ArticleBMC cancer2024
Development of prognostic model incorporating a ferroptosis/cuproptosis-related signature and mutational landscape analysis in muscle-invasive bladder cancer.
Article in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- RRM2/GCH1 signaling decreased cisplatin sensitivity in cervical cancer by modulating the ferroptosis process.Histology and histopathology · 2026Article
- HeptaTB Dx: a diagnostic model leveraging cuproptosis-ferroptosis crosstalk for distinguishing latent from active tuberculosis.Microbiology spectrum · 2026Article
- Article
- 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
- Harnessing ferroptosis for precision oncology: challenges and prospects.BMC biology · 2025Review
- Development of a prognostic model incorporating a cuproptosis-related signature and CNN3 as a predictor in childhood acute myelocytic leukemia.Frontiers in oncology · 2024Article
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5 authors.
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Abstract
backgroundMuscle-invasive bladder cancer (MIBC) is a prevalent and aggressive malignancy. Ferroptosis and cuproptosis are recently discovered forms of programmed cell death (PCD) that have attracted much attention. However, their interactions and impacts on MIBC overall survival (OS) and treatment outcomes remain unclear.
methodsData from the TCGA-BLCA project (as the training set), cBioPortal database, and GEO datasets (GSE13507 and GSE32894, as the test sets) were utilized to identify hub ferroptosis/cuproptosis-related genes (FRGs and CRGs) and develop a prognostic signature. Differential expression analysis (DEA) was conducted, followed by univariate and multivariate Cox's regression analyses and multiple machine learning (ML) techniques to select genetic features. The performance of the ferroptosis/cuproptosis-related signature was evaluated using Kaplan-Meier (K-M) survival analysis and receiver-operating characteristics (ROC) curves. Mutational and tumour immune microenvironment landscapes were also explored. Real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) experiments confirmed the expression patterns of the hub genes, and functional assays assessed the effects of SCD knockdown on cell viability, proliferation, and migration.
resultsDEA revealed dysregulated FRGs and CRGs in the TCGA MIBC cohort. SCD, DDR2, and MT1A were identified as hub genes. A prognostic signature based on the sum of the weighted expression of these genes demonstrated strong predictive efficacy in the training and test sets. Nomogram incorporating this signature accurately predicted 1-, 3-, and 5-year survival probabilities in the TCGA cohort and GSE13507 dataset. Copy number variation (CNV) and tumour immune microenvironment analysis revealed that high risk score level groups were associated with immunosuppression and lower tumour purity. The associations of risk scores with immunotherapy and chemical drugs were also explored, indicating their potential for guiding treatment for MIBC patients. The dysregulated expression patterns of three hub genes were validated by RT-qPCR experiments.
conclusionsTargeting hub FRGs and CRGs could be a promising therapeutic approach for MIBC. Our prognostic model offers a new framework for MIBC subtyping and can inform personalized therapeutic strategies.
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