ArticleInternational journal of clinical and experimental pathology2021
Identification of a tumor microenvironment-associated prognostic gene signature in bladder cancer by integrated bioinformatic analysis.
Article in International journal of clinical and experimental pathology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Matricellular Proteins in Bladder Cancer: Context-Dependent Roles in Tumor Promotion and Suppression.International journal of molecular sciences · 2026Review
- Article
- TGFB1I1 promotes cell proliferation and migration in urothelial carcinoma.The Kaohsiung journal of medical sciences · 2024Article
- Article
- Role of anoikis-related gene PLK1 in kidney renal papillary cell carcinoma: a bioinformatics analysis and preliminary verification on promoting proliferation and migration.Frontiers in pharmacology · 2023Article
- Analysis of immunotherapeutic response-related signatures in esophageal squamous-cell carcinoma.Frontiers in immunology · 2023Article
- Cytoskeletal Protein Palladin in Adult Gliomas Predicts Disease Incidence, Progression, and Prognosis.Cancers · 2022Article
- Identification of a novel prognosis-associated ceRNA network in lung adenocarcinoma via bioinformatics analysis.Biomedical engineering online · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
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Abstract
Bladder cancer is a common malignancy in the urinary system. Stromal and immune cells in tumor microenvironments, including those in the bladder cancer microenvironment, can serve as prognostic markers. However, the complex processes of bladder cancer necessitate large-scale evaluation to better understand the underlying mechanisms and identify biomarkers for diagnosis and treatment. We used the Estimation of STromal and Immune cells in MAlignant Tumors using Expression data algorithm to assess the association between stromal and immune cell-related genes and overall survival of patients with bladder cancer. We also identified and evaluated differentially expressed genes between cancer and non-cancer tissues from The Cancer Genome Atlas. Patients were categorized into different prognosis groups according to their stromal/immune scores based on differential gene expression. In addition, the prognostic value of the differentially expressed genes was assessed in a separate validation cohort using the Gene Expression Omnibus microarray dataset GSE13507, which identified nine genes (
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Registered trials
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