A novel defined risk signature based on pyroptosis-related genes can predict the prognosis of prostate cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35135561", "kind": "science-record", "revision": 4, "content_hash": "sha256:020a13a1b190c806b8f36a6d72f4acdfe61d835ad427ce84115077a97df9386c", "created_at": "2026-11-01T17:36:53Z", "updated_at": "2026-11-01T22:05:49Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A novel defined risk signature based on pyroptosis-related genes can predict the prognosis of prostate cancer.", "doi": "10.1186/s12920-022-01172-5", "pmid": "35135561", "authors": ["Ding Hu", "Qingfei Cao", "Ming Tong", "Chundong Ji", "Zizhi Li", "Weichao Huang", "Yanyang Jin", "Guangquan Tong", "Yutao Wang", "Pengfei Li", "Huashan Zhang"], "journal": "BMC medical genomics", "year": 2022, "abstract": "BACKGROUND: Pyroptosis can not only inhibit the occurrence and development of tumors but also develop a microenvironment conducive to cancer growth. However, pyroptosis research in prostate cancer (PCa) has rarely been reported.\nMETHODS: The expression profile and corresponding clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Patients were divided into different clusters using consensus clustering analysis, and differential genes were obtained. We developed and validated a prognostic biomarker for biochemical recurrence (BCR) of PCa using univariate Cox analysis, Lasso-Cox analysis, Kaplan-Meier (K-M) survival analysis, and time-dependent receiver operating characteristics (ROC) curves.\nRESULTS: The expression levels of most pyroptosis-related genes (PRGs) are different not only between normal and tumor tissues but also between different clusters. Cluster 2 patients have a better prognosis than cluster 1 patients, and there are significant differences in immune cell content and biological pathway between them. Based on the classification of different clusters, we constructed an eight genes signature that can independently predict the progression-free survival (PFS) rate of a patient, and this signature was validated using a GEO data set (GSE70769). Finally, we established a nomogram model with good accuracy.\nCONCLUSIONS: In this study, PRGs were used as the starting point and based on the expression profile and clinical data, a prognostic signature with a high predictive value for biochemical recurrence (BCR) following radical prostatectomy (RP) was finally constructed, and the relationship between pyroptosis, immune microenvironment, and PCa was explored, providing important clues for future research on pyroptosis and immunity.", "claims": [{"id": "claim-method", "statement": "In addition, univariate and multivariate Cox analyses were also employed to test independent prognostic performance of signature.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35135561", "locator": "sections[9] \"Univariate and multivariate Cox regression analyses\" paragraph 2", "quote": "In addition, univariate and multivariate Cox analyses were also employed to test independent prognostic performance of signature."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated and analysed during the current study are available in the TCGA repository, (https://portal.gdc.cancer.gov) and GEO repository, (https://www.ncbi.nlm.nih.gov/geo/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35135561", "locator": "sections[32] \"notes\" paragraph 1", "quote": "The datasets generated and analysed during the current study are available in the TCGA repository, (https://portal.gdc.cancer.gov) and GEO repository, (https://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study developed and validated an eight-gene prognostic signature for progression-free survival in prostate cancer and established a nomogram model.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35135561", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Based on the classification of different clusters, we constructed an eight genes signature that can independently predict the progression-free survival (PFS) rate of a patient, and this signature was validated using a GEO data set (GSE70769). Finally, we established a nomogram model with good accuracy."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study developed and validated an eight-gene prognostic signature for progression-free survival in prostate cancer and established a nomogram model.", "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:35135561"], "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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