Identification and Validation of Prognostic Model for Tumor Microenvironment-Associated Genes in Bladder Cancer Based on Single-Cell RNA Sequencing Data Sets.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39151107", "kind": "science-record", "revision": 2, "content_hash": "sha256:bd64270ac28f687df98081d6c99911a06bc64545bc42e6a938b5fd01a2898d2a", "created_at": "2026-11-01T20:29:16Z", "updated_at": "2026-11-01T21:33:43Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and Validation of Prognostic Model for Tumor Microenvironment-Associated Genes in Bladder Cancer Based on Single-Cell RNA Sequencing Data Sets.", "doi": "10.1200/PO.23.00661", "pmid": "39151107", "authors": ["Imran Safder", "Henkel Valentine", "Nicole Uzzo", "John Sfakianos", "Robert Uzzo", "Shilpa Gupta", "Jason Brown", "Daniel Ranti", "Elizabeth Plimack", "George Haber", "Christopher Weight", "Alexander Kutikov", "Philip Abbosh", "Laura Bukavina"], "journal": "JCO precision oncology", "year": 2024, "abstract": "PURPOSE: The purpose of this study was to elucidate the relationship between the tumor microenvironment (TME) and cellular diversity in bladder cancer (BLCA) progression, leveraging single-cell RNA sequencing (scRNA-seq) data to identify potential prognostic biomarkers and construct a prognostic model for BLCA.\nMETHODS: We analyzed scRNA-seq data of normal and tumor bladder cells from the Gene Expression Omnibus (GEO) database to uncover crucial markers within the bladder TME. The study compared gene expression in normal versus tumor bladder cells, identifying differentially expressed genes. These genes were subsequently assessed for their prognostic significance using patient follow-up data from The Cancer Genome Atlas. Prognostic models were constructed using Least Absolute Shrinkage and Selection Operator and multivariate Cox regression analyses, focusing on eight genes of interest. The predictive performance of the model was also tested against additional GEO data sets (GSE31684, GSE13507, and GSE32894).\nRESULTS: The prognostic model demonstrated reliable prediction of patient outcomes. Validation through gene set enrichment analysis and immune cell infiltration assessment supported the model's efficacy. The results from both the univariate and multivariate analyses suggest that the risk score is an independent prognostic factor with a hazard ratio of 2.97 (95% CI, 2.28 to 3.9, P < .001). In the validation cohort, the AUC at 1, 2, and 3 years is 0.74, 0.74, and 0.72, respectively.\nCONCLUSION: Our findings proposed biomarkers with prognostic potential, laying the groundwork for future in vitro validation and therapeutic exploration. This contributes to a deeper understanding of the genes associated with bladder TME and may improve prognostic precision in BLCA management.", "claims": [{"id": "claim-method", "statement": "To achieve this, we used step-wise Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression and multivariate Cox regression to identify survival-related DEGs and to develop a prognostic model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39151107", "locator": "sections[4] \"Construction of Prognostic Model Based on DEGs From scRNA-Seq Data\" paragraph 2", "quote": "To achieve this, we used step-wise Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression and multivariate Cox regression to identify survival-related DEGs and to develop a prognostic model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "We obtained scRNA sequencing data for normal bladder cells from the Gene Expression Omnibus (GEO) database (data set GSE129845), complemented by tumor cell data courtesy of Dr Sfakianos' lab.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39151107", "locator": "sections[3] \"Single-Cell RNA-Seq Data Set and Preprocessing\" paragraph 2", "quote": "We obtained scRNA sequencing data for normal bladder cells from the Gene Expression Omnibus (GEO) database (data set GSE129845), complemented by tumor cell data courtesy of Dr Sfakianos' lab."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The results from both the univariate and multivariate analyses suggest that the risk score is an independent prognostic factor with a hazard ratio of 2.97 (95% CI, 2.28 to 3.9, P < .001).", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "The results from both the univariate and multivariate analyses suggest that the risk score is an independent prognostic factor with a hazard ratio of 2.97 (95% CI, 2.28 to 3.9, P < .001)."}, "evidence": [{"asset": "source:pmid:39151107", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The results from both the univariate and multivariate analyses suggest that the risk score is an independent prognostic factor with a hazard ratio of 2.97 (95% CI, 2.28 to 3.9, P < .001)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The results from both the univariate and multivariate analyses suggest that the risk score is an independent prognostic factor with a hazard ratio of 2.97 (95% CI, 2.28 to 3.9, P < .001).", "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:39151107"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE129845"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE129845"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39151107", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1200/PO.23.00661", "sha256": 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