Identification and validation of five ferroptosis-related molecular signatures in keloids based on multiple transcriptome data analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39834787", "kind": "science-record", "revision": 3, "content_hash": "sha256:e94c2799ef6094a77b0122c9a1b42ff750978e08edce9ef9e2de8a97d0b854b6", "created_at": "2026-11-01T20:30:08Z", "updated_at": "2026-11-01T22:13:33Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and validation of five ferroptosis-related molecular signatures in keloids based on multiple transcriptome data analysis.", "doi": "10.3389/fmolb.2024.1490745", "pmid": "39834787", "authors": ["Zhen Sun", "Yonghong Qin", "Xuanfen Zhang"], "journal": "Frontiers in molecular biosciences", "year": 2024, "abstract": "Introduction: Keloids are a common skin disorder characterized by excessive fibrous tissue proliferation, which can significantly impact patients' health. Ferroptosis, a form of regulated cell death, plays a crucial role in the development of fibrosis; however, its role in the mechanisms of keloid formation remains poorly understood.\nMethods: This study aimed to identify key genes associated with ferroptosis in keloid formation. Data from the NCBI GEO database, including GSE145725, GSE7890, and GSE44270, were analyzed, comprising a total of 24 keloid and 17 normal skin samples. Additionally, single-cell data from GSE181316, which included 8 samples with complete expression profiles, were also evaluated. Differentially expressed genes were identified, and ferroptosis-related genes were extracted from the GeneCards database. LASSO regression was used to select key genes associated with keloids. Validation was performed using qRT-PCR and Western blot (WB) analysis on tissue samples from five keloid and five normal skin biopsies.\nResults: A total of 471 differentially expressed genes were identified in the GSE145725 dataset, including 225 upregulated and 246 downregulated genes. Five ferroptosis-related genes were selected through gene intersection and LASSO regression. Two of these genes were upregulated, while three were downregulated in keloid tissue. Further analysis through GSEA pathway enrichment, GSVA gene set variation, immune cell infiltration analysis, and single-cell sequencing revealed that these genes were primarily involved in the fibrotic process. The qRT-PCR and WB results confirmed the expression patterns of these genes.\nDiscussion: This study provides novel insights into the molecular mechanisms of ferroptosis in keloid formation. The identified ferroptosis-related genes could serve as potential biomarkers or therapeutic targets for treating keloids.", "claims": [{"id": "claim-method", "statement": "To perform feature screening by Lasso regression, we used the GSE145725 dataset as the training set and the GSE7890 and GSE44270 datasets as the validation sets.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39834787", "locator": "sections[17] \"3.2 Construction of a predictive model for genes associated with ferroptosis in keloids\" paragraph 2", "quote": "To perform feature screening by Lasso regression, we used the GSE145725 dataset as the training set and the GSE7890 and GSE44270 datasets as the validation sets."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39834787", "locator": "sections[27] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material."}], "state": "complete"}, {"id": "claim-target-result", "statement": "LASSO regression identified five ferroptosis-related key genes associated with keloids.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39834787", "locator": "sections[17] \"3.2 Construction of a predictive model for genes associated with ferroptosis in keloids\" paragraph 2", "quote": "Lasso regression identified five key genes associated with keloids, which were then utilized to construct the predictive model (Figures 4A, B)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "LASSO regression identified five ferroptosis-related key genes associated with keloids.", "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:39834787"], "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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