This trial studies biomarkers obtained by bronchoscopy (bronchoalveolar lavage and lung brushings) to determine the effect of smoking e-cigarettes on the lungs. Studying samples of lung cells from participants who smoke e-cigarettes may help doctors learn more about changes that occur in deoxyribonucleic acid and identify biomarkers related to cancer.
PRIMARY OBJECTIVES: I. To assess inflammatory changes over 10 weeks for lung and urine biomarkers in smokers who undergo serial bronchoscopy. The randomized trial includes four conditions: continued use (n=32), complete switching to the nicotine standardized research electronic cigarettes (e-cig) (SREC) (n=32), complete switching to the placebo (nicotine free) SREC (n=32), and complete switching to nicotine replacement therapy (NRT)(n=32). OUTLINE: Participants are randomized to 1 of 4 groups. GROUP I: Participants undergo bronchoscopy over 30-60 minutes at baseline. Participants continue to smoke their usual brand of cigarettes. Participants undergo a second bronchoscopy on day 71. GROUP II: Participants undergo bronchoscopy over 30-60 minutes at baseline. After the baseline bronchoscopy, participants learn to use the SREC with nicotine for 2 weeks and switch completely to the SREC with nicotine for 2 weeks and switch completely to the SREC with nicotine starting day 15 for 8 weeks. Participants undergo a second bronchoscopy on day 71. GROUP III: Participants undergo bronchoscopy over 30-60 minutes at baseline. After the baseline bronchoscopy, participants learn to use the SREC without nicotine for 2 weeks and switch completely to the SREC without nicotine starting day 15 for 8 weeks. Participants will be offered varenicline to aid cessation. Participants undergo a second bronchoscopy on day 71. GROUP IV: Participants undergo bronchoscopy over 30-60 minutes at baseline. Beginning 1 week before the day 15 quit date, participants stop smoking using NRT comprising either patch, gum, or lozenge for 8 weeks. Participants undergo a second bronchoscopy on day 71. After completion of study, participants are followed up at 3 months.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
NONE
Enrollment
239
Undergo bronchoscopy with bronchoalveolar lavage
Smoke usual brand
Smoke SREC with nicotine
Ohio State University Comprehensive Cancer Center
Columbus, Ohio, United States
RECRUITINGChanges in cell counts and cytokines
Obtained via bronchoscopy with saline bronchoalveolar lavage (BAL) and bronchial brushings. Descriptive statistics and clustering (e.g., principal components analysis \[PCA\]), will be performed for all biomarker data measured at the different visits. Baseline data (1st bronchoscopy) will then be compared between the four groups (3 conditions and control) using a one-way analysis of variance (ANOVA). The non-parametric Kruskal-Wallis test (continuous or ordinal variables) or the chi-square test (categorical variables) will be applied when the normality assumption of the data is not met. Controls will be compared to complete substitution with the standardized research electronic cigarettes (SREC) (with and without nicotine) or nicotine replacement therapy (NRT. Generalized linear models (GLM) will be employed with measurement (cell count, gene expression, etc.) as the dependent variable, a covariable for baseline measure, and a main effect of arm.
Time frame: Baseline to day 71
Changes in fractional exhaled nitric oxide (FeNO) levels
FeNO will be measured with the NIOX VERO. Descriptive statistics and clustering (e.g. PCA), will be performed for all biomarker data measured at the different visits. Baseline data (1st bronchoscopy) will then be compared between the four groups (3 conditions and control) using a one-way ANOVA. The non-parametric Kruskal-Wallis test (continuous or ordinal variables) or the chi-square test (categorical variables) will be applied when the normality assumption of the data is not met. Controls will be compared to complete substitution with the SREC (with and without nicotine) or NRT. GLM will be employed with measurement (cell count, gene expression, etc.) as the dependent variable, a covariable for baseline measure, and a main effect of arm.
Time frame: Baseline up to day 71
Changes in messenger (m) ribonucleic acid (RNA) and microRNA (miRNA) gene expression analyzed using sequencing
Total RNA containing small RNAs will be extracted from bronchial brushing specimens using commercially available kits and used for both gene expression using the Affymetrix GeneChip Human Transcriptome Array and for miRNA expression using the Affymetrix GeneChip miRNA Array. Expression will separately be assessed through RNA sequencing. Total RNA will be extracted from lavage cells and saliva for comprehensive profiling of microbiome using commercially available kits. The ?omics? (miRNA, mRNA, and metabolomics) analysis and visualization of the data will be performed in the R statistical language. Data will be log2-transformed and normalized using either quantile normalization for gene expression (miRNA and mRNA) or normalization for metabolomics. Unsupervised clustering analysis, including PCA and hierarchical clustering will be performed to visualize natural clusters in the dataset and evaluate data quality.
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Smoke SREC without nictoine
Correlative studies
Receive NRT comprising patch, gum, or lozenge
Ancillary studies
Time frame: Baseline up to day 71
Changes in deoxyribonucleic acid (DNA) gene methylation
Total DNA will be extracted using commercially available kits and used for genome-wide DNA methylation profiling. Total DNA including mitochondrial DNA (mtDNA) will be extracted using commercially available kits and used for mtDNA mutation using Hiseq Next Generation Sequencing (NGS) and for mtDNA contents using quantitative polymerase chain reaction (qPCR). For preliminary identification of patterns in DNA methylation, unsupervised hierarchical clustering among the groups of samples will be performed. The Euclidian distance among the groups of samples will be calculated by the average linkage. In order to assess variance among samples, PCA will be done.
Time frame: Baseline up to day 71
Changes in the microbiome in BAL cells and saliva
Obtained via bronchoscopy with saline BAL and bronchial brushings. Samples will be analyzed to determine their bacterial composition.
Time frame: Baseline up to day 71
Changes in untargeted metabolomics using mass spectrometry
Obtained via bronchoscopy with saline BAL and bronchial brushings. The omics (miRNA, mRNA, and metabolomics) analysis and visualization of the data will be performed in the R statistical language. Data will be log2-transformed and normalized using either quantile normalization for gene expression (miRNA and mRNA) or normalization for metabolomics. Unsupervised clustering analysis, including PCA and hierarchical clustering will be performed to visualize natural clusters in the dataset and evaluate data quality.
Time frame: Baseline up to day 71