Interaction of cigarette exposure and airway epithelial cell gene expression.

Cigarette smoking is responsible for lung cancer and chronic obstructive pulmonary disease (COPD), the leading cause of death from cancer and the second-leading cause of death in the United States. In the United States, 46 million people smoke, with an equal number of former smokers. Moreover, 20-25% of current or former smokers will develop either disease, and smokers with one disease are at increased risk for developing the other. There are no tools for predicting risk of developing either disease; no accepted tools for early diagnosis of potentially curable lung cancer; and no tools for defining molecular pathways or molecular subtypes of these diseases, for predicting rate of progression, or for assessing response to therapy at a biochemical or molecular level. This review discusses current studies and the future potential of measuring global gene expression in epithelial cells that are in the airway field of injury and of using the genomic information derived to begin to answer some of the above questions.

Airway epithelial gene expression in the diagnostic evaluation of smokers with suspect lung cancer.

Lung cancer is the leading cause of death from cancer in the US and the world. The high mortality rate (80-85% within 5 years) results, in part, from a lack of effective tools to diagnose the disease at an early stage. Given that cigarette smoke creates a field of injury throughout the airway, we sought to determine if gene expression in histologically normal large-airway epithelial cells obtained at bronchoscopy from smokers with suspicion of lung cancer could be used as a lung cancer biomarker. Using a training set (n = 77) and gene-expression profiles from Affymetrix HG-U133A microarrays, we identified an 80-gene biomarker that distinguishes smokers with and without lung cancer. We tested the biomarker on an independent test set (n = 52), with an accuracy of 83% (80% sensitive, 84% specific), and on an additional validation set independently obtained from five medical centers (n = 35). Our biomarker had approximately 90% sensitivity for stage 1 cancer across all subjects. Combining cytopathology of lower airway cells obtained at bronchoscopy with the biomarker yielded 95% sensitivity and a 95% negative predictive value. These findings indicate that gene expression in cytologically normal large-airway epithelial cells can serve as a lung cancer biomarker, potentially owing to a cancer-specific airway-wide response to cigarette smoke.

Transcriptome alterations induced by cigarette smoke.

Cigarette smoke alters the transcriptome of multiple tissues; those directly exposed to toxic products and those exposed to circulating components and metabolic products of tobacco smoke. In most tissues and organs that have been studied, the smoking transcriptome is characterized by increased expression of antioxidant and xenobiotic genes as well as a wide spectrum of inflammation-related genes, and potential oncogenic genes. Smoking is associated with an increased incidence of cancer in a number of organs both those directly exposed (lungs and airways) and those indirectly exposed (bladder, liver, pancreas). Individual transcriptomic responses vary, based to some degree on as yet to be clarified genetic factors, and likely how and what the individual has smoked. The complexity of individual responses to tobacco exposure and of smoking-related cancers in various organs is beginning to be revealed in transcriptomic and whole genome sequencing studies, of both tumors and cytologically normal appearing cells that have been exposed to cigarette smoke or its products creating a genomic "field of injury." The recent application of next generation sequencing to defining the transcriptome alterations induced by cigarette smoke holds the promise of discovering new approaches to personalized prevention and treatment of smoking-related lung diseases in the future.

MicroRNAs as modulators of smoking-induced gene expression changes in human airway epithelium.

We have shown that smoking impacts bronchial airway gene expression and that heterogeneity in this response associates with smoking-related disease risk. In this study, we sought to determine whether microRNAs (miRNAs) play a role in regulating the airway gene expression response to smoking. We examined whole-genome miRNA and mRNA expression in bronchial airway epithelium from current and never smokers (n = 20) and found 28 miRNAs to be differentially expressed (P < 0.05) with the majority being down-regulated in smokers. We further identified a number of mRNAs whose expression level is highly inversely correlated with miRNA expression in vivo. Many of these mRNAs contain potential binding sites for the differentially expressed miRNAs in their 3'-untranslated region (UTR) and are themselves affected by smoking. We found that either increasing or decreasing the levels of mir-218 (a miRNA that is strongly affected by smoking) in both primary bronchial epithelial cells and H1299 cells was sufficient to cause a corresponding decrease or increase in the expression of predicted mir-218 mRNA targets, respectively. Further, mir-218 expression is reduced in primary bronchial epithelium exposed to cigarette smoke condensate (CSC), and alteration of mir-218 levels in these cells diminishes the induction of the predicted mir-218 target MAFG in response to CSC. These data indicate that mir-218 levels modulate the airway epithelial gene expression response to cigarette smoke and support a role for miRNAs in regulating host response to environmental toxins.

Smoking-induced gene expression changes in the bronchial airway are reflected in nasal and buccal epithelium.

BACKGROUND: Cigarette smoking is a leading cause of preventable death and a significant cause of lung cancer and chronic obstructive pulmonary disease. Prior studies have demonstrated that smoking creates a field of molecular injury throughout the airway epithelium exposed to cigarette smoke. We have previously characterized gene expression in the bronchial epithelium of never smokers and identified the gene expression changes that occur in the mainstem bronchus in response to smoking. In this study, we explored relationships in whole-genome gene expression between extrathorcic (buccal and nasal) and intrathoracic (bronchial) epithelium in healthy current and never smokers. RESULTS: Using genes that have been previously defined as being expressed in the bronchial airway of never smokers (the "normal airway transcriptome"), we found that bronchial and nasal epithelium from non-smokers were most similar in gene expression when compared to other epithelial and nonepithelial tissues, with several antioxidant, detoxification, and structural genes being highly expressed in both the bronchus and nose. Principle component analysis of previously defined smoking-induced genes from the bronchus suggested that smoking had a similar effect on gene expression in nasal epithelium. Gene set enrichment analysis demonstrated that this set of genes was also highly enriched among the genes most altered by smoking in both nasal and buccal epithelial samples. The expression of several detoxification genes was commonly altered by smoking in all three respiratory epithelial tissues, suggesting a common airway-wide response to tobacco exposure. CONCLUSION: Our findings support a relationship between gene expression in extra- and intrathoracic airway epithelial cells and extend the concept of a smoking-induced field of injury to epithelial cells that line the mouth and nose. This relationship could potentially be utilized to develop a non-invasive biomarker for tobacco exposure as well as a non-invasive screening or diagnostic tool providing information about individual susceptibility to smoking-induced lung diseases.

Microsensor arrays for saliva diagnostics.

Optical fiber microarrays have been used to screen saliva from patients with end-stage renal disease (ESRD) to ascertain the efficacy of dialysis. We have successfully identified markers in saliva that correlate with kidney disease. Standard assay chemistries for these markers have been converted to disposable test strips such that patients may one day be able to monitor their clinical status at home. Details of these developments are described. In addition, saliva from asthma and chronic obstructive pulmonary disease (COPD) patients is being screened for useful diagnostic markers. Our goal is to develop a multiplexed assay for these protein and nucleic acid biomarkers for diagnosing the cause and severity of pulmonary exacerbations, enabling more effective treatment to be administered. These results are reported in the second part of this article.

SIEGE: Smoking Induced Epithelial Gene Expression Database.

The SIEGE (Smoking Induced Epithelial Gene Expression) database is a clinical resource for compiling and analyzing gene expression data from epithelial cells of the human intra-thoracic airway. This database supports a translational research study whose goal is to profile the changes in airway gene expression that are induced by cigarette smoke. RNA is isolated from airway epithelium obtained at bronchoscopy from current-, former- and never-smoker subjects, and hybridized to Affymetrix HG-U133A Genechips, which measure the level of expression of approximately 22,500 human transcripts. The microarray data generated along with relevant patient information is uploaded to SIEGE by study administrators using the database's web interface, found at http://pulm.bumc.bu.edu/siegeDB. PERL-coded scripts integrated with SIEGE perform various quality control functions including the processing, filtering and formatting of stored data. The R statistical package is used to import database expression values and execute a number of statistical analyses including t-tests, correlation coefficients and hierarchical clustering. Values from all statistical analyses can be queried through CGI-based tools and web forms found on the 'Search' section of the database website. Query results are embedded with graphical capabilities as well as with links to other databases containing valuable gene resources, including Entrez Gene, GO, Biocarta, GeneCards, dbSNP and the NCBI Map Viewer.

Derivation of a bronchial genomic classifier for lung cancer in a prospective study of patients undergoing diagnostic bronchoscopy.

BACKGROUND: The gene expression profile of cytologically-normal bronchial airway epithelial cells has previously been shown to be altered in patients with lung cancer. Although bronchoscopy is often used for the diagnosis of lung cancer, its sensitivity is imperfect, especially for small and peripheral suspicious lesions. In this study, we derived a gene expression classifier from airway epithelial cells that detects the presence of cancer in current and former smokers undergoing bronchoscopy for suspect lung cancer and evaluated its sensitivity to detect lung cancer among patients from an independent cohort. METHODS: We collected bronchial epithelial cells (BECs) from the mainstem bronchus of 299 current or former smokers (223 cancer-positive and 76 cancer-free subjects) undergoing bronchoscopy for suspected lung cancer in a prospective, multi-center study. RNA from these samples was run on gene expression microarrays for training a gene-expression classifier. A logistic regression model was built to predict cancer status, and the finalized classifier was validated in an independent cohort from a previous study. RESULTS: We found 232 genes whose expression levels in the bronchial airway are associated with lung cancer. We then built a classifier based on the combination of 17 cancer genes, gene expression predictors of smoking status, smoking history, and gender, plus patient age. This classifier had a ROC curve AUC of 0.78 (95% CI, 0.70-0.86) in patients whose bronchoscopy did not lead to a diagnosis of lung cancer (n = 134). In the validation cohort, the classifier had a similar AUC of 0.81 (95% CI, 0.73-0.88) in this same subgroup (n = 118). The classifier performed similarly across a range of mass sizes, cancer histologies and stages. The negative predictive value was 94% (95% CI, 83-99%) in subjects with a non-diagnostic bronchoscopy. CONCLUSION: We developed a gene expression classifier measured in bronchial airway epithelial cells that is able to detect lung cancer in current and former smokers who have undergone bronchoscopy for suspicion of lung cancer. Due to the high NPV of the classifier, it could potentially inform clinical decisions regarding the need for further invasive testing in patients whose bronchoscopy is non diagnostic.

Patterns of allelic loss differ in lung adenocarcinomas of smokers and nonsmokers.

Cigarette smoking is the most important cause of lung cancer, however approximately 10% of patients with lung cancer have no history of smoking. While the molecular pathogenesis of smoking associated lung carcinogenesis is becoming well characterized, the pathogenesis of lung cancer in nonsmokers is not. We designed a study to examine the pathogenesis of adenocarcinoma in nonsmokers by determining if loss of heterozygosity (LOH) in tumors of nonsmokers differs from those of smokers. We evaluated six cases of primary adenocarcinoma in never smokers and six selected cases in smokers, matched by clinical and histological criteria. LOH in tumor DNA relative to nonmalignant lung DNA was determined at 52 microsatellites located on ten chromosomal loci. The extent of allelic loss in smokers, as measured by fractional allelic loss (FAL), was compared with nonsmokers. LOH was more frequent in the tumors of nonsmokers than of smokers with mean FAL of 46% in nonsmokers and 28% in smokers (P<0.05). Increased LOH in nonsmokers was most pronounced at chromosomes: 3p, 8p, 9p, 10p, and 18q. Since this study compared allelic loss between lung and tumor-bearing lung, less frequent LOH in smokers' tumors can be interpreted to suggest LOH was already present in the nonmalignant lung of smokers and fewer additional instances of allelic loss were present in the tumors of smokers. Our results suggest that the early steps of lung carcinogenesis differ in nonsmokers compared with smokers. In addition, the chromosomal sites of LOH may identify genes important for lung carcinogenesis in nonsmokers.

Updates and controversies in the rapidly evolving field of lung cancer screening, early detection, and chemoprevention.

Lung cancer remains the leading cause of cancer-related death in the United States. Cigarette smoking is a well-recognized risk factor for lung cancer, and a sustained elevation of lung cancer risk persists even after smoking cessation. Despite identifiable risk factors, there has been minimal improvement in mortality for patients with lung cancer primarily stemming from diagnosis at a late stage when there are few effective therapeutic options. Early detection of lung cancer and effective screening of high-risk individuals may help improve lung cancer mortality. While low dose computerized tomography (LDCT) screening of high risk smokers has been shown to reduce lung cancer mortality, the high rates of false positives and potential for over-diagnosis have raised questions on how to best implement lung cancer screening. The rapidly evolving field of lung cancer screening and early-detection biomarkers may ultimately improve the ability to diagnose lung cancer in its early stages, identify smokers at highest-risk for this disease, and target chemoprevention strategies. This review aims to provide an overview of the opportunities and challenges related to lung cancer screening, the field of biomarker development for early lung cancer detection, and the future of lung cancer chemoprevention.

Comparison of proteomic and transcriptomic profiles in the bronchial airway epithelium of current and never smokers.

BACKGROUND: Although prior studies have demonstrated a smoking-induced field of molecular injury throughout the lung and airway, the impact of smoking on the airway epithelial proteome and its relationship to smoking-related changes in the airway transcriptome are unclear. METHODOLOGY/PRINCIPAL FINDINGS: Airway epithelial cells were obtained from never (n = 5) and current (n = 5) smokers by brushing the mainstem bronchus. Proteins were separated by one dimensional polyacrylamide gel electrophoresis (1D-PAGE). After in-gel digestion, tryptic peptides were processed via liquid chromatography/ tandem mass spectrometry (LC-MS/MS) and proteins identified. RNA from the same samples was hybridized to HG-U133A microarrays. Protein detection was compared to RNA expression in the current study and a previously published airway dataset. The functional properties of many of the 197 proteins detected in a majority of never smokers were similar to those observed in the never smoker airway transcriptome. LC-MS/MS identified 23 proteins that differed between never and current smokers. Western blotting confirmed the smoking-related changes of PLUNC, P4HB1, and uteroglobin protein levels. Many of the proteins differentially detected between never and current smokers were also altered at the level of gene expression in this cohort and the prior airway transcriptome study. There was a strong association between protein detection and expression of its corresponding transcript within the same sample, with 86% of the proteins detected by LC-MS/MS having a detectable corresponding probeset by microarray in the same sample. Forty-one proteins identified by LC-MS/MS lacked detectable expression of a corresponding transcript and were detected in

The field of tissue injury in the lung and airway.

The concept of field cancerization was first introduced over 6 decades ago in the setting of oral cancer. Later, field cancerization involving histologic and molecular changes of neoplasms and adjacent tissue began to be characterized in smokers with or without lung cancer. Investigators also described a diffuse, nonneoplastic field of molecular injury throughout the respiratory tract that is attributable to cigarette smoking and susceptibility to smoking-induced lung disease. The potential molecular origins of field cancerization and the field of injury following cigarette smoke exposure in lung and airway epithelia are critical to understanding their potential impact on clinical diagnostics and therapeutics for smoking-induced lung disease.

Reversible and permanent effects of tobacco smoke exposure on airway epithelial gene expression.

BACKGROUND: Tobacco use remains the leading preventable cause of death in the US. The risk of dying from smoking-related diseases remains elevated for former smokers years after quitting. The identification of irreversible effects of tobacco smoke on airway gene expression may provide insights into the causes of this elevated risk. RESULTS: Using oligonucleotide microarrays, we measured gene expression in large airway epithelial cells obtained via bronchoscopy from never, current, and former smokers (n = 104). Linear models identified 175 genes differentially expressed between current and never smokers, and classified these as irreversible (n = 28), slowly reversible (n = 6), or rapidly reversible (n = 139) based on their expression in former smokers. A greater percentage of irreversible and slowly reversible genes were down-regulated by smoking, suggesting possible mechanisms for persistent changes, such as allelic loss at 16q13. Similarities with airway epithelium gene expression changes caused by other environmental exposures suggest that common mechanisms are involved in the response to tobacco smoke. Finally, using irreversible genes, we built a biomarker of ever exposure to tobacco smoke capable of classifying an independent set of former and current smokers with 81% and 100% accuracy, respectively. CONCLUSION: We have categorized smoking-related changes in airway gene expression by their degree of reversibility upon smoking cessation. Our findings provide insights into the mechanisms leading to reversible and persistent effects of tobacco smoke that may explain former smokers increased risk for developing tobacco-induced lung disease and provide novel targets for chemoprophylaxis. Airway gene expression may also serve as a sensitive biomarker to identify individuals with past exposure to tobacco smoke.

State of the art. Chronic obstructive pulmonary disease, inflammation, and lung cancer.

Both lung cancer and chronic obstructive pulmonary disease (COPD) are associated with cigarette smoking, which, by generating reactive oxidant species, induces a chronic inflammatory state in the lung. Activation, particularly of nuclear factor-kappaB, occurs in both cancer and COPD, and expression of a number of genes is altered in both diseases. In lung cancer, DNA damage, lack of DNA repair, and genomic instability predominate, whereas matrix degradation, lack of repair, and an intense immune response predominate in COPD. The reasons for the different responses to a common inflammatory response induced by smoking remain to be determined, but likely lie in genetic polymorphisms in genes that regulate genome integrity in cancer and that regulate the immune response to tissue destruction in COPD.

Gene expression profiling of human lung tissue from smokers with severe emphysema.

The mechanism by which inhaled smoke causes the anatomic lesions and physiologic impairment of chronic obstructive pulmonary disease remains unknown. We used high-density microarrays to measure gene expression in severely emphysematous lung tissue removed from smokers at lung volume reduction surgery (LVRS) and normal or mildly emphysematous lung tissue from smokers undergoing resection of pulmonary nodules. Class prediction algorithms identified 102 genes that accurately distinguished severe emphysema from non-/mildly emphysematous lung tissue. We also defined a number of genes whose expression levels correlated strongly with lung diffusion capacity for carbon monoxide and/or forced expiratory volume at 1 s. Genes related to oxidative stress, extracellular matrix synthesis, and inflammation were increased in severe emphysema, whereas expression of endothelium-related genes was decreased. To identify candidate genes that might be causally involved in the pathogenesis of emphysema, we linked gene expression profiles to chromosomal regions previously associated with chronic obstructive pulmonary disease in genome-wide linkage analyses. Unsupervised hierarchical clustering of the LVRS samples revealed distinct molecular subclasses of severe emphysema, with body mass index as the only clinical variable that differed between the groups. Class prediction models established a set of genes that predicted functional outcome at 6 mo after LVRS. Our findings suggest that the gene expression profiles from human emphysematous lung tissue may provide insight into pathogenesis, uncover novel molecular subclasses of disease, predict response to LVRS, and identify targets for therapeutic intervention.