Identification of common signatures in idiopathic pulmonary fibrosis and lung cancer using gene expression modeling.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33046043", "kind": "science-record", "revision": 7, "content_hash": "sha256:7b84d6f10c0be340d1315d1f8b0a45a75b6c7cb9ea298714ad50583a96029ac9", "created_at": "2026-11-01T15:41:13Z", "updated_at": "2026-11-01T22:02:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of common signatures in idiopathic pulmonary fibrosis and lung cancer using gene expression modeling.", "doi": "10.1186/s12885-020-07494-w", "pmid": "33046043", "authors": ["Dong Leng", "Jiawen Yi", "Maodong Xiang", "Hongying Zhao", "Yuhui Zhang"], "journal": "BMC cancer", "year": 2020, "abstract": "BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is associated with an increased risk for lung cancer, but the underlying mechanisms driving malignant transformation remain largely unknown. This study aimed to identify differentially expressed genes (DEGs) distinguishing IPF and lung cancer from healthy individuals and common genes driving the transformation from healthy to IPF and lung cancer.\nMETHODS: The gene expression data for IPF and non-small cell lung cancer (NSCLC) were retrieved from the Gene Expression Omnibus (GEO) database. The DEG signatures were identified via unsupervised two-way clustering (TWC) analysis, supervised support vector machine analysis, dimensional reduction, and mutual exclusivity analysis. Gene enrichment and pathway analyses were performed to identify common signaling pathways. The most significant signature genes in common among IPF and lung cancer were further verified by immunohistochemistry.\nRESULTS: The gene expression data from GSE24206 and GSE18842 were merged into a super array dataset comprising 86 patients with lung disorders (17 IPF and 46 NSCLC) and 51 healthy controls and measuring 23,494 unique genes. Seventy-nine signature DEGs were found among IPF and NSCLC. The peroxisome proliferator-activated receptor (PPAR) signaling pathway was the most enriched pathway associated with lung disorders, and matrix metalloproteinase-1 (MMP-1) in this pathway was mutually exclusive with several genes in IPF and NSCLC. Subsequent immunohistochemical analysis verified enhanced MMP1 expression in NSCLC associated with IPF.\nCONCLUSIONS: For the first time, we defined common signature genes for IPF and NSCLC. The mutually exclusive sets of genes were potential drivers for IPF and NSCLC.", "claims": [{"id": "claim-method", "statement": "The unpaired Student’s t-test and two-way clustering (TWC) analysis were used to identify genes that were expressed differentially between disease (IPF and NSCLC) and control samples; genes with P < 0.05 were considered as DEGs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33046043", "locator": "sections[4] \"Unsupervised clustering and supervised classification analysis\" paragraph 2", "quote": "The unpaired Student’s t-test and two-way clustering (TWC) analysis were used to identify genes that were expressed differentially between disease (IPF and NSCLC) and control samples; genes with P < 0.05 were considered as DEGs."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Availability of data and materialsAll relevant data are available upon request from the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33046043", "locator": "sections[29] \"notes\" paragraph 1", "quote": "Availability of data and materialsAll relevant data are available upon request from the corresponding author."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": null, "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:33046043"], "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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