Chronic Obstructive Pulmonary Disease (COPD) is a complex disease. Genetic, epigenetic, and environmental factors are known to contribute to COPD risk and disease progression. Therefore we developed a systematic approach to identify key regulators of COPD that integrates genome-wide DNA methylation, gene expression, and phenotype data in lung tissue from COPD and control samples. Our integrative analysis identified 126 key regulators of COPD. We identified EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple genes sets associated with COPD disease severity. EPAS1 is distinct in comparison with other key regulators in terms of methylation profile and downstream target genes. Genes predicted to be regulated by EPAS1 were enriched for biological processes including signaling, cell communications, and system development. We confirmed that EPAS1 protein levels are lower in human COPD lung tissue compared to non-disease controls and that Epas1 gene expression is reduced in mice chronically exposed to cigarette smoke. As EPAS1 downstream genes were significantly enriched for hypoxia responsive genes in endothelial cells, we tested EPAS1 function in human endothelial cells. EPAS1 knockdown by siRNA in endothelial cells impacted genes that significantly overlapped with EPAS1 downstream genes in lung tissue including hypoxia responsive genes, and genes associated with emphysema severity. Our first integrative analysis of genome-wide DNA methylation and gene expression profiles illustrates that not only does DNA methylation play a ‘causal’ role in the molecular pathophysiology of COPD, but it can be leveraged to directly identify novel key mediators of this pathophysiology.
Chronic Obstructive Pulmonary Disease (COPD) is a common lung disease. It is the fourth leading cause of death in the world and is expected to be the third by 2020. COPD is a heterogeneous and complex disease consisting of obstruction in the small airways, emphysema, and chronic bronchitis. COPD is generally caused by exposure to noxious particles or gases, most commonly from cigarette smoking. However, only 20–25% of smokers develop clinically significant airflow obstruction. Smoking is known to cause epigenetic changes in lung tissues. Thus, genetics, epigenetic, and their interaction with environmental factors play an important role in COPD pathogenesis and progression. Currently, there are no therapeutics that can reverse COPD progression. In order to identify new targets that may lead to the development of therapeutics for curing COPD, we developed a systematic approach to identify key regulators of COPD that integrates genome-wide DNA methylation, gene expression, and phenotype data in lung tissue from COPD and control samples. Our integrative analysis identified 126 key regulators of COPD. We identified EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple genes sets associated with COPD disease severity.
Chronic obstructive pulmonary disease (COPD) is a clinically heterogeneous disease composed of variable degrees of airflow obstruction, emphysematous destruction, and small airway wall thickening. The natural history of this disease, although generally characterized by continued decline in lung function, is also highly variable. Novel transcriptomic approaches to study the airway and lung tissue in COPD hold the potential to improve our understanding of the molecular mechanisms underlying this heterogeneity and identify molecular subtypes of disease that have similar clinical manifestations. This new understanding can be leveraged to develop targeted COPD therapies and ultimately personalize treatment of COPD based on each patient’s specific molecular subphenotype.
chronic obstructive pulmonary disease; airway gene expression; bioinformatics; class discovery; drug discovery
Lung cancer is the leading cause of cancer death, in part due to lack of early diagnostic tools. Bronchoscopy represents a relatively noninvasive initial diagnostic test in smokers with suspect disease, but has low sensitivity. We have reported a gene expression profile in cytologically normal large airway epithelium obtained via bronchoscopic brushings that is a sensitive and specific biomarker for lung cancer. Here, we evaluate the independence of the biomarker from other clinical risk factors and determine the performance of a clinicogenomic model that combines clinical factors and gene expression.
Training (n = 76) and test sets (n = 62) consisted of smokers undergoing bronchoscopy for suspicion of lung cancer at five medical centers. Logistic regression models describing the likelihood of having lung cancer using the biomarker, clinical factors, and these data combined were tested using the independent set of patients with non-diagnostic bronchoscopies. The model predictions were also compared with physicians’ clinical assessment.
The gene expression biomarker is associated with cancer status in the combined clinicogenomic model (p < 0.005). There is a significant difference in performance of the clinicogenomic relative to the clinical model (p < 0.05). In the test set, the clinicogenomic model increases sensitivity and NPV to 100%, and results in higher specificity (91%) and PPV (81%) compared to other models. The clinicogenomic model has high accuracy where physician assessment is most uncertain.
The airway gene expression biomarker provides information about the likelihood of lung cancer not captured by clinical factors, and the clinicogenomic model has the highest prediction accuracy. These findings suggest that use of the clinicogenomic model may expedite more invasive testing and definitive therapy for smokers with lung cancer and reduce invasive diagnostic procedures for individuals without lung cancer.
Errors in sample annotation or labeling often occur in large-scale genetic or genomic studies and are difficult to avoid completely during data generation and management. For integrative genomic studies, it is critical to identify and correct these errors. Different types of genetic and genomic data are inter-connected by cis-regulations. On that basis, we developed a computational approach, Multi-Omics Data Matcher (MODMatcher), to identify and correct sample labeling errors in multiple types of molecular data, which can be used in further integrative analysis. Our results indicate that inspection of sample annotation and labeling error is an indispensable data quality assurance step. Applied to a large lung genomic study, MODMatcher increased statistically significant genetic associations and genomic correlations by more than two-fold. In a simulation study, MODMatcher provided more robust results by using three types of omics data than two types of omics data. We further demonstrate that MODMatcher can be broadly applied to large genomic data sets containing multiple types of omics data, such as The Cancer Genome Atlas (TCGA) data sets.
Many human diseases are complex with multiple genetic and environmental causal factors interacting together to give rise to disease phenotypes. Such factors affect biological systems through many layers of regulations, including transcriptional and epigenetic regulation, and protein changes. To fully understand their molecular mechanisms, complex diseases are often studied in diverse dimensions including genetics (genotype variations by single nucleotide polymorphism (SNP) arrays or whole exome sequencing), transcriptomics, epigenetics, and proteomics. However, errors in sample annotation or labeling often occur in large-scale genetic and genomic studies and are difficult to avoid completely during data generation and management. Identifying and correcting these errors are critical for integrative genomic studies. In this study, we developed a computational approach, Multi-Omics Data Matcher (MODMatcher), to identify and correct sample labeling errors based on multiple types of molecular data before further integrative analysis. Our results indicate that signals increased more than 100% after correction of sample labeling errors in a large lung genomic study. Our method can be broadly applied to large genomic data sets with multiple types of omics data, such as TCGA (The Cancer Genome Atlas) data sets.
Cigarette smoke produces a molecular “field of injury” in epithelial cells lining the respiratory tract. However, the specific signaling pathways that are altered in the airway of smokers and the signaling processes responsible for the transition from smoking-induced airway damage to lung cancer remain unknown. In this study, we use a genomic approach to study the signaling processes associated with tobacco smoke exposure and lung cancer. First, we developed and validated pathway-specific gene expression signatures in bronchial airway epithelium that reflect activation of signaling pathways relevant to tobacco-exposure including ATM, BCL2, GPX1, NOS2, IKBKB, and SIRT1. Using these profiles and four independent gene expression datasets, we found that SIRT1 activity is significantly up-regulated in cytologically normal bronchial airway epithelial cells from active smokers compared to non-smokers. In contrast, this activity is strikingly down-regulated in non-small cell lung cancer. This pattern of signaling modulation was unique to SIRT1, and down-regulation of SIRT1 activity is confined to tumors from smokers. Decreased activity of SIRT1 was validated using genomic analyses of mouse models of lung cancer and biochemical testing of SIRT1 activity in patient lung tumors. Together, our findings indicate a role of SIRT1 in response to smoke and a potential role in repressing lung cancer. Further, our findings suggest that the airway gene-expression signatures derived in this study can provide novel insights into signaling pathways altered in the “field of inury” induced by tobacco smoke and thus may impact strategies for prevention of tobacco-related lung cancer.
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.
lung cancer; screening; early detection; chemoprevention
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.
chronic obstructive pulmonary disease; gene expression profiling; biologic markers
Currently, most of RNA-seq experiments are performed on Illumina platform, but other companies are competing for market share. In this highly competitive environment, cross-platform comparisons and/or validations are becoming increasingly critical. Results of several comparisons in which the same samples were studied using Illumina and Ion Torrent RNA-seq, and different microarray-based approaches are presented. To prepare the libraries, the RNA samples were processed using Illumina TruSeq protocol (a protocol capturing polyadenylated RNA) and sequenced on Illumina HiSeq 2500 producing 100x100-nt paired-end reads. The same samples were processed using the Ion Torrent Total RNA-Seq V2 protocol which is capable of capturing non-coding RNA and preserves the strand specificity. These libraries were sequenced on the Ion Proton using the P1 chip and produced up to 200-nt reads. The data obtained with both platforms was compared for quality, alignment statistics, error rates, evenness and continuity of coverage, RNA biotype representation, and accuracy for expression profiling. Additionally, detailed comparison of technical aspects including input amount, throughput, experimental time and reagent costs is presented. Lastly, the same samples were interrogated using Agilent V2 Human Whole Genome arrays, Affymetrix Gene arrays ST (1.0 and 2.0) and newly commercialized Affymetrix Human Transcriptome Arrays. There was a significant correlation between the Illumina and Ion Torrent RNA-Seq gene expression data and microarray data generated from the same samples; however, the RNA-Seq detects additional transcripts whose expression were either not interrogated or not detected by microarrays.
Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease characterized by varying degrees of emphysematous lung destruction and small airway disease, each with distinct effects on clinical outcomes. There is little known about how microRNAs contribute specifically to the emphysema phenotype. We examined how genome-wide microRNA expression is altered with regional emphysema severity and how these microRNAs regulate disease-associated gene expression networks.
We profiled microRNAs in different regions of the lung with varying degrees of emphysema from 6 smokers with COPD and 2 controls (8 regions × 8 lungs = 64 samples). Regional emphysema severity was quantified by mean linear intercept. Whole genome microRNA and gene expression data were integrated in the same samples to build co-expression networks. Candidate microRNAs were perturbed in human lung fibroblasts in order to validate these networks.
The expression levels of 63 microRNAs (P < 0.05) were altered with regional emphysema. A subset, including miR-638, miR-30c, and miR-181d, had expression levels that were associated with those of their predicted mRNA targets. Genes correlated with these microRNAs were enriched in pathways associated with emphysema pathophysiology (for example, oxidative stress and accelerated aging). Inhibition of miR-638 expression in lung fibroblasts led to modulation of these same emphysema-related pathways. Gene targets of miR-638 in these pathways were amongst those negatively correlated with miR-638 expression in emphysema.
Our findings demonstrate that microRNAs are altered with regional emphysema severity and modulate disease-associated gene expression networks. Furthermore, miR-638 may regulate gene expression pathways related to the oxidative stress response and aging in emphysematous lung tissue and lung fibroblasts.
Purpose: The EGFR tyrosine kinase inhibitors (TKIs) demonstrate efficacy in NSCLC patients whose tumors harbor activating EGFR mutations. However, patients who initially respond to EGFR TKI treatment invariably develop resistance to the drugs. Known mechanisms account for approximately 70% of native and acquired EGFR TKI resistance. In the current study we investigated a novel mechanism of NSCLC resistance to erlotinib. Experimental Design: The mechanisms of acquired erlotinib resistance were evaluated by microarray analysis in thirteen NSCLC cell lines and in vivo in mice. Correlations between plasma neutrophil gelatinase associated lipocalin (NGAL) levels, erlotinib response and the EGFR mutational status were assessed in advanced stage NSCLC patients treated with erlotinib. Results: In 5 of 13 NSCLC cell lines NGAL was significantly upregulated. NGAL knockdown in erlotinib-resistant cells increased erlotinib sensitivity in vitro and in vivo. NGAL overexpression in erlotinib-sensitive cells augmented apoptosis resistance. This was mediated by NGAL-dependent modulation of the pro-apoptotic protein Bim levels. Evaluation of the plasma NGAL levels in NSCLC patients that received erlotinib revealed that patients with lower baseline NGAL demonstrated a better erlotinib response. Compared to patients with wild type EGFR, patients with activating EGFR mutations had lower plasma NGAL at baseline and weeks 4 and 8. Conclusions: Our studies uncover a novel mechanism of NGAL-mediated modulation of Bim levels in NSCLC that might contribute to TKI resistance in lung cancer patients. These findings provide the rationale for the further investigations of the utility of NGAL as a potential therapeutic target or diagnostic biomarker.
Lung cancer; effectors of apoptosis; survival factors; EGFR; erlotinib resistance
The “field of cancerization” refers to histologically normal-appearing tissue adjacent to neoplastic tissue that displays molecular abnormalities, some of which are the same as those of the tumor. Improving our understanding of these molecular events is likely to increase our understanding of carcinogenesis. Here, Kadara et al. attempt to characterize the molecular events associated temporally and spatially within the field of cancerization of early stage non-small cell lung cancer (NSCLC) patients following definitive surgery. They followed patients with bronchoscopies annually after tumor resection and extracted RNA from the serial brushings from different endobronchial sites. They then performed microarray analysis to identify gene expression differences over time and in different sites in the airway. Candidate genes were found that may have biological relevance to the field of cancerization. For example, expression of phosphorylated AKT and ERK1/2 was found to increase in the airway epithelium with time. Despite a number of limitations in the study design, this investigation demonstrates the utility of identifying molecular changes in histologically normal airway epithelium in lung cancer. In addition to increasing our understanding of lung cancer biology, studying the field of cancerization has the potential to identify biomarkers from samples obtained in a minimally invasive manner.
Lung cancer is the leading cause of cancer death worldwide in part due to our inability to identify which smokers are at highest risk and the lack of effective tools to detect the disease at its earliest and potentially curable stage. Recent results from the National Lung Screening Trial have shown that annual screening of high-risk smokers with low-dose helical computed tomography of the chest can reduce lung cancer mortality. However, molecular biomarkers are needed to identify which current and former smokers would benefit most from annual computed tomography scan screening in order to reduce the costs and morbidity associated with this procedure. Additionally, there is an urgent clinical need to develop biomarkers that can distinguish benign from malignant lesions found on computed tomography of the chest given its very high false positive rate. This review highlights recent genetic, transcriptomic and epigenomic biomarkers that are emerging as tools for the early detection of lung cancer both in the diagnostic and screening setting.
Biomarker; Diagnostics; Early detection; Epigenetics; Genetics; Lung cancer; Screening; Transcriptomics
Cigarette smoke creates a molecular field of injury in epithelial cells that line the respiratory tract. We hypothesized that transcriptome sequencing (RNA-Seq) will enhance our understanding of the field of molecular injury in response to tobacco smoke exposure and lung cancer pathogenesis by identifying gene expression differences not interrogated or accurately measured by microarrays. We sequenced the high-molecular-weight fraction of total RNA (>200 nt) from pooled bronchial airway epithelial cell brushings (n = 3 patients per pool) obtained during bronchoscopy from healthy never smoker (NS) and current smoker (S) volunteers and smokers with (C) and without (NC) lung cancer undergoing lung nodule resection surgery. RNA-Seq libraries were prepared using 2 distinct approaches, one capable of capturing non-polyadenylated RNA (the prototype NuGEN Ovation RNA-Seq protocol) and the other designed to measure only polyadenylated RNA (the standard Illumina mRNA-Seq protocol) followed by sequencing generating approximately 29 million 36 nt reads per pool and approximately 22 million 75 nt paired-end reads per pool, respectively. The NuGEN protocol captured additional transcripts not detected by the Illumina protocol at the expense of reduced coverage of polyadenylated transcripts, while longer read lengths and a paired-end sequencing strategy significantly improved the number of reads that could be aligned to the genome. The aligned reads derived from the two complementary protocols were used to define the compendium of genes expressed in the airway epithelium (n = 20,573 genes). Pathways related to the metabolism of xenobiotics by cytochrome P450, retinol metabolism, and oxidoreductase activity were enriched among genes differentially expressed in smokers, whereas chemokine signaling pathways, cytokine–cytokine receptor interactions, and cell adhesion molecules were enriched among genes differentially expressed in smokers with lung cancer. There was a significant correlation between the RNA-Seq gene expression data and Affymetrix microarray data generated from the same samples (P < 0.001); however, the RNA-Seq data detected additional smoking- and cancer-related transcripts whose expression was were either not interrogated by or was not found to be significantly altered when using microarrays, including smoking-related changes in the inflammatory genes S100A8 and S100A9 and cancer-related changes in MUC5AC and secretoglobin (SCGB3A1). Quantitative real-time PCR confirmed differential expression of select genes and non-coding RNAs within individual samples. These results demonstrate that transcriptome sequencing has the potential to provide new insights into the biology of the airway field of injury associated with smoking and lung cancer. The measurement of both coding and non-coding transcripts by RNA-Seq has the potential to help elucidate mechanisms of response to tobacco smoke and to identify additional biomarkers of lung cancer risk and novel targets for chemoprevention.
Although only a subset of smokers develop lung cancer, we cannot determine which smokers are at highest risk for cancer development, nor do we know the signaling pathways altered early in the process of tumorigenesis in these individuals. On the basis of the concept that cigarette smoke creates a molecular field of injury throughout the respiratory tract, this study explores oncogenic pathway deregulation in cytologically normal proximal airway epithelial cells of smokers at risk for lung cancer. We observed a significant increase in a genomic signature of phosphatidylinositol 3-kinase (PI3K) pathway activation in the cytologically normal bronchial airway of smokers with lung cancer and smokers with dysplastic lesions, suggesting that PI3K is activated in the proximal airway before tumorigenesis. Further, PI3K activity is decreased in the airway of high-risk smokers who had significant regression of dysplasia after treatment with the chemopreventive agent myo-inositol, and myo-inositol inhibits the PI3K pathway in vitro. These results suggest that deregulation of the PI3K pathway in the bronchial airway epithelium of smokers is an early, measurable, and reversible event in the development of lung cancer and that genomic profiling of these relatively accessible airway cells may enable personalized approaches to chemoprevention and therapy. Our work further suggests that additional lung cancer chemoprevention trials either targeting the PI3K pathway or measuring airway PI3K activation as an intermediate endpoint are warranted.
Although there have been numerous observations of vitamin D deficiency and its links to chronic diseases, no studies have reported on how vitamin D status and vitamin D3 supplementation affects broad gene expression in humans. The objective of this study was to determine the effect of vitamin D status and subsequent vitamin D supplementation on broad gene expression in healthy adults. (Trial registration: ClinicalTrials.gov NCT01696409).
Methods and Findings
A randomized, double-blind, single center pilot trial was conducted for comparing vitamin D supplementation with either 400 IUs (n = 3) or 2000 IUs (n = 5) vitamin D3 daily for 2 months on broad gene expression in the white blood cells collected from 8 healthy adults in the winter. Microarrays of the 16 buffy coats from eight subjects passed the quality control filters and normalized with the RMA method. Vitamin D3 supplementation that improved serum 25-hydroxyvitamin D concentrations was associated with at least a 1.5 fold alteration in the expression of 291 genes. There was a significant difference in the expression of 66 genes between subjects at baseline with vitamin D deficiency (25(OH)D<20 ng/ml) and subjects with a 25(OH)D>20 ng/ml. After vitamin D3 supplementation gene expression of these 66 genes was similar for both groups. Seventeen vitamin D-regulated genes with new candidate vitamin D response elements including TRIM27, CD83, COPB2, YRNA and CETN3 which have been shown to be important for transcriptional regulation, immune function, response to stress and DNA repair were identified.
Our data suggest that any improvement in vitamin D status will significantly affect expression of genes that have a wide variety of biologic functions of more than 160 pathways linked to cancer, autoimmune disorders and cardiovascular disease with have been associated with vitamin D deficiency. This study reveals for the first time molecular finger prints that help explain the nonskeletal health benefits of vitamin D.
We have previously defined the impact of tobacco smoking on nasal epithelium gene expression using Affymetrix Exon 1.0 ST arrays. In this paper, we compared the performance of the Affymetrix GeneChip Human Gene 1.0 ST array with the Human Exon 1.0 ST array for detecting nasal smoking-related gene expression changes. RNA collected from the nasal epithelium of five current smokers and five never smokers was hybridized to both arrays. While the intersample correlation within each array platform was relatively higher in the Gene array than that in the Exon array, the majority of the genes most changed by smoking were tightly correlated between platforms. Although neither array dataset was powered to detect differentially expressed genes (DEGs) at a false discovery rate (FDR) <0.05, we identified more DEGs than expected by chance using the Gene ST array. These findings suggest that while both platforms show a high degree of correlation for detecting smoking-induced differential gene expression changes, the Gene ST array may be a more cost-effective platform in a clinical setting for gene-level genomewide expression profiling and an effective tool for exploring the host response to cigarette smoking and other inhaled toxins.
The fluid-filled lung exists in relative hypoxia in utero (∼25 mm Hg), but at birth fills with ambient air where the partial pressure of oxygen is ∼150 mm Hg. The impact of this change was studied in mouse lung with microarrays to analyze gene expression one day before, and 2, 6, 12 and 24 hours after birth into room air or 10% O2. The expression levels of >150 genes, representing transcriptional regulation, structure, apoptosis and antioxidants were altered 2 hrs after birth in room air but blunted or absent with birth in 10% O2. Kruppel-like factor 4 (Klf4), a regulator of cell growth arrest and differentiation, was the most significantly altered lung gene at birth. Its protein product was expressed in fibroblasts and airway epithelial cells. Klf4 mRNA was induced in lung fibroblasts exposed to hyperoxia and constitutive expression of Klf4 mRNA in Klf4-null fibroblasts induced mRNAs for p21cip1/Waf1, smooth muscle actin, type 1 collagen, fibronectin and tenascin C. In Klf4 perinatal null lung, p21cip1/Waf1mRNA expression was deficient prior to birth and associated with ongoing cell proliferation after birth; connective tissue gene expression was deficient around birth and smooth muscle actin protein expression was absent from myofibroblasts at tips of developing alveoli; p53, p21cip1/Waf1 and caspase-3 protein expression were widespread at birth suggesting excess apoptosis compared to normal lung. We propose that the changing oxygen environment at birth acts as a physiologic signal to induce lung Klf4 mRNA expression, which then regulates proliferation and apoptosis in fibroblasts and airway epithelial cells, and connective tissue gene expression and myofibroblast differentiation at the tips of developing alveoli.
Delivery of the transcription factors Oct4, Klf4, Sox2 and c-Myc via integrating viral vectors has been widely employed to generate induced pluripotent stem cell (iPSC) lines from both normal and disease-specific somatic tissues, providing an invaluable resource for medical research and drug development. Residual reprogramming transgene expression from integrated viruses nevertheless alters the biological properties of iPSCs and has been associated with a reduced developmental competence both in vivo and in vitro. We performed transcriptional profiling of mouse iPSC lines before and after excision of a polycistronic lentiviral reprogramming vector to systematically define the overall impact of persistent transgene expression on the molecular features of iPSCs. We demonstrate that residual expression of the Yamanaka factors prevents iPSCs from acquiring the transcriptional program exhibited by embryonic stem cells (ESCs) and that the expression profiles of iPSCs generated with and without c-Myc are indistinguishable. After vector excision, we find 36% of iPSC clones show normal methylation of the Gtl2 region, an imprinted locus that marks ESC-equivalent iPSC lines. Furthermore, we show that the reprogramming factor Klf4 binds to the promoter region of Gtl2. Regardless of Gtl2 methylation status, we find similar endodermal and hepatocyte differentiation potential comparing syngeneic Gtl2ON vs Gtl2OFF iPSC clones. Our findings provide new insights into the reprogramming process and emphasize the importance of generating iPSCs free of any residual transgene expression.
Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease consisting of emphysema, small airway obstruction, and/or chronic bronchitis that results in significant loss of lung function over time.
In order to gain insights into the molecular pathways underlying progression of emphysema and explore computational strategies for identifying COPD therapeutics, we profiled gene expression in lung tissue samples obtained from regions within the same lung with varying amounts of emphysematous destruction from smokers with COPD (8 regions × 8 lungs = 64 samples). Regional emphysema severity was quantified in each tissue sample using the mean linear intercept (Lm) between alveolar walls from micro-CT scans.
We identified 127 genes whose expression levels were significantly associated with regional emphysema severity while controlling for gene expression differences between individuals. Genes increasing in expression with increasing emphysematous destruction included those involved in inflammation, such as the B-cell receptor signaling pathway, while genes decreasing in expression were enriched in tissue repair processes, including the transforming growth factor beta (TGFβ) pathway, actin organization, and integrin signaling. We found concordant differential expression of these emphysema severity-associated genes in four cross-sectional studies of COPD. Using the Connectivity Map, we identified GHK as a compound that can reverse the gene-expression signature associated with emphysematous destruction and induce expression patterns consistent with TGFβ pathway activation. Treatment of human fibroblasts with GHK recapitulated TGFβ-induced gene-expression patterns, led to the organization of the actin cytoskeleton, and elevated the expression of integrin β1. Furthermore, addition of GHK or TGFβ restored collagen I contraction and remodeling by fibroblasts derived from COPD lungs compared to fibroblasts from former smokers without COPD.
These results demonstrate that gene-expression changes associated with regional emphysema severity within an individual's lung can provide insights into emphysema pathogenesis and identify novel therapeutic opportunities for this deadly disease. They also suggest the need for additional studies to examine the mechanisms by which TGFβ and GHK each reverse the gene-expression signature of emphysematous destruction and the effects of this reversal on disease progression.
Lung carcinogenesis is a complex, stepwise process that involves the acquisition of genetic mutations and epigenetic changes that alter cellular processes, such as proliferation, differentiation, invasion, and metastasis. Here, we review some of the latest concepts in the pathogenesis of lung cancer and highlight the roles of inflammation, the “field of cancerization,” and lung cancer stem cells in the initiation of the disease. Furthermore, we review how high throughput genomics, transcriptomics, epigenomics, and proteomics are advancing the study of lung carcinogenesis. Finally, we reflect on the potential of current in vitro and in vivo models of lung carcinogenesis to advance the field and on the areas of investigation where major breakthroughs will lead to the identification of novel chemoprevention strategies and therapies for lung cancer.
Field of cancerization; inflammation; stem cells; genomics; epigenomics; proteomics
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.
epithelium; lung neoplasms; chronic obstructive pulmonary disease; asthma; tobacco