Similarities and differences between smoking-related gene expression in nasal and bronchial epithelium
Bioinformatics Program, Boston University, Boston, Massachusetts 02118, USA. Physiological Genomics
(Impact Factor: 2.37).
12/2009; 41(1):1-8. DOI: 10.1152/physiolgenomics.00167.2009
Previous studies have shown that physiological responses to cigarette smoke can be detected via bronchial airway epithelium gene expression profiling and that heterogeneity in this gene expression response to smoking is associated with lung cancer. In this study, we sought to determine the similarity of the effects of tobacco smoke throughout the respiratory tract by determining patterns of smoking-related gene expression in paired nasal and bronchial epithelial brushings collected from 14 healthy nonsmokers and 13 healthy current smokers. Using whole genome expression arrays, we identified 119 genes whose expression was affected by smoking similarly in both bronchial and nasal epithelium, including genes related to detoxification, oxidative stress, and wound healing. While the vast majority of smoking-related gene expression changes occur in both bronchial and nasal epithelium, we also identified 27 genes whose expression was affected by smoking more dramatically in bronchial epithelium than nasal epithelium. Both common and site-specific smoking-related gene expression profiles were validated using independent microarray datasets. Differential expression of select genes was also confirmed by RT-PCR. That smoking induces largely similar gene expression changes in both nasal and bronchial epithelium suggests that the consequences of cigarette smoke exposure can be measured in tissues throughout the respiratory tract. Our findings suggest that nasal epithelial gene expression may serve as a relatively noninvasive surrogate to measure physiological responses to cigarette smoke and/or other inhaled exposures in large-scale epidemiological studies.
Available from: Akila Ranjith
- "and Butcher, 2002; Keith and Miller, 2013; Schembri et al., 2009; Boyle et al., 2010; Beane et al., 2007; Zhang et al., 2010; Harvey et al., 2007 "
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ABSTRACT: High-throughput sequencing of RNA (RNA-Seq) was developed primarily to analyze global gene expression in different tissues. It is also an efficient way to discover coding SNPs and when multiple individuals with different genetic backgrounds were used, RNA-Seq is very effective for the identification of SNPs. The objective of this study was to perform SNP and INDEL discoveries in human airway transcriptome of healthy never smokers, healthy current smokers, smokers without lung cancer and smokers with lung cancer. By preliminary comparative analysis of these four data sets, it is expected to get SNP and INDEL patterns responsible for lung cancer. A total of 85,028 SNPs and 5738 INDELs in healthy never smokers, 32,671 SNPs and 1561 INDELs in healthy current smokers, 50,205 SNPs and 3008 INDELs in smokers without lung cancer and 51,299 SNPs and 3138 INDELs in smokers with lung cancer were identified. The analysis of the SNPs and INDELs in genes that were reported earlier as differentially expressed was also performed. It has been found that a smoking person has SNPs at position 62,186,542 and 62,190,293 in SCGB1A1 gene and 180,017,251, 180,017,252, and 180,017,597 in SCGB3A1 gene and INDELs at position 35,871,168 in NFKBIA gene and 180,017,797 in SCGB3A1 gene. The SNPs identified in this study provides a resource for genetic studies in smokers and shall contribute to the development of a per-sonalized medicine. This study is only a preliminary kind and more vigorous data analysis and wet lab validation are required.
Available from: Navneet Momi
- "However, due to the presence of active salivary RNAses in the oral cavity, RNAs collected from the buccal mucosa are prone to a higher rate of degradation during collection thus causing a vexing problem for gene expression analyses (12). In fact, for these reasons nasal mucosa has been shown to perform better than buccal mucosa (32). Therefore, for buccal biomarkers to be more robust than the labile mRNA, recently, it has become apparent that small non-coding miRNAs are more robust and resistant to degradation (33). "
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ABSTRACT: MicroRNAs (miRNAs) have been shown to be reliable early biomarkers in a variety of cancers including that of lung. We ascertained whether the biomarker potential of miRNAs could be validated in microscopically normal and easily accessible buccal epithelial brushings from cigarette smokers as a consequence of lung cancer linked 'field carcinogenesis'. We found that compared to neoplasia-free subjects, a panel of 68 miRNAs were upregulated and 3 downregulated in the normal appearing buccal mucosal cells collected from patients harboring lung cancer (n=76). The performance characteristics of selected miRNAs (with ≥1-fold change) were excellent with an average under the receiver operator characteristic curve (AUROC) of >0.80. Several miRNAs also displayed gender specificity between the groups. These results provide the first proof-of-concept scenario in which minimally intrusive cheek brushings could provide an initial screening tool in a large at-risk population.
Available from: Manuel C Peitsch
- "Studies have reported that CS exposure is associated with increased expression of genes encoding the xenobiotic metabolism enzymes, such as CYP1A1 and CYP1B1 in both the nasal [17, 18] and buccal epithelia [49, 50]. Similar to the nasal epithelium, buccal epithelium has been postulated as a suitable surrogate tissue for the lung, which could be useful to determine disease risk biomarkers . "
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ABSTRACT: Capturing the effects of exposure in a specific target organ is a major challenge in risk assessment. Exposure to cigarette smoke (CS) implicates the field of tissue injury in the lung as well as nasal and airway epithelia. Xenobiotic metabolism in particular becomes an attractive tool for chemical risk assessment because of its responsiveness against toxic compounds, including those present in CS. This study describes an efficient integration from transcriptomic data to quantitative measures, which reflect the responses against xenobiotics that are captured in a biological network model. We show here that our novel systems approach can quantify the perturbation in the network model of xenobiotic metabolism. We further show that this approach efficiently compares the perturbation upon CS exposure in bronchial and nasal epithelial cells in vivo samples obtained from smokers. Our observation suggests the xenobiotic responses in the bronchial and nasal epithelial cells of smokers were similar to those observed in their respective organotypic models exposed to CS. Furthermore, the results suggest that nasal tissue is a reliable surrogate to measure xenobiotic responses in bronchial tissue.
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