Seven ferroptosis-specific expressed genes are considered as potential biomarkers for the diagnosis and treatment of cigarette smoke-induced chronic obstructive pulmonary disease.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35433978", "kind": "science-record", "revision": 5, "content_hash": "sha256:c63b068d244aa76b55417ad484cc3c85cbece5802953786b5d67ea0823889745", "created_at": "2026-11-01T18:14:17Z", "updated_at": "2026-11-01T22:48:52Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Seven ferroptosis-specific expressed genes are considered as potential biomarkers for the diagnosis and treatment of cigarette smoke-induced chronic obstructive pulmonary disease.", "doi": "10.21037/atm-22-1009", "pmid": "35433978", "authors": ["Zhiwei Lin", "Yifan Xu", "Lili Guan", "Lijie Qin", "Jiabin Ding", "Qingling Zhang", "Luqian Zhou"], "journal": "Annals of translational medicine", "year": 2022, "abstract": "Background: Chronic obstructive pulmonary disease (COPD) is a chronic respiratory disease characterized by incomplete reversible airway obstruction, with high mortality and disability rates, and smoking is the primary risk factor for COPD. Studies performed to date have confirmed that iron and ferroptosis play crucial roles in the development of cigarette smoke-induced COPD, but the exact mechanisms have not been fully elucidated.\nMethods: The microarray datasets GSE10006, GSE11784, and GSE20257 were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between COPD smokers and non-smokers airway epithelial. Protein-protein interaction (PPI) and hub gene networks were constructed using the STRING database and Cytoscape software. At the same time, the 3 datasets were screened for ferroptosis-related genes that were co-differentially expressed. The ferroptosis-related hub genes (FRHGs) that overlapped with the ferroptosis-related genes and hub genes were then identified. Next, the mRNA-miRNA network was constructed, and Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for target genes were performed. Finally, GSE19407, GSE994, and GSE27973 were used to evaluate the expression of hub genes.\nResults: We identified 7 potential FRHGs (NQO1, AKR1C3, AKR1C1, GPX2, TXNRD1, SRXN1, SLC7A11), which showed good diagnostic properties. The molecular functions (MFs) of FRHGs mainly influence biological processes (BPs) responding to oxidative stress. Nrf2 pathways may be the key pathways regulating ferroptosis in cigarette smoke-induced COPD. Meanwhile, co-expressed mRNAs and miRNAs were selected to construct mRNA-miRNA interaction networks. Furthermore, based on the 7 FRHGs mentioned above, we found that benzoic acid showed high drug targeting relevance.\nConclusions: This work identified 7 FRHGs as potential biomarkers for the diagnosis and treatment of COPD and provided insights into the mechanisms of disease development in cigarette smoke-induced COPD at the transcriptome level.", "claims": [{"id": "claim-method", "statement": "Genes with an adjusted P value less than 0.05 and absolute fold change (FC) greater than 1 were considered as DEGs using the ‘limma’ package of R software (22). Receiver operating characteristic (ROC) curve analysis was performed using HiPlot software (version 0.1.0) to determine the sensitivity and specificity of target genes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35433978", "locator": "sections[4] \"Analysis of differential gene expression\" paragraph 3", "quote": "Genes with an adjusted P value less than 0.05 and absolute fold change (FC) greater than 1 were considered as DEGs using the ‘limma’ package of R software (22)."}, {"asset": "source:pmid:35433978", "locator": "sections[9] \"Validation of ferroptosis hub genes\" paragraph 2", "quote": "Receiver operating characteristic (ROC) curve analysis was performed using HiPlot software (version 0.1.0) to determine the sensitivity and specificity of target genes."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The mRNA expression profile datasets GSE10006, GSE11784, GSE20257, GSE19407, GSE994, and GSE27973 were downloaded from the GEO database (https://www.ncbi.nlm.nih.gov/geo/) in the data format MINiML.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35433978", "locator": "sections[3] \"Data acquisition\" paragraph 2", "quote": "The mRNA expression profile datasets GSE10006, GSE11784, GSE20257, GSE19407, GSE994, and GSE27973 were downloaded from the GEO database (https://www.ncbi.nlm.nih.gov/geo/) in the data format MINiML."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We identified 7 potential FRHGs (NQO1, AKR1C3, AKR1C1, GPX2, TXNRD1, SRXN1, SLC7A11), which showed good diagnostic properties.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35433978", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We identified 7 potential FRHGs (NQO1, AKR1C3, AKR1C1, GPX2, TXNRD1, SRXN1, SLC7A11), which showed good diagnostic properties."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We identified 7 potential FRHGs (NQO1, AKR1C3, AKR1C1, GPX2, TXNRD1, SRXN1, SLC7A11), which showed good diagnostic properties.", "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:35433978"], "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:GSE10006"], "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:GSE10006"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35433978", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/atm-22-1009", "sha256": 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Methods: The microarray datasets GSE10006, GSE11784, and GSE20257 we", "sion The normalized expression matrix of the microarray data was downloaded from the 4 datasets and"], "order_basis": "paper_text_order:583", "id": "assay:1"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Genes with an adjusted P value less than 0.05 and absolute fold change (FC) greater than 1 were considered as DEGs using the ‘limma’ package of R software (22). Receiver operating characteristic (ROC) curve analysis was performed using HiPlot software (version 0.1.0) to determine the sensitivity and specificity of target genes."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}