Identification and validation of novel biomarkers affecting bladder cancer immunotherapy via machine learning and its association with M2 macrophages.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36439109", "kind": "science-record", "revision": 2, "content_hash": "sha256:df626367fade0bedb46c37f228c2bcdef96788eeee3875f427a2e8d3e39abe32", "created_at": "2026-11-01T19:00:54Z", "updated_at": "2026-11-01T21:29:33Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and validation of novel biomarkers affecting bladder cancer immunotherapy via machine learning and its association with M2 macrophages.", "doi": "10.3389/fimmu.2022.1051063", "pmid": "36439109", "authors": ["Junkang Wang", "Xiaojuan He", "Yifeng Bai", "Guanghui Du", "Minhong Cai"], "journal": "Frontiers in immunology", "year": 2022, "abstract": "Background: Immunotherapy has shown promising results in bladder cancer therapy options.\nMethods: Analysis of open-access data was conducted using the R software. Open-access data were obtained from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and IMvigor210 databases. Immunofluorescence and co-culture systems were utilized to validate the effect of PTHLH on M2 macrophage polarization.\nResults: Here, through the combined (TCGA, GSE128959, GSE13507, and GSE83586) and IMvigor210 cohorts, we comprehensively investigated the biological and immune microenvironment differences in patients with diverse immunotherapy responses. Meanwhile, we found that M2 macrophage could affect bladder cancer immunotherapy sensibility. Moreover, based on the machine learning algorithm (LASSO logistics regression), PTHLH, BHMT2, and NGFR were identified, which all have good prediction abilities for patient immunotherapy. Then, a logistics regression model was established based on PTHLH, BHMT2, and NGFR, and each patient was assigned a logistics score. Subsequently, we investigated the difference in patients with high low logistics scores, including biological enrichment, immune microenvironment, and genomic characteristics. Meanwhile, data from the Human Protein Atlas database indicated a higher protein level of PTHLH in bladder cancer tissue. Immunofluorescence indicated that the knockdown of PTHLH in bladder cancer cells can significantly inhibit the M2 polarization of co-culture M0 macrophages.\nConclusions: Our study investigated the difference between bladder cancer immunotherapy responders and non-responders. Meanwhile, the PTHLH was identified as a novel biomarker for bladder cancer immunotherapy.", "claims": [{"id": "claim-method", "statement": "The machine learning algorithm, LASSO logistic regression, was used for optimal variable selection (13).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36439109", "locator": "sections[5] \"Machine learning algorithm\" paragraph 2", "quote": "The machine learning algorithm, LASSO logistic regression, was used for optimal variable selection (13)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study, the names of the repositories and accession numbers are available within the article/ Supplementary Material .", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36439109", "locator": "sections[24] \"Data availability statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study, the names of the repositories and accession numbers are available within the article/ Supplementary Material ."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "", "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:36439109"], "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:GSE128959"], "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:GSE128959"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36439109", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2022.1051063", "sha256": 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE128959", "GSE13507", "GSE83586"], "resolved_accessions": ["GSE128959", "GSE13507", "GSE83586"], "statements": ["Publicly available datasets were analyzed in this study, the names of the repositories and accession numbers are available within the article/ Supplementary Material ."], "basis": "The paper names GSE128959, GSE13507, GSE83586 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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Immunofluorescence and co-culture systems were utilized to vali", "ein level of PTHLH in bladder cancer tissue. Immunofluorescence indicated that the knockdown of PTHLH in bla", "cer tissue in mRNA level. (E) Representative immunohistochemistry image of PTHLH protein level in normal bladd", "cer tissue in mRNA level. (G) Representative immunohistochemistry image of BHMT2 protein level in normal bladd"], "order_basis": "paper_text_order:394", "id": "assay:1"}, {"role": "data_generation", "definition_id": "clinical_trial", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["ed based on PTHLH, BHMT2, and NGFR, and each patient was assigned a logistics score. Subsequently, we investig"], "order_basis": "paper_text_order:1127", "id": "assay:2"}, {"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["issue. Immunofluorescence indicated that the knockdown of PTHLH in bladder cancer cells can signifi", "Methods Cell culture and transfection Cell lines T24 and THP-1 were laboratory sto", "ns. Lipofectamine 2000 was selected for cell transfection following the standard steps. The following", "ate its association with M2 macrophages. The knockdown efficiency is shown in Figure S5 . Immunoflu"], "order_basis": "paper_text_order:1503", "id": "assay:3"}, {"role": "analysis", "definition_id": "regression_modelling", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["glm_logit_fit"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The machine learning algorithm, LASSO logistic regression, was used for optimal variable selection (13)."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}