Identification of the Key Genes Involved in the Tumorigenesis and Prognosis of Prostate Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36245843", "kind": "science-record", "revision": 5, "content_hash": "sha256:fc30bd80a66c4a89e8fd5c55e43273feb3ab76d992848ab9655555bb6702dff8", "created_at": "2026-11-01T18:15:37Z", "updated_at": "2026-11-01T22:50:22Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of the Key Genes Involved in the Tumorigenesis and Prognosis of Prostate Cancer.", "doi": "10.1155/2022/5500416", "pmid": "36245843", "authors": ["Wenxuan Wang", "Qinghui Wu", "Ali Mohyeddin", "Yousheng Liu", "Zhitao Liu", "Jianqiang Ge", "Bao Zhang", "Gan Shi", "Weifu Wang", "Dinglan Wu", "Fei Wang"], "journal": "Computational and mathematical methods in medicine", "year": 2022, "abstract": "Background: Prostate cancer (PCa) is a malignant tumor in males, with a majority of the cases advancing to metastatic castration resistance. Metastasis is the leading cause of mortality in PCa. The traditional early detection and prediction approaches cannot differentiate between the different stages of PCa. Therefore, new biomarkers are necessary for early detection and clear differentiation of PCa stages to provide precise therapeutic intervention.\nMethods: The objective of the study was to find significant differences in genes and combine the three GEO datasets with TCGA-PRAD datasets (DEG). Weighted gene coexpression network analysis (WGCNA) determined the gene set and PCa clinical feature correlation module utilizing the TGGA-PRAD clinical feature data. The correlation module genes were rescreened using the biological information analysis tools, with the three hub genes (TOP2A, NCAPG, and BUB1B) for proper verification. Finally, internal (TCGA) and external (GSE32571, GSE70770) validation datasets were used to validate and predict the value of last hub genes.\nResults: The hub gene was abnormally upregulated in PCa samples during verification. The expression of each gene was favorably connected with the Gleason score and TN tumor grade in clinical samples but negatively correlated with the overall survival rate. The expression of these genes was linked to CD8 naive cells and macrophages, among other cells. Antitumor immune cells like NK and NKT were favorably and adversely correlated with infiltrating cells, respectively. Simultaneously, the GSCV and GSEA indicated that the hub gene is connected with cell proliferation, death, and androgen receptor, among other signaling pathways. Therefore, these genes could influence the incidence and progression of PCa by participating in or modulating various signaling pathways. Furthermore, using the online tool of CMap, we examined the individual medications for Hughes and determined that tipifarnib could be useful for the clinical therapy of PCa.\nConclusion: TOP2A, NCAPG, and BUB1B are important genes intimately linked to the clinical prognosis of PCa and can be employed as reliable biomarkers for early diagnosis and prognosis. Moreover, these genes can provide a theoretical basis for precision differentiation and treatment of PCa.", "claims": [{"id": "claim-method", "statement": "Using the NCBI web analytical tool “GEO2R” (https://www.ncbi.nlm.nih.gov/geo/geo2r/), the differences between the selected GEO datasets were aggregated and evaluated to produce the differential gene expression data matrix (P ≤ 0.05 | LogFC | ≥1).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36245843", "locator": "sections[4] \"2.2. Preliminary Screening of Candidate DEGs\" paragraph 2", "quote": "Using the NCBI web analytical tool “GEO2R” (https://www.ncbi.nlm.nih.gov/geo/geo2r/), the differences between the selected GEO datasets were aggregated and evaluated to produce the differential gene expression data matrix (P ≤ 0.05 | LogFC | ≥1)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "TOP2A, NCAPG, and BUB1B are important genes intimately linked to the clinical prognosis of PCa and can be employed as reliable biomarkers for early diagnosis and prognosis.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36245843", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "TOP2A, NCAPG, and BUB1B are important genes intimately linked to the clinical prognosis of PCa and can be employed as reliable biomarkers for early diagnosis and prognosis."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "TOP2A, NCAPG, and BUB1B are important genes intimately linked to the clinical prognosis of PCa and can be employed as reliable biomarkers for early diagnosis and prognosis.", "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:36245843"], "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": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. 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