Establishment of a prognostic risk model for prostate cancer based on Gleason grading and cuprotosis related genes.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39085482", "kind": "science-record", "revision": 2, "content_hash": "sha256:90c78f77dbf7aab2a57a5bd4dcd8d06bc6823a9a9e12d04a730e9a1ab7b1c9a1", "created_at": "2026-11-01T20:29:09Z", "updated_at": "2026-11-01T21:33:34Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Establishment of a prognostic risk model for prostate cancer based on Gleason grading and cuprotosis related genes.", "doi": "10.1007/s00432-024-05899-9", "pmid": "39085482", "authors": ["Haicheng Wang", "Meiyi Xie", "Yuming Zhao", "Yong Zhang"], "journal": "Journal of cancer research and clinical oncology", "year": 2024, "abstract": "INTRODUCTION: Prostate cancer (PCa) is common in aging males, diagnosed via the Gleason grading system. The study explores the unexamined prognostic value of cuprotosis, a distinct cell death type, alongside Gleason grades in PCa.\nMETHODS: We explored Cuprotosis-related genes (CRGs) in prostate cancer (PCa), using NMF on TCGA-PRAD data for patient classification and WGCNA to link genes with Gleason scores and prognosis. A risk model was crafted via LASSO Cox regression. STX3 knockdown in PC-3 cells, analyzed for effects on cell behaviors and tumor growth in mice, highlighted its potential therapeutic impact.\nRESULTS: We identified five genes crucial for a prognostic risk model, with higher risk scores indicating worse prognosis. Survival analysis and ROC curves confirmed the model's predictive accuracy in TCGA-PRAD and GSE70769 datasets. STX3 was a key adverse prognostic factor, with its knockdown significantly reducing mRNA and protein levels, impairing PC-3 cell functions. In vivo, STX3 knockdown in PC-3 cells led to significantly smaller tumors in nude mice, underscoring its potential therapeutic value.\nCONCLUSION: Our prognostic model, using five genes linked to Gleason scores, effectively predicts prostate cancer outcomes, offering a novel treatment strategy angle.", "claims": [{"id": "claim-method", "statement": "We explored Cuprotosis-related genes (CRGs) in prostate cancer (PCa), using NMF on TCGA-PRAD data for patient classification and WGCNA to link genes with Gleason scores and prognosis. A risk model was crafted via LASSO Cox regression.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39085482", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "We explored Cuprotosis-related genes (CRGs) in prostate cancer (PCa), using NMF on TCGA-PRAD data for patient classification and WGCNA to link genes with Gleason scores and prognosis. A risk model was crafted via LASSO Cox regression."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data are available in the main Excel or the supplementary materials. Transcriptomic and clinical data for all patients were obtained from TCGA Prostate Cancer (PRAD) dataset (TCGA-PRAD) (https://portal.gdc.cancer.gov/) available on the University of California Santa Cruz (UCSC) Xena database (https://xenabrowser.net/datapages/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39085482", "locator": "sections[35] \"Data availability\" paragraph 2", "quote": "All data are available in the main Excel or the supplementary materials. Transcriptomic and clinical data for all patients were obtained from TCGA Prostate Cancer (PRAD) dataset (TCGA-PRAD) (https://portal.gdc.cancer.gov/) available on the University of California Santa Cruz (UCSC) Xena database (https://xenabrowser.net/datapages/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Our prognostic model, using five genes linked to Gleason scores, effectively predicts prostate cancer outcomes, offering a novel treatment strategy angle.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39085482", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Our prognostic model, using five genes linked to Gleason scores, effectively predicts prostate cancer outcomes, offering a novel treatment strategy angle."}, {"asset": "source:pmid:39085482", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We identified five genes crucial for a prognostic risk model, with higher risk scores indicating worse prognosis."}, {"asset": "source:pmid:39085482", "locator": "sections[24] \"Construction and validation of the prognostic risk model\" paragraph 2", "quote": "Time-dependent ROC curves demonstrated that the area under the curve (AUC) for DFI at 1-, 3-, and 5-years were 0.81, 0.79, and 0.72, respectively (Fig. 6G)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Our prognostic model, using five genes linked to Gleason scores, effectively predicts prostate cancer outcomes, offering a novel treatment strategy angle.", "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:39085482"], "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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Transcriptomic and clinical data for all patients were obtained from TCGA Prostate Cancer (PRAD) dataset (TCGA-PRAD) (https://portal.gdc.cancer.gov/) available on the University of California Santa Cruz (UCSC) Xena database (https://xenabrowser.net/datapages/).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "All data are available in the main Excel or the supplementary materials. 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A risk model was crafted via LASSO Cox regression."}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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STX3 knockdown in PC-3 cells, analyzed for effects on cell", "as a key adverse prognostic factor, with its knockdown significantly reducing mRNA and protein leve", "impairing PC-3 cell functions. In vivo, STX3 knockdown in PC-3 cells led to significantly smaller t", "istically significant. Cell culture and STX3 knockdown The PC-3 prostate cancer cell line was cultu"], "order_basis": "paper_text_order:551", "id": "assay:1"}, {"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["otein levels, impairing PC-3 cell functions. In vivo, STX3 knockdown in PC-3 cells led to signifi", "r effects on cell behaviors and tumor growth in mice, highlighted its potential therapeutic impac"], "order_basis": "paper_text_order:632", "id": "assay:2"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["and STX3 knockdown The PC-3 prostate cancer cell line was cultured in RPMI1640 with 10% fetal bovine serum at 3", "kdown The PC-3 prostate cancer cell line was cultured in RPMI1640 with 10% fetal bovine serum at 37 °"], "order_basis": "paper_text_order:1733", "id": "assay:3"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["clinical information summarized in Table 1. Immunohistochemical staining was performed on tissues obtained f", "tial expression of STX3 in PCa patients. (A) Immunohistochemical staining of prostate cancer group and normal", "group patients. (B) Statistical analysis of immunohistochemical staining in prostate cancer group and normal"], "order_basis": "paper_text_order:2456", "id": "assay:4"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["We explored Cuprotosis-related genes (CRGs) in prostate cancer (PCa), using NMF on TCGA-PRAD data for patient classification and WGCNA to link genes with Gleason scores and prognosis. A risk model was crafted via LASSO Cox regression."], "order_basis": "consumes_earlier_output", "id": "assay:5"}]}