Computer classification and construction of a novel prognostic signature based on moonlighting genes in prostate cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36276080", "kind": "science-record", "revision": 4, "content_hash": "sha256:01557a005ff9becf630b1c5e9175adc58999223a15a25997a6f1be5a373572ce", "created_at": "2026-11-01T18:15:40Z", "updated_at": "2026-11-01T22:07:55Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Computer classification and construction of a novel prognostic signature based on moonlighting genes in prostate cancer.", "doi": "10.3389/fonc.2022.982267", "pmid": "36276080", "authors": ["Wangli Mei", "Liang Jin", "Bihui Zhang", "Xianchao Sun", "Guosheng Yang", "Sheng Li", "Lin Ye"], "journal": "Frontiers in oncology", "year": 2022, "abstract": "Advanced prostate cancer (PRAD) patients have poor prognosis and rising morbidity despite the ongoing iteration of molecular therapeutic agents. As newly discovered proteins with several functions, Moonlighting proteins have showed an important role in tumor progression but has not been extensively investigated in PRAD. Our study aimed to identify moonlighting-related prognostic biomarkers and prospective PRAD therapy targets. 103 moonlighting genes were gathered from previous literatures. A PRAD classification and multivariate Cox prognostic signature were constructed using dataset from The Cancer Genome Atlas (TCGA). Subsequently, we tested our signature's potential to predict biochemical failure-free survival (BFFS) using GSE21032, a prostate cancer dataset from Gene Expression Omnibus (GEO). The performance of this signature was demonstrated by Kaplan-Meier (KM), receiver operator characteristic (ROC), areas under ROC curve (AUC), and calibration curves. Additionally, immune infiltration investigation was conducted to determine the impact of these genes on immune system. This signature's influence on drug susceptibility was examined using CellMiner's drug database. Both training and validation cohorts demonstrated well predictive capacity of this 9-gene signature for PRAD. The 3-year AUCs for TCGA-PRAD and GSE21032 were 0.802 and 0.60 respectively. It can effectively classify patients into various biochemical recurrence risk groups. These genes were also assessed to be connected with tumor mutation burden (TMB), immune infiltration and therapy. This work created and validated a moonlighting gene signature, revealing fresh perspectives on moonlighting proteins in predicting prognosis and improving treatment of PRAD.", "claims": [{"id": "claim-method", "statement": "PRAD patients in TCGA and GEO cohorts were investigated using univariate and multivariate Cox regression analysis to construct one signature that predicted prognosis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36276080", "locator": "sections[10] \"Statistical analyses\" paragraph 2", "quote": "PRAD patients in TCGA and GEO cohorts were investigated using univariate and multivariate Cox regression analysis to construct one signature that predicted prognosis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. This data can be found here: The RNA-seq and clinical data could be acquired from TCGA (https://portal.gdc.cancer.gov/) and GEO database (https://www.ncbi.nlm.nih.gov/geo/). Data of immune, estimate and stromal scores of TCGA-PRAD samples were acquired from ESTIMATE database (https://bioinformatics.mdanderson.org/estimate). The data of drug sensitivity could be obtained from CellMiner (https://discover.nci.nih.gov/cellminer). Code used in our study are available from corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36276080", "locator": "sections[23] \"Data availability statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. This data can be found here: The RNA-seq and clinical data could be acquired from TCGA (https://portal.gdc.cancer.gov/) and GEO database (https://www.ncbi.nlm.nih.gov/geo/). Data of immune, estimate and stromal scores of TCGA-PRAD samples were acquired from ESTIMATE database (https://bioinformatics.mdanderson.org/estimate). The data of drug sensitivity could be obtained from CellMiner (https://discover.nci.nih.gov/cellminer). Code used in our study are available from corresponding author on reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The 3-year AUCs for TCGA-PRAD and GSE21032 were 0.802 and 0.60 respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36276080", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The 3-year AUCs for TCGA-PRAD and GSE21032 were 0.802 and 0.60 respectively."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The 3-year AUCs for TCGA-PRAD and GSE21032 were 0.802 and 0.60 respectively.", "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:36276080"], "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:GSE21032"], "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:GSE21032"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36276080", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2022.982267", "sha256": "sha256:2419649b2d1de20ec95d20a8956479c68f51a2ccae243ccf51ef8ad100d86a92", "bytes": 50864, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fonc.2022.982267", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9585316", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE21032", "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=GSE21032", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE21032", "version": null, "note": "Publicly available datasets were analyzed in this study. This data can be found here: The RNA-seq and clinical data could be acquired from TCGA (https://portal.gdc.cancer.gov/) and GEO database (https://www.ncbi.nlm.nih.gov/geo/). Data of immune, estimate and stromal scores of TCGA-PRAD samples were acquired from ESTIMATE database (https://bioinformatics.mdanderson.org/estimate). The data of drug sensitivity could be obtained from CellMiner (https://discover.nci.nih.gov/cellminer). Code used in our study are available from corresponding author on reasonable request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. This data can be found here: The RNA-seq and clinical data could be acquired from TCGA (https://portal.gdc.cancer.gov/) and GEO database (https://www.ncbi.nlm.nih.gov/geo/). Data of immune, estimate and stromal scores of TCGA-PRAD samples were acquired from ESTIMATE database (https://bioinformatics.mdanderson.org/estimate). The data of drug sensitivity could be obtained from CellMiner (https://discover.nci.nih.gov/cellminer). 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