Bioinformatics analysis and in vivo validation of ferroptosis-related genes in ischemic stroke.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36506580", "kind": "science-record", "revision": 3, "content_hash": "sha256:37d5b93b98507d9ab77c1d8323e5d9ca0cb4535c35ff52804e8307e8862cd50f", "created_at": "2026-11-01T19:01:00Z", "updated_at": "2026-11-01T22:08:18Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics analysis and in vivo validation of ferroptosis-related genes in ischemic stroke.", "doi": "10.3389/fphar.2022.940260", "pmid": "36506580", "authors": ["Chang Liu", "Zhixi Li", "Hongjie Xi"], "journal": "Frontiers in pharmacology", "year": 2022, "abstract": "Ischemic stroke (IS) is a neurological condition associated with high mortality and disability rates. Although the molecular mechanisms underlying IS remain unclear, ferroptosis was shown to play an important role in its pathogenesis. Hence, we applied bioinformatics analysis to identify ferroptosis-related therapeutic targets in IS. IS-related microarray data from the GSE61616 dataset were downloaded from the Gene Expression Omnibus (GEO) database and intersected with the FerrDb database. In total, 33 differentially expressed genes (DEGs) were obtained and subjected to functional enrichment and protein-protein interaction (PPI) network analyses. Four candidate genes enriched in the HIF-1 signaling pathway (HMOX1, STAT3, CYBB, and TLR4) were selected based on the hierarchical clustering of the PPI dataset. We also downloaded the IR-related GSE35338 dataset and GSE58294 dataset from the GEO database to verify the expression levels of these four genes. ROC monofactor analysis demonstrated a good performance of HMOX1, STAT3, CYBB, and TLR4 in the diagnosis of ischemic stroke. Transcriptional levels of the above four genes, and translational level of GPX4, the central regulator of ferroptosis, were verified in a mouse model of middle cerebral artery occlusion (MCAO)-induced IS by qRT-PCR and western blotting. Considering the regulation of the HIF-1 signaling pathway, dexmedetomidine was applied to the MCAO mice. We found that expression of these four genes and GPX4 in MCAO mice were significantly reduced, while dexmedetomidine reversed these changes. In addition, dexmedetomidine significantly reduced MCAO-induced cell death, improved neurobehavioral deficits, and reduced the serum and brain levels of inflammatory factors (TNF-α and IL-6) and oxidative stress mediators (MDA and GSSG). Further, we constructed an mRNA-miRNA-lncRNA network based on the four candidate genes and predicted possible transcription factors. In conclusion, we identified four ferroptosis-related candidate genes in IS and proposed, for the first time, a possible mechanism for dexmedetomidine-mediated inhibition of ferroptosis during IS. These findings may help design novel therapeutic strategies for the treatment of IS.", "claims": [{"id": "claim-method", "statement": "ROC univariate analysis was performed in the GSE58294 dataset to assess the diagnostic value of four candidate genes for IS.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36506580", "locator": "sections[26] \"The diagnostic value of four candidate genes in IS\" paragraph 2", "quote": "ROC univariate analysis was performed in the GSE58294 dataset to assess the diagnostic value of four candidate genes for IS."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analyzed for this study can be found in the GEO database (www.ncbi.nlm.nih.gov/geo/). The accession numbers can be found in the article.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36506580", "locator": "sections[34] \"Data availability statement\" paragraph 2", "quote": "The datasets analyzed for this study can be found in the GEO database (www.ncbi.nlm.nih.gov/geo/). The accession numbers can be found in the article."}], "state": "complete"}, {"id": "claim-target-result", "statement": "ROC univariate analysis of the GSE58294 dataset showed diagnostic accuracies of 0.820 for HMOX1, 0.841 for STAT3, 0.911 for CYBB, and 0.895 for TLR4.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36506580", "locator": "sections[26] \"The diagnostic value of four candidate genes in IS\" paragraph 2", "quote": "As a result, the accuracy of HMOX1, STAT3, CYBB, and TLR4 in diagnosing IS in the GSE58294 dataset was 0.820, 0.841, 0.911, and 0.895, respectively (Figure 6C)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "ROC univariate analysis of the GSE58294 dataset showed diagnostic accuracies of 0.820 for HMOX1, 0.841 for STAT3, 0.911 for CYBB, and 0.895 for TLR4.", "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:36506580"], "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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