Identification of Prognosis-Related Genes in Bladder Cancer Microenvironment across TCGA Database.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33204728", "kind": "science-record", "revision": 7, "content_hash": "sha256:c89ef2f52bd818d94eba9686b4dab5656440348dec11649e7b9ac7316f26f618", "created_at": "2026-11-01T15:41:16Z", "updated_at": "2026-11-01T22:02:33Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Prognosis-Related Genes in Bladder Cancer Microenvironment across TCGA Database.", "doi": "10.1155/2020/9143695", "pmid": "33204728", "authors": ["Xin Zhao", "Yu Tang", "Haoyu Ren", "Yi Lei"], "journal": "BioMed research international", "year": 2020, "abstract": "BACKGROUND: Bladder cancer (BCa) is a common urothelial malignancy. The Cancer Genome Atlas (TCGA) database allows for an opportunity to analyze the relationship between gene expression and clinical outcomes in bladder cancer patients. This study is aimed at identifying prognosis-related genes in the bladder cancer microenvironment.\nMETHODS: Immune scores and stromal scores were calculated by applying the ESTIMATE algorithm. We divided bladder cancer patients into high and low groups based on their immune/stromal scores. Then, differentially expressed genes (DEGs) were identified in bladder cancer patients based on the TCGA database. We evaluated the correlation between immune/stromal scores and clinical characteristics as well as prognosis. Finally, we validated identified genes associated with bladder cancer prognosis through a cohort study in the Gene Expression Omnibus (GEO) database.\nRESULTS: A higher stromal score was associated with female (vs. malep = 0.037), age > 65 (vs.age ≤ 65 p = 0.015), T3/4 (vs. T1/2,p < 0.001), N status(p = 0.016), and pathological high grade (vs. low gradeP < 0.001). By analyzing DEGs, there were 1125 genes commonly upregulated, and 209 genes were commonly downregulated. Protein-protein interaction networks further showed the important protein that may be involved in the biological behavior and prognosis of BCa, such as FN1, CXCL12, CD3E, LCK, and ZAP70. A total of 14 DEGs were found to be associated with overall survival of bladder cancer. After validation by a cohort of 165 BCa cases with detailed follow-up information from GSE13507, 10 immune-associated DEGs were demonstrated to be predictive of prognosis in BCa. Among them, 5 genes have not been reported previously associated with the prognosis of BCa, including BTBD16, OLFML2B, PRRX1, SPINK4, and SPON2.\nCONCLUSIONS: Our study elucidated tight associations between stromal score and clinical characteristics as well as prognosis in BCa. Moreover, we obtained a group of genes closely related to the prognosis of BCa in the tumor microenvironment.", "claims": [{"id": "claim-method", "statement": "The correlations between clinicopathological parameters and immune/stromal scores were analyzed using a two-side student t test.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33204728", "locator": "sections[7] \"2.5. Statistical Analysis\" paragraph 2", "quote": "The correlations between clinicopathological parameters and immune/stromal scores were analyzed using a two-side student t test."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets supporting the conclusions of this article are available in the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) with the accession numbers GSE13507. All of those studies previously were approved by their respective institutional review boards.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33204728", "locator": "sections[17] \"Data Availability\" paragraph 2", "quote": "The datasets supporting the conclusions of this article are available in the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) with the accession numbers GSE13507. 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