Molecular epidemiology of lung cancer

Neo-Darwinian Principles Exemplified in Cancer Genomics

Within the last two decades, the advent of next-generation sequencing accompanied by single-cell technologies has enabled cancer researchers to study in detail mutations and other genetic aberrations that transpire during transformation of cells to a neoplastic state. This article covers the insights gained through these extensive studies where neo-Darwinian principles can be inferred to play roles throughout neoplastic transformation. The cells promoted during cancer development exhibit cancer hallmarks combined with the related enabling characteristics as outlined by Hanahan and Weinberg, analogous to natural selection and survival of the fittest. Selection of driver mutations that inactivate proteins encoded by tumor suppressor genes differs in profound ways from mutations that activate tumor promoter proteins. In most cases, the later stages of cancer development are characterized by sudden, extensive damage to chromosomes in a process that is not Darwinian in nature. Nevertheless, cells that survive these cataclysmic events remain subject to Darwinian selection promoting clones exhibiting the greatest rates of progression. Duplications of chromosomal segments containing oncogenes, deletions of segments harboring tumor suppressor genes, or distinctive chromosomal rearrangements are often found in cells progressing into later stages of cancer. In summary, the technological developments in genome sequencing since the start of the century have given us clear insights into genomic alterations promoting tumor progression where neo-Darwinian mechanisms of clonal selection can be inferred to play a primary role.

Predictive role of polymorphic variants of phase II drug metabolising enzyme in modulating toxicity in North Indian lung cancer patients undergoing chemotherapy

Genetic polymorphism of drug-metabolizing enzymes such as NQO1, SULT1A1, EPHX1, and NAT2 alters its activity which hampers the detoxification and disposal of chemotherapeutic compounds. Thus, in the present study, we have comprehensively investigated the associations between SNPs of the Phase II detoxifying genes and its relationship towards platinum-induced toxicity of lung cancer patients.A total of 273 samples were enrolled in this study and polymorphisms of gene NQO1 (609C > T), SULT1A1 (Arg²¹³ His), EPHX1 (Tyr¹¹³His, His¹³⁹Arg), and NAT2 (481C > T, 803A > G, 590 G > A, 857 G > A) were evaluated in our study for their associated adverse events caused due to the administration of platinum-based chemotherapy to the lung cancer patients.For NQO1 609C > T polymorphism, the TT genotype showed reduced risk of constipation (OR =0.10, p=0.04) and anorexia (OR =0.15, p=0.03). For SULT1A1 Arg²¹³His, heterozygous genotype (Arg/His) (AOR =0.38, p=0.006) and combined genotype (Arg/His + His/His) were not associated with increased risk of nephrotoxicity (AOR =0.38, p= 0.004). For NAT2, heterozygous (NAT2*4/*6) and combined genotypes (NAT2*4/*4 + *4/*6) for NAT2*6 polymorphism exhibit 2.4 folds (p=0.005), and two-folds (p=0.01) increased risk of hematological toxicity. The heterozygous (AOR =0.45, p=0.004) and variant genotype (AOR =0.39, p=0.02) for NAT2*5C had decreased risk for hematological toxicity. The heterozygous genotype for NAT2*7 polymorphism showed two-fold increased risk for developing thrombocytopenia.This study provides association of NAT2 polymorphic variants in predicting haematological toxicity.

Localization and Activity of iNOS in Normal Human Lung Tissue and Lung Cancer Tissue

Inducible nitric oxide synthase (iNOS) is one of three enzymes generating nitric oxide (NO) from the amino acid L-arginine. iNOS-derived NO plays an important role in several physiological and pathophysiological conditions. NO is a free radical which produces many reactive intermediates that account for its bioactivity. In the human lung, the alveolar macrophage is an important producer of cytokines and this production may be modified by NO. Moreover, high concentrations of NO have been shown to increase nuclear factor KB (NF-kB) activation. Recent investigations of NO expression in tumor tissue indicated that, at least for certain tumors, NO may mediate one or more roles during the growth of human cancer. We have studied iNOS in two tissue groups: normal human lung tissue and human lung cancer tissue. We localized iNOS in these tissues by immunohistochemistry and tested the mRNA expression by RT-PCR, the protein level by Western blot, and the protein activity by radiometric analysis. The results demonstrate different expression, localization and activity of iNOS in normal versus tumor tissue. This is suggestive of a role for NO production from iNOS in human lung cancer because high concentrations of this short molecule may transform to highly reactive compounds such as peroxynitrite (ONOO-); moreover, through the upregulator NF-kB, they can induce a chronic inflammatory state representing an elevated risk for cell transformation to cancer.

Transcriptome sequencing reveals e-cigarette vapor and mainstream-smoke from tobacco cigarettes activate different gene expression profiles in human bronchial epithelial cells

Electronic cigarettes (e-cigarettes) generate an aerosol vapor (e-vapor) thought to represent a less risky alternative to main stream smoke (MSS) of conventional tobacco cigarettes. RNA-seq analysis was used to examine the transcriptomes of differentiated human bronchial epithelial (HBE) cells exposed to air, MSS from 1R5F tobacco reference cigarettes, and e-vapor with and without added nicotine in an in vitro air-liquid interface model for cellular exposure. Our results indicate that while e-vapor does not elicit many of the cell toxicity responses observed in MSS-exposed HBE cells, e-vapor exposure is not benign, but elicits discrete transcriptomic signatures with and without added nicotine. Among the cellular pathways with the most significantly enriched gene expression following e-vapor exposure are the phospholipid and fatty acid triacylglycerol metabolism pathways. Our data suggest that alterations in cellular glycerophopholipid biosynthesis are an important consequences of e-vapor exposure. Moreover, the presence of nicotine in e-vapor elicits a cellular response distinct from e-vapor alone including alterations of cytochrome P450 function, retinoid metabolism, and nicotine catabolism. These studies establish a baseline for future analysis of e-vapor and e-vapor additives that will better inform the FDA and other governmental bodies in discussions of the risks and future regulation of these products.

Mucins in lung cancer: diagnostic, prognostic, and therapeutic implications

Aberrant expression of mucins is associated with cancer development and metastasis. An overexpression of few mucins contributes to oncogenesis by enhancing cancer cell growth and providing constitutive survival signals. This review focuses on the importance of mucins both in the normal bronchial epithelial cells and the malignant tumors of the lung and their contribution in the diagnosis and prognosis of lung cancer patients. During lung cancer progression, mucins either alone or through their interaction with many receptor tyrosine kinases mediate cell signals for growth and survival of cancer cells. Also, stage-specific expression of certain mucins, like MUC1, is associated with poor prognosis from lung cancer. Thus, mucins are emerging as attractive targets for developing novel therapeutic approaches for lung cancer. Several strategies targeting mucin expression and function are currently being investigated to control lung cancer progression.

Quantification of plasma microRNAs in a group of healthy smokers, ex-smokers and non-smokers and correlation to biomarkers of tobacco exposure

The stability of circulating miRNAs, their non-invasive sampling techniques and deregulation in diseases make them potential candidate biomarkers of biological effect. Here, we profiled the level of 84 plasma miRNAs in 30 smokers, 20 non-smokers and 20 ex-smokers. A robust statistical strategy was applied with replicate samples to account for reproducibility of the results. We identified differential expression of miR-124 and let-7a between the smoking and control groups. We further explored the dose–response relationship of miR-124 and let-7a with two biomarkers of tobacco exposure and found that this relationship was affected by adjustments based on age, pack-year and gender.

NGS meta data analysis for identification of SNP and INDEL patterns in human airway transcriptome: A preliminary indicator for lung cancer

High-throughput sequencing of RNA (RNA-Seq) was developed primarily to analyze global gene expression in different tissues. It is also an efficient way to discover coding SNPs and when multiple individuals with different genetic backgrounds were used, RNA-Seq is very effective for the identification of SNPs. The objective of this study was to perform SNP and INDEL discoveries in human airway transcriptome of healthy never smokers, healthy current smokers, smokers without lung cancer and smokers with lung cancer. By preliminary comparative analysis of these four data sets, it is expected to get SNP and INDEL patterns responsible for lung cancer. A total of 85,028 SNPs and 5738 INDELs in healthy never smokers, 32,671 SNPs and 1561 INDELs in healthy current smokers, 50,205 SNPs and 3008 INDELs in smokers without lung cancer and 51,299 SNPs and 3138 INDELs in smokers with lung cancer were identified. The analysis of the SNPs and INDELs in genes that were reported earlier as differentially expressed was also performed. It has been found that a smoking person has SNPs at position 62,186,542 and 62,190,293 in SCGB1A1 gene and 180,017,251, 180,017,252, and 180,017,597 in SCGB3A1 gene and INDELs at position 35,871,168 in NFKBIA gene and 180,017,797 in SCGB3A1 gene. The SNPs identified in this study provides a resource for genetic studies in smokers and shall contribute to the development of a personalized medicine. This study is only a preliminary kind and more vigorous data analysis and wet lab validation are required.

Linking polymorphic p53 response elements with gene expression in airway epithelial cells of smokers and cancer risk

Chronic cigarette smoking exposes airway epithelial cells to thousands of carcinogens, oxidants and DNA-damaging agents, creating a field of molecular injury in the airway and altering gene expression. Studies of cytologically normal bronchial epithelial cells from smokers have identified transcription-based biomarkers that may prove useful in early diagnosis of lung cancer, including a number of p53-regulated genes. The ability of p53 to regulate transcription is critical for tumor suppression, and this suggests that single-nucleotide polymorphisms (SNPs) in functional p53 binding sites (p53 response elements, or p53REs) that affect gene expression could influence susceptibility to cancer. To connect p53RE SNP genotype with gene expression and cancer risk, we identified a set of 204 SNPs in putative p53REs, and performed cis expression quantitative trait loci (eQTL) analysis, assessing associations between SNP genotypes and mRNA levels of adjacent genes in bronchial epithelial cells obtained from 44 cigarette smokers. To further test and validate these genotype-expression associations, we searched published eQTL studies from independent populations and determined that 53% (39/74) of the bronchial epithelial eQTLs were observed in at least one of other studies. SNPs in p53REs were also evaluated for effects on p53-DNA binding using a quantitative in vitro protein-DNA binding assay. Last, based on linkage disequilibrium, we found 6 p53RE SNPs associated with gene expression were identified as cancer risk SNPs by either genome-wide association studies or candidate gene studies. We provide an approach for identifying and evaluating potentially functional SNPs that may modulate the airway gene expression response to smoking and may influence susceptibility to cancers.

CSEO - the Cigarette Smoke Exposure Ontology

BACKGROUND

In the past years, significant progress has been made to develop and use experimental settings for extensive data collection on tobacco smoke exposure and tobacco smoke exposure-associated diseases. Due to the growing number of such data, there is a need for domain-specific standard ontologies to facilitate the integration of tobacco exposure data.

RESULTS

The CSEO (version 1.0) is composed of 20091 concepts. The ontology in its current form is able to capture a wide range of cigarette smoke exposure concepts within the knowledge domain of exposure science with a reasonable sensitivity and specificity. Moreover, it showed a promising performance when used to answer domain expert questions. The CSEO complies with standard upper-level ontologies and is freely accessible to the scientific community through a dedicated wiki at https://publicwiki-01.fraunhofer.de/CSEO-Wiki/index.php/Main_Page.

CONCLUSIONS

The CSEO has potential to become a widely used standard within the academic and industrial community. Mainly because of the emerging need of systems toxicology to controlled vocabularies and also the lack of suitable ontologies for this domain, the CSEO prepares the ground for integrative systems-based research in the exposure science.

NF-κB-mediated inflammation leading to EMT via miR-200c is involved in cell transformation induced by cigarette smoke extract

Cigarette smoking constitutes a major human health hazard because it is the most important risk factor for lung cancer. Although evidence for smoking-induced lung cancer in humans is strong, the molecular mechanisms by which smoking causes cancer remain to be established. In this investigation, we evaluated the roles of inflammation and the epithelial-mesenchymal transition (EMT) in cigarette smoke extract (CSE)-induced transformation of human bronchial epithelial (HBE) cells. The results showed that chronic exposure to CSE induced EMT and transformation of these cells. Activation of nuclear factor-κB (NF-κB) by CSE increased levels of the proinflammatory interleukin-6 (IL-6), and acute and chronic exposures to CSE caused decreases in miR-200c levels. By blocking NF-κB with Bay11-7082 and IL-6 with anti-IL-6 antibody and enhancement of IL-6 with human recombinant IL-6, we found that the NF-κB signal pathway was involved in CSE-induced increases of IL-6, which suppressed miR-200c expression and promoted EMT. Moreover, IL-6 was necessary for maintenance of CSE-induced transformation and for malignant progression of HBE cells. Finally, blocking of NF-κB with Bay11-7082 prevented CSE-induced EMT and malignant transformation due to decreases of E-cadherin and miR-200c and elevations of IL-6, N-cadherin, and vimentin. Thus, we have defined a link between inflammation and EMT, processes involved in the malignant transformation of cells caused by CSE. This link, mediated through miRNAs, establishes a mechanism for CSE-induced lung carcinogenesis.

Cigarette smoking substantially alters plasma microRNA profiles in healthy subjects

Circulating microRNAs (miRNAs) are receiving attention as potential biomarkers of various diseases, including cancers, chronic obstructive pulmonary disease, and cardiovascular disease. However, it is unknown whether the levels of circulating miRNAs in a healthy subject might vary with external factors in daily life. In this study, we investigated whether cigarette smoking, a habit that has spread throughout the world and is a risk factor for various diseases, affects plasma miRNA profiles. We determined the profiles of 11 smokers and 7 non-smokers by TaqMan MicroRNA array analysis. A larger number of miRNAs were detected in smokers than in non-smokers, and the plasma levels of two-thirds of the detected miRNAs (43 miRNAs) were significantly higher in smokers than in non-smokers. A principal component analysis of the plasma miRNA profiles clearly separated smokers and non-smokers. Twenty-four of the miRNAs were previously reported to be potential biomarkers of disease, suggesting the possibility that smoking status might interfere with the diagnosis of disease. Interestingly, we found that quitting smoking altered the plasma miRNA profiles to resemble those of non-smokers. These results suggested that the differences in the plasma miRNA profiles between smokers and non-smokers could be attributed to cigarette smoking. In addition, we found that an acute exposure of ex-smokers to cigarette smoke (smoking one cigarette) did not cause a dramatic change in the plasma miRNA profile. In conclusion, we found that repeated cigarette smoking substantially alters the plasma miRNA profile, interfering with the diagnosis of disease or signaling potential smoking-related diseases.

Association between CYP2A6 genetic polymorphisms and lung cancer: a meta-analysis of case-control studies

Cytochrome P450 2A6 (CYP2A6) is an enzyme responsible for the metabolism of nicotine and some tobacco-specific carcinogens (such as N-nitrosamines). CYP2A6 genetic variations are associated with the activity of the CYP2A6 enzyme, which affects smoking behavior and the rate at which some tobacco-specific carcinogens are metabolized, which in turn determines the incidence of lung cancer. Several studies have investigated the relationship between CYP2A6 genotypes and lung cancer; however, the results are controversial. In this meta-analysis, we searched for all studies on the association between CYP2A6 genotypes and lung cancer indexed in the MEDLINE, PubMed, Embase, China Biological Medicine, and Wanfang databases from January 1, 1966 to August 1, 2011. The pooled odds ratios (ORs) for one CYP2A6 mutant allele and two CYP2A6 mutant alleles, in comparison with the wild-type CYP2A6 gene, were 0.82 [95% confidence interval (CI) = 0.73-0.92] and 0.57 (95% CI = 0.48-0.68), respectively. Furthermore, in two studies of participants who were all smokers, the associations of one CYP2A6 mutant allele and two CYP2A6 mutant alleles with reduced risk of lung cancer were strengthened, and the pooled ORs were 0.71 (95% CI = 0.58-0.87) and 0.47 (95% CI = 0.35-0.62), respectively. However, we did not find statistically significant relationships between CYP2A6 genotypes and lung cancer in studies that included both never smokers and smokers (pooled OR(one CYP2A6 mutant allele) = 0.88, 95% CI = 0.76-1.01; pooled OR(two CYP2A6 mutant alleles) = 0.61, 95% CI = 0.35-1.06). The results of this meta-analysis suggest that the reduced-activity CYP2A6 genotype may decrease the risk of lung cancer in smokers only.

Comparison of nasal epithelial smoking-induced gene expression on Affymetrix Exon 1.0 and Gene 1.0 ST arrays

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.

SIRT1 pathway dysregulation in the smoke-exposed airway epithelium and lung tumor tissue

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 upregulated in cytologically normal bronchial airway epithelial cells from active smokers compared with nonsmokers. In contrast, this activity is strikingly downregulated in non-small cell lung cancer. This pattern of signaling modulation was unique to SIRT1, and downregulation 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. Furthermore, 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 injury" induced by tobacco smoke and thus may impact strategies for prevention of tobacco-related lung cancer.

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.

p53 codon 72 polymorphism and the risk of lung cancer in a Korean population

The aim of this study was to assess whether p53 codon 72 polymorphism is associated with an increased risk of lung cancer (LC) in a South Korean population. We conducted a population-based, large-scale, case-control study including 3939 patients with LC and 1700 controls. P53 codon 72 polymorphism was determined by real-time polymerase chain reaction (PCR). The frequencies of p53 codon 72 polymorphisms (Arg/Arg, Arg/Pro, and Pro/Pro) in LC were 37.0%, 46.2%, and 16.7%, respectively; frequencies in the controls were 43.2%, 45.6%, and 11.2%, respectively (p<0.01). The Arg/Pro and Pro/Pro genotype were significantly associated with increased risk of LC (odds ratio (OR)=1.22, 95% confidence interval (CI)=1.06-1.14 and OR=1.83, 95% CI=1.48-2.26, respectively) compared with the Arg/Arg genotype. Risk was compared in different subgroups. The OR of Pro/Pro genotype was significantly higher in small cell lung cancer (SCC) and squamous cell carcinoma (SQC) than in adenocarcinoma (ADC). Higher OR of Pro/Pro genotype was also seen among males. However, relationships between gender, age, smoking, and genotypes were not found. P53 codon 72 polymorphism was associated with an increased risk of LC in this Korean population; the association was especially noteworthy in SQC, SCC, and males.

Genetic variation and antioxidant response gene expression in the bronchial airway epithelium of smokers at risk for lung cancer

Prior microarray studies of smokers at high risk for lung cancer have demonstrated that heterogeneity in bronchial airway epithelial cell gene expression response to smoking can serve as an early diagnostic biomarker for lung cancer. As a first step in applying functional genomic analysis to population studies, we have examined the relationship between gene expression variation and genetic variation in a central molecular pathway (NRF2-mediated antioxidant response) associated with smoking exposure and lung cancer. We assessed global gene expression in histologically normal airway epithelial cells obtained at bronchoscopy from smokers who developed lung cancer (SC, n = 20), smokers without lung cancer (SNC, n = 24), and never smokers (NS, n = 8). Functional enrichment analysis showed that the NRF2-mediated, antioxidant response element (ARE)-regulated genes, were significantly lower in SC, when compared with expression levels in SNC. Importantly, we found that the expression of MAFG (a binding partner of NRF2) was correlated with the expression of ARE genes, suggesting MAFG levels may limit target gene induction. Bioinformatically we identified single nucleotide polymorphisms (SNPs) in putative ARE genes and to test the impact of genetic variation, we genotyped these putative regulatory SNPs and other tag SNPs in selected NRF2 pathway genes. Sequencing MAFG locus, we identified 30 novel SNPs and two were associated with either gene expression or lung cancer status among smokers. This work demonstrates an analysis approach that integrates bioinformatics pathway and transcription factor binding site analysis with genotype, gene expression and disease status to identify SNPs that may be associated with individual differences in gene expression and/or cancer status in smokers. These polymorphisms might ultimately contribute to lung cancer risk via their effect on the airway gene expression response to tobacco-smoke exposure.

Similarities and differences between smoking-related gene expression in nasal and bronchial epithelium

Previous studies have shown that physiological responses to cigarette smoke can be detected via bronchial airway epithelium gene expression profiling and that heterogeneity in this gene expression response to smoking is associated with lung cancer. In this study, we sought to determine the similarity of the effects of tobacco smoke throughout the respiratory tract by determining patterns of smoking-related gene expression in paired nasal and bronchial epithelial brushings collected from 14 healthy nonsmokers and 13 healthy current smokers. Using whole genome expression arrays, we identified 119 genes whose expression was affected by smoking similarly in both bronchial and nasal epithelium, including genes related to detoxification, oxidative stress, and wound healing. While the vast majority of smoking-related gene expression changes occur in both bronchial and nasal epithelium, we also identified 27 genes whose expression was affected by smoking more dramatically in bronchial epithelium than nasal epithelium. Both common and site-specific smoking-related gene expression profiles were validated using independent microarray datasets. Differential expression of select genes was also confirmed by RT-PCR. That smoking induces largely similar gene expression changes in both nasal and bronchial epithelium suggests that the consequences of cigarette smoke exposure can be measured in tissues throughout the respiratory tract. Our findings suggest that nasal epithelial gene expression may serve as a relatively noninvasive surrogate to measure physiological responses to cigarette smoke and/or other inhaled exposures in large-scale epidemiological studies.

Pattern of antioxidant and DNA repair gene expression in normal airway epithelium associated with lung cancer diagnosis

In previous studies, we reported that key antioxidant and DNA repair genes are regulated differently in normal bronchial epithelial cells of lung cancer cases compared with non-lung cancer controls. In an effort to develop a biomarker for lung cancer risk, we evaluated the transcript expressions of 14 antioxidant, DNA repair, and transcription factor genes in normal bronchial epithelial cells (HUGO names CAT, CEBPG, E2F1, ERCC4, ERCC5, GPX1, GPX3, GSTM3, GSTP1, GSTT1, GSTZ1, MGST1, SOD1, and XRCC1). A test comprising these 14 genes accurately identified the lung cancer cases in two case-control studies. The receiver operating characteristic-area under the curve was 0.82 (95% confidence intervals, 0.68-0.91) for the first case-control set (25 lung cancer cases and 24 controls), and 0.87 (95% confidence intervals, 0.73-0.96) for the second set (18 cases and 22 controls). For each gene included in the test, the key difference between cases and controls was altered distribution of transcript expression among cancer cases compared with controls, with more lung cancer cases expressing at both extremes among all genes (Kolmorogov-Smirnov test, D = 0.0795; P = 0.041). A novel statistical approach was used to identify the lower and upper boundaries of transcript expression that optimally classifies cases and controls for each gene. Based on the data presented here, there is an increased prevalence of lung cancer diagnosis among individuals that express a threshold number of key antioxidant, DNA repair, and transcription factor genes at either very high or very low levels in the normal airway epithelium.

Phase I metabolic genes and risk of lung cancer: multiple polymorphisms and mRNA expression

Polymorphisms in genes coding for enzymes that activate tobacco lung carcinogens may generate inter-individual differences in lung cancer risk. Previous studies had limited sample sizes, poor exposure characterization, and a few single nucleotide polymorphisms (SNPs) tested in candidate genes. We analyzed 25 SNPs (some previously untested) in 2101 primary lung cancer cases and 2120 population controls from the Environment And Genetics in Lung cancer Etiology (EAGLE) study from six phase I metabolic genes, including cytochrome P450s, microsomal epoxide hydrolase, and myeloperoxidase. We evaluated the main genotype effects and genotype-smoking interactions in lung cancer risk overall and in the major histology subtypes. We tested the combined effect of multiple SNPs on lung cancer risk and on gene expression. Findings were prioritized based on significance thresholds and consistency across different analyses, and accounted for multiple testing and prior knowledge. Two haplotypes in EPHX1 were significantly associated with lung cancer risk in the overall population. In addition, CYP1B1 and CYP2A6 polymorphisms were inversely associated with adenocarcinoma and squamous cell carcinoma risk, respectively. Moreover, the association between CYP1A1 rs2606345 genotype and lung cancer was significantly modified by intensity of cigarette smoking, suggesting an underling dose-response mechanism. Finally, increasing number of variants at CYP1A1/A2 genes revealed significant protection in never smokers and risk in ever smokers. Results were supported by differential gene expression in non-tumor lung tissue samples with down-regulation of CYP1A1 in never smokers and up-regulation in smokers from CYP1A1/A2 SNPs. The significant haplotype associations emphasize that the effect of multiple SNPs may be important despite null single SNP-associations, and warrants consideration in genome-wide association studies (GWAS). Our findings emphasize the necessity of post-GWAS fine mapping and SNP functional assessment to further elucidate cancer risk associations.

The field of tissue injury in the lung and airway

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

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.

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

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

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

BACKGROUND

Cigarette smoking is a leading cause of preventable death and a significant cause of lung cancer and chronic obstructive pulmonary disease. Prior studies have demonstrated that smoking creates a field of molecular injury throughout the airway epithelium exposed to cigarette smoke. We have previously characterized gene expression in the bronchial epithelium of never smokers and identified the gene expression changes that occur in the mainstem bronchus in response to smoking. In this study, we explored relationships in whole-genome gene expression between extrathorcic (buccal and nasal) and intrathoracic (bronchial) epithelium in healthy current and never smokers.

RESULTS

Using genes that have been previously defined as being expressed in the bronchial airway of never smokers (the "normal airway transcriptome"), we found that bronchial and nasal epithelium from non-smokers were most similar in gene expression when compared to other epithelial and nonepithelial tissues, with several antioxidant, detoxification, and structural genes being highly expressed in both the bronchus and nose. Principle component analysis of previously defined smoking-induced genes from the bronchus suggested that smoking had a similar effect on gene expression in nasal epithelium. Gene set enrichment analysis demonstrated that this set of genes was also highly enriched among the genes most altered by smoking in both nasal and buccal epithelial samples. The expression of several detoxification genes was commonly altered by smoking in all three respiratory epithelial tissues, suggesting a common airway-wide response to tobacco exposure.

CONCLUSION

Our findings support a relationship between gene expression in extra- and intrathoracic airway epithelial cells and extend the concept of a smoking-induced field of injury to epithelial cells that line the mouth and nose. This relationship could potentially be utilized to develop a non-invasive biomarker for tobacco exposure as well as a non-invasive screening or diagnostic tool providing information about individual susceptibility to smoking-induced lung diseases.

A prediction model for lung cancer diagnosis that integrates genomic and clinical features

Lung cancer is the leading cause of cancer death due, in part, to lack of early diagnostic tools. Bronchoscopy represents a relatively noninvasive initial diagnostic test in smokers with suspect disease, but it has low sensitivity. We have reported a gene expression profile in cytologically normal large airway epithelium obtained via bronchoscopic brushings, which 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 (n = 62) sets 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 nondiagnostic 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 negative predictive value to 100% and results in higher specificity (91%) and positive predictive value (81%) compared with 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.

The sociobiologic integrative model (SBIM): enhancing the integration of sociobehavioral, environmental, and biomolecular knowledge in urban health and disparities research

Disentangling the myriad determinants of disease, within the context of urban health or health disparities, requires a transdisciplinary approach. Transdisciplinary approaches draw on concepts from multiple scientific disciplines to develop a novel, integrated perspective from which to conduct scientific investigation. Most historic and contemporary conceptual models of health were derived either from the sociobehavioral sciences or the biomolecular sciences. Those models deriving from the sociobehavioral sciences generally lack detail on involved biological mechanisms whereas those derived from the biomolecular sciences largely do not consider socioenvironmental determinants. As such, advances in transdisciplinary characterizations of health in complex systems like the urban environment or health disparities may be impeded. This paper suggests a sociobiologic organizing model that encourages a multilevel, integrative perspective in the study of urban health and health disparities.

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 database's web interface, found at http://pulm.bumc.bu.edu/siegeDB. PERL-coded scripts integrated with SIEGE perform various quality control functions including the processing, filtering and formatting of stored data. The R statistical package is used to import database expression values and execute a number of statistical analyses including t-tests, correlation coefficients and hierarchical clustering. Values from all statistical analyses can be queried through CGI-based tools and web forms found on the ‘Search’ section of the database website. Query results are embedded with graphical capabilities as well as with links to other databases containing valuable gene resources, including Entrez Gene, GO, Biocarta, GeneCards, dbSNP and the NCBI Map Viewer.

Biomarkers for risk assessment in molecular epidemiology of cancer

One out of four deaths in the USA is due to cancer. Identification of populations at risk of developing cancer is important as it provides opportunities for prevention and treatment of cancer. Biomarkers are measurable indicators of exposure effects and susceptibility or disease state, and are used to understand the mechanisms of cancer progression. In recent molecular epidemiology studies genomic, proteomic, and epigenomic markers have been utilized which exhibit high sensitivity and specificity for different tumor types and can be assayed in biofluids and other specimens collected by non-invasive technologies. The current challenges and future directions in the field are discussed in this article.

Spectra of antinuclear antibodies in patients with squamous cell carcinoma of the lung and of the head and neck

Squamous cell carcinoma of the head and neck (HNSCC) and of the lung (LSCC) share some important risk factors, but differ substantially in terms of prognosis and treatment. A pulmonary nodule developing in patients with surgically cured HNSCC may pose a diagnostic dilemma. Markers able to distinguish these two common malignancies would be of major clinical importance. In this work we compared the spectrum of antinuclear antibodies (ANA) from 22 patients with SCCL to that of 40 patients with HNSCC. Patient sera were used to probe immunoblots of nuclear extracts from all four major lung cancer cell types, normal lung fibroblasts, cells cultured from a HNSCC, and keratinocytes cultured from the field cancerization. The ability to classify retrospectively LSCC from HNSCC based on serum ANA reactivities was determined by recursive partitioning analyses. We found that while both malignancies share reactivities to a small group of nuclear antigens, other reactivities are directed against proteins uniquely or preferentially expressed in either SCCL or in SCCHN cells. Our work shows that autoimmunity is a prominent feature of squamous cell carcinoma and suggests that molecular characterization of nuclear antigens recognized by ANAs may lead to the discovery of markers valuable to distinguish LSCC from HNSCC.

Effects of cigarette smoke on the human airway epithelial cell transcriptome

Cigarette smoke is the major cause of lung cancer, the leading cause of cancer death, and of chronic obstructive pulmonary disease, the fourth leading cause of death in the United States. Using high-density gene expression arrays, we describe genes that are normally expressed in a subset of human airway epithelial cells obtained at bronchoscopy (the airway transcriptome), define how cigarette smoking alters the transcriptome, and detail the effects of variables, such as cumulative exposure, age, sex, and race, on cigarette smoke-induced changes in gene expression. We also determine which changes in gene expression are and are not reversible when smoking is discontinued. The persistent altered expression of a subset of genes in former smokers may explain the risk these individuals have for developing lung cancer long after they have discontinued smoking. The use of gene expression profiling to explore the normal biology of a specific subset of cells within a complex organ across a broad spectrum of healthy individuals and to define the reversible and irreversible genetic effects of cigarette smoke on human airway epithelial cells has not been previously reported.

Smoking, DNA repair capacity and risk of nonsmall cell lung cancer

Tobacco-related carcinogens cause a variety of DNA damage that is repaired by different enzymatic pathways, suggesting that DNA repair plays an important role in tobacco-induced carcinogenesis. In a large hospital-based case-control study, we investigated DNA repair capacity (DRC) as a biomarker for susceptibility to nonsmall cell lung cancer (NSCLC) and evaluated the possible interaction between DRC and tobacco smoke in 467 newly diagnosed NSCLC patients and 488 cancer-free controls. We measured DRC in cultured peripheral lymphocytes using the host-cell reactivation assay with a reporter gene damaged by an activated tobacco carcinogen, benzo[a]pyrene diol epoxide. The results showed that current smokers exhibited the highest DRCs as compared to former and nonsmokers both among patients and control subjects. There were no differences of DRC among 3 different histopathologic types of NSCLC. Logistic regression analysis revealed that suboptimal DRC and pack-years smoked were independent predictors of NSCLC risk. The overall 15.5% reduction in DRC observed in the cases (7.84%) compared to the controls (9.28%) (p<0.001) was associated with an approximately 2-fold increased risk of NSCLC (adjusted odds ratio (OR) = 1.85, 95% confidence interval (CI) 1.42-2.42). There was a significant dose-response association between decreased DRC and increased risk of lung cancer. Furthermore, we observed a nonstatistically significant additive but not multiplicative interaction between DRC and pack-years smoked on lung cancer risk, particularly in the histopathologic types of NSCLC other than adenocarcinoma. The results suggest that suboptimal DRC is associated with increased risk of NSCLC and DRC may modulate the risk of lung cancer associated with smoking but the latter needs to be verified in larger studies.

A catalogue of polymorphisms related to xenobiotic metabolism and cancer susceptibility

High-throughput genotyping technology of multiple genes based on large samples of cases and controls are likely to be important in identifying common genes which have a moderate effect on the development of specific diseases. We present here a comprehensive list of 313 known experimentally confirmed polymorphisms in 54 genes which are particularly relevant for metabolism of drugs, alcohol, tobacco, and other potential carcinogens. We have compiled a catalog with a standardized format that summarizes the genetic and biochemical properties of the selected polymorphisms. We have also confirmed or redesigned experimental conditions for simplex or multiplex PCR amplification of a subset of 168 SNPs of particular interest, which will provide the basis for the design of assays compatible with high-throughput genotyping.

Effect of smoking cessation on major histologic types of lung cancer

STUDY OBJECTIVES

It is well-recognized that the risk of lung cancer declines after smoking cessation. However, the degree of decline in different histologic types of lung cancer is not well understood. We conducted a meta-analysis of peer-reviewed studies to assess the effect of smoking cessation on rates of major histologic types of lung cancer.

DESIGN

Studies published in English between 1970 and 1999 were identified through searches of computerized databases (ie, MEDLINE and CANCERLIT). Combined estimates of relative risk and 95% confidence intervals were calculated for 27 studies using fixed and random effects models. Separate analyses were conducted for men and women.

RESULTS

Smoking cessation was associated with a reduction in the risk of all the major histologic types of lung cancer. The highest reduction was in small cell lung carcinoma (SCLC) and squamous cell carcinoma (SQC), and the lowest reduction was seen in large cell cancer and adenocarcinoma. In women, the combined risks for SQC and SCLC were higher than those in men. The dose-response curve for intensity of smoking was steeper in women.

CONCLUSION

The findings of this study suggest that smoking cessation results in the greatest reductions for SCLC and SQC. This effect is most marked in heavy smokers, particularly among women.

Putting the search for genes in perspective

The sequencing of the human genome has been heralded by both the mass media and scientists as a breakthrough that will allow the detection of individuals at increased risk for common diseases and the tailoring of drugs to an individual's genetic profile in order to prevent disease. Sequencing is likely to benefit those at risk of developing rare diseases in which inherited mutations in a single gene play a major causal role. In the vast majority of people with common diseases, however, genotypes at many different loci, as well as environmental exposures, must be simultaneously present before disease appears. Elucidating the genes involved will prove elusive. In addition to the large number, different combinations account for a particular disease. Most of the genotypes that contribute to the constellation of necessary genes are uncommon and will be difficult to find. Common genotypes may confer susceptibility but will be weak predictors of disease. Because of the difficulty of discovering genes for common diseases, designing therapies will also prove difficult. More attention to environmental risk factors for particular diseases will have greater yield than a genetic search, but this too will be difficult because of environmental-genetic and other interactions. The search for risk factors for particular diseases neglects the political and social milieu in which individuals swim or sink and in which all diseases occur.