A prognosis marker MUC1 correlates with metabolism and drug resistance in bladder cancer: a bioinformatics research.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35879749", "kind": "science-record", "revision": 4, "content_hash": "sha256:82e40dd11559132722ad7df7ded48c5166ec4038f301f07b8b3ec0ba74507a2f", "created_at": "2026-11-01T18:14:58Z", "updated_at": "2026-11-01T22:07:07Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A prognosis marker MUC1 correlates with metabolism and drug resistance in bladder cancer: a bioinformatics research.", "doi": "10.1186/s12894-022-01067-8", "pmid": "35879749", "authors": ["Liangliang Qing", "Qingchao Li", "Yongjin Yang", "Wenbo Xu", "Zhilong Dong"], "journal": "BMC urology", "year": 2022, "abstract": "BACKGROUND: MUC1 is a type I transmembrane protein that plays an important role in tumor cell signal transduction. Although current studies have shown that MUC1 is upregulated in bladder cancer (BC), the specific mechanism is still unclear.\nMETHODS: We performed expression analysis, gene set enrichment analysis, survival analysis, immune infiltration analysis, drug sensitivity analysis, and metabolism-related gene expression analysis on TCGA-BLCA, GES31684 and GSE13507.\nRESULTS: The expression of MUC1 in the tumor and lymphatic metastasis positive samples was significantly increased. Genes related to MUC1 expression were significantly enriched in immune response, ribosomes, exosomes, and energy metabolism. The results of the immune infiltration analysis showed that M1 macrophages in BC with high MUC1 expression were significantly decreased. Expression of MUC1 increases drug resistance in BC patients. In addition, MUC1 increases glycolysis, glucose uptake, and lactate production by inducing metabolic reprogramming.\nCONCLUSION: MUC1 has a significant effect on the metabolism and immune cell infiltration of BC, which may be the cause of increased drug resistance, and can be used as a molecular target for the diagnosis and treatment of BC.", "claims": [{"id": "claim-method", "statement": "Univariate and multivariate analyses were conducted using the Cox Proportional Hazards Regression model on the remaining samples to obtain risk scores.\n\nAfter dividing the samples into high and low expression group according to the median expression of MUC1, KM survival analysis was conducted to analyze the overall survival (OS) rate of BC patients related to MUC1 expression.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35879749", "locator": "sections[5] \"Prognostic analysis\" paragraph 2", "quote": "Univariate and multivariate analyses were conducted using the Cox Proportional Hazards Regression model on the remaining samples to obtain risk scores."}, {"asset": "source:pmid:35879749", "locator": "sections[5] \"Prognostic analysis\" paragraph 2", "quote": "After dividing the samples into high and low expression group according to the median expression of MUC1, KM survival analysis was conducted to analyze the overall survival (OS) rate of BC patients related to MUC1 expression."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analysed during the current study are available in the TCGA and GEO repository. The link is as follows: TCGA_BLCA: https://portal.gdc.cancer.gov; GSE13507: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13507; GSE31684: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31684.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35879749", "locator": "sections[24] \"notes\" paragraph 1", "quote": "The datasets analysed during the current study are available in the TCGA and GEO repository. The link is as follows: TCGA_BLCA: https://portal.gdc.cancer.gov; GSE13507: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13507; GSE31684: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31684."}], "state": "complete"}, {"id": "claim-target-result", "statement": "MUC1 expression is an independent prognostic factor in bladder cancer.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35879749", "locator": "sections[13] \"The role of MUC1 in the prognosis of bladder cancer\" paragraph 2", "quote": "Next, multivariate Cox proportional hazards regression analysis showed that MUC1 expression is an independent prognostic factor (Fig. 2A, Table 3)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "MUC1 expression is an independent prognostic factor in bladder cancer.", "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:35879749"], "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:35879749", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12894-022-01067-8", "sha256": "sha256:ea2290cd16a96da9509ea9b266f861cddab32aa8a18a55927a226af615ec30dc", "bytes": 35492, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12894-022-01067-8", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9309451", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE13507", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13507", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE13507", "version": null, "note": "The datasets analysed during the current study are available in the TCGA and GEO repository. 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