The detection of tumor suppressor gene promoter methylation in sputum-derived exfoliated cells predicts early lung cancer. Here we identified genetic determinants for this epigenetic process and examined their biological effects on gene regulation. A two-stage approach involving discovery and replication was employed to assess the association between promoter hypermethylation of a 12-gene panel and common variation in 40 genes involved in carcinogen metabolism, regulation of methylation, and DNA damage response in members of the Lovelace Smokers Cohort (n=1434). Molecular validation of three identified variants was conducted using primary bronchial epithelial cells. Association of study-wide significance (P<8.2×10−5) was identified for rs1641511, rs3730859, and rs1883264 in TP53, LIG1, and BIK, respectively. These SNPs were significantly associated with altered expression of the corresponding genes in primary bronchial epithelial cells. In addition, rs3730859 in LIG1 was also moderately associated with increased risk for lung cancer among Caucasian smokers. Together, our findings suggest that genetic variation in DNA replication and apoptosis pathways impacts the propensity for gene promoter hypermethylation in the aerodigestive tract of smokers. The incorporation of genetic biomarkers for gene promoter hypermethylation with clinical and somatic markers may improve risk assessment models for lung cancer.

Background

No prior studies have related a tobacco-specific carcinogen to risk of lung cancer in smokers. Of the over 60 known carcinogens in cigarette smoke, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) is specific to tobacco and causes lung cancer in laboratory animals. Its metabolites, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol and its glucuronides (total NNAL), have been studied as biomarkers of exposure to NNK. We studied the relation of prospectively measured NNK biomarkers to lung cancer risk.

Methods

In a case-control study nested in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, we randomly selected 100 lung cancer cases and 100 controls who smoked at baseline and analyzed their baseline serum for total NNAL, cotinine and r-1,t-2,3,c-4-tetrahydroxy-1,2,3,4-tetrahydrophenanthrene (PheT), a biomarker of polycyclic aromatic hydrocarbon exposure and metabolic activation. To examine the association of the biomarkers with all lung cancer and for histologic subtypes, we computed odds ratios (OR) for total NNAL, PheT and cotinine using logistic regression to adjust for potential confounders.

Findings

Individual associations of age, smoking duration, and total NNAL with lung cancer risk were statistically significant. After adjustment, total NNAL was the only biomarker significantly associated with risk (OR = 1.57 per unit standard deviation increase, 95% confidence interval: 1.08, 2.28). A similar statistically significant result was obtained for adenocarcinoma risk, but not for non-adenocarcinoma.

Conclusions

This first reporting of the effect of the prospectively measured tobacco-specific biomarker, total NNAL, on risk of lung cancer in smokers provides insight into the etiology of smoking-related lung cancer and reinforces targeting NNK for cancer prevention.

Background

Other than male sex, family history, advanced age, and race, risk factors for chronic lymphocytic leukemia and small lymphocytic lymphoma (CLL/SLL) are unknown. Very few studies have investigated diet in relation to these leukemias, and no consistent associations are known.

Methods

Using two large prospective population-based studies, we evaluated the relationship between diet and CLL/SLL risk. Among 525,982 men and women free of cancer at enrollment, we identified 1,129 incident CLL/SLL cases during 11.2 years of follow-up.

Results

We found no associations between total fat, saturated fat, fiber, red meat, processed meat, fruit or vegetable intake and risk of CLL/SLL. We noted a suggestive positive association between body mass index (BMI) and CLL/SLL (hazard ratio =1.30; 95% confidence interval= 0.99-1.36).

Conclusion

We did not find any associations between foods or nutrients and CLL/SLL.

Impact

Our large prospective study indicates that diet may not play a role in CLL/SLL development.

BACKGROUND

Tobacco-induced lung cancer is characterized by a deregulated inflammatory microenvironment. Variants in multiple genes in inflammation pathways may contribute to risk of lung cancer.

METHODS

We therefore conducted a three-stage comprehensive pathway analysis (discovery, replication and meta-analysis) of inflammation gene variants in ever smoking lung cancer cases and controls. A discovery set (1096 cases; 727 controls) and an independent and non-overlapping internal replication set (1154 cases; 1137 controls) were derived from an ongoing case-control study. For discovery, we used an iSelect BeadChip to interrogate a comprehensive panel of 11737 inflammation pathway SNPs and selected nominally significant (p<0.05) SNPs for internal replication.

RESULTS

There were 6 SNPs that achieved statistical significance (p<0.05) in the internal replication dataset with concordant risk estimates for former smokers and 5 concordant and replicated SNPs in current smokers. Replicated hits were further tested in a subsequent meta-analysis using external data derived from two published GWAS and a case-control study. Two of these variants (a BCL2L14 SNP in former smokers and a SNP in IL2RB in current smokers) were further validated. In risk score analyses, there was a 26% increase in risk with each additional adverse allele when we combined the genotyped SNP and the most significant imputed SNP in IL2RB in current smokers and a 36% similar increase in risk for former smokers associated with genotyped and imputed BCL2L14 SNPs.

CONCLUSIONS/IMPACT

Before they can be applied for risk prediction efforts, these SNPs should be subject to further external replication and more extensive fine mapping studies.

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 (EAGLE) study using PWB and paired snap-frozen tumor and non-involved 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 non-involved 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-non tumor 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.

Background

Inflammation and pulmonary diseases, including interstitial lung diseases, are associated with increased lung cancer risk. Circulating levels of surfactant protein-D (SP-D) and Krebs von Lungren-6 (KL-6) are elevated in interstitial lung disease patients, and may be useful markers of processes contributing to lung cancer.

Methods

We conducted a nested case-control study, including 532 lung cancer cases, 582 matched controls and 150 additional controls with chest x-ray (CXR) evidence of pulmonary scarring, in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Serum SP-D and KL-6 levels were measured using enzyme immunoassay. Logistic regression was used to estimate the associations of SP-D and KL-6 with lung cancer and CXR scarring.

Results

Cases had higher levels than controls for SP-D (median 118.7 vs. 105.4 ng/ml, p-value=0.008) and KL-6 (372.0 vs. 325.8 μg/ml, p-value=0.001). Lung cancer risk increased with SP-D (p-trend=0.0003) and KL-6 levels (p-trend=0.005). Compared to the lowest quartile, lung cancer risk was elevated among those with the highest quartiles of SP-D (odds ratio [OR]=1.87; 95% confidence interval [CI] 1.32–2.64), or KL-6 (OR=1.58; 95% CI 1.11–2.25). Among controls, participants with CXR scarring were more likely than those without scarring to have elevated levels of SP-D (quartile 4 vs. quartile 1: OR=1.67; 95% CI: 1.04–2.70; p-trend=0.05) but not of KL-6 (OR=1.04; 95% CI: 0.64–1.68; p-trend=0.99).

Conclusion

Circulating levels of SP-D and KL-6 are associated with subsequent lung cancer risk.

Impact

Our findings support a potential role for interstitial lung disease in lung cancer etiology or early detection, but additional research is needed.

AIM: To explore the association between methylation in leukocyte DNA and colorectal cancer (CRC) risk in male smokers using the α-tocopherol, β-carotene cancer prevention study.

METHODS: About 221 incident CRC cases, and 219 controls, frequency-matched on age and smoking intensity were included. DNA methylation of 1505 CpG sites selected from 807 genes were evaluated using Illumina GoldenGate Methylation Cancer Panel I in pre-diagnostic blood leukocytes of study subjects. Tertiles of methylation level classified according to the distribution in controls for each CpG site were used to analyze the association between methylation level and CRC risk with logistic regression. The time between blood draw to cancer diagnosis (classifying cases according to latency) was incorporated in further analyses using proportional odds regression.

RESULTS: We found that methylation changes of 31 CpG sites were associated with CRC risk at P < 0.01 level. Though none of these 31 sites remained statistically significant after Bonferroni correction, the most statistically significant CpG site associated with CRC risk achieved a P value of 1.0 × 10-4. The CpG site is located in DSP gene, and the risk estimate was 1.52 (95% CI: 0.91-2.53) and 2.62 (95% CI: 1.65-4.17) for the second and third tertile comparing with the lowest tertile respectively. Taking the latency information into account strengthened some associations, suggesting that the methylation levels of corresponding sites might change over time with tumor progression.

CONCLUSION: The results suggest that the methylation level of some genes were associated with cancer susceptibility and some were related to tumor development over time. Further studies are warranted to confirm and refine our results.

Although it is recognized that many common complex diseases are a result of multiple genetic and environmental risk factors, studies of gene-environment interaction remain a challenge and have had limited success to date. Given the current state-of-the-science, NIH sought input on ways to accelerate investigations of gene-environment interplay in health and disease by inviting experts from a variety of disciplines to give advice about the future direction of gene-environment interaction studies. Participants of the NIH Gene-Environment Interplay Workshop agreed that there is a need for continued emphasis on studies of the interplay between genetic and environmental factors in disease and that studies need to be designed around a multifaceted approach to reflect differences in diseases, exposure attributes, and pertinent stages of human development. The participants indicated that both targeted and agnostic approaches have strengths and weaknesses for evaluating main effects of genetic and environmental factors and their interactions. The unique perspectives represented at the workshop allowed the exploration of diverse study designs and analytical strategies, and conveyed the need for an interdisciplinary approach including data sharing, and data harmonization to fully explore gene-environment interactions. Further, participants also emphasized the continued need for high-quality measures of environmental exposures and new genomic technologies in ongoing and new studies.

Background

Mood disorders may affect lung cancer risk. We evaluated this hypothesis in two large studies.

Methodology/Principal Findings

We examined 1,939 lung cancer cases and 2,102 controls from the Environment And Genetics in Lung cancer Etiology (EAGLE) case-control study conducted in Italy (2002–2005), and 82,945 inpatients with a lung cancer diagnosis and 3,586,299 person-years without a lung cancer diagnosis in the U.S. Veterans Affairs Inpatient Cohort (VA study), composed of veterans with a VA hospital admission (1969–1996). In EAGLE, we calculated odds ratios (ORs) and 95% confidence intervals (CI), with extensive adjustment for tobacco smoking and multiple lifestyle factors. In the VA study, we estimated lung cancer relative risks (RRs) and 95% CIs with time-dependent Poisson regression, adjusting for attained age, calendar year, hospital visits, time within the study, and related previous medical diagnoses. In EAGLE, we found decreased lung cancer risk in subjects with a personal history of mood disorders (OR: 0.59, 95% CI: 0.44–0.79, based on 121 lung cancer incident cases and 192 controls) and family history of mood disorders (OR: 0.62, 95% CI: 0.50–0.77, based on 223 lung cancer cases and 345 controls). The VA study analyses yielded similar results (RR: 0.74, 95% CI: 0.71–0.77, based on 2,304 incident lung cancer cases and 177,267 non-cancer person-years) in men with discharge diagnoses for mood disorders. History of mood disorders was associated with nicotine dependence, alcohol and substance use and psychometric scales of depressive and anxiety symptoms in controls for these studies.

Conclusions/Significance

The consistent finding of a relationship between mood disorders and lung cancer risk across two large studies calls for further research into the complex interplay of risk factors associated with these two widespread and debilitating diseases. Although we adjusted for smoking effects in EAGLE, residual confounding of the results by smoking cannot be ruled out.

While lung cancer is largely caused by tobacco smoking, inherited genetic factors play a role in its etiology. Genome-wide association studies (GWAS) in Europeans have robustly demonstrated only three polymorphic variations influencing lung cancer risk. Tumor heterogeneity may have hampered the detection of association signal when all lung cancer subtypes were analyzed together. In a GWAS of 5,355 European smoking lung cancer cases and 4,344 smoking controls, we conducted a pathway-based analysis in lung cancer histologic subtypes with 19,082 SNPs mapping to 917 genes in the HuGE-defined “inflammation” pathway. We identified a susceptibility locus for squamous cell lung carcinoma (SQ) at 12p13.33 (RAD52, rs6489769), and replicated the association in three independent samples totaling 3,359 SQ cases and 9,100 controls (odds ratio=1.20, Pcombined=2.3×10−8).

Significance

The combination of pathway-based approaches and information on disease specific subtypes can improve the identification of cancer susceptibility loci in heterogeneous diseases.

Background

Previous studies that were based primarily on small numbers of patients suggested that certain circulating proinflammatory cytokines may be associated with lung cancer; however, large independent studies are lacking.

Methods

Associations between serum interleukin 6 (IL-6) and interleukin 8 (IL-8) levels and lung cancer were analyzed among 270 case patients and 296 control subjects participating in the National Cancer Institute-Maryland (NCI-MD) case–control study. Results were validated in 532 case patients and 595 control subjects in a nested case–control study within the prospective Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Association with C-reactive protein (CRP), a systemic inflammation biomarker, was also analyzed. Associations between biomarkers and lung cancer were estimated using logistic regression models adjusted for smoking, stage, histology, age, and sex. The 10-year standardized absolute risks of lung cancer were estimated using a weighted Cox regression model.

Results

Serum IL-6 and IL-8 levels in the highest quartile were associated with lung cancer in the NCI-MD study (IL-6, odds ratio [OR] = 3.29, 95% confidence interval [CI] = 1.88 to 5.77; IL-8, OR = 2.06, 95% CI = 1.19 to 3.57) and with lung cancer risk in the PLCO study (IL-6, OR = 1.48, 95% CI = 1.04 to 2.10; IL-8, OR = 1.57, 95% CI = 1.10 to 2.24), compared with the lowest quartile. In the PLCO study, increased IL-6 levels were only associated with lung cancer diagnosed within 2 years of blood collection, whereas increased IL-8 levels were associated with lung cancer diagnosed more than 2 years after blood collection (OR = 1.57, 95% CI = 1.15 to 2.13). The 10-year standardized absolute risks of lung cancer in the PLCO study were highest among current smokers with high IL-8 and CRP levels (absolute risk = 8.01%, 95% CI = 5.77% to 11.05%).

Conclusions

Although increased levels of both serum IL-6 and IL-8 are associated with lung cancer, only IL-8 levels are associated with lung cancer risk several years before diagnosis. Combination of IL-8 and CRP are more robust biomarkers than either marker alone in predicting subsequent lung cancer.

Introduction

Identification of individuals at high risk for lung cancer should be of value to individuals, patients, clinicians, and researchers. Existing prediction models have only modest capabilities to classify persons at risk accurately.

Methods

Prospective data from 70 962 control subjects in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) were used in models for the general population (model 1) and for a subcohort of ever-smokers (N = 38 254) (model 2). Both models included age, socioeconomic status (education), body mass index, family history of lung cancer, chronic obstructive pulmonary disease, recent chest x-ray, smoking status (never, former, or current), pack-years smoked, and smoking duration. Model 2 also included smoking quit-time (time in years since ever-smokers permanently quit smoking). External validation was performed with 44 223 PLCO intervention arm participants who completed a supplemental questionnaire and were subsequently followed. Known available risk factors were included in logistic regression models. Bootstrap optimism-corrected estimates of predictive performance were calculated (internal validation). Nonlinear relationships for age, pack-years smoked, smoking duration, and quit-time were modeled using restricted cubic splines. All reported P values are two-sided.

Results

During follow-up (median 9.2 years) of the control arm subjects, 1040 lung cancers occurred. During follow-up of the external validation sample (median 3.0 years), 213 lung cancers occurred. For models 1 and 2, bootstrap optimism-corrected receiver operator characteristic area under the curves were 0.857 and 0.805, and calibration slopes (model-predicted probabilities vs observed probabilities) were 0.987 and 0.979, respectively. In the external validation sample, models 1 and 2 had area under the curves of 0.841 and 0.784, respectively. These models had high discrimination in women, men, whites, and nonwhites.

Conclusion

The PLCO lung cancer risk models demonstrate high discrimination and calibration.

DNA damage is thought to play a critical role in the development of colorectal adenoma. Variation in DNA repair genes may alter their capacity to correct endogenous and exogenous DNA damage. We explored the association between common single-nucleotide polymorphisms (SNPs) in DNA repair genes and adenoma risk with a case–control study nested in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. A total of 1338 left sided, advanced colorectal adenoma cases and 1503 matched controls free of left-sided polyps were included in the study. Using DNA extracted from blood, 3144 tag SNPs in 149 DNA repair genes were successfully genotyped. Among Caucasians, 30 SNPs were associated with adenoma risk at P < 0.01, with four SNPs remaining significant after gene-based adjustment for multiple testing. The most significant finding was for a non-synonymous SNP (rs9350) in Exonuclease-1 (EXO1) [odds ratio (OR) = 1.30, 95% confidence interval (CI) = 1.11–1.51, P = 0.001)], which was predicted to be damaging using bioinformatics methods. However, the association was limited to smokers with a strong risk for current smokers (OR = 2.15, 95% CI = 1.27–3.65) and an intermediate risk for former smokers (OR = 1.45, 95% CI = 1.14–1.82) and no association for never smokers (OR = 0.98, 95% CI = 0.76–1.25) (Pinteraction = 0.002). Among the top findings, an SNP (rs17503908) in ataxia telangiectasia mutated (ATM) was inversely related to adenoma risk (OR = 0.75, 95% CI = 0.63–0.91). The association was restricted to never smokers (OR = 0.55, 95% CI = 0.40–0.76) with no increased risk observed among smokers (OR = 0.89, 95% CI = 0.70–1.13) (Pinteraction = 0.006). This large comprehensive study, which evaluated all presently known DNA repair genes, suggests that polymorphisms in EXO1 and ATM may be associated with risk for advanced colorectal adenoma with the associations modified by tobacco-smoking status.

DNA repair genes are important for maintaining genomic stability and limiting carcinogenesis. We analyzed all single nucleotide polymorphisms (SNPs) of 125 DNA repair genes covered by the Illumina HumanHap300 (v1.1) BeadChips in a previously conducted genome-wide association study (GWAS) of 1,154 lung cancer cases and 1,137 controls and replicated the top-hits of XRCC4 SNPs in an independent set of 597 cases and 611 controls in Texas populations. We found that six of 20 XRCC4 SNPs were associated with a decreased risk of lung cancer with a P value of 0.01 or lower in the discovery dataset, of which the most significant SNP was rs10040363 (P for allelic test = 4.89 ×10−4). Moreover, the data in this region allowed us to impute a potentially functional SNP rs2075685 (imputed P for allelic test = 1.3 ×10−3). A luciferase reporter assay demonstrated that the rs2075685G>T change in the XRCC4 promoter increased expression of the gene. In the replication study of rs10040363, rs1478486, rs9293329, and rs2075685, however, only rs10040363 achieved a borderline association with a decreased risk of lung cancer in a dominant model (adjusted OR = 0.80, 95% CI = 0.62–1.03, P = 0.079). In the final combined analysis of both the Texas GWAS discovery and replication datasets, the strength of the association was increased for rs10040363 (adjusted OR = 0.77, 95% CI = 0.66–0.89, Pdominant = 5×10−4 and P for trend = 5×10−4) and rs1478486 (adjusted OR = 0.82, 95% CI = 0.71 −0.94, Pdominant = 6×10−3 and P for trend = 3.5×10−3). Finally, we conducted a meta-analysis of these XRCC4 SNPs with available data from published GWA studies of lung cancer with a total of 12,312 cases and 47,921 controls, in which none of these XRCC4 SNPs was associated with lung cancer risk. It appeared that rs2075685, although associated with increased expression of a reporter gene and lung cancer risk in the Texas populations, did not have an effect on lung cancer risk in other populations. This study underscores the importance of replication using published data in larger populations.

Published genome-wide association studies (GWASs) have identified few variants in the known biological pathways involved in lung cancer etiology. To mine the possibly hidden causal single nucleotide polymorphisms (SNPs), we explored all SNPs in the extrinsic apoptosis pathway from our published GWAS dataset for 1154 lung cancer cases and 1137 cancer-free controls. In an initial association analysis of 611 tagSNPs in 41 apoptosis-related genes, we identified only 10 tagSNPs associated with lung cancer risk with a P value <10−2, including four tagSNPs in DAPK1 and three tagSNPs in TNFSF8. Unlike DAPK1 SNPs, TNFSF8 rs2181033 tagged other four predicted functional but untyped SNPs (rs776576, rs776577, rs31813148 and rs2075533) in the promoter region. Therefore, we further tested binding affinity of these four SNPs by performing the electrophoretic mobility shift assay. We found that only rs2075533T allele modified levels of nuclear proteins bound to DNA, leading to significantly decreased expression of luciferase reporter constructs by 5- to –10-fold in H1299, HeLa and HCT116 cell lines compared with the C allele. We also performed a replication study of the untyped rs2075533 in an independent Texas population but did not confirm the protective effect. We further performed a mini meta-analysis for SNPs of TNFSF8 obtained from other four published lung cancer GWASs with 12  214 cases and 47  721 controls, and we found that only rs3181366 (r2 = 0.69 with the untyped rs2075533) was associated to lung cancer risk (P = 0.008). Our findings suggest a possible role of novel TNFSF8 variants in susceptibility to lung cancer.

Genome-wide association study (GWAS) consortia and collaborations formed to detect genetic loci for common phenotypes or investigate gene-environment (G*E) interactions are increasingly common. While these consortia effectively increase sample size, phenotype heterogeneity across studies represents a major obstacle that limits successful identification of these associations. Investigators are faced with the challenge of how to harmonize previously collected phenotype data obtained using different data collection instruments which cover topics in varying degrees of detail and over diverse time frames. This process has not been described in detail. We describe here some of the strategies and pitfalls associated with combining phenotype data from varying studies. Using the Gene Environment Association Studies (GENEVA) multi-site GWAS consortium as an example, this paper provides an illustration to guide GWAS consortia through the process of phenotype harmonization and describes key issues that arise when sharing data across disparate studies. GENEVA is unusual in the diversity of disease endpoints and so the issues it faces as its participating studies share data will be informative for many collaborations. Phenotype harmonization requires identifying common phenotypes, determining the feasibility of cross-study analysis for each, preparing common definitions, and applying appropriate algorithms. Other issues to be considered include genotyping timeframes, coordination of parallel efforts by other collaborative groups, analytic approaches, and imputation of genotype data. GENEVA's harmonization efforts and policy of promoting data sharing and collaboration, not only within GENEVA but also with outside collaborations, can provide important guidance to ongoing and new consortia.

Monoclonal B cell lymphocytosis (MBL) is a hematologic condition wherein small B cell clones can be detected in the blood of asymptomatic individuals. Most MBL have an immunophenotype similar to chronic lymphocytic leukemia (CLL), and “CLL-like” MBL is a precursor to CLL. We used flow cytometry to identify MBL from unaffected members of CLL kindreds. We identified 101 MBL cases from 622 study subjects; of these, 82 individuals with MBL were further characterized. Ninety-one unique MBL clones were detected: 73 CLL-like MBL (CD5+CD20dimsIgdim), 11 atypical MBL (CD5+CD20+sIg+), and 7 CD5neg MBL (CD5negCD20+sIgneg). Extended immunophenotypic characterization of these MBL subtypes was performed, and significant differences in cell surface expression of CD23, CD49d, CD79b, and FMC-7 were observed among the groups. Markers of risk in CLL such as CD38, ZAP70, and CD49d were infrequently expressed in CLL-like MBL, but were expressed in the majority of atypical MBL. Interphase cytogenetics was performed in 35 MBL cases, and del 13q14 was most common (22/30 CLL-like MBL cases). Gene expression analysis using oligonucleotide arrays was performed on 7 CLL-like MBL, and showed activation of B cell receptor associated pathways. Our findings underscore the diversity of MBL subtypes and further clarify the relationship between MBL and other lymphoproliferative disorders.

Lung cancer is the leading cause of cancer mortality worldwide. Helicobacter pylori (H. pylori) is a risk factor for distal stomach cancer, and a few small studies have suggested that H. pylori may be a potential risk factor for lung cancer. To test this hypothesis, we conducted a study of 350 lung adenocarcinoma cases, 350 squamous cell carcinoma cases, and 700 controls nested within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (ATBC) cohort of male Finnish smokers. Controls were one-to-one matched by age and date of baseline serum draw. Using enzyme-linked immunosorbent assays to detect immunoglobulin G antibodies against H. pylori whole-cell and cytotoxin-associated gene (CagA) antigens, we calculated odds ratios (ORs) and 95% confidence intervals (95% CIs) for associations between H. pylori seropositivity and lung cancer risk using conditional logistic regression. H. pylori seropositivity was detected in 79.7% of cases and 78.5% of controls. After adjusting for pack-years and cigarettes smoked per day, H. pylori seropositivity was not associated with either adenocarcinoma (OR: 1.1, 95% CI: 0.75–1.6) or squamous cell carcinoma (OR: 1.1, 95% CI: 0.77–1.7). Results were similar for CagA-negative and CagA-positive H. pylori seropositivity. Despite earlier small studies suggesting that H. pylori may contribute to lung carcinogenesis, H. pylori seropositivity does not appear to be associated with lung cancer.

Recombination, together with mutation, is the ultimate source of genetic variation in populations. We leverage the recent mixture of people of African and European ancestry in the Americas to build a genetic map measuring the probability of crossing-over at each position in the genome, based on about 2.1 million crossovers in 30,000 unrelated African Americans. At intervals of more than three megabases it is nearly identical to a map built in Europeans. At finer scales it differs significantly, and we identify about 2,500 recombination hotspots that are active in people of West African ancestry but nearly inactive in Europeans. The probability of a crossover at these hotspots is almost fully controlled by the alleles an individual carries at PRDM9 (P<10−245). We identify a 17 base pair DNA sequence motif that is enriched in these hotspots, and is an excellent match to the predicted binding target of African-enriched alleles of PRDM9.

An important follow-up step after genetic markers are found to be associated with a disease outcome is a more detailed analysis investigating how the implicated gene or chromosomal region and an established environment risk factor interact to influence the disease risk. The standard approach to this study of gene–environment interaction considers one genetic marker at a time and therefore could misrepresent and underestimate the genetic contribution to the joint effect when one or more functional loci, some of which might not be genotyped, exist in the region and interact with the environment risk factor in a complex way. We develop a more global approach based on a Bayesian model that uses a latent genetic profile variable to capture all of the genetic variation in the entire targeted region and allows the environment effect to vary across different genetic profile categories. We also propose a resampling-based test derived from the developed Bayesian model for the detection of gene–environment interaction. Using data collected in the Environment and Genetics in Lung Cancer Etiology (EAGLE) study, we apply the Bayesian model to evaluate the joint effect of smoking intensity and genetic variants in the 15q25.1 region, which contains a cluster of nicotinic acetylcholine receptor genes and has been shown to be associated with both lung cancer and smoking behavior. We find evidence for gene–environment interaction (P-value = 0.016), with the smoking effect appearing to be stronger in subjects with a genetic profile associated with a higher lung cancer risk; the conventional test of gene–environment interaction based on the single-marker approach is far from significant.

Author Summary

Many common diseases result from a complex interplay of genetic and environmental risk factors. It is important to study the potential genetic and environmental risk factors jointly in order to achieve a better understanding of the mechanisms underlying disease development. The standard single-marker approach that studies the environmental risk factor and one genetic marker at a time could misrepresent the gene–environment interaction, as the single genetic marker might not be an appropriate surrogate for the underlying genetic functioning polymorphisms. We propose a method to look at gene–environment interaction at the gene/region level by integrating information observed on multiple genetic markers within the selected gene/region with measures of environmental exposure. Using data collected in the Environment and Genetics in Lung Cancer Etiology (EAGLE) study, we apply the proposed model to evaluate the joint effect of smoking intensity and genetic variants in the 15q25.1 region and find evidence for gene–environment interaction (P-value = 0.016), with the smoking effect varying according to a subject's genetic profile.

Recent epidemiological studies have suggested that red and processed meat may increase the risk of lung cancer. Possible underlying mechanisms include mutagens produced during high temperature cooking or preservation, or formed endogenously from heme iron in meat. We used data from 99,579 participants of both screened and non-screened arms of the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), aged 55–74 years, to investigate whether meat type, cooking method, doneness level, intake of specific meat mutagens 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx), 2-amino-3,4,8-trimethylimidazo[4,5-f]quinoxaline] (DiMeIQx), 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP), and benzo(a)pyrene (B(a)P)] and heme iron are associated with lung cancer. Participants’ diet was assessed prospectively using a 124-item food frequency questionnaire and an additional meat-cooking module. Dietary data were used in conjunction with a database to estimate intake of MeIQx, DiMeIQx, PhIP, B(a)P and heme iron. After up to 8 years of follow-up, 782 incident lung cancer cases were ascertained. Lung cancer risk was not associated with the consumption of either red (men: HRQ5vs.Q1 = 1.11, 95% CI = 0.79–1.56, Ptrend = 0.42; women: HRQ5vs.Q1 = 1.30, 95% CI = 0.87–1.95, Ptrend = 0.65) or processed meat (men: HRQ5vs.Q1 = 1.12, 95% CI = 0.83–1.53, Ptrend = 0.22; women: HRQ5vs.Q1 = 0.98, 95% CI = 0.68–1.41, Ptrend = 0.32) in multivariable models. High temperature cooking methods, level of meat doneness, meat mutagens and heme iron had no effect on lung cancer risk. In this population, we found no association between meat type, cooking method, doneness level, or intake of specific meat mutagens or heme iron and lung cancer risk.

Pathway analysis of genome-wide association studies (GWAS) offer a unique opportunity to collectively evaluate genetic variants with effects that are too small to be detected individually. We applied a pathway analysis to a bladder cancer GWAS containing data from 3,532 cases and 5,120 controls of European background (n = 5 studies). Thirteen hundred and ninety-nine pathways were drawn from five publicly available resources (Biocarta, Kegg, NCI-PID, HumanCyc, and Reactome), and we constructed 22 additional candidate pathways previously hypothesized to be related to bladder cancer. In total, 1421 pathways, 5647 genes and ∼90,000 SNPs were included in our study. Logistic regression model adjusting for age, sex, study, DNA source, and smoking status was used to assess the marginal trend effect of SNPs on bladder cancer risk. Two complementary pathway-based methods (gene-set enrichment analysis [GSEA], and adapted rank-truncated product [ARTP]) were used to assess the enrichment of association signals within each pathway. Eighteen pathways were detected by either GSEA or ARTP at P≤0.01. To minimize false positives, we used the I2 statistic to identify SNPs displaying heterogeneous effects across the five studies. After removing these SNPs, seven pathways (‘Aromatic amine metabolism’ [PGSEA = 0.0100, PARTP = 0.0020], ‘NAD biosynthesis’ [PGSEA = 0.0018, PARTP = 0.0086], ‘NAD salvage’ [PARTP = 0.0068], ‘Clathrin derived vesicle budding’ [PARTP = 0.0018], ‘Lysosome vesicle biogenesis’ [PGSEA = 0.0023, PARTP<0.00012], ’Retrograde neurotrophin signaling’ [PGSEA = 0.00840], and ‘Mitotic metaphase/anaphase transition’ [PGSEA = 0.0040]) remained. These pathways seem to belong to three fundamental cellular processes (metabolic detoxification, mitosis, and clathrin-mediated vesicles). Identification of the aromatic amine metabolism pathway provides support for the ability of this approach to identify pathways with established relevance to bladder carcinogenesis.

Introduction

Urban U.S. populations are burdened by intersecting epidemics of HIV-infection, injection drug use, and cigarette smoking. Given the substantial morbidity attributable to tobacco in these populations, we characterized smoking behaviors, nicotine addiction, and tobacco exposure among HIV-infected and HIV-uninfected injection drug users (IDUs) in Baltimore, Maryland.

Methods

Smoking behaviors among participants in the ALIVE Study were assessed using interviewer-administered questionnaires. Smoking history and nicotine dependence (Fagerstrom Index scores) were compared by HIV and drug injecting status. Serum cotinine (a nicotine metabolite) was measured for a sample of participants by enzyme immunoassay.

Results

Among 1,052 participants (29.7% HIV-infected, 39.8% active injectors), 85.2% were current smokers and 9.3% former smokers. Smoking prevalence, age at smoking initiation, and cumulative tobacco exposure were similar by HIV status. Median Fagerstrom scores of 4 for HIV-infected and HIV-uninfected smokers indicated moderate nicotine dependence. Daily cigarette consumption was identical by HIV status (median 10 cigarettes), although HIV-infected participants were less likely to smoke 1+ pack daily compared to HIV-uninfected participants (18.0% vs. 26.9%, p=0.001). Compared to former injectors, active injectors had higher smoking prevalence (90.5% vs. 81.7%, p=0.0001), greater daily cigarette consumption (30.7% vs. 19.6% smoked 1+ pack daily, p=0.0001), and slightly higher Fagerstrom scores (median 5 vs. 4). Cotinine levels paralleled self-reported cigarette consumption.

Discussion

Tobacco use is extremely common among inner city IDUs. Smoking behavior and nicotine dependence did not materially differ by HIV status but were associated with active drug injection. Cessation efforts should target the dual dependence of cigarettes and drugs experienced among this population.

Mutagen challenge and DNA repair assays have been used in case–control studies for nearly three decades to assess human cancer risk. The findings still engender controversy because blood was drawn after cancer diagnosis so the results may be biased, a type called ‘reverse causation’. We therefore used Epstein–Barr virus-transformed lymphoblastoid cell lines established from prospectively collected peripheral blood samples to evaluate lung cancer risk in relation to three DNA repair assays: alkaline Comet assay, host cell reactivation (HCR) assay with the mutagen benzo[a]pyrene diol epoxide and the bleomycin mutagen sensitivity assay. Cases (n = 117) were diagnosed with lung cancer between 0.3 and 6 years after blood collection and controls (n = 117) were frequency matched on calendar year and age at blood collection, gender and smoking history; all races were included. Case and control status was unknown to laboratory investigators. In unconditional logistic regression analyses, statistically significantly increased lung cancer odds ratios (ORadjusted) were observed for bleomycin mutagen sensitivity as quartiles of chromatid breaks/cell [relative to the lowest quartile, OR = 1.2, 95% confidence interval (CI): 0.5–2.5; OR = 1.4, 95% CI: 0.7–3.1; OR = 2.1, 95% CI: 1.0–4.4, respectively, Ptrend = 0.04]. The magnitude of the association between the bleomycin assay and lung cancer risk was modest compared with those reported in previous lung cancer studies but was strengthened when we included only incident cases diagnosed more than a year after blood collection (Ptrend = 0.02), supporting the notion the assay may be a measure of cancer susceptibility. The Comet and HCR assays were unrelated to lung cancer risk.