ArticleZhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences2023
Classification of bladder cancer based on immune cell infiltration and construction of a risk prediction model for prognosis.
Article in Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- HOXB5 in precision oncology: regulatory networks, functional duality, and clinical prospects.Journal of translational medicine · 2026Review
- Aging associated immunosenescence in rheumatoid arthritis identified by machine learning and single cell profiling.Scientific reports · 2025Article
- ProSAAS neuropeptides and receptors GPR171 and GPR83: Potential therapeutic applications for pain, anxiety, and body weight regulation.The Journal of pharmacology and experimental therapeutics · 2025Review
- A novel prognostic model based on epithelial cell progression genes identifies OAS1 as a suppressor of bladder cancer aggressiveness.Frontiers in molecular biosciences · 2025Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo classify bladder cancer based on immune cell infiltration score and to construct a prognosis assessment model of patients with bladder cancer.
methodsThe transcriptome data and clinical data of breast cancer patients were obtained from the The Cancer Genome Atlas (TCGA) database. Single sample gene set enrichment analysis was used to calculate the infiltration scores of 16 immune cells. The classification of breast cancer patients was achieved by unsupervised clustering, and the sensitivity of patients with different types to immunotherapy and chemotherapy was analyzed. The key modules significantly related to the infiltration of key immune cells were identified by weighted correlation network analysis (WGCNA), and the key genes in the modules were identified. A risk scoring model and a nomogram for prognosis assessment of bladder cancer patients were constructed and verified.
resultsB cells, mast cells, neutrophils, T helper cells and tumor infiltrating lymphocytes were determined to be the key immune cells of bladder cancer. The patients were clustered into two groups (Cluster 1 ´ and Custer 2) based on immune cell infiltration scores. Compared with patients with Cluster 1 ´, patients with Cluster 2 were more likely to benefit from immunotherapy (
conclusionsAccording to the immune cell infiltration score, bladder cancer patients can be classified. Furthermore, bladder cancer prognosis risk scoring model and nomogram based on key immune cell-related genes have high accuracy in predicting the prognosis of bladder cancer patients.
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