Bioinformatics Identification and Validation of Ferroptosis-Related Key Genes and Therapeutic Compounds in Septic Lung Injury.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39600675", "kind": "science-record", "revision": 3, "content_hash": "sha256:5630dcf1400de080a298e59886d081d3481f3101b476bd97f99903db192f751e", "created_at": "2026-11-01T20:29:52Z", "updated_at": "2026-11-01T22:13:12Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics Identification and Validation of Ferroptosis-Related Key Genes and Therapeutic Compounds in Septic Lung Injury.", "doi": "10.2147/JIR.S476522", "pmid": "39600675", "authors": ["Zhile Li", "Han Gan", "Siyuan Li", "Yuchen Xue", "Kai Luo", "Kai Huang", "Yunqian Zhang", "Yan Wang", "Lai Jiang", "Hui Zhang"], "journal": "Journal of inflammation research", "year": 2024, "abstract": "Background: Septic lung injury (SLI) is a severe condition with high mortality, and ferroptosis, a form of programmed cell death, is implicated in its pathogenesis. However, the explicit mechanisms underlying this condition remain unclear. This study aimed to elucidate and validate key ferroptosis-related genes involved in the pathogenesis of SLI through bioinformatics analysis and experimental validation.\nMethods: Microarray data related to SLI from the GSE130936 dataset were downloaded from the Gene Expression Omnibus (GEO) database. These data were then intersected with the FerrDb database to obtain ferroptosis-related differentially expressed genes (DEGs). Protein-protein interaction (PPI) networks and functional enrichment analysis were employed to identify key ferroptosis-related DEGs. The Connectivity Map (c-MAP) tool was used to search for potential compounds or drugs that may inhibit ferroptosis-related DEGs. The transcriptional levels of the key genes and potential therapeutic compounds were verified in an LPS-induced mouse model of lung injury. The expression of these key genes was further verified using the GSE60088 and GSE137342 datasets.\nResults: 38 ferroptosis-related DEGs were identified between the septic and control mice. PPI network analysis revealed four modules, the most significant of which included eight ferroptosis-related DEGs. Functional enrichment analysis showed that these genes were enriched in the HIF-1 signaling pathway, including IL-6 (Interleukin-6), TIMP1 (Tissue Inhibitor of Metalloproteinase 1), HIF-1α (Hypoxia-Inducible Factor-1α), and HMOX1 (Heme Oxygenase-1). Phloretin, a natural compound, was identified as a potential inhibitor of these genes. Treatment with phloretin significantly reduced the expression of these genes (p < 0.05), mitigated lung injury, improved inflammatory profiles by approximately 50%, and ferroptosis profiles by nearly 30% in the SLI models.\nConclusion: This study elucidates the significant role of ferroptosis in SLI and identifies phloretin as a potential therapeutic agent. However, further research, particularly involving human clinical trials, is necessary to validate these findings for clinical use.", "claims": [{"id": "claim-method", "statement": "Expression data between the LPS and Control groups in the GSE130936 were analyzed using GEO2R. The cut-off criteria for DEGs dataset were set as |log2FC| >1 and padjusted < 0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39600675", "locator": "sections[19] \"Identification of Ferroptosis-Related Differentially Expressed Genes in Sepsis-Induced Lung Injury Models\" paragraph 2", "quote": "Expression data between the LPS and Control groups in the GSE130936 were analyzed using GEO2R. The cut-off criteria for DEGs dataset were set as |log2FC| >1 and padjusted < 0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The raw data supporting the conclusions of this article will be made available by the authors without any undue reservation.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39600675", "locator": "sections[26] \"Data Sharing Statement\" paragraph 2", "quote": "The raw data supporting the conclusions of this article will be made available by the authors without any undue reservation."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The analysis identified 38 ferroptosis-related differentially expressed genes in the LPS-induced septic lung injury model.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39600675", "locator": "sections[19] \"Identification of Ferroptosis-Related Differentially Expressed Genes in Sepsis-Induced Lung Injury Models\" paragraph 2", "quote": "Then, to explore the correlation between ferroptosis and SLI, 340 ferroptosis-related genes obtained from the FerrDb database were intersected with sepsis-associated DEGs, and 38 ferroptosis-related DEGs were obtained and are shown in a Venn diagram and heat map (Figure 1B and 1C), including 26 up-regulated and 12 down-regulated genes (Table 1)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The analysis identified 38 ferroptosis-related differentially expressed genes in the LPS-induced septic lung injury model.", "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:39600675"], "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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