Related Experiment Video
Updated: Jul 1, 2025
An Orthotopic Bladder Cancer Model for Gene Delivery Studies
Published on: December 1, 2013
Development of a prognostic model for muscle-invasive bladder cancer using glutamine metabolism
Sida Hao1, Lin Shen2, Pengju Liu2
1Department of Urology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, China; Department of Urology, Zhejiang Integrated Traditional Chinese and Western Medicine Hospital, Hangzhou, 310003, Zhejiang, China.
Background:
Muscle-invasive bladder cancer (MIBC) is distinguished by its pronounced invasiveness and unfavorable prognosis. Immunotherapy and targeted therapy have emerged as key treatment options for various types of cancer. Altered metabolism is a defining characteristic of cancer cells, and there is mounting evidence suggesting the important role of glutamine metabolism (GM) in tumor metabolism. Nevertheless, the relationship between GM and clinical outcomes, immune microenvironment, and immunotherapy in MIBC remains unknown.
Methods:
This study employed Mendelian randomization to explore the causal relationship between blood metabolites and bladder tumors. We systematically evaluated 373 glutamine metabolism-related genes and identified prognostic-related genes, leading to the construction of a glutamine-associated prognostic model. Further analysis confirmed the correlation between high and low-risk groups with the tumor microenvironment, immune cell infiltration, and tumor mutation burden. Subsequently, we assessed the relationship between the risk score and the sensitivity to various immunotherapies and anticancer drugs.
Results:
We identified 14 blood metabolites at the molecular level that have a causal relationship with bladder tumors. At the gene level, the study discussed differentially expressed GM genes in MIBC. First, we established a risk model predicting overall survival (OS) based on GM genes, confirming its reliable predictive ability in MIBC patients and validated it in a GEO cohort. Additionally, a reliable column line chart was created. Secondly, two distinct molecular subtypes were identified, and the associations between different risk groups and tumor microenvironment and immune infiltration were observed. In addition, the predicted risk values correlated with responses to a broad range of pharmaceutical agents.
Conclusion:
In summary, we confirmed the causal relationship between blood metabolites and bladder tumors. Furthermore, a risk scoring model related to glutamine metabolism consisting of 9 genes was developed. This model could potentially serve as a useful tool for predicting prognosis and guiding the treatment of MIBC patients.
