Identifying hub genes and common biological pathways between COVID-19 and benign prostatic hyperplasia by machine learning algorithms

Aug 5, 2026

Upload by Himbo

This original research examines potential biological targets and shared mechanisms linking SARS-CoV-2 infection with benign prostatic hyperplasia (BPH) and its related symptoms. Public GEO expression datasets for COVID-19 and BPH were analyzed to derive common differentially expressed genes, followed by PPI, GO enrichment, and KEGG pathway mapping. Three machine-learning approaches identified five hub genes, validated in independent datasets, and CIBERSORT supported immune-cell associations. The study further proposes drug candidates and small molecules for therapeutic exploration.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages14

Reading Time35 min

AccessFree to download

Background

Methods

Results

Conclusion

Keywords

Introduction

TYPE Original Research PUBLISHED 23 June 2023 DOI 10.3389/fimmu.2023.1172724 OPEN ACCESS EDITED BY William Tolbert, Henry M Jackson Foundation for the Advancement of Military Medicine (HJF), United States REVIEWED BY Linda Vignozzi, University of Florence, Italy Yupeng Wu, First Afﬁliated Hospital of Fujian Medical University, China Yuxuan Song, Peking University People ’s Hospital, China *CORRESPONDENCE Xiaoqiang Liu [xiaoqiangliu1@163.com](xiaoqiangliu1@163.com) †These authors have contributed equally to this work RECEIVED 23 February 2023 ACCEPTED 07 June 2023 PUBLISHED 23 June 2023 CITATION Zhou H, Xu M, Hu P, Li Y, Ren C, Li M, Pan Y, Wang S and Liu X (2023) Identifying hub genes and common biological pathways between COVID-19 and benign prostatic hyperplasia by machine learning algorithms. Front. Immunol. 14:1172724 . doi: 10.3389/fimmu.2023.1172724 COPYRIGHT © 2023 Zhou, Xu, Hu, Li, Ren, Li, Pan, Wang and Liu. 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. Identifying hub genes and common biological pathways between COVID-19 and benign prostatic hyperplasia by machine learning algorithms Hang Zhou 1†, Mingming Xu 1†, Ping Hu 2†, Yuezheng Li 1, Congzhe Ren 1, Muwei Li 1, Yang Pan 1, Shangren Wang 1 and Xiaoqiang Liu 1* 1 Department of Urology, Tianjin Medical University General Hospital, Tianjin, China, 2 Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China Background: COVID-19, a serious respiratory disease that has the potential to affect numerous organs, is a serious threat to the health of people around the world. The objective of this article is to investigate the potential biological targetsand mechanisms by which SARS-CoV-2 affects benign prostatic hyperplasia (BPH) and related symptoms. Methods: We downloaded the COVID-19 datasets (GSE157103 and GSE166253) and the BPH datasets (GSE7307 and GSE132714) from the Gene Expression Omnibus (GEO) database. In GSE157103 and GSE7307, differentially expressed genes (DEGs) were found using the “Limma” package, and the intersection was utilized to obtain common DEGs. Further analyses followed, including those using Protein-Protein Interaction (PPI), Gene Ontology (GO) function enrichment analysis, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) . Potential hub genes were screened using three machine learning methods, and they were later veriﬁed using GSE132714 and GSE166253 . The CIBERSORT analysis and the identiﬁcation of transcription factors, miRNAs, and drugs as candidates were among the subsequent analyses. Results: We identiﬁed 97 common DEGs from GSE157103 and GSE7307 . According to the GO and KEGG analyses, the primary gene enrichment pathways were immune-related pathways. Machine learning methods were used to identify ﬁve hub genes (BIRC5, DNAJC4, DTL, LILRB2, and NDC80) . They had good diagnostic properties in the training sets and were validated in the validation sets. According to CIBERSORT analysis, hub genes were closely related to CD4 memory activated of T cells, T cells regulatory and NK cells activated. The top 10 drug candidates (lucanthone, phytoestrogens, etoposide, dasatinib, piroxicam, pyrvinium, rapamycin, niclosamide, genistein, and testosterone) will also be evaluated by the P value, which is expected to be helpful for the treatment of COVID-19-infected patients with BPH. Frontiers in Immunology 01 [frontiersin.org](frontiersin.org) Conclusion: Our ﬁndings reveal common signaling pathways, possible biological targets, and promising small molecule drugs

FAQs

本文的研究目的是什么？

研究旨在探讨SARS-CoV-2影响BPH及相关症状时可能存在的生物学靶点与共同机制。

研究使用了哪些数据与方法来筛选关键基因？

从GEO获取COVID-19与BPH表达数据，使用Limma筛选差异基因并取交集；随后结合PPI、GO与KEGG富集分析，并用三种机器学习方法筛选枢纽基因。

枢纽基因与免疫细胞的关系如何验证？

通过CIBERSORT分析，结果显示枢纽基因与CD4记忆活化T细胞、T细胞调节及被活化的NK细胞密切相关，并在独立数据集中进行验证。

Aug 5, 2026

Upload by Himbo