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Identification of Hub Genes Associated With Tuberculous Pleurisy by Integrated Bioinformatics Analysis

Improving the understanding of the molecular mechanism of tuberculous pleurisy is required to develop diagnosis and new therapy strategies of targeted genes. The purpose of this study is to identify important genes related to tuberculous pleurisy. In this study, the expression profile obtained by se...

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Autores principales: Shi, Lei, Wen, Zilu, Li, Hongwei, Song, Yanzheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8678451/
https://www.ncbi.nlm.nih.gov/pubmed/34925441
http://dx.doi.org/10.3389/fgene.2021.730491
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author Shi, Lei
Wen, Zilu
Li, Hongwei
Song, Yanzheng
author_facet Shi, Lei
Wen, Zilu
Li, Hongwei
Song, Yanzheng
author_sort Shi, Lei
collection PubMed
description Improving the understanding of the molecular mechanism of tuberculous pleurisy is required to develop diagnosis and new therapy strategies of targeted genes. The purpose of this study is to identify important genes related to tuberculous pleurisy. In this study, the expression profile obtained by sequencing the surgically resected pleural tissue was used to explore the differentially co-expressed genes between tuberculous pleurisy tissue and normal tissue. 29 differentially co-expressed genes were screened by weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis methods. According to the functional annotation analysis of R clusterProfiler software package, these genes are mainly enriched in nucleotide−sugar biosynthetic process (biological process), ficolin−1−rich granule lumen (cell component), and electron transfer activity (molecular function). In addition, in the protein-protein interaction (PPI) network, 20 hub genes of DEGs and WCGNA genes were identified using the CytoHubba plug-in of Cytoscape. In the end, RPL17 was identified as a gene that can be the biomarker of tuberculous pleurisy. At the same time, there are seven genes that may have relationship with the disease (UBA7, NDUFB8, UQCRFS1, JUNB, PSMC4, PHPT1, and MAPK11).
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spelling pubmed-86784512021-12-18 Identification of Hub Genes Associated With Tuberculous Pleurisy by Integrated Bioinformatics Analysis Shi, Lei Wen, Zilu Li, Hongwei Song, Yanzheng Front Genet Genetics Improving the understanding of the molecular mechanism of tuberculous pleurisy is required to develop diagnosis and new therapy strategies of targeted genes. The purpose of this study is to identify important genes related to tuberculous pleurisy. In this study, the expression profile obtained by sequencing the surgically resected pleural tissue was used to explore the differentially co-expressed genes between tuberculous pleurisy tissue and normal tissue. 29 differentially co-expressed genes were screened by weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis methods. According to the functional annotation analysis of R clusterProfiler software package, these genes are mainly enriched in nucleotide−sugar biosynthetic process (biological process), ficolin−1−rich granule lumen (cell component), and electron transfer activity (molecular function). In addition, in the protein-protein interaction (PPI) network, 20 hub genes of DEGs and WCGNA genes were identified using the CytoHubba plug-in of Cytoscape. In the end, RPL17 was identified as a gene that can be the biomarker of tuberculous pleurisy. At the same time, there are seven genes that may have relationship with the disease (UBA7, NDUFB8, UQCRFS1, JUNB, PSMC4, PHPT1, and MAPK11). Frontiers Media S.A. 2021-12-03 /pmc/articles/PMC8678451/ /pubmed/34925441 http://dx.doi.org/10.3389/fgene.2021.730491 Text en Copyright © 2021 Shi, Wen, Li and Song. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Shi, Lei
Wen, Zilu
Li, Hongwei
Song, Yanzheng
Identification of Hub Genes Associated With Tuberculous Pleurisy by Integrated Bioinformatics Analysis
title Identification of Hub Genes Associated With Tuberculous Pleurisy by Integrated Bioinformatics Analysis
title_full Identification of Hub Genes Associated With Tuberculous Pleurisy by Integrated Bioinformatics Analysis
title_fullStr Identification of Hub Genes Associated With Tuberculous Pleurisy by Integrated Bioinformatics Analysis
title_full_unstemmed Identification of Hub Genes Associated With Tuberculous Pleurisy by Integrated Bioinformatics Analysis
title_short Identification of Hub Genes Associated With Tuberculous Pleurisy by Integrated Bioinformatics Analysis
title_sort identification of hub genes associated with tuberculous pleurisy by integrated bioinformatics analysis
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8678451/
https://www.ncbi.nlm.nih.gov/pubmed/34925441
http://dx.doi.org/10.3389/fgene.2021.730491
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