ArticleFrontiers in surgery2022
Identification of Bladder Cancer Subtypes Based on Necroptosis-Related Genes, Construction of a Prognostic Model.
Article in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 12 citations in OpenAlex.
- Integrated bioinformatics analyses for GSDMB in carcinogenesis and progression of bladder cancer.Translational andrology and urology · 2026Article
- Identification of Necroptosis and Immune Infiltration in Heart Failure Through Bioinformatics Analysis.Journal of inflammation research · 2025Article
- Article
- Identification of a Novel Mesenchymal Stem Cell-Related Signature for Predicting the Prognosis and Therapeutic Responses of Bladder Cancer.Stem cells international · 2024Article
- Article
- CERCAM is a prognostic biomarker associated with immune infiltration of macrophage M2 polarization in head and neck squamous carcinoma.BMC oral health · 2023Article
- Identification and validation of novel signature associated with hepatocellular carcinoma prognosis using Single-cell and WGCNA analysis.International journal of medical sciences · 2023Article
- Identification and Validation of Prognosis-Related Necroptosis Genes for Prognostic Prediction in Hepatocellular Carcinoma.Journal of oncology · 2022Article
- Identification of necroptosis subtypes and development of necroptosis-related risk score model for in ovarian cancer.Frontiers in genetics · 2022Article
- Exploration of the Prognostic Value of PANoptosis-Related Genes in Bladder Cancer.American journal of men's healthArticle
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6 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Necroptosis is associated with the development of many tumors but in bladder cancer the tumor microenvironment (TME) and prognosis associated with necroptosis is unclear. Methods: We classified patients into different necroptosis subtypes by the expression level of NRGS (necroptosis-related genes) and analyzed the relationship between necroptosis subtypes of bladder cancer and TME, then extracted differentially expressed genes (DEGS) of necroptosis subtypes, classified patients into different gene subtypes according to DEGS, and performed univariate COX analysis on DEGS to obtain prognosis-related DEGS. All patients included in the analysis were randomized into the Train and Test groups in a 1:1 ratio, and the prognostic model was obtained using the LASSO algorithm and multivariate COX analysis with the Train group as the sample, and external validation of the model was conducted using the GSE32894. Results: Two necroptosis subtypes and three gene subtypes were obtained by clustering analysis and the prognosis-related DEGS was subjected to the LASSO algorithm and multivariate COX analysis to determine six predictors to construct the prognostic model using the formula: riskScore = CERCAM × 0.0035 + POLR1H × -0.0294 + KCNJ15 × -0.0172 + GSDMB × -0.0109 + EHBP1 × 0.0295 + TRIM38 × -0.0300. The results of the survival curve, roc curve, and risk curve proved the reliability of the prognostic model by validating the model with the test group and the results of the calibration chart of the Nomogram applicable to the clinic also showed its good accuracy. Necroptosis subtype A with high immune infiltration had a higher risk score than necroptosis subtype B, gene subtype B with low immune infiltration had a lower risk score than gene subtypes A and C, CSC index was negatively correlated with the risk score and drug sensitivity prediction showed that commonly used chemotherapeutic agents were highly sensitive to the high-risk group. Conclusion: Our analysis of NRGS in bladder cancer reveals their potential role in TME, immunity, and prognosis. These findings may improve our understanding of necroptosis in bladder cancer and provide some reference for predicting prognosis and developing immunotherapies.
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