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PMID: 41653270 Published · epublish English

Development and validation of a novel senescence-associated gene signature for prediction of survival and endocrine-disrupting chemicals in bladder cancer.

Discover oncology ·Vol. 17 ·No. 1 ·2026-02-07

Qin M, Xie G, Xie H, Lin B, Dai Z, Cheng Z, Wang L, Zhang J, Wang F

Abstract

Endocrine-disrupting chemicals (EDCs) are prevalent in various aspects of daily life, impacting the homeostasis of physiological processes and potentially contributing to the pathogenesis of cancer. Bladder cancer (BLCA) is the most common malignancy of the urinary system and one of the most prevalent malignancies globally. Cellular senescence is increasingly recognized as a key factor in cancer development. However, research remains limited regarding how EDCs influence BLCA through senescence-related genes (SRGs). In this study, expression data and clinical information were sourced from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Senescence phenotype-related differentially expressed genes (DEGs) were identified. A senescence-related risk model was developed and validated by TCGA and GEO datasets. EDCs targeting DEGs, were extrapolated using the chemical toxicogenomic database (CTD). A Sankey diagram is employed to visualize the relationships between EDCs and key genes, identifying AKR1B1, EPHA3, IRF5, PGR, SREBF1 and TEAD4, as key factors in predicting cellular senescence in BLCA. Finally, molecular docking analysis was conducted to investigate the interaction between key genes and EDCs, thereby validating their feasibility. Our findings provide new insights into the role of SRGs in BLCA stratification and precision medicine. Furthermore, we elucidated the relationship between EDC-mediated cell SRGs and the pathogenesis of BLCA.

Keywords
Bladder cancer Endocrine-disrupting chemicals Molecular docking Senescence
Article Info
Journal
Discover oncology
Abbr.
Discov Oncol
ISSN
2730-6011
Published
2026-02-07
Language
English
Country/Region
United States
NLM ID
101775142
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