Bronchial gene expression alterations associated with radiological bronchiectasis.

OBJECTIVES: Discovering airway gene expression alterations associated with radiological bronchiectasis may improve the understanding of the pathobiology of early-stage bronchiectasis. METHODS: Presence of radiological bronchiectasis in 173 individuals without a clinical diagnosis of bronchiectasis was evaluated. Bronchial brushings from these individuals were transcriptomically profiled and analysed. Single-cell deconvolution was performed to estimate changes in cellular landscape that may be associated with early disease progression. RESULTS: 20 participants have widespread radiological bronchiectasis (three or more lobes). Transcriptomic analysis reflects biological processes associated with bronchiectasis including decreased expression of genes involved in cell adhesion and increased expression of genes involved in inflammatory pathways (655 genes, false discovery rate <0.1, log2 fold-change >0.25). Deconvolution analysis suggests that radiological bronchiectasis is associated with an increased proportion of ciliated and deuterosomal cells, and a decreased proportion of basal cells. Gene expression patterns separated participants into three clusters: normal, intermediate and bronchiectatic. The bronchiectatic cluster was enriched by participants with more lobes of radiological bronchiectasis (p<0.0001), more symptoms (p=0.002), higher SERPINA1 mutation rates (p=0.03) and higher computed tomography derived bronchiectasis scores (p<0.0001). CONCLUSIONS: Genes involved in cell adhesion, Wnt signalling, ciliogenesis and interferon-γ pathways had altered expression in the bronchus of participants with widespread radiological bronchiectasis, possibly associated with decreased basal and increased ciliated cells. This gene expression pattern is not only highly enriched among individuals with radiological bronchiectasis, but also associated with airway-related symptoms in those without discernible radiological bronchiectasis, suggesting that it reflects a bronchiectasis-associated, but non-bronchiectasis-specific lung pathophysiological process.

Bronchial epithelial gene expression and interstitial lung abnormalities.

INTRODUCTION: Interstitial lung abnormalities (ILA) often represent early fibrotic changes that can portend a progressive fibrotic phenotype. In particular, the fibrotic subtype of ILA is associated with increased mortality and rapid decline in lung function. Understanding the differential gene expression that occurs in the lungs of participants with fibrotic ILA may provide insight into development of a useful biomarker for early detection and therapeutic targets for progressive pulmonary fibrosis. METHODS: Measures of ILA and gene expression data were available in 213 participants in the Detection of Early Lung Cancer Among Military Personnel (DECAMP1 and DECAMP2) cohorts. ILA was defined using Fleischner Society guidelines and determined by sequential reading of computed tomography (CT) scans. Primary analysis focused on comparing gene expression in ILA with usual interstitial pneumonia (UIP) pattern with those with no ILA. RESULTS: ILA was present in 51 (24%) participants, of which 16 (7%) were subtyped as ILA with a UIP pattern. One gene, pro platelet basic protein (PPBP) and seventeen pathways (e.g. TNF-α signalling) were significantly differentially expressed between those with a probable or definite UIP pattern of ILA compared to those without ILA. 16 of these 17 pathways, but no individual gene, met significance when comparing those with ILA to those without ILA. CONCLUSION: Our study demonstrates that abnormal inflammatory processes are apparent in the bronchial airway gene expression profiles of smokers with and without lung cancer with ILA. Future studies with larger and more diverse populations will be needed to confirm these findings.

Bronchial gene expression signature associated with rate of subsequent FEV1 decline in individuals with and at risk of COPD.

BACKGROUND: COPD is characterised by progressive lung function decline. Leveraging prior work demonstrating bronchial airway COPD-associated gene expression alterations, we sought to determine if there are alterations associated with differences in the rate of FEV1 decline. METHODS: We examined gene expression among ever smokers with and without COPD who at baseline had bronchial brushings profiled by Affymetrix microarrays and had longitudinal lung function measurements (n=134; mean follow-up=6.38±2.48 years). Gene expression profiles associated with the rate of FEV1 decline were identified by linear modelling. RESULTS: Expression differences in 171 genes were associated with rate of FEV1 decline (false discovery rate <0.05). The FEV1 decline signature was replicated in an independent dataset of bronchial biopsies from patients with COPD (n=46; p=0.018; mean follow-up=6.76±1.32 years). Genes elevated in individuals with more rapid FEV1 decline are significantly enriched among the genes altered by modulation of XBP1 in two independent datasets (Gene Set Enrichment Analysis (GSEA) p<0.05) and are enriched in mucin-related genes (GSEA p<0.05). CONCLUSION: We have identified and replicated an airway gene expression signature associated with the rate of FEV1 decline. Aspects of this signature are related to increased expression of XBP1-regulated genes, a transcription factor involved in the unfolded protein response, and genes related to mucin production. Collectively, these data suggest that molecular processes related to the rate of FEV1 decline can be detected in airway epithelium, identify a possible indicator of FEV1 decline and make it possible to detect, in an early phase, ever smokers with and without COPD most at risk of rapid FEV1 decline.

The molecular and cellular mechanisms associated with the destruction of terminal bronchioles in COPD.

RATIONALE: Peripheral airway obstruction is a key feature of chronic obstructive pulmonary disease (COPD), but the mechanisms of airway loss are unknown. This study aims to identify the molecular and cellular mechanisms associated with peripheral airway obstruction in COPD. METHODS: Ten explanted lung specimens donated by patients with very severe COPD treated by lung transplantation and five unused donor control lungs were sampled using systematic uniform random sampling (SURS), resulting in 240 samples. These samples were further examined by micro-computed tomography (CT), quantitative histology and gene expression profiling. RESULTS: Micro-CT analysis showed that the loss of terminal bronchioles in COPD occurs in regions of microscopic emphysematous destruction with an average airspace size of ≥500 and <1000 µm, which we have termed a "hot spot". Based on microarray gene expression profiling, the hot spot was associated with an 11-gene signature, with upregulation of pro-inflammatory genes and downregulation of inhibitory immune checkpoint genes, indicating immune response activation. Results from both quantitative histology and the bioinformatics computational tool CIBERSORT, which predicts the percentage of immune cells in tissues from transcriptomic data, showed that the hot spot regions were associated with increased infiltration of CD4 and CD8 T-cell and B-cell lymphocytes. INTERPRETATION: The reduction in terminal bronchioles observed in lungs from patients with COPD occurs in a hot spot of microscopic emphysema, where there is upregulation of IFNG signalling, co-stimulatory immune checkpoint genes and genes related to the inflammasome pathway, and increased infiltration of immune cells. These could be potential targets for therapeutic interventions in COPD.

Effect of long-term corticosteroid treatment on microRNA and gene-expression profiles in COPD.

The aim was to investigate whether microRNA (miRNA) expression is modulated by inhaled corticosteroid (ICS) treatmentWe performed genome-wide miRNA analysis on bronchial biopsies of 69 moderate/severe chronic obstructive pulmonary disease (COPD) patients at baseline and after 6- and 30-month treatment with the ICS fluticasone propionate or placebo. The effect of ICS on miRNA expression was validated in differentiated primary bronchial epithelial cultures, and functional studies were conducted in BEAS-2B cells. MiRNAs affected by ICS and their predicted targets were compared to an independent miRNA dataset of bronchial brushings from COPD patients and healthy controls.Treatment with ICS for both 6 and 30 months significantly altered the expression of four miRNAs, including miR-320d, which was increased during ICS treatment compared with placebo. The ICS-induced increase of miR-320d was confirmed in primary airway epithelial cells. MiR-320d negatively correlated targets were enriched for pro-inflammatory genes and were increased in the bronchial brushes of patients with lower lung function in the independent dataset. Overexpression of miR-320d in BEAS-2B cells dampened cigarette smoke extract-induced pro-inflammatory activity via inhibition of nuclear factor-κB.Collectively, we identified miR-320d as a novel mediator of ICS, regulating the pro-inflammatory response of the airway epithelium.

A Bronchial Genomic Classifier for the Diagnostic Evaluation of Lung Cancer.

BACKGROUND: Bronchoscopy is frequently nondiagnostic in patients with pulmonary lesions suspected to be lung cancer. This often results in additional invasive testing, although many lesions are benign. We sought to validate a bronchial-airway gene-expression classifier that could improve the diagnostic performance of bronchoscopy. METHODS: Current or former smokers undergoing bronchoscopy for suspected lung cancer were enrolled at 28 centers in two multicenter prospective studies (AEGIS-1 and AEGIS-2). A gene-expression classifier was measured in epithelial cells collected from the normal-appearing mainstem bronchus to assess the probability of lung cancer. RESULTS: A total of 639 patients in AEGIS-1 (298 patients) and AEGIS-2 (341 patients) met the criteria for inclusion. A total of 43% of bronchoscopic examinations were nondiagnostic for lung cancer, and invasive procedures were performed after bronchoscopy in 35% of patients with benign lesions. In AEGIS-1, the classifier had an area under the receiver-operating-characteristic curve (AUC) of 0.78 (95% confidence interval [CI], 0.73 to 0.83), a sensitivity of 88% (95% CI, 83 to 92), and a specificity of 47% (95% CI, 37 to 58). In AEGIS-2, the classifier had an AUC of 0.74 (95% CI, 0.68 to 0.80), a sensitivity of 89% (95% CI, 84 to 92), and a specificity of 47% (95% CI, 36 to 59). The combination of the classifier plus bronchoscopy had a sensitivity of 96% (95% CI, 93 to 98) in AEGIS-1 and 98% (95% CI, 96 to 99) in AEGIS-2, independent of lesion size and location. In 101 patients with an intermediate pretest probability of cancer, the negative predictive value of the classifier was 91% (95% CI, 75 to 98) among patients with a nondiagnostic bronchoscopic examination. CONCLUSIONS: The gene-expression classifier improved the diagnostic performance of bronchoscopy for the detection of lung cancer. In intermediate-risk patients with a nondiagnostic bronchoscopic examination, a negative classifier score provides support for a more conservative diagnostic approach. (Funded by Allegro Diagnostics and others; AEGIS-1 and AEGIS-2 ClinicalTrials.gov numbers, NCT01309087 and NCT00746759.).

Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data.

Small RNA sequencing can be used to gain an unprecedented amount of detail into the microRNA transcriptome. The relatively high cost and low throughput of sequencing bases technologies can potentially be offset by the use of multiplexing. However, multiplexing involves a trade-off between increased number of sequenced samples and reduced number of reads per sample (i.e., lower depth of coverage). To assess the effect of different sequencing depths owing to multiplexing on microRNA differential expression and detection, we sequenced the small RNA of lung tissue samples collected in a clinical setting by multiplexing one, three, six, nine, or 12 samples per lane using the Illumina HiSeq 2000. As expected, the numbers of reads obtained per sample decreased as the number of samples in a multiplex increased. Furthermore, after normalization, replicate samples included in distinct multiplexes were highly correlated (R > 0.97). When detecting differential microRNA expression between groups of samples, microRNAs with average expression >1 reads per million (RPM) had reproducible fold change estimates (signal to noise) independent of the degree of multiplexing. The number of microRNAs detected was strongly correlated with the log2 number of reads aligning to microRNA loci (R = 0.96). However, most additional microRNAs detected in samples with greater sequencing depth were in the range of expression which had lower fold change reproducibility. These findings elucidate the trade-off between increasing the number of samples in a multiplex with decreasing sequencing depth and will aid in the design of large-scale clinical studies exploring microRNA expression and its role in disease.

Nasal gene expression differentiates COPD from controls and overlaps bronchial gene expression.

BACKGROUND: Nasal gene expression profiling is a promising method to characterize COPD non-invasively. We aimed to identify a nasal gene expression profile to distinguish COPD patients from healthy controls. We investigated whether this COPD-associated gene expression profile in nasal epithelium is comparable with the profile observed in bronchial epithelium. METHODS: Genome wide gene expression analysis was performed on nasal epithelial brushes of 31 severe COPD patients and 22 controls, all current smokers, using Affymetrix Human Gene 1.0 ST Arrays. We repeated the gene expression analysis on bronchial epithelial brushes in 2 independent cohorts of mild-to-moderate COPD patients and controls. RESULTS: In nasal epithelium, 135 genes were significantly differentially expressed between severe COPD patients and controls, 21 being up- and 114 downregulated in COPD (false discovery rate < 0.01). Gene Set Enrichment Analysis (GSEA) showed significant concordant enrichment of COPD-associated nasal and bronchial gene expression in both independent cohorts (FDRGSEA < 0.001). CONCLUSION: We identified a nasal gene expression profile that differentiates severe COPD patients from controls. Of interest, part of the nasal gene expression changes in COPD mimics differentially expressed genes in the bronchus. These findings indicate that nasal gene expression profiling is potentially useful as a non-invasive biomarker in COPD. TRIAL REGISTRATION: ClinicalTrials.gov registration number NCT01351792 (registration date May 10, 2011), ClinicalTrials.gov registration number NCT00848406 (registration date February 19, 2009), ClinicalTrials.gov registration number NCT00807469 (registration date December 11, 2008).

Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer.

BACKGROUND: High mitotic activity is associated with the genesis and progression of many cancers. Small molecule inhibitors of mitotic apparatus proteins are now being developed and evaluated clinically as anticancer agents. With clinical trials of several of these experimental compounds underway, it is important to understand the molecular mechanisms that determine high mitotic activity, identify tumor subtypes that carry molecular aberrations that confer high mitotic activity, and to develop molecular markers that distinguish which tumors will be most responsive to mitotic apparatus inhibitors. METHODS: We identified a coordinately regulated mitotic apparatus network by analyzing gene expression profiles for 53 malignant and non-malignant human breast cancer cell lines and two separate primary breast tumor datasets. We defined the mitotic network activity index (MNAI) as the sum of the transcriptional levels of the 54 coordinately regulated mitotic apparatus genes. The effect of those genes on cell growth was evaluated by small interfering RNA (siRNA). RESULTS: High MNAI was enriched in basal-like breast tumors and was associated with reduced survival duration and preferential sensitivity to inhibitors of the mitotic apparatus proteins, polo-like kinase, centromere associated protein E and aurora kinase designated GSK462364, GSK923295 and GSK1070916, respectively. Co-amplification of regions of chromosomes 8q24, 10p15-p12, 12p13, and 17q24-q25 was associated with the transcriptional upregulation of this network of 54 mitotic apparatus genes, and we identify transcription factors that localize to these regions and putatively regulate mitotic activity. Knockdown of the mitotic network by siRNA identified 22 genes that might be considered as additional therapeutic targets for this clinically relevant patient subgroup. CONCLUSIONS: We define a molecular signature which may guide therapeutic approaches for tumors with high mitotic network activity.

Asthma-COPD overlap. Clinical relevance of genomic signatures of type 2 inflammation in chronic obstructive pulmonary disease.

RATIONALE: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and likely includes a subgroup that is biologically comparable to asthma. Studying asthma-associated gene expression changes in COPD could add insight into COPD pathogenesis and reveal biomarkers that predict a favorable response to corticosteroids. OBJECTIVES: To determine whether asthma-associated gene signatures are increased in COPD and associated with asthma-related features. METHODS: We compared disease-associated airway epithelial gene expression alterations in an asthma cohort (n = 105) and two COPD cohorts (n = 237, 171). The T helper type 2 (Th2) signature (T2S) score, a gene expression metric induced in Th2-high asthma, was evaluated in these COPD cohorts. The T2S score was correlated with asthma-related features and response to corticosteroids in COPD in a randomized, placebo-controlled trial, the Groningen and Leiden Universities study of Corticosteroids in Obstructive Lung Disease (GLUCOLD; n = 89). MEASUREMENTS AND MAIN RESULTS: The 200 genes most differentially expressed in asthma versus healthy control subjects were enriched among genes associated with more severe airflow obstruction in these COPD cohorts (P < 0.001), suggesting significant gene expression overlap. A higher T2S score was associated with decreased lung function (P < 0.001), but not asthma history, in both COPD cohorts. Higher T2S scores correlated with increased airway wall eosinophil counts (P = 0.003), blood eosinophil percentage (P = 0.03), bronchodilator reversibility (P = 0.01), and improvement in hyperinflation after corticosteroid treatment (P = 0.019) in GLUCOLD. CONCLUSIONS: These data identify airway gene expression alterations that can co-occur in asthma and COPD. The association of the T2S score with increased severity and "asthma-like" features (including a favorable corticosteroid response) in COPD suggests that Th2 inflammation is important in a COPD subset that cannot be identified by clinical history of asthma.

Host Response to the Lung Microbiome in Chronic Obstructive Pulmonary Disease.

RATIONALE: The relatively sparse but diverse microbiome in human lungs may become less diverse in chronic obstructive pulmonary disease (COPD). This article examines the relationship of this microbiome to emphysematous tissue destruction, number of terminal bronchioles, infiltrating inflammatory cells, and host gene expression. METHODS: Culture-independent pyrosequencing microbiome analysis was used to examine the V3-V5 regions of bacterial 16S ribosomal DNA in 40 samples of lung from 5 patients with COPD (Global Initiative for Chronic Obstructive Lung Disease [GOLD] stage 4) and 28 samples from 4 donors (controls). A second protocol based on the V1-V3 regions was used to verify the bacterial microbiome results. Within lung tissue samples the microbiome was compared with results of micro-computed tomography, infiltrating inflammatory cells measured by quantitative histology, and host gene expression. MEASUREMENTS AND MAIN RESULTS: Ten operational taxonomic units (OTUs) was found sufficient to discriminate between control and GOLD stage 4 lung tissue, which included known pathogens such as Haemophilus influenzae. We also observed a decline in microbial diversity that was associated with emphysematous destruction, remodeling of the bronchiolar and alveolar tissue, and the infiltration of the tissue by CD4(+) T cells. Specific OTUs were also associated with neutrophils, eosinophils, and B-cell infiltration (P < 0.05). The expression profiles of 859 genes and 235 genes were associated with either enrichment or reductions of Firmicutes and Proteobacteria, respectively, at a false discovery rate cutoff of less than 0.1. CONCLUSIONS: These results support the hypothesis that there is a host immune response to microorganisms within the lung microbiome that appears to contribute to the pathogenesis of COPD.

MicroRNA 4423 is a primate-specific regulator of airway epithelial cell differentiation and lung carcinogenesis.

Smoking is a significant risk factor for lung cancer, the leading cause of cancer-related deaths worldwide. Although microRNAs are regulators of many airway gene-expression changes induced by smoking, their role in modulating changes associated with lung cancer in these cells remains unknown. Here, we use next-generation sequencing of small RNAs in the airway to identify microRNA 4423 (miR-4423) as a primate-specific microRNA associated with lung cancer and expressed primarily in mucociliary epithelium. The endogenous expression of miR-4423 increases as bronchial epithelial cells undergo differentiation into mucociliary epithelium in vitro, and its overexpression during this process causes an increase in the number of ciliated cells. Furthermore, expression of miR-4423 is reduced in most lung tumors and in cytologically normal epithelium of the mainstem bronchus of smokers with lung cancer. In addition, ectopic expression of miR-4423 in a subset of lung cancer cell lines reduces their anchorage-independent growth and significantly decreases the size of the tumors formed in a mouse xenograft model. Consistent with these phenotypes, overexpression of miR-4423 induces a differentiated-like pattern of airway epithelium gene expression and reverses the expression of many genes that are altered in lung cancer. Together, our results indicate that miR-4423 is a regulator of airway epithelium differentiation and that the abrogation of its function contributes to lung carcinogenesis.

Gene-expression profiling of buccal epithelium among non-smoking women exposed to household air pollution from smoky coal.

In China's rural counties of Xuanwei and Fuyuan, lung cancer rates are among the highest in the world. While the elevated disease risk in this population has been linked to the usage of smoky (bituminous) coal as compared to smokeless (anthracite) coal, the underlying molecular changes associated with this exposure remains unclear. To understand the physiologic effects of smoky coal exposure, we analyzed the genome-wide gene-expression profiles in buccal epithelial cells collected from healthy, non-smoking female residents of Xuanwei and Fuyuan who burn smoky (n = 26) and smokeless (n = 9) coal. Gene-expression was profiled via microarrays, and changes associated with coal type were correlated to household levels of fine particulate matter (PM2.5) and polycyclic aromatic hydrocarbons (PAHs). Expression levels of 282 genes were altered with smoky versus smokeless coal exposure (P < 0.005), including the 2-fold increase of proinflammatory IL8 and decrease of proapoptotic CASP3. This signature was more correlated with carcinogenic PAHs (e.g. Benzo[a]pyrene; r = 0.41) than with non-carcinogenic PAHs (e.g. Fluorene; r = 0.08) or PM2.5 (r = 0.05). Genes altered with smoky coal exposure were concordantly enriched with tobacco exposure in previously profiled buccal biopsies of smokers and non-smokers (GSEA, q < 0.05). This is the first study to identify a signature of buccal epithelial gene-expression that is associated with smoky coal exposure, which in part is similar to the molecular response to tobacco smoke, thereby lending biologic plausibility to prior epidemiological studies that have linked this exposure to lung cancer risk.

DNA methylation is globally disrupted and associated with expression changes in chronic obstructive pulmonary disease small airways.

DNA methylation is an epigenetic modification that is highly disrupted in response to cigarette smoke and involved in a wide spectrum of malignant and nonmalignant diseases, but surprisingly not previously assessed in small airways of patients with chronic obstructive pulmonary disease (COPD). Small airways are the primary sites of airflow obstruction in COPD. We sought to determine whether DNA methylation patterns are disrupted in small airway epithelia of patients with COPD, and evaluate whether changes in gene expression are associated with these disruptions. Genome-wide methylation and gene expression analysis were performed on small airway epithelial DNA and RNA obtained from the same patient during bronchoscopy, using Illumina's Infinium HM27 and Affymetrix's Genechip Human Gene 1.0 ST arrays. To control for known effects of cigarette smoking on DNA methylation, methylation and gene expression profiles were compared between former smokers with and without COPD matched for age, pack-years, and years of smoking cessation. Our results indicate that aberrant DNA methylation is (1) a genome-wide phenomenon in small airways of patients with COPD, and (2) associated with altered expression of genes and pathways important to COPD, such as the NF-E2-related factor 2 oxidative response pathway. DNA methylation is likely an important mechanism contributing to modulation of genes important to COPD pathology. Because these methylation events may underlie disease-specific gene expression changes, their characterization is a critical first step toward the development of epigenetic markers and an opportunity for developing novel epigenetic therapeutic interventions for COPD.

Airway gene expression in COPD is dynamic with inhaled corticosteroid treatment and reflects biological pathways associated with disease activity.

BACKGROUND: A core feature of chronic obstructive pulmonary disease (COPD) is the accelerated decline in forced expiratory volume in one second (FEV1). The recent Groningen and Leiden Universities study of Corticosteroids in Obstructive Lung Disease (GLUCOLD) study suggested that particular phenotypes of COPD benefit from fluticasone±salmeterol by reducing the rate of FEV1 decline, yet the underlying mechanisms are unknown. METHODS: Whole-genome gene expression profiling using the Affymetrix Gene ST array (V.1.0) was performed on 221 bronchial biopsies available from 89 COPD patients at baseline and after 6 and 30 months of fluticasone±salmeterol and placebo treatment in GLUCOLD. RESULTS: Linear mixed effects modelling revealed that the expression of 138 genes decreased, whereas the expression of 140 genes significantly upregulated after both 6 and 30 months of treatment with fluticasone±salmeterol versus placebo. A more pronounced treatment-induced change in the expression of 50 and 55 of these 278 genes was associated with a lower rate of decline in FEV1 and Saint George Respiratory Questionnaire, respectively. Genes decreasing with treatment were involved in pathways related to cell cycle, oxidative phosphorylation, epithelial cell signalling, p53 signalling and T cell signalling. Genes increasing with treatment were involved in pathways related to focal adhesion, gap junction and extracellular matrix deposition. Finally, the fluticasone-induced gene expression changes were enriched among genes that change in the airway epithelium in smokers with versus without COPD in an independent data set. CONCLUSIONS: The present study suggests that gene expression in biological pathways of COPD is dynamic with treatment and reflects disease activity. This study opens the gate to targeted and molecular phenotype-driven therapy of COPD.

Genetic regulation of gene expression in the lung identifies CST3 and CD22 as potential causal genes for airflow obstruction.

BACKGROUND: COPD is a complex chronic disease with poorly understood pathogenesis. Integrative genomic approaches have the potential to elucidate the biological networks underlying COPD and lung function. We recently combined genome-wide genotyping and gene expression in 1111 human lung specimens to map expression quantitative trait loci (eQTL). OBJECTIVE: To determine causal associations between COPD and lung function-associated single nucleotide polymorphisms (SNPs) and lung tissue gene expression changes in our lung eQTL dataset. METHODS: We evaluated causality between SNPs and gene expression for three COPD phenotypes: FEV(1)% predicted, FEV(1)/FVC and COPD as a categorical variable. Different models were assessed in the three cohorts independently and in a meta-analysis. SNPs associated with a COPD phenotype and gene expression were subjected to causal pathway modelling and manual curation. In silico analyses evaluated functional enrichment of biological pathways among newly identified causal genes. Biologically relevant causal genes were validated in two separate gene expression datasets of lung tissues and bronchial airway brushings. RESULTS: High reliability causal relations were found in SNP-mRNA-phenotype triplets for FEV(1)% predicted (n=169) and FEV(1)/FVC (n=80). Several genes of potential biological relevance for COPD were revealed. eQTL-SNPs upregulating cystatin C (CST3) and CD22 were associated with worse lung function. Signalling pathways enriched with causal genes included xenobiotic metabolism, apoptosis, protease-antiprotease and oxidant-antioxidant balance. CONCLUSIONS: By using integrative genomics and analysing the relationships of COPD phenotypes with SNPs and gene expression in lung tissue, we identified CST3 and CD22 as potential causal genes for airflow obstruction. This study also augmented the understanding of previously described COPD pathways.

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.

A dynamic bronchial airway gene expression signature of chronic obstructive pulmonary disease and lung function impairment.

RATIONALE: Molecular phenotyping of chronic obstructive pulmonary disease (COPD) has been impeded in part by the difficulty in obtaining lung tissue samples from individuals with impaired lung function. OBJECTIVES: We sought to determine whether COPD-associated processes are reflected in gene expression profiles of bronchial airway epithelial cells obtained by bronchoscopy. METHODS: Gene expression profiling of bronchial brushings obtained from 238 current and former smokers with and without COPD was performed using Affymetrix Human Gene 1.0 ST Arrays. MEASUREMENTS AND MAIN RESULTS: We identified 98 genes whose expression levels were associated with COPD status, FEV1% predicted, and FEV1/FVC. In silico analysis identified activating transcription factor 4 (ATF4) as a potential transcriptional regulator of genes with COPD-associated airway expression, and ATF4 overexpression in airway epithelial cells in vitro recapitulates COPD-associated gene expression changes. Genes with COPD-associated expression in the bronchial airway epithelium had similarly altered expression profiles in prior studies performed on small-airway epithelium and lung parenchyma, suggesting that transcriptomic alterations in the bronchial airway epithelium reflect molecular events found at more distal sites of disease activity. Many of the airway COPD-associated gene expression changes revert toward baseline after therapy with the inhaled corticosteroid fluticasone in independent cohorts. CONCLUSIONS: Our findings demonstrate a molecular field of injury throughout the bronchial airway of active and former smokers with COPD that may be driven in part by ATF4 and is modifiable with therapy. Bronchial airway epithelium may ultimately serve as a relatively accessible tissue in which to measure biomarkers of disease activity for guiding clinical management of COPD.

Identification of a gene expression signature of vascular invasion and recurrence in stage I lung adenocarcinoma via bulk and spatial transcriptomics.

Microscopic vascular invasion (VI) is predictive of recurrence and benefit from lobectomy in stage I lung adenocarcinoma (LUAD) but is difficult to assess in resection specimens and cannot be accurately predicted prior to surgery. Thus, new biomarkers are needed to identify this aggressive subset of stage I LUAD tumors. To assess molecular and microenvironment features associated with angioinvasive LUAD we profiled 162 resected stage I tumors with and without VI by RNA-seq and explored spatial patterns of gene expression in a subset of 15 samples by high-resolution spatial transcriptomics (stRNA-seq). Despite the small size of invaded blood vessels, we identified a gene expression signature of VI from the bulk RNA-seq discovery cohort (n=103) and found that it was associated with VI foci, desmoplastic stroma, and high-grade patterns in our stRNA-seq data. We observed a stronger association with high-grade patterns from VI+ compared with VI- tumors. Using the discovery cohort, we developed a transcriptomic predictor of VI, that in an independent validation cohort (n=60) was associated with VI (AUROC=0.86; p=5.42×10-6) and predictive of recurrence-free survival (HR=1.98; p=0.024), even in VI- LUAD (HR=2.76; p=0.003). To determine our VI predictor's robustness to intra-tumor heterogeneity we used RNA-seq data from multi-region sampling of stage I LUAD cases in TRACERx, where the predictor scores showed high correlation (R=0.87, p<2.2×10-16) between two randomly sampled regions of the same tumor. Our study suggests that VI-associated gene expression changes are detectable beyond the site of intravasation and can be used to predict the presence of VI. This may enable the prediction of angioinvasive LUAD from biopsy specimens, allowing for more tailored medical and surgical management of stage I LUAD.

A single-sample microarray normalization method to facilitate personalized-medicine workflows.

Gene-expression microarrays allow researchers to characterize biological phenomena in a high-throughput fashion but are subject to technological biases and inevitable variabilities that arise during sample collection and processing. Normalization techniques aim to correct such biases. Most existing methods require multiple samples to be processed in aggregate; consequently, each sample's output is influenced by other samples processed jointly. However, in personalized-medicine workflows, samples may arrive serially, so renormalizing all samples upon each new arrival would be impractical. We have developed Single Channel Array Normalization (SCAN), a single-sample technique that models the effects of probe-nucleotide composition on fluorescence intensity and corrects for such effects, dramatically increasing the signal-to-noise ratio within individual samples while decreasing variation across samples. In various benchmark comparisons, we show that SCAN performs as well as or better than competing methods yet has no dependence on external reference samples and can be applied to any single-channel microarray platform.