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ORIGINAL RESEARCH article

Front. Immunol.
Sec. Cancer Immunity and Immunotherapy
Volume 15 - 2024 | doi: 10.3389/fimmu.2024.1516362
This article is part of the Research Topic Big Data and Precision Medicine: Diagnosis and Treatment, Drug Discovery, and Integration of Multiple Omics View all articles

Immune-Related Diagnostic Markers for Benign Prostatic Hyperplasia and Their Potential as Drug Targets

Provisionally accepted
YaXuan Wang YaXuan Wang 1Jing Wang Jing Wang 2Jibin Liu Jibin Liu 3Haixia Zhu Haixia Zhu 3*
  • 1 First Affiliated Hospital of Harbin Medical University, Harbin, China
  • 2 Affiliated Jinling Hospital, School of Medicine, Nanjing University, Nanjing, Jiangsu Province, China
  • 3 Nantong Tumor Hospital, Nantong, Jiangsu Province, China

The final, formatted version of the article will be published soon.

    Background: Benign prostatic hyperplasia (BPH) is a common issue among older men. Diagnosis of BPH currently relies on imaging tests and assessment of urinary flow rate due to the absence of definitive diagnostic markers. Developing more accurate markers is crucial to improve BPH diagnosis.The BPH dataset utilized in this study was sourced from the Gene Expression Omnibus (GEO). Initially, differential expression and functional analyses were conducted, followed by the application of multiple machine learning techniques to identify key diagnostic markers. Subsequent investigations have focused on elucidating the functions and mechanisms associated with these markers. The ssGSEA method was employed to evaluate immune cell scores in BPH samples, facilitating the exploration of the relationship between key diagnostic markers and immune cells. Additionally, molecular docking was performed to assess the binding affinity of these key markers to therapeutic drugs for BPH. Tissue samples from BPH patients were collected for experimental validation of the expression differences of the aforementioned genes.Result: A total of 185 differential genes were identified, comprising 67 up-regulated and 118 down-regulated genes. These genes are implicated in pathways that regulate extracellular matrix tissue composition and cellular responses to transforming growth factor beta stimulation, as well as critical signaling pathways such as AMPK and mTOR. Through the application of various machine learning techniques, DACH1, CACNA1D, STARD13, and RUNDC3B were identified as key diagnostic markers. The ssGSEA algorithm further corroborated the association of these diagnostic genes with diverse immune cells. Moreover, molecular docking analysis revealed strong binding affinities of these markers to tamsulosin and finasteride, suggesting their potential as drug targets. Finally, experimental validation confirmed the expression differences of DACH1, CACNA1D, STARD13, and RUNDC3B in BPH tissues.This study introduces novel immune-related diagnostic markers for BPH and highlights their promise as new drug targets, providing a valuable approach for predictive diagnosis and targeted therapy of BPH.

    Keywords: BPH, biomarkers, machine learning, drug target, immune signatures

    Received: 24 Oct 2024; Accepted: 20 Nov 2024.

    Copyright: © 2024 Wang, Wang, Liu and Zhu. 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) or licensor 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.

    * Correspondence: Haixia Zhu, Nantong Tumor Hospital, Nantong, 226000, Jiangsu Province, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.