Biologic Phenotyping of the Human Small Airway Epithelial Response to Cigarette Smoking
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Yael Strulovici-Barel
PROVIDER: E-GEOD-11784 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Publications
Biologic phenotyping of the human small airway epithelial response to cigarette smoking.
Tilley Ann E AE O'Connor Timothy P TP Hackett Neil R NR Strulovici-Barel Yael Y Salit Jacqueline J Amoroso Nancy N Zhou Xi Kathy XK Raman Tina T Omberg Larsson L Clark Andrew A Mezey Jason J Crystal Ronald G RG
PloS one 20110728 7
<h4>Background</h4>The first changes associated with smoking are in the small airway epithelium (SAE). Given that smoking alters SAE gene expression, but only a fraction of smokers develop chronic obstructive pulmonary disease (COPD), we hypothesized that assessment of SAE genome-wide gene expression would permit biologic phenotyping of the smoking response, and that a subset of healthy smokers would have a "COPD-like" SAE transcriptome.<h4>Methodology/principal findings</h4>SAE (10th-12th gener ...[more]
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2011-06-27 | E-GEOD-20257 | biostudies-arrayexpress
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2011-04-20 | E-GEOD-19407 | biostudies-arrayexpress
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2012-06-19 | E-GEOD-22047 | biostudies-arrayexpress
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2011-10-27 | GSE11784 | GEO
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2009-01-13 | E-GEOD-7832 | biostudies-arrayexpress
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2009-07-13 | E-GEOD-11952 | biostudies-arrayexpress
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2017-07-18 | GSE64614 | GEO
Project description:Rationale: Even after quitting smoking, the risk of the development of chronic obstructive pulmonary disease (COPD) and lung cancer remains significantly higher compared to never-smokers. Objectives: Based on the knowledge that COPD and most lung cancers start in the small airway epithelium (SAE), we hypothesized that smoking modulates miRNA expression in the SAE linked to the pathogenesis of smoking-induced airway disease, and that some of these changes persist after smoking cessation. Methods: SAE was collected from 10th to 12th order bronchi using fiberoptic bronchoscopy. Affymetrix miRNA 2.0 arrays were used to assess miRNA expression in the SAE from 10 healthy never-smokers and 10 healthy smokers, before and after they quit for 3 months. Smoking status was determined by urine nicotine and cotinine measurement. Results: There were significant differences in the expression of 34 miRNAs between healthy smokers and healthy never-smokers (p<0.01, fold-change >1.5), with functions associated with lung development, airway epithelium differentiation, inflammation and cancer. After quitting smoking for 3 months, 12 out of the 34 miRNAs did not return to normal levels, with Wnt/β-catenin signaling pathway the top enriched pathway of the target genes of the persistent deregulated miRNAs. Conclusions: In the context that many of these persistent smoking-dependent miRNAs are associated with differentiation, inflammation diseases or lung cancer, it is likely that persistent smoking-related changes in small airway epithelium miRNAs play a role in the subsequent development of these disorders.
2015-11-23 | GSE53519 | GEO
Project description:Microarray technology provides a powerful tool for defining gene expression profiles of airway epithelium that lend insight into the pathogenesis of human airway disorders. The focus of this study was to establish rigorous quality control parameters to ensure that microarray assessment of the airway epithelium is not confounded by experimental artifact. Samples (total n=223) of trachea, large and small airway epithelium were collected by fiberoptic bronchoscopy of 144 individuals (42 healthy non-smokers, 49 healthy smokers, 11 symptomatic smokers, 22 smokers with lone emphysema with normal spirometry, and 20 smokers with COPD) were processed and hybridized to Affymetrix HG-U133 2.0 Plus microarrays. The pre- and post-chip quality control (QC) criteria established, included: (1) RNA quality, assessed by RNA Integrity Number (RIN) ≥7.0 using Agilent 2100 Bioanalyzer software; (2) cRNA transcript integrity, assessed by signal intensity ratio of GAPDH 3' to 5' probe sets ≤3.0; and (3) the multi-chip normalization scaling factor ≤10.0 Of the 223 samples, 213 (95.5%) passed the QC criteria. In a data set of 34 arrays (10 samples failing QC criteria, 24 randomly chosen samples passing QC criteria), correlation coefficients for pairwise comparisons of expression levels for 100 housekeeping genes in which at least one array failed the QC criteria were significantly lower (average Pearson r = 0.90 ± 0.04) and more broadly dispersed than correlation coefficients for pairwise comparisons between any two arrays that passed the QC criteria (average Pearson r = 0.97 ± 0.01). By using the QC cutoff criteria, the inter-array variability, as assessed by the coefficient of variation in the expression levels for 100 housekeeping genes, was reduced from 35.7% to 21.7%. Based on the aberrant housekeeping gene data generated from samples failing the established QC criteria, we propose that the QC criteria outlined in this study can accurately distinguish high quality from low quality data and can be used to delete poor quality microarray samples before proceeding to higher-order biological analyses and interpretation. Affymetrix arrays were used to assess the quality of gene expression data in trachea, large airway and small airway epithelium obtained by fiberoptic bronchoscopy of 42 healthy non-smokers, 49 healthy smokers, 11 symptomatic smokers, 22 smokers with lone emphysema with normal spirometry, and 20 smokers with COPD.
2010-09-19 | E-GEOD-11906 | biostudies-arrayexpress