Bioinformatic analysis of biological changes involved in pelvic organ prolapse

Author:

Wang Wei Guo1ORCID,Chen Zhang Sen Di1,Sun Ji1,Yang Chun Mei1,He Hong Bo1,Lu Xian Kun2,Wang Wei Yuan3

Affiliation:

1. Department of Integrated Traditional Chinese and Western Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China

2. Science and Technology Department of Sichuan Province, Chengdu, Sichuan, China

3. Department of Pathology, Xiangya Hospital, Central South University, Changsha, Hunan, China.

Abstract

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.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Medicine

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