ArticleMedicine2019
Identification of gene and microRNA changes in response to smoking in human airway epithelium by bioinformatics analyses.
Article in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
10 citing papers in PubMed, 22 citations in OpenAlex.
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- The blood proteome of imminent lung cancer diagnosis.Nature communications · 2023Article
- The Profile of MicroRNA Expression and Potential Role in the Regulation of Drug-Resistant Genes in Doxorubicin and Topotecan Resistant Ovarian Cancer Cell Lines.International journal of molecular sciences · 2022Article
- Comprehensive analysis of the LncRNAs, MiRNAs, and MRNAs acting within the competing endogenous RNA network of LGG.Genetica · 2022Article
- A novel 14-gene signature for overall survival in lung adenocarcinoma based on the Bayesian hierarchical Cox proportional hazards model.Scientific reports · 2022Article
- Identification ofFrontiers in oncology · 2021Article
- Host Factor Interaction Networks Identified by Integrative Bioinformatics Analysis Reveals Therapeutic Implications in COPD Patients With COVID-19.Frontiers in pharmacology · 2021Article
- Identification of key genes in calcific aortic valve disease by integrated bioinformatics analysis.Medicine · 2020Article
- Immunomodulatory Effects of Hydrolyzed Seawater Pearl Tablet (HSPT) on Th1/Th2 Functionality in a Mice Model of Chronic Obstructive Pulmonary Disease (COPD) Induced by Cigarette Smoke.Evidence-based complementary and alternative medicine : eCAM · 2020Review
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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