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Updated: Sep 17, 2025
An Orthotopic Bladder Cancer Model for Gene Delivery Studies
Published on: December 1, 2013
Comprehensive analysis of phagocytosis regulatory genes in bladder cancer: implications for prognosis and
Xueming Ma1,2,3, Dongnuan Yao1,2,3, Weitao Yu1,2,3
1Department of Urology, The Second Hospital of Lanzhou University, Lanzhou, China.
Background:
Bladder cancer is a common malignant tumor of the urinary system. Its incidence and mortality rates are on the rise, and the existing treatment methods are difficult to meet the prognostic needs of patients. Phagocytosis plays a crucial role in tumor immune surveillance and the regulation of the tumor microenvironment. Phagocytosis regulatory genes (PRGs) are involved in regulating the immune response against tumor cells, and in-depth research on them in bladder cancer is extremely urgent.
Methods:
Multi-omics data from the TCGA and GEO databases were integrated, and strict data preprocessing was carried out. A variety of algorithms and analysis techniques, such as Kaplan-Meier analysis, Cox regression analysis, and ConsensusClusterPlus clustering analysis, were used to identify PRGs related to the prognosis of bladder cancer patients, and functional analysis and clustering analysis were conducted in depth. A prognostic model was constructed and verified, and the risk score was calculated. At the same time, the relationships between the model and the tumor microenvironment (TME), immune infiltration, mutation, and drug sensitivity were comprehensively analyzed.
Results:
It was found that 37 genes had a strong positive correlation with the macrophage score, and 200 PRGs were significantly enriched in immune-related biological processes and pathways. The patients were divided into PRG cluster A and PRG cluster B. Patients in PRG cluster A had a worse survival outcome and were closely related to higher tumor grades, stages, and the infiltration of specific immune cells. A total of 1,696 differentially expressed genes and two phagocytosis-related gene subtypes were identified. The constructed prognostic model showed excellent predictive performance, and the areas under the curves of survival rates at different times were all high in both the training set and the test set. Finally, the drug sensitivity analysis showed that high-risk patients benefited more from immunotherapy and chemotherapy drugs.
Conclusion:
This study has greatly deepened the understanding of the potential molecular mechanisms of bladder cancer, provided new insights and valuable potential therapeutic targets for the precision treatment of bladder cancer, and is expected to promote the innovation and optimization of bladder cancer treatment strategies.
