Evidence map›Paper›PMID 41794917›Full record

ArticleScientific reports2026

Key hub genes identification and therapeutic target prediction via multi-validation for the senescence-inflammation axis in prostate cancer.

Ying Wang, Qin Liu, Mei Yi, Yan Liu, Ji'ang'shu He, Han Chao Zhang

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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6 authors.

Ying Wang *Department of Emergency, The Affiliated Hospital and Clinical Medical College of Chengdu University, Chengdu, Sichuan, China.
Qin Liu *Department of Human Anatomy, School of Basic Medical Sciences, Southwest Medical University, Luzhou, Sichuan, China.
Mei YiDepartment of Nephrology and Rheumatology, The Affiliated Hospital and Clinical Medical College of Chengdu University, Chengdu, Sichuan, China.
Yan LiuHospital-Acquired Infection Control Department, The Affiliated Hospital and Clinical Medical College of Chengdu University, Chengdu, Sichuan, China.
Ji'ang'shu HeDepartment of Urology, The Affiliated Hospital and Clinical Medical College of Chengdu University, Chengdu, Sichuan, China.
Han Chao ZhangDepartment of Urology, The Affiliated Hospital and Clinical Medical College of Chengdu University, Chengdu, Sichuan, China. zhanghanchao@cdu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cellular senescence remodels the microenvironment via SASP, and immune inflammation promotes carcinogenesis through DNA damage and immune remodeling; the “senescence-inflammation” vicious cycle formed by these two processes is a core driver of cancer development and progression, yet its mechanism in prostate cancer progression remains unclear. The regulatory mechanisms of “senescence-inflammation” related genes in prostate cancer were revealed, targeted drugs were predicted, and new insights were provided for the clinical treatment of prostate cancer. In this study, gene expression profile data of prostate cancer were obtained from the Gene Expression Omnibus (GEO). Differentially expressed genes were screened out through bioinformatics analysis and verified by experiments; GO and KEGG analyses were used to explore the prostate cancer-specific biological processes and signaling pathways involved, immune infiltration characteristics were revealed by combining immune infiltration tools with single-cell technology, and finally, drugs with therapeutic potential were predicted through core gene target analysis. Prostate cancer-related differentially expressed genes were found to number 203. Notable hub genes included ACTB, RPLP0, TOP2A, TXN, HSP90B1, TAGLN, RPSA, and ANXA2. According to enrichment analysis, apoptosis, cellular senescence, inflammation, and the initiation of immunological responses are the main factors contributing to the development of bladder cancer. The immunological processes of prostate cancer are significantly influenced by memory B cells, CD8 T cells, follicular helper T cells, M1 macrophages, monocytes, and NK cells, as confirmed by immune infiltration and single-cell data. Furthermore, hub genes were found to be significantly expressed in a variety of immune cells by single-cell studies; monocytes and macrophages in particular exhibited high levels of ACTB, RPLP0, RPSA, and ANXA2. We next used Western blotting, PCR, and immunohistochemistry to evaluate these genes’ expression in clinical samples. Lastly, Miconazole, Fostamatinib, Quercetin, Resveratrol, and Regorafenib were shown to be possible important drugs or ingredients for the treatment of prostate cancer by our drug-target interaction prediction analysis. We clarified the mechanism by which immune-inflammatory and aging-related genes contribute to the pathogenesis of prostate cancer. We identified and validated four core genes, namely TXN, TOP2A, ANXA2, and HSP90B1, and predicted potential therapeutic agents, specifically resveratrol and regorafenib. These findings provide a theoretical basis for research on the molecular mechanisms of prostate cancer and its clinical treatment.

Indexed as

Cellular SenescenceInflammationProstatic NeoplasmsBiomarkers, TumorComputational BiologyGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansMaleSignal TransductionTumor MicroenvironmentBiomarkers, TumorBiomarkersDrug-target interaction predictionImmunityInflammationProstate cancer

Identifiers

PMID41794917
PMCPMC13087266

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