Oxidative stress reprograms benign prostatic hyperplasia microenvironments: insights from integrative multi-omics and machine learning

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Authors: Jie Chen, Jingxing Bai, Bo Chen, Yin Huang, Jinze Li, Zeyu Chen, Biao Ran, Qiang Wei, Jianzhong Ai, Liangren Liu, Dehong Cao
Cited by: 1
References: 23

Abstract

BACKGROUND: Oxidative stress (OS) is increasingly implicated in benign prostatic hyperplasia (BPH), yet the underlying cellular programs remain unclear. We integrated multi-omics and machine learning to identify OS-associated biomarkers and to characterize OS-linked stromal states, with targeted experimental validation. METHODS: Two bulk transcriptomic datasets (12 BPH, 16 controls) were integrated to identify DEGs and OS-associated DEGs, followed by WGCNA, enrichment analyses, and four machine-learning algorithms to prioritize hub genes and build a diagnostic nomogram. Consensus clustering defined molecular subtypes. Candidate compounds were screened in silico. Single-cell RNA-seq (124,616 cells) and spatial transcriptomics were analyzed for OS scoring, trajectories, and inferred intercellular communication. Experimentally, WPMY-1 prostatic stromal cells were exposed to LPS to induce OS; intracellular ROS (flow cytometry), ACOX2 expression (RT-qPCR/western blot), proliferation (EdU), and apoptosis (Annexin V) were assessed under ACOX2 overexpression or shRNA knockdown. ACOX2 expression in human prostate tissues was evaluated by immunohistochemistry. RESULTS: We identified 499 DEGs and 26 OS-DEGs. Machine learning converged on three upregulated hub genes: ACOX2, CTSB, and SERPINF1, which with diagnostic AUCs of 0.880 (0.753-1.000), 0.828 (0.663-0.993), and 0.854 (0.711-0.997); however, given the modest sample size, these findings should be interpreted as hypothesis-generating. Two BPH subtypes were identified (immune-infiltrated vs. non-immune). Single-cell analyses showed elevated OS scores across cell types, highest in fibroblasts; ACOX2-high fibroblasts were expanded in BPH and exhibited trajectory-associated increases in ACOX2 with enriched inferred signaling (including TNFSF12-TNFRSF12A). Spatial transcriptomics revealed regional OS heterogeneity and spatial association of hub-gene expression with OS-enriched areas. In vitro, LPS increased ROS and upregulated ACOX2, ACOX2 overexpression increased proliferation and reduced apoptosis, whereas knockdown showed opposite effects and attenuated LPS-associated proliferative phenotypes. IHC showed stronger ACOX2 staining in hyperplastic vs. normal prostate tissues. CONCLUSIONS: These results nominate ACOX2, CTSB, and SERPINF1 as candidate OS-associated markers in BPH and support a hypothesis-generating multi-omics signature that warrants validation in larger independent human cohorts. Experimental perturbation and tissue staining provide validation for an ACOX2-associated activation-like phenotype under OS, motivating biomarker-guided stratification and OS-targeted therapeutic exploration.

Fields of Study & Subjects

Urinary Bladder and Prostate Research Ferroptosis and cancer prognosis Machine Learning in Bioinformatics

Publication details

Journal / source
Journal of Translational Medicine
Publisher
Springer Science and Business Media LLC
Volume
24
Issue
1
Publication date
1 April 2026
Language
EN