ArticleScientific reports2024
Identification of bladder cancer subtypes and predictive signature for prognosis, immune features, and immunotherapy based on immune checkpoint genes.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Single-cell and immune-context integration identifies basement-membrane/metastasis signatures that sharpen bladder-cancer diagnosis and prognosis.Discover oncology · 2026Article
- Extracellular volume fraction quantification by equilibrium contrast-enhanced CT via automated segmentation predicts survival outcomes in bladder cancer: a propensity score-matched study.Annals of medicine · 2025Article
- Identification and validation of a 9-RBPs-related gene signature associated with prognosis and immune infiltration in bladder cancer based on bioinformatics analysis and machine learning.Translational andrology and urology · 2025Article
- Proteomic and In Silico Analyses Highlight Complement System's Role in Bladder Cancer Immune Regulation.Medicina (Kaunas, Lithuania) · 2025Article
- Explainable machine learning model predicts response to adjuvant therapy after radical cystectomy in bladder cancer.Frontiers in oncology · 2025Article
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Authors and funding
9 authors.
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Abstract
Immunotherapy based on immune checkpoint genes (ICGs) has recently made significant progress in the treatment of bladder cancer patients, but many patients still cannot benefit from it. In the present study, we aimed to perform a comprehensive analysis of ICGs in bladder cancer tissues with the aim of evaluating patient responsiveness to immunotherapy and prognosis. We scored ICGs in each BLCA patient from TCGA and GEO databases by using ssGSEA and selected genes that were significantly associated with ICGs scores by using the WCGNA algorithm. NMF clustering analysis was performed to identify different bladder cancer molecular subtypes based on the expression of ICGs-related genes. Based on the immune related genes differentially expressed among subgroups, we further constructed a novel stratified model containing nine genes by uni-COX regression, LASSO regression, SVM algorithm and multi-COX regression. The model and the nomogram constructed based on the model can accurately predict the prognosis of bladder cancer patients. Besides, the patients classified based on this model have large differences in sensitivity to immunotherapy and chemotherapy, which can provide a reference for individualized treatment of bladder cancer.
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