage of chronic liver disease with high short-term mortality and no definitely effective treatment. Oxidative stress (OS) is involved in the development of ACLF. OS-related genes targeted therapy may provide additional assistance for the treatment of ACLF. ACLF related gene sets and oxidative stress-related genes (OSGs) were respectively downloaded from gene expression omnibus (GEO) database and GeneCards database for integrated bioinformatics analyses (functional enrichment, weighted gene co-expression network and immune cells infiltration). Immune-related differentially expressed oxidative stress-related genes (DEOSGs) in ACLF were used for construction of protein–protein interaction (PPI) network in which hub genes were screened out. Hub genes with consistently good diagnostic or prognostic value for ACLF in four gene sets were named as key genes. DEOSGs were significantly enriched in biological process and signaling pathways related to inflammation, immune response and oxidative stress. Six key genes (MPO, CCL5, ITGAM, TLR2, TLR4, and TIMP1) were identified and found to be highly correlated with immune response and metabolic process. This study deepened our understanding of the impact of oxidative stress on the pathogenesis and prognosis of ACLF and provided more insights into the prediction of prognosis and molecular targeted therapy in ACLF.
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spelling pubmed-105648512023-10-12 Identification of oxidative stress-related biomarkers associated with the development of acute-on-chronic liver failure using bioinformatics Zhu, Zongyi Jiang, Huiqing Sci Rep Article Acute-on-chronic liver failure (ACLF) is a serious stage of chronic liver disease with high short-term mortality and no definitely effective treatment. Oxidative stress (OS) is involved in the development of ACLF. OS-related genes targeted therapy may provide additional assistance for the treatment of ACLF. ACLF related gene sets and oxidative stress-related genes (OSGs) were respectively downloaded from gene expression omnibus (GEO) database and GeneCards database for integrated bioinformatics analyses (functional enrichment, weighted gene co-expression network and immune cells infiltration). Immune-related differentially expressed oxidative stress-related genes (DEOSGs) in ACLF were used for construction of protein–protein interaction (PPI) network in which hub genes were screened out. Hub genes with consistently good diagnostic or prognostic value for ACLF in four gene sets were named as key genes. DEOSGs were significantly enriched in biological process and signaling pathways related to inflammation, immune response and oxidative stress. Six key genes (MPO, CCL5, ITGAM, TLR2, TLR4, and TIMP1) were identified and found to be highly correlated with immune response and metabolic process. This study deepened our understanding of the impact of oxidative stress on the pathogenesis and prognosis of ACLF and provided more insights into the prediction of prognosis and molecular targeted therapy in ACLF. Nature Publishing Group UK 2023-10-10 /pmc/articles/PMC10564851/ /pubmed/37816833 http://dx.doi.org/10.1038/s41598-023-44343-9 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
Zhu, Zongyi
Jiang, Huiqing
Identification of oxidative stress-related biomarkers associated with the development of acute-on-chronic liver failure using bioinformatics
title Identification of oxidative stress-related biomarkers associated with the development of acute-on-chronic liver failure using bioinformatics
title_full Identification of oxidative stress-related biomarkers associated with the development of acute-on-chronic liver failure using bioinformatics
title_fullStr Identification of oxidative stress-related biomarkers associated with the development of acute-on-chronic liver failure using bioinformatics
title_full_unstemmed Identification of oxidative stress-related biomarkers associated with the development of acute-on-chronic liver failure using bioinformatics
title_short Identification of oxidative stress-related biomarkers associated with the development of acute-on-chronic liver failure using bioinformatics
title_sort identification of oxidative stress-related biomarkers associated with the development of acute-on-chronic liver failure using bioinformatics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10564851/
https://www.ncbi.nlm.nih.gov/pubmed/37816833
http://dx.doi.org/10.1038/s41598-023-44343-9
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