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The “field of injury” hypothesis proposes that exposure to an inhaled insult such as cigarette smoke elicits a common molecular response throughout the respiratory tract. This response can therefore be quantified in any airway tissue, including readily accessible epithelial cells in the bronchus, nose, and mouth. High-throughput technologies, such as whole-genome gene expression microarrays, can be employed to catalog the physiological consequences of such exposures in the airway epithelium. Pulmonary diseases such as chronic obstructive pulmonary disease, lung cancer, and asthma are also thought to be associated with a field of injury, and in patients with these diseases, airway epithelial cells can be a useful surrogate for diseased tissue that is often difficult to obtain. Global measurement of mRNA and microRNA expression in these cells can provide useful information about the molecular pathogenesis of such diseases and may be useful for diagnosis and for predicting prognosis and response to therapy. In this review, our aim is to summarize the history and state of the art of such “transcriptomic” studies in the human airway epithelium, especially in smoking and smoking-related lung diseases, and to highlight future directions for this field.
Lung diseases associated with cigarette smoking, such as lung cancer and chronic obstructive pulmonary disease (COPD), are leading causes of morbidity and mortality in the United States and throughout the world. Much remains to be learned about the molecular pathogenesis of these diseases, partly because of the relative difficulty of obtaining diseased tissue from distal sites within the lung and the risks associated with invasive procedures in individuals with impaired lung function. If disease processes that occur in lung tissue are reflected at the molecular level in the airway epithelium, it may be possible to use this more readily accessible population of cells as a surrogate to study these diseases.
The “field of injury” hypothesis proposes that the entire respiratory system of an individual reacts to environmental insults such as tobacco smoke in a similar manner and that common aspects of this response can be measured in airway epithelium. Genome-wide gene expression profiling can be used to obtain a detailed molecular portrait of this physiological response. Similarly, pulmonary diseases may also create a field of injury throughout the respiratory system, and disease-specific changes in the expression of mRNAs and microRNAs in the airway epithelium may therefore provide insight into the molecular mechanisms of these diseases and yield biomarkers for diagnosis, prognosis, and response to therapy. In this review, our aim is to describe the state of the art of studies (summarized in Table 1 and Figure 1) that use genome-wide technologies to measure gene expression changes in the human airway epithelium that are associated with smoking and smoking-related lung diseases.
The first transcriptomic study that used microarrays to measure changes in airway gene expression (1) involved bronchial brushings obtained from the third-generation bronchi of volunteer smokers and nonsmokers. Although bronchial epithelium was profiled with an early “whole genome” array platform, the authors focused their analysis on a curated set of 44 antioxidant-related genes. Several classes of these genes, especially those involved in glutathione metabolism and redox balance, were both up-regulated and highly variable within smokers. Our group also profiled bronchial brushings of the large airway, expanding on the list of genes with smoking-associated differential expression and confirming that there is significant variability within the up-regulation of antioxidant-related genes in smokers (2). This variability may offer a biological explanation as to why only a subset of current and former smokers appears to be susceptible to smoking-induced lung diseases. These reports were followed by a similar study (3) that found that many of the same genes were also differentially expressed in the small airway epithelium (brushings of 10–12th-generation bronchi) of smokers, suggesting that the response to cigarette smoke is similar throughout the bronchial epithelium.
Smoking-induced lung diseases affect similar percentages of both current and former smokers, suggesting that genomic changes that occur in the airway of smokers persist after smoking cessation and may be associated with the development of these diseases. The question of which changes in airway gene expression persist after smoking cessation was first addressed in a 2004 study (2) and more fully addressed in a subsequent study (4). In both studies, our group profiled gene expression in brushings of the right mainstem bronchus of healthy current, former, and never-smokers. These studies found that the expression levels of most genes that are differentially expressed in active smokers rapidly revert to the levels seen in nonsmokers within a few months of smoking cessation. However, there is a subset of genes whose expression levels remained irreversibly altered for more than 10 years after smoking cessation. This set of genes includes a cluster of metallothioneins located at 16q13 that is irreversibly repressed in smokers, suggesting that smoking may have long-term effects on the antioxidant response of the airway epithelium. These genes were also found to be coordinately differentially expressed in the bronchial epithelium in an independent set of current and former smokers, suggesting that irreversible smoking-associated changes in gene expression could be used as a biomarker of prior exposure to tobacco smoke (4). The finding of irreversibly altered changes in bronchial airway gene expression among former smokers has been confirmed by two other groups using both microarray and SAGE (Serial Analysis of Gene Expression) platforms (5, 6).
The discovery of the role of microRNA in regulating key biological processes and the availability of whole-genome microRNA arrays has prompted investigation into the potential role of microRNAs in regulating the transcriptional response to cigarette smoke. We profiled mRNA and microRNA in parallel from bronchial brushings of the large airway epithelium of current and never-smokers (7). The majority of differentially expressed microRNAs are down-regulated in smokers, whereas the majority of mRNAs that are differentially expressed in smokers are up-regulated, which is intriguing given the role of microRNAs largely as negative regulators of mRNA levels. The expression of one microRNA in particular, miR-218, was inversely correlated with the expression of several of its computationally predicted mRNA targets, including MAFG (v-maf musculoaponeurotic fibrosarcoma oncogene homolog G, avian), a transcription factor whose binding site is overrepresented among genes that are differentially expressed in response to smoking. We further found that, in vitro, overexpression of miR-218 in cultured bronchial epithelial cells attenuated the up-regulation of MAFG in response to treatment with cigarette smoke condensate. These results suggest that miR-218 may be an important regulator of the transcriptional response of the airway epithelium to tobacco smoke.
Although the aforementioned studies have shown that changes in the expression of mRNAs and microRNAs occur throughout the bronchial epithelium of smokers, sampling of the bronchial airway via bronchoscopy is an invasive procedure that is not a feasible method for screening large populations at risk for smoking-related lung disease. Several groups have performed studies to determine whether the field of injury extends to upper, extrathoracic airway epithelia that could be collected less invasively than bronchial epithelium. Our group identified concordant smoking-associated changes in gene expression in brushings of the large airway and nasal epithelium in both cross-sectional (8) and paired (9) studies. Another study (10) demonstrated that a number of genes previously reported to be differentially expressed in the bronchus of smokers, especially xenobiotic detoxification genes, are also differentially expressed in the buccal mucosa of smokers obtained via biopsy, which is consistent with our findings of a modest smoking-related buccal gene-expression signature (8). These results suggest that there is a common response to tobacco smoke throughout the airway, and that changes in gene expression at any of these sites may be representative of changes in the bronchial epithelium in response to cigarette smoke. This point is illustrated in a side-by-side comparison of the differential expression of smoking-associated genes in epithelial cells of the small and large airway, trachea, and nose (Figure 2). Genes that were identified as differentially expressed in the bronchial airway of smokers in one data set (4) behave similarly in the small airway, trachea, and nose of smokers profiled in other studies (9, 11, 12).
The consistency of the physiological response to tobacco smoke exposure across airway epithelia, as measured by similar patterns of tobacco smoke exposure–associated changes in gene expression, may reflect the direct response of cells with a common physiology to compounds in tobacco smoke that are present throughout the respiratory tree of smokers. An important question, therefore, is whether signatures of processes that contribute to the molecular pathogenesis of pulmonary disease in general, and tobacco-related pulmonary diseases in particular, can also be detected globally in tissues throughout the respiratory system. The ability to detect the pathogenesis of disease in readily accessible tissue that is removed from the site of disease would not only facilitate studies focused on better understanding the mechanisms of disease formation, but might also be clinically useful for disease detection and monitoring. For pulmonary diseases in general, the potential to detect disease-specific changes in apparently nondiseased tissue might reflect aspects of disease that affect the entire respiratory system. For smoking-related pulmonary diseases in particular, it is additionally possible that in those smokers who develop a specific disease, cells throughout the respiratory system respond to tobacco smoke exposure in a manner that is consistent with disease formation. This scenario would suggest that not only might this prodisease response be detected throughout the respiratory system of smokers with clinical disease manifestation, but also that it might be possible to detect this prodisease response to tobacco exposure before disease manifestation.
The significant heterogeneity in smoking-associated differential gene expression observed in the normal airway of smokers has led several authors to postulate that certain smokers may have a qualitatively different response to tobacco smoke that predisposes them to the development of lung diseases such as lung cancer (2, 13) or COPD (1). Further evidence of a relationship between the response to smoking and lung tumorigenesis has been provided by two genome-wide gene expression profiling studies of lung tumors and normal bronchial epithelium (14, 15). These studies identified changes in gene expression associated with current smoking status in the normal bronchial epithelium that were also present in lung tumors versus normal bronchial epithelium (irrespective of smoking status). These changes included the up-regulation of genes involved in the oxidant and xenobiotic response and the down-regulation of genes encoding tumor suppressors.
These observations suggest that there is a connection between airway gene expression and lung cancer and that gene expression in the normal airway epithelium might serve as a diagnostic or screening tool for this disease. Our group has investigated this possibility and has developed a gene expression profile that can serve as an early diagnostic biomarker for lung cancer, using bronchial brushings of cytologically normal large airway epithelium from individuals undergoing bronchoscopy for suspect lung cancer (16). This biomarker improves diagnostic accuracy when combined with traditional diagnostic bronchoscopy (16), and is independent of clinical factors as a diagnostic risk factor (17). The concept that gene expression in normal airway epithelium can be used as a biomarker of lung cancer was also used by Blomquist and colleagues to identify 14 genes (including antioxidant and DNA repair genes) whose expression was altered in brushings of normal bronchial epithelium of patients with lung cancer versus those without lung cancer (18).
The finding that changes in gene expression in the normal bronchial epithelium are associated with the presence of lung cancer raises the possibility that preneoplastic disease may be associated with similar changes. To test this hypothesis, our group used whole-genome gene expression microarrays to profile cytologically normal bronchial epithelium in smokers with and without dysplastic airway lesions (19). A gene expression signature of phosphoinositide-3-kinase signaling pathway activation was coordinately differentially expressed in smokers with these dysplastic lesions, as well as in the cytologically normal large airway epithelium of smokers with lung cancer from our previous study (16). Furthermore, pharmacological inhibition of this pathway led to the regression of dysplastic lesions and a concomitant reversal of the perturbation of the phosphoinositide-3-kinase gene expression signature in the subset of smokers with regression. This suggests that smoking-induced changes in airway gene expression may reflect early, potentially reversible deregulation of specific molecular pathways related to lung carcinogenesis, and that monitoring of these changes might assist in the selection of specific chemopreventive agents for smokers at highest risk for lung cancer.
COPD is clinically defined as obstruction to airflow that is not completely reversible with bronchodilator treatment. However, COPD is a heterogeneous disease with a variable natural history, and individuals with COPD exhibit varying degrees of small airway inflammation, bronchitis, and emphysema. Early transcriptomic studies of gene expression in COPD relied on lung tissue specimens from individuals undergoing surgery (20–25). These studies were generally hampered by small sample sizes, limited phenotyping of COPD, and confounding variables such as smoking status and concomitant lung cancer, and the overlap between sets of COPD-related differentially expressed genes reported by each study was small. However, meta-analysis of these studies by Gene Set Enrichment Analysis (GSEA) (26) has shown that these studies demonstrate reproducible COPD-related gene expression changes in COPD-affected lung tissue (27).
If a COPD-associated field of injury extends to the bronchial airway, it may be possible to measure COPD pathogenesis in airway epithelium. As current studies of COPD have been limited by the availability of surgical samples, this approach would facilitate expanded studies of the mechanisms of COPD pathogenesis in primary human samples. Two studies have demonstrated the feasibility of this approach. By profiling bronchial epithelial brushings, Pierrou and colleagues found that genes that were differentially expressed in the airway epithelium of smokers with and without COPD were enriched in genes from curated oxidative stress response pathways (28). Similarly, Tilley and colleagues identified that a subset of genes from the Notch signaling pathway were down-regulated in the small airway epithelium of smokers with COPD compared with smokers without COPD (29). As we described in an abstract presented at the 2010 Aspen Lung Conference, genome-wide gene expression profiling of bronchial brushings from large numbers of matched subjects with and without COPD has identified concordant differential expression of genes whose expression is known to be perturbed in lung tissue of smokers with COPD. This suggests that airway gene expression in COPD reflects molecular processes occurring in more distal diseased lung tissue, and that the bronchial airway epithelium may therefore serve as a surrogate that can be sampled less invasively to study COPD.
Asthma is defined clinically as reversible obstruction of the airway. It is caused by exposure to inhaled allergens, which leads to helper T-cell type 2 (Th2)–mediated inflammation of the airways and results in inflammatory cell infiltration, airway hyperresponsiveness, and tissue remodeling. Because asthma is associated with an airway-wide inhaled exposure, it might also induce an airway-wide field of injury reflecting the presence and severity of this disease. If so, an airway epithelium transcriptomic signature of asthma might be a useful tool for developing personalized therapies, discovering new drugs, and creating prognostic biomarkers.
The first genome-wide study of airway epithelial gene expression in asthma used microarrays to profile bronchial brushings from nonsmokers with and without asthma (30). This study identified changes in gene expression associated with the presence of asthma, as well as those associated with treatment with the inhaled corticosteroid fluticasone. A follow-up study identified a set of genes induced by IL-13 and IL-4, whose expression was increased in a subset of individuals with asthma (31). This “Th2-high” pattern of gene expression was reversed after 4 to 8 weeks of treatment with fluticasone, accompanied by improvements in FEV1. These observations suggest that asthma is associated with a field of injury in the airway, and that airway gene expression profiling of individuals with asthma has the potential to identify individuals with distinct subtypes of asthma that may preferentially respond to particular therapies.
As described previously regarding smoking and smoking-associated diseases, the field of injury related to asthma may also extend to the epithelia of the upper airway. Asthma-related biomarkers measured in these epithelia would allow for less invasive specimen collection, which is especially important for studies involving children who are affected by this disease. Guajardo and colleagues established a nasal asthma-associated field of injury by profiling nasal mucosal brushings from children with stable or acute asthma as well as from healthy control subjects (32). Several functional categories of genes were differentially expressed in both asthmatic groups, including genes related to immune function and signal transduction. Distinct gene expression profiles were also associated with either stable or acute asthma, suggesting that the nasal field of injury reflects disease heterogeneity and may be useful in identifying subgroups of individuals with asthma who are refractory to particular therapies or who might be at higher risk for more frequent exacerbations of this disease.
As described in this review, significant progress has been made in establishing that an airway-wide field of injury occurs in response to tobacco smoke and in establishing that a similar field of injury exists in response to smoking-related diseases such as lung cancer and COPD, or inhaled exposure–related diseases such as asthma. Through the use of genome-wide gene expression profiling technologies, it has been possible to create detailed molecular portraits of these fields of injury that are useful not only for understanding mechanisms of disease pathogenesis but also for developing biomarkers capable of monitoring disease formation and progression in readily accessible airway tissues. The rapid emergence of next-generation sequencing of RNA promises to provide us with an even more comprehensive view of the transcriptional changes associated with this airway field of injury.
The airway epithelium is the first barrier to environmental exposures in the lung, and as such, patterns of gene expression in these cells are likely to be the most informative about the response of the lung to inhaled insults. However, other cell types have potential advantages as sites for studies of airway disease. Several studies (e.g., References 33 and 34) have measured genome-wide gene expression in alveolar macrophages collected by bronchoalveolar lavage, samples enriched in inflammatory cells that might participate directly in some disease processes within the lung. Sputum is also a potential biosample for gene expression studies, although this is technically challenging because of mRNA degradation. Peripheral blood is a routinely collected clinical specimen that is also a source of inflammatory cells that are exposed to inhaled insults because of the high degree of lung vascularization. Studies have measured the effect of chronic smoking on gene expression in peripheral blood mononuclear cells (35, 36) and the use of peripheral blood mononuclear cell gene expression as a biomarker of lung cancer has also been reported (37). Ongoing work in these and other cell types should be especially helpful for understanding the systemic effects of tobacco smoke exposure and tobacco-related disease and for creating additional biomarkers of pulmonary disease that may complement those measured in airway epithelium.
Although tobacco smoke is the most well-characterized chronic insult to the airway epithelium, other environmental exposures contribute to disease, including ozone, diesel exhaust, unvented coal smoke, and asbestos. Although these agents have been studied using cell culture and animal models, there are limited transcriptomic studies that have measured the effect of these exposures on gene expression in human airway epithelium. Understanding the similarities and differences between the fields of injury induced by these different exposures may help to better define the repertoire of physiological responses to inhaled exposures and allow the identification of aspects of these responses that contribute to disease formation.
Several other pulmonary diseases, including interstitial lung disease, acute respiratory distress syndrome, and sarcoidosis, may also be associated with a field of injury in the lung and respiratory tract. Genome-wide gene expression has been measured in these diseases in lung tissue or in surrogates such as blood and bronchoalveolar lavage fluid (38–42). Airway-based transcriptomic studies of these diseases could complement these studies and be useful for elucidating molecular pathologies, identifying clinically relevant subclasses of disease, and creating diagnostic and prognostic biomarkers. They may also serve to more generally define how disease processes that may be less directly connected with inhaled exposures affect the physiology of the entire respiratory system and thereby give rise to an airway field of injury.
Author Disclosure: A.C.G. received grant support from the NIH. K.S. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript. J.F.B. received grant support from the NIH. M.E.L. was a consultant for and owns stock in Allegro Diagnostics Inc., and he received grant support from the NIH. A.S. was a consultant for and owns stock in Allegro Diagnostics Inc., and he received grant support from the NIH.