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Bioinformatic analysis of biological changes involved in pelvic organ prolapse
The molecular mechanisms involved in the pathogenesis of pelvic organ prolapse (POP) remain unclear. This study aimed to identify key molecules involved in the pathogenesis and progression of POP. Differentially expressed genes (DEGs) were identified based on gene expression data extracted from the...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10237711/ https://www.ncbi.nlm.nih.gov/pubmed/37266648 http://dx.doi.org/10.1097/MD.0000000000033823 |
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author | Wang, Wei Guo Chen, Zhang Sen Di Sun, Ji Yang, Chun Mei He, Hong Bo Lu, Xian Kun Wang, Wei Yuan |
author_facet | Wang, Wei Guo Chen, Zhang Sen Di Sun, Ji Yang, Chun Mei He, Hong Bo Lu, Xian Kun Wang, Wei Yuan |
author_sort | Wang, Wei Guo |
collection | PubMed |
description | The molecular mechanisms involved in the pathogenesis of pelvic organ prolapse (POP) remain unclear. This study aimed to identify key molecules involved in the pathogenesis and progression of POP. Differentially expressed genes (DEGs) were identified based on gene expression data extracted from the GSE53868, GSE28660, and GSE12852 datasets in the gene expression omnibus database. The R software was used for data mining, and gene ontology functional annotation and Kyoto encyclopedia of genes and genomes enrichment analyses were performed to explore the biological functions of DEGs. A protein–protein interaction network (PPI) was constructed using the Search Tool for the Retrieval of Interacting Genes database, and hub genes were identified by the Cytoscape plug-in cytoHubba. In addition, the CIBERSORT algorithm was used to analyze and evaluate immune cell infiltration in POP tissues. A total of 92 upregulated DEGs were identified and subjected to enrichment analysis. Gene ontology analysis revealed that these DEGs were associated with response to hormones, positive regulation of cell death, collagen-containing extracellular matrix, and extracellular matrix. Kyoto encyclopedia of genes and genomes pathway analysis showed that the upregulated genes were mainly enriched in the phosphatidylinositol 3-kinase–AKT signaling pathway. The PPI network was structured. Nodes in the PPI network were associated with structural molecular activity and collagen-containing extracellular matrix. A total of 10 hub genes were identified, namely, CDKN1A, IL-6, PPARG, ADAMTS4, ADIPOQ, AREG, activating transcription factor 3, CCL2, CD36, and Cell death-inducing DNA fragmentation factor-like effector A. Furthermore, patients with POP were found to have a higher abundance of CD8-positive T cells in the 3 gene expression omnibus datasets. The abundance of CD8-positive T cells was negatively correlated with that of follicular helper T cells (Pearson correlation coefficient = −0.34, P < .01) or gamma delta T cells (Pearson correlation coefficient = −0.33, P < .01). But was positively correlated with that of M2 macrophages (Pearson correlation coefficient = 0.35, P < .01) and activated memory CD4 T cells (Pearson correlation coefficient = 0.34, P < .01). Altogether, PPARG, ADAMTS4, ADIPOQ, AREG, CD36, and Cell death-inducing DNA fragmentation factor-like effector A genes were discovered in the POP process for the first time, which should be intensively investigated. |
format | Online Article Text |
id | pubmed-10237711 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-102377112023-06-03 Bioinformatic analysis of biological changes involved in pelvic organ prolapse Wang, Wei Guo Chen, Zhang Sen Di Sun, Ji Yang, Chun Mei He, Hong Bo Lu, Xian Kun Wang, Wei Yuan Medicine (Baltimore) 5600 The molecular mechanisms involved in the pathogenesis of pelvic organ prolapse (POP) remain unclear. This study aimed to identify key molecules involved in the pathogenesis and progression of POP. Differentially expressed genes (DEGs) were identified based on gene expression data extracted from the GSE53868, GSE28660, and GSE12852 datasets in the gene expression omnibus database. The R software was used for data mining, and gene ontology functional annotation and Kyoto encyclopedia of genes and genomes enrichment analyses were performed to explore the biological functions of DEGs. A protein–protein interaction network (PPI) was constructed using the Search Tool for the Retrieval of Interacting Genes database, and hub genes were identified by the Cytoscape plug-in cytoHubba. In addition, the CIBERSORT algorithm was used to analyze and evaluate immune cell infiltration in POP tissues. A total of 92 upregulated DEGs were identified and subjected to enrichment analysis. Gene ontology analysis revealed that these DEGs were associated with response to hormones, positive regulation of cell death, collagen-containing extracellular matrix, and extracellular matrix. Kyoto encyclopedia of genes and genomes pathway analysis showed that the upregulated genes were mainly enriched in the phosphatidylinositol 3-kinase–AKT signaling pathway. The PPI network was structured. Nodes in the PPI network were associated with structural molecular activity and collagen-containing extracellular matrix. A total of 10 hub genes were identified, namely, CDKN1A, IL-6, PPARG, ADAMTS4, ADIPOQ, AREG, activating transcription factor 3, CCL2, CD36, and Cell death-inducing DNA fragmentation factor-like effector A. Furthermore, patients with POP were found to have a higher abundance of CD8-positive T cells in the 3 gene expression omnibus datasets. The abundance of CD8-positive T cells was negatively correlated with that of follicular helper T cells (Pearson correlation coefficient = −0.34, P < .01) or gamma delta T cells (Pearson correlation coefficient = −0.33, P < .01). But was positively correlated with that of M2 macrophages (Pearson correlation coefficient = 0.35, P < .01) and activated memory CD4 T cells (Pearson correlation coefficient = 0.34, P < .01). Altogether, PPARG, ADAMTS4, ADIPOQ, AREG, CD36, and Cell death-inducing DNA fragmentation factor-like effector A genes were discovered in the POP process for the first time, which should be intensively investigated. Lippincott Williams & Wilkins 2023-06-02 /pmc/articles/PMC10237711/ /pubmed/37266648 http://dx.doi.org/10.1097/MD.0000000000033823 Text en Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC) (https://creativecommons.org/licenses/by-nc/4.0/) , where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. |
spellingShingle | 5600 Wang, Wei Guo Chen, Zhang Sen Di Sun, Ji Yang, Chun Mei He, Hong Bo Lu, Xian Kun Wang, Wei Yuan Bioinformatic analysis of biological changes involved in pelvic organ prolapse |
title | Bioinformatic analysis of biological changes involved in pelvic organ prolapse |
title_full | Bioinformatic analysis of biological changes involved in pelvic organ prolapse |
title_fullStr | Bioinformatic analysis of biological changes involved in pelvic organ prolapse |
title_full_unstemmed | Bioinformatic analysis of biological changes involved in pelvic organ prolapse |
title_short | Bioinformatic analysis of biological changes involved in pelvic organ prolapse |
title_sort | bioinformatic analysis of biological changes involved in pelvic organ prolapse |
topic | 5600 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10237711/ https://www.ncbi.nlm.nih.gov/pubmed/37266648 http://dx.doi.org/10.1097/MD.0000000000033823 |
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