Identification of key genes associated with polycystic ovary syndrome (PCOS) and ovarian cancer using an integrated bioinformatics analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35227296", "kind": "science-record", "revision": 4, "content_hash": "sha256:979c35da41be10129774c20f1c3a1ebc18615e15f42c5aa2d14faa47630222b7", "created_at": "2026-11-01T17:36:59Z", "updated_at": "2026-11-01T22:06:00Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of key genes associated with polycystic ovary syndrome (PCOS) and ovarian cancer using an integrated bioinformatics analysis.", "doi": "10.1186/s13048-022-00962-w", "pmid": "35227296", "authors": ["Juan Zou", "Yukun Li", "Nianchun Liao", "Jue Liu", "Qunfeng Zhang", "Min Luo", "Jiao Xiao", "Yanhua Chen", "Mengjie Wang", "Kexin Chen", "Juan Zeng", "Zhongcheng Mo"], "journal": "Journal of ovarian research", "year": 2022, "abstract": "BACKGROUND: Accumulating evidence suggests a strong association between polycystic ovary syndrome (PCOS) and ovarian cancer (OC), but the potential molecular mechanism remains unclear. In this study, we identified previously unrecognized genes that are significantly correlated with PCOS and OC via bioinformatics.\nMATERIALS AND METHODS: Multiple bioinformatic analyses, such as differential expression analysis, univariate Cox analysis, functional and pathway enrichment analysis, protein-protein interaction (PPI) network construction, survival analysis, and immune infiltration analysis, were utilized. We further evaluated the effect of OGN on FSHR expression via immunofluorescence.\nRESULTS: TCGA-OC, GSE140082 (for OC) and GSE34526 (for PCOS) datasets were downloaded. Twelve genes, including RNF144B, LPAR3, CRISPLD2, JCHAIN, OR7E14P, IL27RA, PTPRD, STAT1, NR4A1, OGN, GALNT6 and CXCL11, were identified as signature genes. Drug sensitivity analysis showed that OGN might represent a hub gene in the progression of PCOS and OC. Experimental analysis found that OGN could increase FSHR expression, indicating that OGN could regulate the hormonal response in PCOS and OC. Furthermore, correlation analysis indicated that OGN function might be closely related to m6A and ferroptosis.\nCONCLUSIONS: Our study identified a 12-gene signature that might be involved in the prognostic significance of OC. Furthermore, the hub gene OGN represent a significant gene involved in OC and PCOS progression by regulating the hormonal response.", "claims": [{"id": "claim-method", "statement": "Univariate Cox analysis was used to select genes associated with prognosis, and a prognostic correlation model was further constructed.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35227296", "locator": "sections[6] \"Establishing prognostic indicators based on DEGs\" paragraph 2", "quote": "Univariate Cox analysis was used to select genes associated with prognosis, and a prognostic correlation model was further constructed."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data used to support the findings of this study are available from the corresponding author upon request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35227296", "locator": "sections[30] \"Availability of data and material\" paragraph 2", "quote": "The data used to support the findings of this study are available from the corresponding author upon request."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "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:35227296"], "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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RESULTS: TCGA-OC, GSE140082 (for OC) and GS"], "order_basis": "paper_text_order:764", "id": "assay:1"}, {"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": ["Materials and methods Cell culture and transfection Human ovarian cancer cell lines (SKOV3 and K", "Biotechnology, MD, USA). For transient cell transfection, SKOV3 and KGN cells were seeded in 6-well p", "lates for 24 h. 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