Prognostic Signature Development on the Basis of Macrophage Phagocytosis-Mediated Oxidative Phosphorylation in Bladder Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36211821", "kind": "science-record", "revision": 5, "content_hash": "sha256:69973acaa40056adf4d9f73b8a799d57f508c03ef1dbb53b8e7594136b66b496", "created_at": "2026-11-01T18:15:32Z", "updated_at": "2026-11-01T22:50:17Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Prognostic Signature Development on the Basis of Macrophage Phagocytosis-Mediated Oxidative Phosphorylation in Bladder Cancer.", "doi": "10.1155/2022/4754935", "pmid": "36211821", "authors": ["Genyi Qu", "Yong Xu", "Zhenquan Lu", "Haibo Nie", "Cheng Tang", "Jian Hou", "Xiangyang Wen"], "journal": "Oxidative medicine and cellular longevity", "year": 2022, "abstract": "Background: Macrophages are correlated with the occurrence and progression of bladder cancer (BCa). However, few research has focused on the predictive relevance of macrophage phagocytosis-mediated oxidative phosphorylation (MPOP) with BCa overall survival. Herein, we aimed to propose the targeted macrophage control based on MPOP as a treatment method for BCa immunotherapy.\nMethods: The mRNA expression data sets and clinical data of bladder cancer originated from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data set. A systematic study of several GEO data sets found differentially expressed macrophage phagocytosis regulators (DE-MPR) between BCa and normal tissues. To discover overall survival-associated DE-MPR and develop prognostic gene signature with performance validated based on receiver operating curves and Kaplan-Meier curves, researchers used univariate and Lasso Cox regression analysis (ROC). External validation was done with GSE13057 and GSE69795. To clarify its molecular mechanism and immune relevance, GO/KEGG enrichment analysis and tumor immune analysis were used. To find independent bladder cancer prognostic variables, researchers employed multivariate Cox regression analysis. Finally, using TCGA data set, a predictive nomogram was built.\nResults: In BCa, a four-gene signature of oxidative phosphorylation composed of PTPN6, IKZF3, HDLBP, and EMC1 was found to predict overall survival. With the MPOP feature, the ROC curve showed that TCGA data set and the external validation data set performed better in predicting overall survival than the traditional AJCC stage. The four-gene signature can identify cancers from normal tissue and separate patients into the high-risk and low-risk groups with different overall survival rates. The four MPOP-gene signature was an independent predictive factor for BCa. In predicting overall survival, a nomogram integrating genetic and clinical prognostic variables outperformed AJCC staging. Multiple oncological features and invasion-associated pathways were identified in the high-risk group, which were also correlated with significantly lower levels of immune cell infiltration.\nConclusion: This paper found the MPOP-feature gene and developed a predictive nomogram capable of accurately predicting bladder cancer overall survival. The above discoveries can contribute to the development of personalized treatments and medical decisions.", "claims": [{"id": "claim-method", "statement": "To discover overall survival-associated DE-MPR and develop prognostic gene signature with performance validated based on receiver operating curves and Kaplan-Meier curves, researchers used univariate and Lasso Cox regression analysis (ROC).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36211821", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "To discover overall survival-associated DE-MPR and develop prognostic gene signature with performance validated based on receiver operating curves and Kaplan-Meier curves, researchers used univariate and Lasso Cox regression analysis (ROC)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All generated as well as analyzed data in the present research are contained in this manuscript.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36211821", "locator": "sections[24] \"Data Availability\" paragraph 2", "quote": "All generated as well as analyzed data in the present research are contained in this manuscript."}], "state": "complete"}, {"id": "claim-target-result", "statement": "In BCa, a four-gene signature of oxidative phosphorylation composed of PTPN6, IKZF3, HDLBP, and EMC1 was found to predict overall survival.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36211821", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "In BCa, a four-gene signature of oxidative phosphorylation composed of PTPN6, IKZF3, HDLBP, and EMC1 was found to predict overall survival."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "In BCa, a four-gene signature of oxidative phosphorylation composed of PTPN6, IKZF3, HDLBP, and EMC1 was found to predict overall survival.", "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:36211821"], "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:GSE13507"], "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:GSE13507"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36211821", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/4754935", "sha256": 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