An 8-ferroptosis-related genes signature from Bronchoalveolar Lavage Fluid for prognosis in patients with idiopathic pulmonary fibrosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34983465", "kind": "science-record", "revision": 4, "content_hash": "sha256:7ce2ca6419b7c4a54a5267a8f043d09f544359cc247b0b143b97cc4d446124d2", "created_at": "2026-11-01T17:36:41Z", "updated_at": "2026-11-01T22:05:29Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "An 8-ferroptosis-related genes signature from Bronchoalveolar Lavage Fluid for prognosis in patients with idiopathic pulmonary fibrosis.", "doi": "10.1186/s12890-021-01799-7", "pmid": "34983465", "authors": ["Yaowu He", "Yu Shang", "Yupeng Li", "Menghan Wang", "Dongping Yu", "Yi Yang", "Shangwei Ning", "Hong Chen"], "journal": "BMC pulmonary medicine", "year": 2022, "abstract": "BACKGROUND: With the rapid advances of genetic and genomic technologies, the pathophysiological mechanisms of idiopathic pulmonary fibrosis (IPF) were gradually becoming clear, however, the prognosis of IPF was still poor. This study aimed to systematically explore the ferroptosis-related genes model associated with prognosis in IPF patients.\nMETHODS: Datasets were collected from the Gene Expression Omnibus (GEO). The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to create a multi-gene predicted model from patients with IPF in the Freiburg cohort of the GSE70866 dataset. The Siena cohort and the Leuven cohort were used for validation.\nRESULTS: Nineteen differentially expressed genes (DEGs) between the patients with IPF and control were associated with poor prognosis based on the univariate Cox regression analysis (all P < 0.05). According to the median value of the risk score derived from an 8-ferroptosis-related genes signature, the three cohorts' patients were stratified into two risk groups. Prognosis of high-risk group (high risk score) was significantly poorer compared with low-risk group in the three cohorts. According to multivariate Cox regression analyses, the risk score was an independently predictor for poor prognosis in the three cohorts. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) confirmed the signature's predictive value in the three cohorts. According to functional analysis, inflammation- and immune-related pathways and biological process could participate in the progression of IPF.\nCONCLUSIONS: These results imply that the 8-ferroptosis-related genes signature in the bronchoalveolar lavage samples might be an effective model to predict the poor prognosis of IPF.", "claims": [{"id": "claim-method", "statement": "In order to minimize the risk of overfitting, a prognostic model was constructed by LASSO-penalized (least absolute shrinkage and selection operator) Cox regression analysis according to the R package \"glmnet\" (v.4.1-1) [23, 24].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34983465", "locator": "sections[4] \"Construction and validation of a prognostic ferroptosis-related gene signature\" paragraph 2", "quote": "In order to minimize the risk of overfitting, a prognostic model was constructed by LASSO-penalized (least absolute shrinkage and selection operator) Cox regression analysis according to the R package \"glmnet\" (v.4.1-1) [23, 24]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used and/or analyzed in the current study are available in the GEO repository, https://doi.org/10.1164/rccm.201712-2551OC [9].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34983465", "locator": "sections[22] \"Availability of data and materials\" paragraph 2", "quote": "The datasets used and/or analyzed in the current study are available in the GEO repository, https://doi.org/10.1164/rccm.201712-2551OC [9]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "These results imply that the 8-ferroptosis-related genes signature in the bronchoalveolar lavage samples might be an effective model to predict the poor prognosis of IPF.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34983465", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "These results imply that the 8-ferroptosis-related genes signature in the bronchoalveolar lavage samples might be an effective model to predict the poor prognosis of IPF."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "These results imply that the 8-ferroptosis-related genes signature in the bronchoalveolar lavage samples might be an effective model to predict the poor prognosis of IPF.", "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:34983465"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE70866"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE70866"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34983465", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12890-021-01799-7", "sha256": "sha256:f462af008f8d364184f64f2ffecbb6803bb98e1eab9b8ebbbcd18ad950d6d4c2", "bytes": 44496, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12890-021-01799-7", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8728942", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE70866", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE70866", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE70866", "version": null, "note": "The datasets used and/or analyzed in the current study are available in the GEO repository, 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