Transient Receptor Potential Melastatin 4 (TRPM4) is associated with an immuno-stimulatory TME and better prognosis in BLCA.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41266683", "kind": "science-record", "revision": 3, "content_hash": "sha256:d5c25155db7939173ea8ab01b1749b28686f3804d839c23a6c94eac50b595474", "created_at": "2026-11-01T20:31:18Z", "updated_at": "2026-11-01T22:15:02Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Transient Receptor Potential Melastatin 4 (TRPM4) is associated with an immuno-stimulatory TME and better prognosis in BLCA.", "doi": "10.1007/s12672-025-04080-z", "pmid": "41266683", "authors": ["Yiqiang Da", "Xuerui Chen", "Lanxin Yu", "Yunxin Li", "Zixu Chen", "Yuyue Zhang", "Hualin Wang", "Zhuang Zhu", "Yuan Liu", "Yao Geng"], "journal": "Discover oncology", "year": 2025, "abstract": "OBJECTIVE: Bladder cancer (BLCA) is one of the most invasive and malignant tumors in the world, thus leading to the urgent need of an accurate and recognizable biomarker. Several previous research has shown that Transient Receptor Potential Melastatin 4 (TRPM4) plays an important role in measuring vascular fragility and endothelial function. However, the role of TRPM4 in tumor hasn't been explored.\nMETHODS: We obtained the clinical data and gene expression profiles of The Cancer Genome Atlas (TCGA) datasets via UCSC Xena. The tumor microenvironment (TME) was also evaluated by the amount of immunomodulators. The role of TRPM4 was demonstrated using the dataset GSE130001 via the website ( http://tisch.comp-genomics.org/ ). We also validated the results of the pathway analysis through the Polymerase Chain Reaction (PCR).\nRESULTS: Patients with higher TRPM4 expression showed better prognosis. We found out that high TRPM4 tended to shape an immuno-stimulatory TME with less T cell exhaustion and lower level of immune overdrive. We demonstrated that TRPM4 could predict the molecular subtype and different therapy options in BLCA. We also found the important influence of TRPM4 in P53 pathway and TNF-a pathway. Last but not least, we developed a prognostic model centered on TRPM4 using ten machine learning algorithms, which showed excellent predictive ability.\nCONCLUSION: High TRPM4 shapes a more immuno-stimulatory tumor microenvironment and can not only predict the immune phenotypes but also predict the clinical phenotypes in BLCA. High TRPM4 predicts better prognosis. TRPM4 is a potential biomarker in the future for identifying the immunogenicity and immune-therapy probability of BLCA.", "claims": [{"id": "claim-method", "statement": "Kaplan–Meier (KM) analyses were conducted with the Log-Rank test.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41266683", "locator": "sections[8] \"Statistical analysis\" paragraph 2", "quote": "Kaplan–Meier (KM) analyses were conducted with the Log-Rank test."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data is available from the authors upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41266683", "locator": "sections[27] \"notes\" paragraph 1", "quote": "All data is available from the authors upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The C-index of the model could be 0.879 in TCGA-BLCA.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:41266683", "locator": "sections[20] \"The construction of prognostic model relating TRPM4\" paragraph 2", "quote": "The C-index of the model could be 0.879 in TCGA-BLCA."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The C-index of the model could be 0.879 in TCGA-BLCA.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:41266683"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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