Sun Yizhang, Yi Xincheng, Zhou Chenchao, Huang Yuhua
Department of Urology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Hum Mutat. 2025 Sep 12;2025:2227219. doi: 10.1155/humu/2227219. eCollection 2025.
Bladder urothelial carcinoma (BLCA) is a prevalent malignant tumor known for its high recurrence rates and limited therapeutic efficacy. Cellular senescence has been extensively shown to inhibit tumorigenesis via cell cycle arrest. Consequently, the identification of senescence-associated biomarkers is essential for enhancing the diagnosis, prognosis, and immunotherapeutic outcomes of BLCA. This study integrated the TCGA-BLCA and GSE13507 datasets to analyze senescence-related genes. ConsensusClusterPlus was employed for cluster analysis, while immune infiltration was assessed using CIBERSORT. A diagnostic and prognostic model for BLCA was developed and validated through the combination of various machine learning algorithms. Experimental validation was conducted using qRT-PCR, colony formation, and Transwell assays to evaluate the functional role of PAQR4. Our study revealed that aging-related samples demonstrated improved survival rates and a lower incidence of high-grade tumors. Cluster analysis identified two distinct subgroups of BLCA characterized by unique immune infiltration profiles and varying responses to immune checkpoint blockade. The diagnostic and prognostic models developed from aging-related genes were subsequently validated. Notably, PAQR4 was identified as a critical aging-related gene linked to poor prognosis and an immunosuppressive microenvironment. The knockdown of PAQR4 significantly inhibited the proliferation and metastasis of BLCA cells. PAQR4 is a novel biomarker and therapeutic target for BLCA, influencing cellular senescence, immune evasion, and metastasis. This study provides insights into the senescence-related mechanisms and offers tools for precision diagnosis and the optimization of immunotherapy in BLCA.