Identification of gene and microRNA changes in response to smoking in human airway epithelium by bioinformatics analyses.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31568004", "kind": "science-record", "revision": 4, "content_hash": "sha256:d271f7984af52d615ee1a2f331ddf14d7c8015c243f51d1ec8869cfbf04dfef8", "created_at": "2026-11-01T17:33:05Z", "updated_at": "2026-11-01T22:00:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of gene and microRNA changes in response to smoking in human airway epithelium by bioinformatics analyses.", "doi": "10.1097/MD.0000000000017267", "pmid": "31568004", "authors": ["Jizhen Huang", "Wanli Jiang", "Xiang Tong", "Li Zhang", "Yuan Zhang", "Hong Fan"], "journal": "Medicine", "year": 2019, "abstract": "Smoking is a substantial risk factor for many respiratory diseases. This study aimed to identify the gene and microRNA changes related to smoking in human airway epithelium by bioinformatics analysis.From the Gene Expression Omnibus (GEO) database, the mRNA datasets GSE11906, GSE22047, GSE63127, and microRNA dataset GSE14634 were downloaded, and were analyzed using GEO2R. Functional enrichment analysis of the differentially expressed genes (DEGs) was enforced using DAVID. The protein-protein interaction (PPI) network and differentially expressed miRNAs (DEMs)- DEGs network were executed by Cytoscape.In total, 107 DEGs and 10 DEMs were determined. Gene Ontology (GO) analysis revealed that DEGs principally enriched in oxidation-reduction process, extracellular space and oxidoreductase activity. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway demonstrated that DEGs were principally enriched in metabolism of xenobiotics by cytochrome P450 and chemical carcinogenesis. The PPI network revealed 15 hub genes, including NQO1, CYP1B1, AKR1C1, CYP1A1, AKR1C3, CEACAM5, MUCL1, B3GNT6, MUC5AC, MUC12, PTGER4, CALCA, CBR1, TXNRD1, and CBR3. Cluster analysis showed that these hub genes were associated with adenocarcinoma in situ, squamous cell carcinoma, cell differentiation, inflammatory response, oxidative DNA damage, oxidative stress response and tumor necrosis factor. Hsa-miR-627-5p might have the most target genes, including ITLN1, TIMP3, PPP4R4, SLC1A2, NOVA1, RNFT2, CLDN10, TMCC3, EPHA7, SRPX2, PPP1R16B, GRM1, HS3ST3A1, SFRP2, SLC7A11, and KLHDC8A.We identified several molecular changes induced by smoking in human airway epithelium. This study may provide some candidate genes and microRNAs for assessing the risk of lung diseases caused by smoking.", "claims": [{"id": "claim-data-access", "statement": "From the GEO database (https://www.ncbi.nlm.nih.gov/geo/), the microRNA microarray dataset GSE14634[10] and the mRNA datasets GSE11906,[11] GSE22047[12] and GSE63127[13] were downloaded.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31568004", "locator": "sections[3] \"Gene expression data\" paragraph 2", "quote": "From the GEO database (https://www.ncbi.nlm.nih.gov/geo/), the microRNA microarray dataset GSE14634[10] and the mRNA datasets GSE11906,[11] GSE22047[12] and GSE63127[13] were downloaded."}], "state": "complete"}, {"id": "claim-target-result", "statement": "In total, 107 DEGs and 10 DEMs were determined.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:31568004", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "In total, 107 DEGs and 10 DEMs were determined."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "In total, 107 DEGs and 10 DEMs were determined.", "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:31568004"], "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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"complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: ppi_network."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE11906", "GSE22047", "GSE63127", "GSE14634"], "resolved_accessions": ["GSE11906", "GSE22047", "GSE63127", "GSE14634"], "statements": ["From the GEO database (https://www.ncbi.nlm.nih.gov/geo/), the microRNA microarray dataset GSE14634[10] and the mRNA datasets GSE11906,[11] GSE22047[12] and GSE63127[13] were downloaded."], "basis": "The paper names GSE11906, GSE22047, GSE63127, GSE14634 in Gene Expression Omnibus (GEO) database and the accession resolves in the repository. 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