Jennifer Beane

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 ∼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.

RNAi Targeting of West Nile Virus in Mosquito Midguts Promotes Virus Diversification

West Nile virus (WNV) exists in nature as a genetically diverse population of competing genomes. This high genetic diversity and concomitant adaptive plasticity has facilitated the rapid adaptation of WNV to North American transmission cycles and contributed to its explosive spread throughout the New World. WNV is maintained in nature in a transmission cycle between mosquitoes and birds, with intrahost genetic diversity highest in mosquitoes. The mechanistic basis for this increase in genetic diversity in mosquitoes is poorly understood. To determine whether the high mutational diversity of WNV in mosquitoes is driven by RNA interference (RNAi), we characterized the RNAi response to WNV in the midguts of orally exposed Culex pipiens quinquefasciatus using high-throughput, massively parallel sequencing and estimated viral genetic diversity. Our data demonstrate that WNV infection in orally exposed vector mosquitoes induces the RNAi pathway and that regions of the WNV genome that are more intensely targeted by RNAi are more likely to contain point mutations compared to weakly targeted regions. These results suggest that, under natural conditions, positive selection of WNV within mosquitoes is stronger in regions highly targeted by the host RNAi response. Further, they provide a mechanistic basis for the relative importance of mosquitoes in driving WNV diversification.

The SERPINE2 Gene Is Associated with Chronic Obstructive Pulmonary Disease

RATIONALE Chronic obstructive pulmonary disease (COPD) is a complex disease influenced by multiple genes and environmental factors. A region on chromosome 2q has been shown to be linked to COPD. A positional candidate gene from the chromosome 2q region SERPINE2 (Serpin peptidase inhibitor, clade E [nexin, plasminogen activator inhibitor type 1], member 2), was previously evaluated as a susceptibility gene for COPD in two association studies, but the results were contradictory. OBJECTIVES To identify the relationship between SERPINE2 polymorphisms and COPD-related phenotypes using family-based and case-control association studies. METHODS In the present study, we genotyped 25 single nucleotide polymorphisms (SNPs) from SERPINE2 and analyzed qualitative and quantitative COPD phenotypes in 635 pedigrees with 1,910 individuals and an independent case-control population that included 973 COPD cases and 956 control subjects. The family data were analyzed using family-based association tests. The case-control data were analyzed using logistic regression and linear models. MEASUREMENTS AND MAIN RESULTS Six SNPs demonstrated significant associations with COPD phenotypes in the family-based association analysis (0.0016<or=p<or=0.042). Five of these SNPs demonstrated replicated associations in the case-control analysis (0.021<or=p<or=0.031). In addition, the results of haplotype analyses supported the results from single SNP analyses. CONCLUSIONS These data provide further support for SERPINE2 as a COPD susceptibility gene.

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

BackgroundTobacco 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.ResultsUsing 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.ConclusionWe 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.

Characterizing the Impact of Smoking and Lung Cancer on the Airway Transcriptome Using RNA-Seq

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. Cancer Prev Res; 4(6); 803–17. ©2011 AACR.

The Case for a Pre-Cancer Genome Atlas (PCGA)

Understanding the earliest molecular and cellular events associated with cancer initiation remains a key bottleneck to transforming our approach to cancer prevention and detection. While TCGA has provided unprecedented insights into the genomic events associated with advanced stage cancer, there have been few studies comprehensively profiling premalignant and early-stage disease or elucidating the role of the microenvironment in premalignancy and tumor initiation. In this article, we make a call for development of a “Pre-Cancer Genome Atlas (PCGA),” a concerted initiative to characterize the molecular alterations in premalignant lesions and the corresponding changes in the microenvironment associated with progression to invasive carcinoma. This initiative will require a multicenter coordinated effort to comprehensively profile (cellular and molecular) premalignant lesions and their corresponding “field of injury” collected longitudinally as the lesion progresses towards or regresses from frank malignancy across multiple tumor types. Genomic characterization of alterations in premalignant lesions and their microenvironment, for both bulk tissue and single cells, will enable development of biomarkers for early detection and risk stratification as well as allow for the development of novel targeted cancer interception strategies. The multi-institutional and multidisciplinary collaborative “big-data” effort underlying the PCGA will help usher in a new era of precision medicine for cancer detection and prevention. Cancer Prev Res; 9(2); 119–24. ©2016 AACR.

Noninvasive method for obtaining RNA from buccal mucosa epithelial cells for gene expression profiling

Swabs and scrapings from the buc-cal mucosa in the mouth have been used to obtain DNA from epithelial cells for genetic studies (1,2). RNA has been obtained from resected tissues and from biopsy samples of mouth epithelium in various disease states to measure gene expression (3,4). How-ever, RNA has not been extracted from scrapings of buccal mucosa because ribonucleases that are present in saliva rapidly degrade epithelial cell RNA (5) during collection. To collect intact RNA from buc-cal mucosal epithelium for studies of the biologic effect of smoking on the airway epithelium, we developed a relatively noninvasive method for ob-taining small amounts of RNA from the mouth. We measured the expres-sion of selected genes in individual subjects using real-time PCR and used a recently described mass spectrometry method that requires only nanogram amounts of total RNA for analysis and lends itself to high-throughput analysis of hundreds of genes (6).Initially, we used a micropipet tip cut lengthwise to collect epithelial cells from the buccal mucosa in a relatively noninvasive fashion. We subsequently designed a standardized plastic tool that is concave with serrated edges. It is 5/16 inches wide and 1 6/16 inches long with a 3 inch handle that can be broken off when the scraping tool with the collected cells is inserted into a 2-mL mi-crofuge tube containing 1 mL RNAlater™ solution (Qiagen, Valencia, CA, USA). The tool has two features that allow the collection of a significant amount of good-quality RNA from the buccal mucosa: a finely serrated edge that can scrape off several layers of epithelial cells and a concave surface that collects the cells. Using gentle pressure, the serrated edge was scraped (10 times) against the buccal mucosa on the inside of the cheek, and the cells collected were immediately immersed in 1 cm

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 ∼22 500 human transcripts. The microarray data generated along with relevant patient information is uploaded to SIEGE by study administrators using the databases 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.

Experimental Evolution of an RNA Virus in Wild Birds: Evidence for Host-Dependent Impacts on Population Structure and Competitive Fitness

Within hosts, RNA viruses form populations that are genetically and phenotypically complex. Heterogeneity in RNA virus genomes arises due to error-prone replication and is reduced by stochastic and selective mechanisms that are incompletely understood. Defining how natural selection shapes RNA virus populations is critical because it can inform treatment paradigms and enhance control efforts. We allowed West Nile virus (WNV) to replicate in wild-caught American crows, house sparrows and American robins to assess how natural selection shapes RNA virus populations in ecologically relevant hosts that differ in susceptibility to virus-induced mortality. After five sequential passages in each bird species, we examined the phenotype and population diversity of WNV through fitness competition assays and next generation sequencing. We demonstrate that fitness gains occur in a species-specific manner, with the greatest replicative fitness gains in robin-passaged WNV and the least in WNV passaged in crows. Sequencing data revealed that intrahost WNV populations were strongly influenced by purifying selection and the overall complexity of the viral populations was similar among passaged hosts. However, the selective pressures that control WNV populations seem to be bird species-dependent. Specifically, crow-passaged WNV populations contained the most unique mutations (~1.7× more than sparrows, ~3.4× more than robins) and defective genomes (~1.4× greater than sparrows, ~2.7× greater than robins), but the lowest average mutation frequency (about equal to sparrows, ~2.6× lower than robins). Therefore, our data suggest that WNV replication in the most disease-susceptible bird species is positively associated with virus mutational tolerance, likely via complementation, and negatively associated with the strength of selection. These differences in genetic composition most likely have distinct phenotypic consequences for the virus populations. Taken together, these results reveal important insights into how different hosts may contribute to the emergence of RNA viruses.

Clinical Impact of High-Throughput Gene Expression Studies in Lung Cancer

Lung cancer is the leading cause of cancer death in the United States and the world. The high mortality rate results, in part, from the lack of effective tools for early detection and the inability to identify subsets of patients who would benefit from adjuvant chemotherapy or targeted therapies. The development of high-throughput genome-wide technologies for measuring gene expression, such as microarrays, have the potential to impact the mortality rate of lung cancer patients by improving diagnosis, prognosis, and treatment. This review will highlight recent studies using high-throughput gene expression technologies that have led to clinically relevant insights into lung cancer. The hope is that diagnostic and prognostic biomarkers that have been developed as part of this work will soon be ready for wide-spread clinical application and will have a dramatic impact on the evaluation of patients with suspect lung cancer, leading to effective personalized treatment regimens.