Lung Cancer Etiology Study Research Articles

Rare germline deleterious variants increase susceptibility for lung cancer.

Although multiple common susceptibility loci for lung cancer (LC) have been identified by genome-wide association studies, they can explain only a small portion of heritability. The etiological contribution of rare deleterious variants (RDVs) to LC risk is not fully characterized and may account for part of the missing heritability. Here, we sequenced the whole exomes of 2777 participants from the Environment and Genetics in Lung cancer Etiology study, a homogenous population including 1461 LC cases and 1316 controls. In single-variant analyses, we identified a new RDV, rs77187983 [EHBP1, odds ratio (OR) = 3.13, 95% confidence interval (CI) = 1.34-7.30, P = 0.008] and replicated two previously reported RDVs, rs11571833 (BRCA2, OR = 2.18; 95% CI = 1.25-3.81, P = 0.006) and rs752672077 (MPZL2, OR = 3.70, 95% CI = 1.04-13.15, P = 0.044). In gene-based analyses, we confirmed BRCA2 (P = 0.007) and ATM (P = 0.014) associations with LC risk and identified TRIB3 (P = 0.009), involved in maintaining genome stability and DNA repair, as a new candidate susceptibility gene. Furthermore, cases were enriched with RDVs in homologous recombination repair [carrier frequency (CF) = 22.9% versus 19.5%, P = 0.017] and Fanconi anemia (CF = 12.5% versus 10.2%, P = 0.036) pathways. Our results were not significant after multiple testing corrections but were enriched in cases versus controls from large scale public biobank resources, including The Cancer Genome Atlas, FinnGen and UK Biobank. Our study identifies novel candidate genes and highlights the importance of RDVs in DNA repair-related genes for LC susceptibility. These findings improve our understanding of LC heritability and may contribute to the development of risk stratification and prevention strategies.

Epigenome-wide analysis of DNA methylation in lung tissue shows concordance with blood studies and identifies tobacco smoke-inducible enhancers.

Smoking-associated DNA hypomethylation has been observed in blood cells and linked to lung cancer risk. However, its cause and mechanistic relationship to lung cancer remain unclear. We studied the association between tobacco smoking and epigenome-wide methylation in non-tumor lung (NTL) tissue from 237 lung cancer cases in the Environment And Genetics in Lung cancer Etiology study, using the Infinium HumanMethylation450 BeadChip. We identified seven smoking-associated hypomethylated CpGs (P < 1.0 × 10-7), which were replicated in NTL data from The Cancer Genome Atlas. Five of these loci were previously reported as hypomethylated in smokers' blood, suggesting that blood-based biomarkers can reflect changes in the target tissue for these loci. Four CpGs border sequences carrying aryl hydrocarbon receptor binding sites and enhancer-specific histone modifications in primary alveolar epithelium and A549 lung adenocarcinoma cells. A549 cell exposure to cigarette smoke condensate increased these enhancer marks significantly and stimulated expression of predicted target xenobiotic response-related genes AHRR (P = 1.13 × 10-62) and CYP1B1 (P < 2.49 × 10-61). Expression of both genes was linked to smoking-related transversion mutations in lung tumors. Thus, smoking-associated hypomethylation may be a consequence of enhancer activation, revealing environmentally-induced regulatory elements implicated in lung carcinogenesis.

A Novel Pathway-Based Approach Improves Lung Cancer Risk Prediction Using Germline Genetic Variations.

Although genome-wide association studies (GWAS) have identified many genetic variants that are strongly associated with lung cancer, these variants have low penetrance and serve as poor predictors of lung cancer in individuals. We sought to increase the predictive value of germline variants by considering their cumulative effects in the context of biologic pathways. For individuals in the Environment and Genetics in Lung Cancer Etiology study (1,815 cases/1,971 controls), we computed pathway-level susceptibility effects as the sum of relevant SNP variant alleles weighted by their log-additive effects from a separate lung cancer GWAS meta-analysis (7,766 cases/37,482 controls). Logistic regression models based on age, sex, smoking, genetic variants, and principal components of pathway effects and pathway-smoking interactions were trained and optimized in cross-validation and further tested on an independent dataset (556 cases/830 controls). We assessed prediction performance using area under the receiver operating characteristic curve (AUC). Compared with typical binomial prediction models that have epidemiologic predictors (AUC = 0.607) in addition to top GWAS variants (AUC = 0.617), our pathway-based smoking-interactive multinomial model significantly improved prediction performance in external validation (AUC = 0.656, P < 0.0001). Our biologically informed approach demonstrated a larger increase in AUC over nongenetic counterpart models relative to previous approaches that incorporate variants. This model is the first of its kind to evaluate lung cancer prediction using subtype-stratified genetic effects organized into pathways and interacted with smoking. We propose pathway-exposure interactions as a potentially powerful new contributor to risk inference. Cancer Epidemiol Biomarkers Prev; 25(8); 1208-15. ©2016 AACR.

Abstract 286: Epigenome-wide association study of normal lung tissues identifies hypomethylation of multiple CpG sites associated with cigarette smoking

Abstract Background: DNA methylation due to tobacco smoking have been reported in studies of blood genomic DNA, indicating a possible role of methylation changes due to smoking in multiple adverse health outcomes. Since DNA methylation is known to be tissue-specific, we profiled methylation in normal human lung tissues and evaluated the association with cigarette smoking based on a large sample size. Methods: We studied histologically normal lung tissues of 237 lung cancer patients (121 current cigarette smokers and 116 current nonsmokers) from the Environment And Genetics in Lung cancer Etiology study. DNA methylation was assayed using the Illumina Infinium HumanMethylation450 BeadChip arrays and methylation for 338,456 autosomal probes remained after quality control filters. We examined the association of log-transformed methylation with current smoking status, as well as with quantitative measures of smoking, using linear regression models adjusting for covariates. We sought to replicate the findings in The Cancer Genome Atlas normal lung samples (12 current smokers and 50 nonsmokers). Results: Eight CpG sites were significantly hypomethylated in lung tissues of current smokers after Bonferroni-correction (P&amp;lt;1.48×10-7). Of them, six were associated with smoking duration, pack-years and years from quitting smoking, and were replicated in TCGA samples (P&amp;lt;0.10), including cg17113147 (NXN), cg05575921 (AHRR), cg07992500 (CDC42EP3), cg14120703 (NOTCH1), cg11152412 (EDC3), and cg03224163 (HIPK2). These loci have not been reported in prior studies, except for cg05575921, which was shown to be hypomethylated in smokers in studies of blood DNA. Conclusions: Our study in lung tissues shows that smoking is associated with alterations in DNA methylation in genes involved in tobacco smoking metabolism or cancer progression. These findings suggest that smoking-associated epigenetic changes may have an important role in lung tumorigenesis. Citation Format: Wen-Qing Li, Jianxin Shi, William Wheeler, Neil Caporaso, Ite Laird-Offspringa, Maria Teresa Landi. Epigenome-wide association study of normal lung tissues identifies hypomethylation of multiple CpG sites associated with cigarette smoking. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 286. doi:10.1158/1538-7445.AM2014-286

A regression model for risk difference estimation in population-based case-control studies clarifies gender differences in lung cancer risk of smokers and never smokers.

BackgroundAdditive risk models are necessary for understanding the joint effects of exposures on individual and population disease risk. Yet technical challenges have limited the consideration of additive risk models in case–control studies.MethodsUsing a flexible risk regression model that allows additive and multiplicative components to estimate absolute risks and risk differences, we report a new analysis of data from the population-based case–control Environment And Genetics in Lung cancer Etiology study, conducted in Northern Italy between 2002–2005. The analysis provides estimates of the gender-specific absolute risk (cumulative risk) for non-smoking- and smoking-associated lung cancer, adjusted for demographic, occupational, and smoking history variables.ResultsIn the multiple-variable lexpit regression, the adjusted 3-year absolute risk of lung cancer in never smokers was 4.6 per 100,000 persons higher in women than men. However, the absolute increase in 3-year risk of lung cancer for every 10 additional pack-years smoked was less for women than men, 13.6 versus 52.9 per 100,000 persons.ConclusionsIn a Northern Italian population, the absolute risk of lung cancer among never smokers is higher in women than men but among smokers is lower in women than men. Lexpit regression is a novel approach to additive-multiplicative risk modeling that can contribute to clearer interpretation of population-based case–control studies.

A Gene Expression Signature from Peripheral Whole Blood for Stage I Lung Adenocarcinoma

Affordable early screening in subjects with high risk of lung cancer has great potential to improve survival from this deadly disease. We measured gene expression from lung tissue and peripheral whole blood (PWB) from adenocarcinoma cases and controls to identify dysregulated lung cancer genes that could be tested in blood to improve identification of at-risk patients in the future. Genome-wide mRNA expression analysis was conducted in 153 subjects (73 adenocarcinoma cases, 80 controls) from the Environment And Genetics in Lung cancer Etiology study using PWB and paired snap-frozen tumor and noninvolved lung tissue samples. Analyses were conducted using unpaired t tests, linear mixed effects, and ANOVA models. The area under the receiver operating characteristic curve (AUC) was computed to assess the predictive accuracy of the identified biomarkers. We identified 50 dysregulated genes in stage I adenocarcinoma versus control PWB samples (false discovery rate ≤0.1, fold change ≥1.5 or ≤0.66). Among them, eight (TGFBR3, RUNX3, TRGC2, TRGV9, TARP, ACP1, VCAN, and TSTA3) differentiated paired tumor versus noninvolved lung tissue samples in stage I cases, suggesting a similar pattern of lung cancer-related changes in PWB and lung tissue. These results were confirmed in two independent gene expression analyses in a blood-based case-control study (n = 212) and a tumor-nontumor paired tissue study (n = 54). The eight genes discriminated patients with lung cancer from healthy controls with high accuracy (AUC = 0.81, 95% CI = 0.74-0.87). Our finding suggests the use of gene expression from PWB for the identification of early detection markers of lung cancer in the future.

Dietary quercetin, quercetin-gene interaction, metabolic gene expression in lung tissue and lung cancer risk

Epidemiological and mechanistic evidence on the association of quercetin-rich food intake with lung cancer risk and carcinogenesis are inconclusive. We investigated the role of dietary quercetin and the interaction between quercetin and P450 and glutathione S-transferase (GST) polymorphisms on lung cancer risk in 1822 incident lung cancer cases and 1991 frequency-matched controls from the Environment And Genetics in Lung cancer Etiology study. In non-tumor lung tissue from 38 adenocarcinoma patients, we assessed the correlation between quercetin intake and messenger RNA expression of the same P450 and GST metabolic genes. Multivariate odds ratios (ORs) and 95% confidence intervals (CIs) for sex-specific quintiles of intake were calculated using unconditional logistic regression adjusting for putative risk factors. Frequent intake of quercetin-rich foods was inversely associated with lung cancer risk (OR = 0.49; 95% CI: 0.37-0.67; P-trend < 0.001) and did not differ by P450 or GST genotypes, gender or histological subtypes. The association was stronger in subjects who smoked >20 cigarettes per day (OR = 0.35; 95% CI: 0.19-0.66; P-trend = 0.003). Based on a two-sample t-test, we compared gene expression and high versus low consumption of quercetin-rich foods and observed an overall upregulation of GSTM1, GSTM2, GSTT2, and GSTP1 as well as a downregulation of specific P450 genes (P-values < 0.05, adjusted for age and smoking status). In conclusion, we observed an inverse association of quercetin-rich food with lung cancer risk and identified a possible mechanism of quercetin-related changes in the expression of genes involved in the metabolism of tobacco carcinogens in humans. Our findings suggest an interplay between quercetin intake, tobacco smoking, and lung cancer risk. Further research on this relationship is warranted.