ORIGINAL RESEARCH article
Front. Oncol.
Sec. Molecular and Cellular Oncology
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1604169
Untargeted metabolomics revealed urinary metabolic pattern for discriminating prostate cancer from benign prostatic hyperplasia in Chinese participants
Provisionally accepted- 1Department of Urology, The Second Hospital of Jiaxing, Jiaxing, China
- 2Jiaxing University Master Degree Cultivation Base, Zhejiang Chinese Medical University, Hangzhou, China
- 3Department of science and education, The Second Hospital of Jiaxing, Jiaxing, China
- 4Zhejiang Key Laboratory of Digital Technology in Medical Diagnostics, Dian Diagnostics Group Co., Ltd., Hangzhou, Jiangsu Province, China
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Introduction: Precise screening and discriminating of prostatic hyperplasia (PH) could avoid unnecessary biopsy and overdiagnosis. However, the metabolic pattern of patients with prostatic hyperplasia in Chinese population is rarely reported.Methods: Urine samples of Chinese participants with prostate cancer (PCa), benign prostatic hyperplasia (BPH) and non-prostate diseases (NPD) were detected with four ultra-performance liquid chromatography/tandem mass spectrometric (UPLC-MS/MS) methods to profile the metabolic disturbance.In patients with PH, the most significant dysregulation was observed in metabolites categorized as lipid or amino acid, especially those involved in histidine metabolism, purine metabolism, tryptophan metabolism and tyrosine metabolism. For discrimination BPH from PCa, apart from previouly reported metabolites related to phospholipid metabolism or tryptophan metabolism, metabolites of dipeptides and androgenic steroids, such as leucylhydroxyproline and etiocholanolone glucuronide, also exhibited potential to discriminate PCa from BPH.This study conducts precise detection of urinary metabolomic pattern for patients with benign prostatic hyperplasia or prostate cancer, and could inform their potential application as discriminant biomarkers.
Keywords: Prostatic Hyperplasia, prostate cancer, Urinary metabolomics, discriminant biomarkers, untargeted metabolomics
Received: 01 Apr 2025; Accepted: 10 Jun 2025.
Copyright: © 2025 Tang, Guo, Zou, Wang, Sheng, Shen, Sun, Li and Shen. 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:
Chun Sun, Department of Urology, The Second Hospital of Jiaxing, Jiaxing, China
Shuo Li, Zhejiang Key Laboratory of Digital Technology in Medical Diagnostics, Dian Diagnostics Group Co., Ltd., Hangzhou, Jiangsu Province, China
Ruilin Shen, Department of Urology, The Second Hospital of Jiaxing, Jiaxing, China
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