Comprehensive analysis of cuproptosis and m6A-Target gene signatures for diagnostic significance and immune microenvironment characterization in polycystic ovary syndrome.

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Recent evidence implicates cuproptosis, a copper-induced regulated cell death pathway, and N6-methyladenosine (m6A) RNA modifications in metabolic and inflammatory processes central to PCOS pathogenesis. This study aimed to construct integrated diagnostic signatures based on cuproptosis- and m6A-related gene expression. Transcriptome data from GEO datasets (GSE95728, GSE106724, GSE114419) comprising 28 PCOS and 22 control granulosa cell samples were merged and batch-corrected. Differentially expressed genes (DEGs) overlapping with curated cuproptosis-related and m6A-target gene sets were identified. LASSO regression was applied to generate diagnostic models based on selected DEGs: CASK, AGMAT, NEDD4, and PTGES3 (cuproptosis); CLDN1, ACLY, and DDX3X (m6A). The combined model achieved excellent diagnostic accuracy (AUC up to 0.960), validated in an independent dataset (GSE168404). ssGSEA analysis revealed immune dysregulation involving dendritic cells, T cell subsets, and myeloid-derived suppressor cells, which correlated with risk scores. Drug-gene association analysis via CellMiner indicated therapeutic relevance of targets such as ACLY and CLDN1 (Vinblastine), as well as CASK and CLDN1 (XAV-939). qRT-PCR validation in granulosa cells from 5 PCOS patients and 5 controls confirmed gene expression trends. These findings suggest cuproptosis- and m6A-based signatures may enable accurate PCOS diagnosis and guide individualized immunomodulatory strategies.", "claims": [{"id": "claim-method", "statement": "Differentially expressed genes (DEGs) between the PCOS and normal groups were identified using the R package ‘limma’.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40481029", "locator": "sections[4] \"Identification of differentially expressed genes\" paragraph 2", "quote": "Differentially expressed genes (DEGs) between the PCOS and normal groups were identified using the R package ‘limma’."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data generated or analysed during this study are included in this published article.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40481029", "locator": "sections[28] \"Data availability\" paragraph 2", "quote": "All data generated or analysed during this study are included in this published article."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The combined cuproptosis- and m6A-based model achieved an AUC of up to 0.960 for diagnosing PCOS and was validated in an independent dataset.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40481029", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The combined model achieved excellent diagnostic accuracy (AUC up to 0.960), validated in an independent dataset (GSE168404)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The combined cuproptosis- and m6A-based model achieved an AUC of up to 0.960 for diagnosing PCOS and was validated in an independent dataset.", "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:40481029"], "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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