ArticleFrontiers in immunology2023
Identification of a glutamine metabolism reprogramming signature for predicting prognosis, immunotherapy efficacy, and drug candidates in bladder cancer.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 21 citations in OpenAlex.
- Evaluation of FASP for Mass Spectrometry-Based Untargeted Metabolomics Analysis of Urine Samples.Journal of proteome research · 2026Article
- A systematic characterization of amino acid metabolism-related genes reveals molecular subtypes and a prognostic signature in bladder cancer.Frontiers in oncology · 2026Article
- Hypoxia-induced PYCR1 regulates glycolysis and histone lactylation to promote bladder cancer progression and metastasis via SLC6A14/Glutamine metabolism.Cancer biology & therapy · 2025Article
- Targeting glutamine metabolism as a potential target for cancer treatment.Journal of experimental & clinical cancer research : CR · 2025Review
- Advancing Cancer Treatment: A Review of Immune Checkpoint Inhibitors and Combination Strategies.Cancers · 2025Review
- Identification of an Amino Acid Metabolism Reprogramming Signature for Predicting Prognosis, Immunotherapy Efficacy, and Drug Candidates in Colon Cancer.Applied biochemistry and biotechnology · 2025Article
- Metabolic Reprogramming in Urological Tumors: New Perspectives from Tumor Metabolic Phenotypes to Therapeutic Targets.International journal of biological sciences · 2025Review
- Establishment of an anaplastic stratification signature for gastric cancer based on diverse regulated cell-death.Frontiers in immunology · 2025Article
- Identification of potential biomarkers for hepatocellular carcinoma based on machine learning and bioinformatics analysis.Discover oncology · 2024Article
- A Machine Learning Computational Framework Develops a Multiple Programmed Cell Death Index for Improving Clinical Outcomes in Bladder Cancer.Biochemical genetics · 2024Article
- Integrating machine learning and multi-omics analysis to develop an asparagine metabolism immunity index for improving clinical outcome and drug sensitivity in lung adenocarcinoma.Immunologic research · 2024Article
- Article
- Deciphering glutamine metabolism patterns for malignancy and tumor microenvironment in clear cell renal cell carcinoma.Clinical and experimental medicine · 2024Article
- Integration of multi-omics and clinical treatment data reveals bladder cancer therapeutic vulnerability gene combinations and prognostic risks.Frontiers in immunology · 2023Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Bladder cancer is the most common malignancy of the urinary system. However, patient prognosis and treatment outcomes in bladder cancer are difficult to predict owing to high tumor heterogeneity. Given that abnormal glutamine metabolism has been identified as a key factor driving the progression of bladder cancer, it is necessary to assess the prognosis and therapeutic efficacy of bladder cancer treatments based on an analysis of glutamine metabolism-related genes. Methods: We used bladder cancer sample data downloaded from The Cancer Genome Atlas to identify glutamine metabolism-related genes as prognostic markers, and established a novel Glutamine Metabolism Immunity Index (GMII) based on univariate and multivariate COX regression analyses. On the basis of GMII values, bladder cancer patients were divided into high- and low-risk groups, and systematic analysis was conducted for clinical features, somatic mutations, immune cell infiltration, chemotherapeutic response, and immunotherapeutic efficacy. Candidate small-molecule drugs targeting the GMII core target proteins were identified based on molecular docking analysis. Results: The GMII consisting of eight independent prognostic genes was established to be an excellent tool for predicting the survival in patients with bladder cancer and was validated using multiple datasets. Compared with patients in the high-risk group, those in the low-risk group had significantly better responses to gemcitabine and immune checkpoint blockade. In addition, we predicted 12 potential small-molecule drugs that could bind to three of the GMII core target proteins. Conclusions: The GMII can be used to accurately predict the prognosis and immunotherapeutic response of bladder cancer patients, as well as candidate small-molecule drugs. Furthermore, the novel "Glutamine Metabolism-related Gene"-guided strategy for predicting survival and chemo-immunotherapeutic efficacy may also be applicable for cancers other than bladder cancer.
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