Abstract 2292: Lung function and lung cancer risk: a Mendelian randomization study of UK Biobank cohort and the International Lung Cancer Consortium

Background: Impaired lung function (LF) is strongly associated with increased lung cancer risk. However, since airflow obstruction is a diagnostic criterion for obstructive lung disease, and a consequence of tobacco smoking, isolating the causal relationship between LF and lung cancer has remained a challenge.

Methods: We investigated 3 standardized (mean=0, standard deviation=1) LF metrics: forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), and FEV1/FVC. To evaluate the causal relevance of LF in lung cancer etiology we conducted: i) survival analyses in the UK Biobank cohort (UKB); and ii) Mendelian Randomization (MR) analyses using genetic instrumental variables (IVs) developed in UKB and tested using individual-level data from the OncoArray, a genome-wide array with in-depth coverage for common cancers. Results: 702 incident lung cancers were diagnosed in 484,194 UKB participants during follow-up. Cox regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI), adjusted for age, sex, smoking status, socioeconomic status, and assessment center. Adjustment for other smoking metrics yielded similar results. Lung cancer risk increased per 1 unit decrease in FEV1 (HR=1.80, 95% CI: 1.64-1.98, p=3.3×10-34), FVC (HR=1.45, 1.30-1.60, p=2.3×10-12), and FEV1/FVC (HR=1.39, 1.33-1.46, p=1.3×10-38). This pattern was observed for adenocarcinoma (n=300): FEV1 (HR=1.77, p=6.0×10-12), FVC (HR=1.48, p=1.4×10-5), FEV1/FVC (HR=1.34, p=8.3×10-11); and squamous cell carcinoma (n=166): FEV1 (HR=1.97, p=9.9×10-10), FVC (HR=1.60, p=1.0×10-4), FEV1/FVC (HR=1.38, p=5.9×10-8). Next, a genome-wide association study of 67,708 UKB participants and 12.6 million variants was carried out to develop genetic IVs for LF.

Results were filtered to retain independent variants (R2<0.2) associated with each LF phenotype (p<5×10-8). The following IVs were developed: FEV1 (n=28 variants, 0.72% of variation explained), FVC (n=44, 1.08%), and FEV1/FVC (n=45, 1.85%). Odds ratios (OR) for each IV and lung cancer were estimated for 18,686 cases 15,190 controls (>80% European ancestry) from 23 studies. Effect estimates were combined using maximum-likelihood MR models to estimate causal ORs. MR results indicate that genetic scores associated with improved airflow are unrelated to lung cancer risk: FEV1 (OR=1.00, 95% CI: 0.96-1.03, p=0.86), FVC (OR=1.00, 0.97-1.03, p=0.93) and FEV1/FVC (OR=1.00, 0.91-1.10, p=0.95). The null association observed for the genetic determinants of FEV1, FVC and FEV1/FVC was not modified by tumor histology or smoking status.

Conclusions: LF is a robust predictor of lung cancer risk, however, our findings do not support the existence of causal pathways that are independent of obstructive lung disease or smoking. This apparent lack of a causal relationship should be interpreted with caution since pleiotropic effects of LF loci cannot be ruled out.

Citation Format: Linda Kachuri, Mattias Johansson, Paul Brennan, Phillip Haycock, Geoffrey Liu, Maria Teresa Landi, David C. Christiani, Neil E. Caporaso, Xifeng Wu, Melinda C. Aldrich, Demetrius Albanes, Adonina Tardón, Gad Rennert, Chu Chen, Gary E. Goodman, Jennifer A. Doherty, Heike Bickeböller, Dawn Teare, Lambertus A. Kiemeney, Stig E. Bojesen, John K. Field, Aage Haugen, Stephen Lam, Loic Le Marchand, Matthew B. Schabath, Angeline S. Andrew, Jonas Manjer, Philip Lazarus, Susanne M. Arnold, Valérie Gaborieau, Richard Martin, Caroline Relton, George Davey Smith, Christopher I. Amos, James D. McKay, Rayjean J. Hung. Lung function and lung cancer risk: a Mendelian randomization study of UK Biobank cohort and the International Lung Cancer Consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2292. doi:10.1158/1538-7445.AM2017-2292

Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes

Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer.

Menstrual and reproductive factors and lung cancer risk: A pooled analysis from the international lung cancer consortium

Many clinical features of lung cancer are different in women and men. Sex steroid hormones exert effects in nonreproductive organs, such as the lungs. The association between menstrual and childbearing factors and the risk of lung cancer among women is still debated. We performed a pooled analysis of eight studies contributing to the International Lung Cancer Consortium (4,386 cases and 4,177 controls). Pooled associations between menstrual or reproductive factors and lung cancer were estimated using multivariable unconditional logistic regression. Subgroup analyses were done for menopause status, smoking habits and histology. We found no strong support for an association of age at menarche and at menopause with lung cancer, but peri/postmenopausal women were at higher risk compared to premenopausal (OR 1.47, 95% CI 1.11-1.93). Premenopausal women showed increased risks associated with parity (OR 1.74, 95% CI 1.03-2.93) and number of children (OR 2.88, 95% CI 1.21-6.93 for more than 3 children; p for trend 0.01) and decreased with breastfeeding (OR 0.54, 95% CI 0.30-0.98). In contrast, peri/postmenopausal subjects had ORs around unity for the same exposures. No major effect modification was exerted by smoking status or cancer histology. Menstrual and reproductive factors may play a role in the genesis of lung cancer, yet the mechanisms are unclear, and smoking remains the most important modifiable risk factor. More investigations in large well-designed studies are needed to confirm these findings and to clarify the underlying mechanisms of gender differences in lung cancer risk.

Alcohol and lung cancer risk among never smokers: A pooled analysis from the international lung cancer consortium and the SYNERGY study

It is not clear whether alcohol consumption is associated with lung cancer risk. The relationship is likely confounded by smoking, complicating the interpretation of previous studies. We examined the association of alcohol consumption and lung cancer risk in a large pooled international sample, minimizing potential confounding of tobacco consumption by restricting analyses to never smokers. Our study included 22 case-control and cohort studies with a total of 2548 never-smoking lung cancer patients and 9362 never-smoking controls from North America, Europe and Asia within the International Lung Cancer Consortium (ILCCO) and SYNERGY Consortium. Alcohol consumption was categorized into amounts consumed (grams per day) and also modelled as a continuous variable using restricted cubic splines for potential non-linearity. Analyses by histologic sub-type were included. Associations by type of alcohol consumed (wine, beer and liquor) were also investigated. Alcohol consumption was inversely associated with lung cancer risk with evidence most strongly supporting lower risk for light and moderate drinkers relative to non-drinkers (>0-4.9 g per day: OR = 0.80, 95% CI = 0.70-0.90; 5-9.9 g per day: OR = 0.82, 95% CI = 0.69-0.99; 10-19.9 g per day: OR = 0.79, 95% CI = 0.65-0.96). Inverse associations were found for consumption of wine and liquor, but not beer. The results indicate that alcohol consumption is inversely associated with lung cancer risk, particularly among subjects with low to moderate consumption levels, and among wine and liquor drinkers, but not beer drinkers. Although our results should have no relevant bias from the confounding effect of smoking we cannot preclude that confounding by other factors contributed to the observed associations. Confounding in relation to the non-drinker reference category may be of particular importance.

Environmental and Occupational Exposures and Amyotrophic Lateral Sclerosis in New England

BACKGROUND

Recent data provide support for the concept that potentially modifiable exposures are responsible for sporadic amyotrophic lateral sclerosis (ALS).

OBJECTIVE

To evaluate environmental and occupational exposures as risk factors for sporadic ALS.

METHODS

We performed a case-control study of ALS among residents of New England, USA. The analysis compared questionnaire responses from 295 patients with a confirmed ALS diagnosis to those of 225 controls without neurodegenerative illness.

RESULTS

Self-reported job- or hobby-related exposure to one or more chemicals, such as pesticides, solvents, or heavy metals, increased the risk of ALS (adjusted OR 2.51; 95% CI 1.64-3.89). Industries with a higher toxicant exposure potential (construction, manufacturing, mechanical, military, or painting) were associated with an elevated occupational risk (adjusted OR 3.95; 95% CI 2.04-8.30). We also identified increases in the risk of ALS associated with frequent participation in water sports, particularly waterskiing (adjusted OR 3.89; 95% CI 1.97-8.44). Occupation and waterskiing both retained independent statistical significance in a composite model containing age, gender, and smoking status.

CONCLUSIONS

Our study contributes to a growing body of literature implicating occupational- and hobby-related toxicant exposures in ALS etiology. These epidemiologic study results also provide motivation for future evaluation of water-body-related risk factors.

Complex systems analysis of bladder cancer susceptibility reveals a role for decarboxylase activity in two genome-wide association studies

Background

Bladder cancer is common disease with a complex etiology that is likely due to many different genetic and environmental factors. The goal of this study was to embrace this complexity using a bioinformatics analysis pipeline designed to use machine learning to measure synergistic interactions between single nucleotide polymorphisms (SNPs) in two genome-wide association studies (GWAS) and then to assess their enrichment within functional groups defined by Gene Ontology. The significance of the results was evaluated using permutation testing and those results that replicated between the two GWAS data sets were reported.

Results

In the first step of our bioinformatics pipeline, we estimated the pairwise synergistic effects of SNPs on bladder cancer risk in both GWAS data sets using Multifactor Dimensionality Reduction (MDR) machine learning method that is designed specifically for this purpose. Statistical significance was assessed using a 1000-fold permutation test. Each single SNP was assigned a p-value based on its strongest pairwise association. Each SNP was then mapped to one or more genes using a window of 500 kb upstream and downstream from each gene boundary. This window was chosen to capture as many regulatory variants as possible. Using Exploratory Visual Analysis (EVA), we then carried out a gene set enrichment analysis at the gene level to identify those genes with an overabundance of significant SNPs relative to the size of their mapped regions. Each gene was assigned to a biological functional group defined by Gene Ontology (GO). We next used EVA to evaluate the overabundance of significant genes in biological functional groups. Our study yielded one GO category, carboxy-lysase activity (GO:0016831), that was significant in analyses from both GWAS data sets. Interestingly, only the gamma-glutamyl carboxylase (GGCX) gene from this GO group was significant in both the detection and replication data, highlighting the complexity of the pathway-level effects on risk. The GGCX gene is expressed in the bladder, but has not been previously associated with bladder cancer in univariate GWAS. However, there is some experimental evidence that carboxy-lysase activity might play a role in cancer and that genes in this pathway should be explored as drug targets. This study provides a genetic basis for that observation.

Conclusions

Our machine learning analysis of genetic associations in two GWAS for bladder cancer identified numerous associations with pairs of SNPs. Gene set enrichment analysis found aggregation of risk-associated SNPs in genes and significant genes in GO functional groups. This study supports a role for decarboxylase protein complexes in bladder cancer susceptibility. Previous research has implicated decarboxylases in bladder cancer etiology; however, the genes that we found to be significant in the detection and replication data are not known to have direct influence on bladder cancer, suggesting some novel hypotheses. This study highlights the need for a complex systems approach to the genetic and genomic analysis of common diseases such as cancer.

Abstract 1255: Loss of the ubiquitin protease USP18 represses KRAS mutant lung cancer tumorigenicity in mice by destabilizing KRAS protein

KRAS is frequently mutated in lung cancers. Innovative strategies are needed to combat KRAS mutant lung cancers because these tumors are often resistant to therapy. This study reports that loss of the deubiquitinase USP18 leads to destabilization of the KRAS oncogenic protein in panels of murine and human lung cancer cells. In marked contrast, engineered gain of USP18 expression using retroviral vectors introduced into the same panel of murine and human lung cancer cells stabilized KRAS protein. Loss of USP18 expression in KRAS mutant-expressing lung cancer cells inhibited their growth while gain of USP18 expression opposed this effect. We sought to identify mechanisms engaged in this KRAS protein destabilization. Intriguingly, immunoprecipitation assays established that KRAS conjugates with the ubiquitin-like protein ISG15. This leads to KRAS protein destabilization. Using the protein synthesis inhibitor cycloheximide, USP18 knockdown was shown to destabilize mutant KRAS more prominently than wild-type KRAS protein. To independently confirm that KRAS directly complexes with ISG15, site-directed mutagenesis was performed to render the C-terminal domain of KRAS lysine-less. This led to stabilization of KRAS, despite knockdown of USP18. These studies were confirmed and extended in the in vivo setting of KRAS-driven lung cancers in KRASLA2/+ mice within the FVB strain background. We crossed these mice with USP18 null (USP18-/-) mice to obtain KRASLA2/+;USP18-/- compound mice. Strikingly, these compound mice had statistically significantly (P < 0.05) reduced lung cancers as compared to parental KRASLA2/+ mice. To establish the biological importance of this finding, USP18 immunohistochemical expression was compared in these engineered mice versus a second engineered mouse lung cancer model that was not driven by KRAS, but by aberrant cyclin E expression. USP18 immunohistochemical expression was substantially higher in the KRAS-driven than cyclin E-dependent lung cancers. To explore the translational relevance of this work, lung cancer tissue arrays were examined in 551 lung cancers where a clinical database was available. USP18 immunohistochemical expression was significantly (P < 0.001) higher in KRAS mutant adenocarcinomas as compared to wild-type cases. There was also a significant increase in USP18 expression in adenocarcinoma versus squamous cell carcinoma cases. Taken together, these studies broaden the role of USP18 as an antineoplastic target to combat lung cancers that harbor KRAS mutations.

Citation Format: Lisa Maria Mustachio, Yun Lu, Laura J. Tafe, Angeline S. Andrew, Vincent Memoli, Jaime Rodriguez-Canales, Pamela A. Villalobos, Ignacio Wistuba, Jun Yu, Jack J. Lee, Fadzai Chinyengetere, David J. Sekula, Xi Liu, Sarah J. Freemantle, Ethan Dmitrovsky. Loss of the ubiquitin protease USP18 represses KRAS mutant lung cancer tumorigenicity in mice by destabilizing KRAS protein. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1255.

Detecting gene-gene interactions using a permutation-based random forest method

Background

Identifying gene-gene interactions is essential to understand disease susceptibility and to detect genetic architectures underlying complex diseases. Here, we aimed at developing a permutation-based methodology relying on a machine learning method, random forest (RF), to detect gene-gene interactions. Our approach called permuted random forest (pRF) which identified the top interacting single nucleotide polymorphism (SNP) pairs by estimating how much the power of a random forest classification model is influenced by removing pairwise interactions.

Results

We systematically tested our approach on a simulation study with datasets possessing various genetic constraints including heritability, number of SNPs, sample size, etc. Our methodology showed high success rates for detecting the interaction SNP pair. We also applied our approach to two bladder cancer datasets, which showed consistent results with well-studied methodologies, such as multifactor dimensionality reduction (MDR) and statistical epistasis network (SEN). Furthermore, we built permuted random forest networks (PRFN), in which we used nodes to represent SNPs and edges to indicate interactions.

Conclusions

We successfully developed a scale-invariant methodology to detect pure gene-gene interactions based on permutation strategies and the machine learning method random forest. This methodology showed great potential to be used for detecting gene-gene interactions to study underlying genetic architectures in a scale-free way, which could be benefit to uncover the complex disease mechanisms.

Functional dyadicity and heterophilicity of gene-gene interactions in statistical epistasis networks

BACKGROUND

The interaction effect among multiple genetic factors, i.e. epistasis, plays an important role in explaining susceptibility on common human diseases and phenotypic traits. The uncertainty over the number of genetic attributes involved in interactions poses great challenges in genetic association studies and calls for advanced bioinformatics methodologies. Network science has gained popularity in modeling genetic interactions thanks to its structural characterization of large numbers of entities and their complex relationships. However, little has been done on functionally interpreting statistically inferred epistatic interactions using networks.

RESULTS

In this study, we propose to characterize gene functional properties in the context of interaction network structure. We used Gene Ontology (GO) to functionally annotate genes as vertices in a statistical epistasis network, and quantitatively characterize the correlation between the distribution of gene functional properties and the network structure by measuring dyadicity and heterophilicity of each functional category in the network. These two parameters quantify whether genetic interactions tend to occur more frequently for genes from the same functional category, i.e. dyadic effect, or more frequently for genes from across different functional categories, i.e. heterophilic effect.

CONCLUSIONS

By applying this framework to a population-based bladder cancer dataset, we were able to identify several GO categories that have significant dyadicity or heterophilicity associated with bladder cancer susceptibility. Thus, our informatics framework suggests a new methodology for embedding functional analysis in network modeling of statistical epistasis in genetic association studies.

Expression of tumor suppressive microRNA-34a is associated with a reduced risk of bladder cancer recurrence

Bladder cancer is the fourth most common cancer among men in the United States and more than half of patients experience recurrences within 5 years after initial diagnosis. Additional clinically informative and actionable biomarkers of the recurrent bladder cancer phenotypes are needed to improve screening and molecular therapeutic approaches for recurrence prevention. MicroRNA-34a (miR-34a) is a short noncoding regulatory RNA with tumor suppressive attributes. We leveraged our unique, large, population-based prognostic study of bladder cancer in New Hampshire, United States to evaluate miR-34a expression levels in individual tumor cells to assess prognostic value. We collected detailed exposure and medical history data, as well as tumor tissue specimens from bladder patients and followed them long-term for recurrence, progression and survival. Fluorescence-based in situ hybridization assays were performed on urothelial carcinoma tissue specimens (n = 229). A larger proportion of the nonmuscle invasive tumors had high levels of miR-34a within the carcinoma cells compared to those tumors that were muscle invasive. Patients with high miR-34a levels in their baseline nonmuscle invasive tumors experienced lower risks of recurrence (adjusted hazard ratio 0.57, 95% confidence interval 0.34-0.93). Consistent with these observations, we demonstrated a functional tumor suppressive role for miR-34a in cultured urothelial cells, including reduced matrigel invasion and growth in soft agar. Our results highlight the need for further clinical studies of miR-34a as a guide for recurrence screening and as a possible candidate therapeutic target in the bladder.

CHRNA5 risk variant predicts delayed smoking cessation and earlier lung cancer diagnosis--a meta-analysis

BACKGROUND

Recent meta-analyses show strong evidence of associations among genetic variants in CHRNA5 on chromosome 15q25, smoking quantity, and lung cancer. This meta-analysis tests whether the CHRNA5 variant rs16969968 predicts age of smoking cessation and age of lung cancer diagnosis.

METHODS

Meta-analyses examined associations between rs16969968, age of quitting smoking, and age of lung cancer diagnosis in 24 studies of European ancestry (n = 29 072). In each dataset, we used Cox regression models to evaluate the association between rs16969968 and the two primary phenotypes (age of smoking cessation among ever smokers and age of lung cancer diagnosis among lung cancer case patients) and the secondary phenotype of smoking duration. Heterogeneity across studies was assessed with the Cochran Q test. All statistical tests were two-sided.

RESULTS

The rs16969968 allele (A) was associated with a lower likelihood of smoking cessation (hazard ratio [HR] = 0.95, 95% confidence interval [CI] = 0.91 to 0.98, P = .0042), and the AA genotype was associated with a four-year delay in median age of quitting compared with the GG genotype. Among smokers with lung cancer diagnoses, the rs16969968 genotype (AA) was associated with a four-year earlier median age of diagnosis compared with the low-risk genotype (GG) (HR = 1.08, 95% CI = 1.04 to 1.12, P = 1.1*10(-5)).

CONCLUSION

These data support the clinical significance of the CHRNA5 variant rs16969968. It predicts delayed smoking cessation and an earlier age of lung cancer diagnosis in this meta-analysis. Given the existing evidence that this CHRNA5 variant predicts favorable response to cessation pharmacotherapy, these findings underscore the potential clinical and public health importance of rs16969968 in CHRNA5 in relation to smoking cessation success and lung cancer risk.

CDK2 Inhibition Causes Anaphase Catastrophe in Lung Cancer through the Centrosomal Protein CP110

Aneuploidy is frequently detected in human cancers and is implicated in carcinogenesis. Pharmacologic targeting of aneuploidy is an attractive therapeutic strategy, as this would preferentially eliminate malignant over normal cells. We previously discovered that CDK2 inhibition causes lung cancer cells with more than two centrosomes to undergo multipolar cell division leading to apoptosis, defined as anaphase catastrophe. Cells with activating KRAS mutations were especially sensitive to CDK2 inhibition. Mechanisms of CDK2-mediated anaphase catastrophe and how activated KRAS enhances this effect were investigated. Live-cell imaging provided direct evidence that following CDK2 inhibition, lung cancer cells develop multipolar anaphase and undergo multipolar cell division with the resulting progeny apoptotic. The siRNA-mediated repression of the CDK2 target and centrosome protein CP110 induced anaphase catastrophe of lung cancer cells. In contrast, CP110 overexpression antagonized CDK2 inhibitor-mediated anaphase catastrophe. Furthermore, activated KRAS mutations sensitized lung cancer cells to CDK2 inhibition by deregulating CP110 expression. Thus, CP110 is a critical mediator of CDK2 inhibition-driven anaphase catastrophe. Independent examination of murine and human paired normal-malignant lung tissues revealed marked upregulation of CP110 in malignant versus normal lung. Human lung cancers with KRAS mutations had significantly lower CP110 expression as compared with KRAS wild-type cancers. Thus, a direct link was found between CP110 and CDK2 inhibitor antineoplastic response. CP110 plays a mechanistic role in response of lung cancer cells to CDK2 inhibition, especially in the presence of activated KRAS mutations.

Genetic polymorphisms modify bladder cancer recurrence and survival in a USA population-based prognostic study

OBJECTIVE

To identify genetic variants that modify bladder cancer prognosis focusing on genes involved in major biological carcinogenesis processes (apoptosis, proliferation, DNA repair, hormone regulation, immune surveillance, and cellular metabolism), as nearly half of patients with bladder cancer experience recurrences reliable predictors of this recurrent phenotype are needed to guide surveillance and treatment.

PATIENTS AND METHODS

We analysed variant genotypes hypothesised to modify these processes in 563 patients with urothelial-cell carcinoma enrolled in a population-based study of incident bladder cancer conducted in New Hampshire, USA. After diagnosis, patients were followed over time to ascertain recurrence and survival status, making this one of the first population-based studies with detailed prognosis data. Cox proportional hazards regression was used to assess the relationship between single nucleotide polymorphisms (SNPs) and prognosis endpoints.

RESULTS

Patients with aldehyde dehydrogenase 2 (ALDH2) variants had a shorter time to first recurrence (adjusted non-invasive hazard ratio [HR] 1.90, 95% confidence interval [CI] 1.29-2.78). There was longer survival among patients with non-invasive tumours associated with DNA repair X-ray repair cross-complementing protein 4 (XRCC4) heterozygous genotype compared with wild-type (adjusted HR 0.53, 95% CI 0.38-0.74). Time to recurrence was shorter for patients who had a variant allele in vascular cellular adhesion molecule 1 (VCAM1) and were treated with immunotherapy (P interaction < 0.001).

CONCLUSIONS

Our analysis suggests candidate prognostic SNPs that could guide personalised bladder cancer surveillance and treatment.

A screening-testing approach for detecting gene-environment interactions using sequential penalized and unpenalized multiple logistic regression

Gene-environment (G × E) interactions are biologically important for a wide range of environmental exposures and clinical outcomes. Because of the large number of potential interactions in genomewide association data, the standard approach fits one model per G × E interaction with multiple hypothesis correction (MHC) used to control the type I error rate. Although sometimes effective, using one model per candidate G × E interaction test has two important limitations: low power due to MHC and omitted variable bias. To avoid the coefficient estimation bias associated with independent models, researchers have used penalized regression methods to jointly test all main effects and interactions in a single regression model. Although penalized regression supports joint analysis of all interactions, can be used with hierarchical constraints, and offers excellent predictive performance, it cannot assess the statistical significance of G × E interactions or compute meaningful estimates of effect size. To address the challenge of low power, researchers have separately explored screening-testing, or two-stage, methods in which the set of potential G × E interactions is first filtered and then tested for interactions with MHC only applied to the tests actually performed in the second stage. Although two-stage methods are statistically valid and effective at improving power, they still test multiple separate models and so are impacted by MHC and biased coefficient estimation. To remedy the challenges of both poor power and omitted variable bias encountered with traditional G × E interaction detection methods, we propose a novel approach that combines elements of screening-testing and hierarchical penalized regression. Specifically, our proposed method uses, in the first stage, an elastic net-penalized multiple logistic regression model to jointly estimate either the marginal association filter statistic or the gene-environment correlation filter statistic for all candidate genetic markers. In the second stage, a single multiple logistic regression model is used to jointly assess marginal terms and G × E interactions for all genetic markers that pass the first stage filter. A single likelihood-ratio test is used to determine whether any of the interactions are statistically significant. We demonstrate the efficacy of our method relative to alternative G × E detection methods on a bladder cancer data set.

Abstract 1274: Alcohol and lung cancer risk: a pooled analysis using International Lung Cancer Consortium studies

Background: Alcohol consumption is known to be associated with risk of developing several cancers. It is unclear, however, whether alcohol consumption is a risk factor for lung cancer. The relationship between lung cancer and alcohol consumption is likely to be confounded by smoking. To minimize potential confounding by tobacco consumption, we conducted a pooled analysis to examine the association of alcohol consumption with lung cancer risk in a large sample of never-smokers.

Methods: We pooled data from 22 case-control and cohort studies from North America, Europe and Asia within the International Lung Cancer Consortium (ILCCO) and SYNERGY Consortium. We examined the association of average lifetime alcohol consumption (expressed as average grams per day intake) with lung cancer risk in never smokers using logistic regression to model categories of alcohol consumption (0&lt;5g per day, 5&lt;10g per day, 10&lt;20g per day, 20&lt;30g per day, 30&lt;45g per day, 45+ g per day). To investigate the shape of the dose response relationship, we applied restricted cubic spline models to examine the association for lung cancer risk overall and by histological subtype. Additional analyses examined wine, beer and liquor consumption in relation to risk, with mutual adjustment for each alcoholic beverage. All analyses were adjusted for age, sex, education, ethnicity and study.

Results: A total of 2548 never-smoking cases and 9362 never-smoking controls were included in the analysis. The results showed lower risk among consumers of alcohol with strongest evidence found for moderate drinkers relative to non-drinkers with ORs of 0.80 (95% CI 0.70-0.90) and 0.82 (95% CI 0.69-0.99) for &lt;5grams and 5-10 grams of alcohol per day respectively. Non-linear restricted cubic splines showed reduced lung cancer risk among moderate drinkers relative to non-drinkers with risk increasing towards the null as consumption increased. Similar results were seen for adenocarcinoma and squamous cell carcinoma. Associations with lung cancer differed for wine and beer consumption. Reduced risk was observed for wine drinking particularly at low levels of drinking, OR of 0.80 (95% CI=0.69-0.94) for &lt;5g per day. Risk for beer consumption increased from close to null among occasional drinkers to 1.54 (95% CI 0.90-2.65) among consumers of 20-30g of alcohol per day (test for trend P=0.09).

Conclusions: These results indicate an inverse association between moderate drinking and lung cancer risk relative to never drinkers. However, the inverse association was restricted to wine consumption, not consumption of beer. Lifestyle differences between consumers of beer and wine may play a role in differing patterns of risk found by alcohol type.

Citation Format: Gordon Fehringer, Darren Brenner, Zuo-Feng Zhang, Yuan-Chin Amy Lee, Keitaro Matsuo, Isabelle Stucker, Paolo Vineis, Paolo Boffetta, Paul Brennan, Maria T. Landi, Hal Morgenstern, Curtis C. Harris, Qing Lan, Yun-Chul Hong, Jack Siemiatycki, John R. McLaughlin, Philip Lazarus, Joshua Muscat, Ann G. Schwartz, Juan M. Barros Dios, Alberto R. Raviña, Gad Rennert, David C. Christiani, Adonina Tardon, Loic Le Marchand, Irene Orlow, Eric J. Duell, Angeline S. Andrew, Hermann Brenner, Dario Consonni, Ann Olsson, Kurt Straif, Rayjean J. Hung. Alcohol and lung cancer risk: a pooled analysis using International Lung Cancer Consortium studies. [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 1274. doi:10.1158/1538-7445.AM2014-1274

Abstract 4549: CDK2 inhibition causes anaphase catastrophe through the centrosomal protein CP110

Aneuploidy is frequently detected in human cancers and is implicated in carcinogenesis. Whether aneuploidy is an anti-neoplastic target remains to be learnt. We previously uncovered an unrecognized consequence of Cdk2 inhibition that causes lung cancer cells to undergo anaphase catastrophe, growth inhibition and apoptosis. Cells with activating KRAS mutations were especially sensitive to Cdk2 inhibition. The mechanism of Cdk2-mediated anaphase catastrophe and how activated KRAS promotes this effect was the subject of this study. Live-cell imaging provided direct evidence that after Cdk2 inhibition, lung cancer cells develop multipolar anaphase, undergo multipolar cell division, and the fate of the progeny of these divisions is apoptosis and death. The centrosomal protein CP110, a Cdk2 target protein, was found to be a critical mediator of Cdk2-inhibition-driven anaphase catastrophe. Intriguingly, siRNA-mediated CP110 repression induced anaphase catastrophe of lung cancer cells. By contrast, overexpression of CP110 antagonized anaphase catastrophe caused by Cdk2 inhibition. Furthermore, we found that activated KRAS mutations sensitized lung cancer cells to Cdk2 inhibition by deregulating CP110 expression. Immunohistochemical examination of a paired normal-malignant lung cancer tissue array revealed a statistically significant upregulation of CP110 in lung cancers as compared with normal lung tissues. Notably, CP110 expression was reduced in smokers where KRAS mutations are frequently present. Taken together, this study presents a CP110-dependent pathway that engages anaphase catastrophe in lung cancer cells. It also provides a mechanistic explanation that lung cancers and potentially other cancers with activated KRAS mutation are more sensitive to Cdk2 inhibition due to CP110 deregulation.

Citation Format: Shanhu Hu, Alexey V. Danilov, Kristina M. Godek, Bernardo Orr, Laura J. Tafe, Vincent A. Memoli, Fabrizio Galimberti, Saranya Ravi, Andrew J. DeCastro, Yun Lu, Lisa Maria Mustachio, David J. Sekula, Angeline S. Andrew, Sarah J. Freemantle, Duane A. Compton, Ethan Dmitrovsky. CDK2 inhibition causes anaphase catastrophe through the centrosomal protein CP110. [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 4549. doi:10.1158/1538-7445.AM2014-4549

Functional genomics annotation of a statistical epistasis network associated with bladder cancer susceptibility

BACKGROUND

Several different genetic and environmental factors have been identified as independent risk factors for bladder cancer in population-based studies. Recent studies have turned to understanding the role of gene-gene and gene-environment interactions in determining risk. We previously developed the bioinformatics framework of statistical epistasis networks (SEN) to characterize the global structure of interacting genetic factors associated with a particular disease or clinical outcome. By applying SEN to a population-based study of bladder cancer among Caucasians in New Hampshire, we were able to identify a set of connected genetic factors with strong and significant interaction effects on bladder cancer susceptibility.

FINDINGS

To support our statistical findings using networks, in the present study, we performed pathway enrichment analyses on the set of genes identified using SEN, and found that they are associated with the carcinogen benzo[a]pyrene, a component of tobacco smoke. We further carried out an mRNA expression microarray experiment to validate statistical genetic interactions, and to determine if the set of genes identified in the SEN were differentially expressed in a normal bladder cell line and a bladder cancer cell line in the presence or absence of benzo[a]pyrene. Significant nonrandom sets of genes from the SEN were found to be differentially expressed in response to benzo[a]pyrene in both the normal bladder cells and the bladder cancer cells. In addition, the patterns of gene expression were significantly different between these two cell types.

CONCLUSIONS

The enrichment analyses and the gene expression microarray results support the idea that SEN analysis of bladder in population-based studies is able to identify biologically meaningful statistical patterns. These results bring us a step closer to a systems genetic approach to understanding cancer susceptibility that integrates population and laboratory-based studies.

Exposure to secondhand tobacco smoke and lung cancer by histological type: a pooled analysis of the International Lung Cancer Consortium (ILCCO)

While the association between exposure to secondhand smoke and lung cancer risk is well established, few studies with sufficient power have examined the association by histological type. In this study, we evaluated the secondhand smoke-lung cancer relationship by histological type based on pooled data from 18 case-control studies in the International Lung Cancer Consortium (ILCCO), including 2,504 cases and 7,276 control who were never smokers and 10,184 cases and 7,176 controls who were ever smokers. We used multivariable logistic regression, adjusting for age, sex, race/ethnicity, smoking status, pack-years of smoking, and study. Among never smokers, the odds ratios (OR) comparing those ever exposed to secondhand smoke with those never exposed were 1.31 (95% CI: 1.17-1.45) for all histological types combined, 1.26 (95% CI: 1.10-1.44) for adenocarcinoma, 1.41 (95% CI: 0.99-1.99) for squamous cell carcinoma, 1.48 (95% CI: 0.89-2.45) for large cell lung cancer, and 3.09 (95% CI: 1.62-5.89) for small cell lung cancer. The estimated association with secondhand smoke exposure was greater for small cell lung cancer than for nonsmall cell lung cancers (OR=2.11, 95% CI: 1.11-4.04). This analysis is the largest to date investigating the relation between exposure to secondhand smoke and lung cancer. Our study provides more precise estimates of the impact of secondhand smoke on the major histological types of lung cancer, indicates the association with secondhand smoke is stronger for small cell lung cancer than for the other histological types, and suggests the importance of intervention against exposure to secondhand smoke in lung cancer prevention.

A system-level pathway-phenotype association analysis using synthetic feature random forest

As the cost of genome-wide genotyping decreases, the number of genome-wide association studies (GWAS) has increased considerably. However, the transition from GWAS findings to the underlying biology of various phenotypes remains challenging. As a result, due to its system-level interpretability, pathway analysis has become a popular tool for gaining insights on the underlying biology from high-throughput genetic association data. In pathway analyses, gene sets representing particular biological processes are tested for significant associations with a given phenotype. Most existing pathway analysis approaches rely on single-marker statistics and assume that pathways are independent of each other. As biological systems are driven by complex biomolecular interactions, embracing the complex relationships between single-nucleotide polymorphisms (SNPs) and pathways needs to be addressed. To incorporate the complexity of gene-gene interactions and pathway-pathway relationships, we propose a system-level pathway analysis approach, synthetic feature random forest (SF-RF), which is designed to detect pathway-phenotype associations without making assumptions about the relationships among SNPs or pathways. In our approach, the genotypes of SNPs in a particular pathway are aggregated into a synthetic feature representing that pathway via Random Forest (RF). Multiple synthetic features are analyzed using RF simultaneously and the significance of a synthetic feature indicates the significance of the corresponding pathway. We further complement SF-RF with pathway-based Statistical Epistasis Network (SEN) analysis that evaluates interactions among pathways. By investigating the pathway SEN, we hope to gain additional insights into the genetic mechanisms contributing to the pathway-phenotype association. We apply SF-RF to a population-based genetic study of bladder cancer and further investigate the mechanisms that help explain the pathway-phenotype associations using SEN. The bladder cancer associated pathways we found are both consistent with existing biological knowledge and reveal novel and plausible hypotheses for future biological validations.

Distinct patterns of DNA methylation in conventional adenomas involving the right and left colon

Recent studies have shown two distinct non-CIMP methylation clusters in colorectal cancer, raising the possibility that DNA methylation, involving non-CIMP genes, may play a role in the conventional adenoma-carcinoma pathway. A total of 135 adenomas (65 left colon and 70 right colon) were profiled for epigenome-wide DNA methylation using the Illumina HumanMethylation450 BeadChip. A principal components analysis was performed to examine the association between variability in DNA methylation and adenoma location. Linear regression and linear mixed effects models were used to identify locus-specific differential DNA methylation in adenomas of right and left colon. A significant association was present between the first principal component and adenoma location (P=0.007), even after adjustment for subject age and gender (P=0.009). A total of 168 CpG sites were differentially methylated between right- and left-colon adenomas and these loci demonstrated enrichment of homeobox genes (P=3.0 × 10(-12)). None of the 168 probes were associated with CIMP genes. Among CpG loci with the largest difference in methylation between right- and left-colon adenomas, probes associated with PRAC (prostate cancer susceptibility candidate) gene showed hypermethylation in right-colon adenomas whereas those associated with CDX2 (caudal type homeobox transcription factor 2) showed hypermethylation in left-colon adenomas. A subgroup of left-colon adenomas enriched for current smokers (OR=6.1, P=0.004) exhibited a methylation profile similar to right-colon adenomas. In summary, our results indicate distinct patterns of DNA methylation, independent of CIMP genes, in adenomas of the right and left colon.

Enabling personal genomics with an explicit test of epistasis

One goal of personal genomics is to use information about genomic variation to predict who is at risk for various common diseases. Technological advances in genotyping have spawned several personal genetic testing services that market genotyping services directly to the consumer. An important goal of consumer genetic testing is to provide health information along with the genotyping results. This has the potential to integrate detailed personal genetic and genomic information into healthcare decision making. Despite the potential importance of these advances, there are some important limitations. One concern is that much of the literature that is used to formulate personal genetics reports is based on genetic association studies that consider each genetic variant independently of the others. It is our working hypothesis that the true value of personal genomics will only be realized when the complexity of the genotype-to-phenotype mapping relationship is embraced, rather than ignored. We focus here on complexity in genetic architecture due to epistasis or nonlinear gene-gene interaction. We have previously developed a multifactor dimensionality reduction (MDR) algorithm and software package for detecting nonlinear interactions in genetic association studies. In most prior MDR analyses, the permutation testing strategy used to assess statistical significance was unable to differentiate MDR models that captured only interaction effects from those that also detected independent main effects. Statistical interpretation of MDR models required post-hoc analysis using entropy-based measures of interaction information. We introduce here a novel permutation test that allows the effects of nonlinear interactions between multiple genetic variants to be specifically tested in a manner that is not confounded by linear additive effects. We show using simulated nonlinear interactions that the power using the explicit test of epistasis is no different than a standard permutation test. We also show that the test has the appropriate size or type I error rate of approximately 0.05. We then apply MDR with the new explicit test of epistasis to a large genetic study of bladder cancer and show that a previously reported nonlinear interaction between is indeed significant, even after considering the strong additive effect of smoking in the model. Finally, we evaluated the power of the explicit test of epistasis to detect the nonlinear interaction between two XPD gene polymorphisms by simulating data from the MDR model of bladder cancer susceptibility. The results of this study provide for the first time a simple method for explicitly testing epistasis or gene-gene interaction effects in genetic association studies. Although we demonstrated the method with MDR, an important advantage is that it can be combined with any modeling approach. The explicit test of epistasis brings us a step closer to the type of routine gene-gene interaction analysis that is needed if we are to enable personal genomics.

Body mass and smoking are modifiable risk factors for recurrent bladder cancer

BACKGROUND

In the Western world, bladder cancer is the fourth most common cancer in men and the eighth most common in women. Recurrences frequently occur, and continued surveillance is necessary to identify and treat recurrent tumors. Efforts to identify risk factors that are potentially modifiable to reduce the rate of recurrence are needed.

METHODS

Cigarette smoking behavior and body mass index were investigated at diagnosis for associations with bladder cancer recurrence in a population-based study of 726 patients with bladder cancer in New Hampshire, United States. Patients diagnosed with non-muscle invasive urothelial cell carcinoma were followed to ascertain long-term prognosis. Analysis of time to recurrence was performed using multivariate Cox regression models.

RESULTS

Smokers experienced shorter time to recurrence (continuing smoker hazard ratio [HR] = 1.51, 95% confidence interval [CI] = 1.08-2.13). Although being overweight (body mass index > 24.9 kg/m(2) ) at diagnosis was not a strong independent factor (HR = 1.33, 95% CI = 0.94-1.89), among continuing smokers, being overweight more than doubled the risk of recurrence compared to smokers of normal weight (HR = 2.67, 95% CI = 1.14-6.28).

CONCLUSIONS

These observational results suggest that adiposity is a risk factor for bladder cancer recurrence, particularly among tobacco users. Future intervention studies are warranted to evaluate whether both smoking cessation and weight reduction strategies reduce bladder tumor recurrences.

Hormone use and risk for lung cancer: a pooled analysis from the International Lung Cancer Consortium (ILCCO)

BACKGROUND

The association between oral contraceptive (OC) use, hormone replacement therapy (HRT) and lung cancer risk in women is still debated.

METHODS

We performed a pooled analysis of six case-control studies (1961 cases and 2609 controls) contributing to the International Lung Cancer Consortium. Potential associations were investigated with multivariable unconditional logistic regression and meta-analytic models. Multinomial logistic regressions were performed to investigate lung cancer risk across histologic types.

RESULTS

A reduced lung cancer risk was found for OC (odds ratio (OR)=0.81; 95% confidence interval (CI): 0.68-0.97) and HRT ever users (OR=0.77; 95% CI: 0.66-0.90). Both oestrogen only and oestrogen+progestin HRT were associated with decreased risk (OR=0.76; 95% CI: 0.61-0.94, and OR=0.66; 95% CI: 0.49-0.88, respectively). No dose-response relationship was observed with years of OC/HRT use. The greatest risk reduction was seen for squamous cell carcinoma (OR=0.53; 95% CI: 0.37-0.76) in OC users and in both adenocarcinoma (OR=0.79; 95% CI: 0.66-0.95) and small cell carcinoma (OR=0.37; 95% CI: 0.19-0.71) in HRT users. No interaction with smoking status or BMI was observed.

CONCLUSION

Our findings suggest that exogenous hormones can play a protective role in lung cancer aetiology. However, given inconsistencies with epidemiological evidence from cohort studies, further and larger investigations are needed for a more comprehensive view of lung cancer development in women.

Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: a learning classifier system approach

BACKGROUND AND OBJECTIVE

Detecting complex patterns of association between genetic or environmental risk factors and disease risk has become an important target for epidemiological research. In particular, strategies that provide multifactor interactions or heterogeneous patterns of association can offer new insights into association studies for which traditional analytic tools have had limited success.

MATERIALS AND METHODS

To concurrently examine these phenomena, previous work has successfully considered the application of learning classifier systems (LCSs), a flexible class of evolutionary algorithms that distributes learned associations over a population of rules. Subsequent work dealt with the inherent problems of knowledge discovery and interpretation within these algorithms, allowing for the characterization of heterogeneous patterns of association. Whereas these previous advancements were evaluated using complex simulation studies, this study applied these collective works to a 'real-world' genetic epidemiology study of bladder cancer susceptibility.

RESULTS AND DISCUSSION

We replicated the identification of previously characterized factors that modify bladder cancer risk--namely, single nucleotide polymorphisms from a DNA repair gene, and smoking. Furthermore, we identified potentially heterogeneous groups of subjects characterized by distinct patterns of association. Cox proportional hazard models comparing clinical outcome variables between the cases of the two largest groups yielded a significant, meaningful difference in survival time in years (survivorship). A marginally significant difference in recurrence time was also noted. These results support the hypothesis that an LCS approach can offer greater insight into complex patterns of association.

CONCLUSIONS

This methodology appears to be well suited to the dissection of disease heterogeneity, a key component in the advancement of personalized medicine.

Polymorphisms in the XRCC1 gene modify survival of bladder cancer patients treated with chemotherapy

Survival of bladder cancer patients depends on several factors including disease stage and grade at diagnosis, age, health status of the patient and the applied treatment. Several studies investigated the role of DNA repair genetic variants in cancer susceptibility, but only few studies investigated their role in survival and response to chemotherapy for bladder cancer. We genotyped 28 single nucleotide polymorphisms (SNP) in DNA repair genes in 456 bladder cancer patients, reconstructed haplotypes and calculated a score for combinations of the SNPs. We estimated Hazard Ratios (adjHR) for time to death. Among patients treated with chemotherapy, variant alleles of five SNPs in the XRCC1 gene conferred better survival (rs915927 adjHR 0.55 (95%CI 0.32-0.94); rs76507 adjHR 0.48 (95%CI 0.27-0.84); rs2854501 adjHR 0.25 (95%CI 0.12-0.52); rs2854509 adjHR 0.21 (95%CI 0.09-0.46); rs3213255 adjHR 0.46 (95%CI 0.26-0.80). In this group of patients, an increasing number of variant alleles in a XRCC1 gene score were associated with a better survival (26% decrease of risk of death for each additional variant allele in XRCC1). By functional analyses we demonstrated that the previous XRCC1 SNPs confer lower DNA repair capacity. This may support the hypothesis that survival in these patients may be modulated by the different DNA repair capacity determined by genetic variants. Chemotherapy treated cancer patients bearing an increasing number of "risky" alleles in XRCC1 gene had a better survival, suggesting that a proficient DNA repair may result in resistance to therapy and shorter survival. This finding may have clinical implications for the choice of therapy.

Statistical epistasis networks reduce the computational complexity of searching three-locus genetic models

The rapid development of sequencing technologies makes thousands to millions of genetic attributes available for testing associations with various biological traits. Searching this enormous high-dimensional data space imposes a great computational challenge in genome-wide association studies. We introduce a network-based approach to supervise the search for three-locus models of disease susceptibility. Such statistical epistasis networks (SEN) are built using strong pairwise epistatic interactions and provide a global interaction map to search for higher-order interactions by prioritizing genetic attributes clustered together in the networks. Applying this approach to a population-based bladder cancer dataset, we found a high susceptibility three-way model of genetic variations in DNA repair and immune regulation pathways, which holds great potential for studying the etiology of bladder cancer with further biological validations. We demonstrate that our SEN-supervised search is able to find a small subset of three-locus models with significantly high associations at a substantially reduced computational cost.

HSD3B and gene-gene interactions in a pathway-based analysis of genetic susceptibility to bladder cancer

Bladder cancer is the 4(th) most common cancer among men in the U.S. We analyzed variant genotypes hypothesized to modify major biological processes involved in bladder carcinogenesis, including hormone regulation, apoptosis, DNA repair, immune surveillance, metabolism, proliferation, and telomere maintenance. Logistic regression was used to assess the relationship between genetic variation affecting these processes and susceptibility in 563 genotyped urothelial cell carcinoma cases and 863 controls enrolled in a case-control study of incident bladder cancer conducted in New Hampshire, U.S. We evaluated gene-gene interactions using Multifactor Dimensionality Reduction (MDR) and Statistical Epistasis Network analysis. The 3'UTR flanking variant form of the hormone regulation gene HSD3B2 was associated with increased bladder cancer risk in the New Hampshire population (adjusted OR 1.85 95%CI 1.31-2.62). This finding was successfully replicated in the Texas Bladder Cancer Study with 957 controls, 497 cases (adjusted OR 3.66 95%CI 1.06-12.63). The effect of this prevalent SNP was stronger among males (OR 2.13 95%CI 1.40-3.25) than females (OR 1.56 95%CI 0.83-2.95), (SNP-gender interaction P = 0.048). We also identified a SNP-SNP interaction between T-cell activation related genes GATA3 and CD81 (interaction P = 0.0003). The fact that bladder cancer incidence is 3-4 times higher in males suggests the involvement of hormone levels. This biologic process-based analysis suggests candidate susceptibility markers and supports the theory that disrupted hormone regulation plays a role in bladder carcinogenesis.

Previous lung diseases and lung cancer risk: a pooled analysis from the International Lung Cancer Consortium

To clarify the role of previous lung diseases (chronic bronchitis, emphysema, pneumonia, and tuberculosis) in the development of lung cancer, the authors conducted a pooled analysis of studies in the International Lung Cancer Consortium. Seventeen studies including 24,607 cases and 81,829 controls (noncases), mainly conducted in Europe and North America, were included (1984-2011). Using self-reported data on previous diagnoses of lung diseases, the authors derived study-specific effect estimates by means of logistic regression models or Cox proportional hazards models adjusted for age, sex, and cumulative tobacco smoking. Estimates were pooled using random-effects models. Analyses stratified by smoking status and histology were also conducted. A history of emphysema conferred a 2.44-fold increased risk of lung cancer (95% confidence interval (CI): 1.64, 3.62 (16 studies)). A history of chronic bronchitis conferred a relative risk of 1.47 (95% CI: 1.29, 1.68 (13 studies)). Tuberculosis (relative risk = 1.48, 95% CI: 1.17, 1.87 (16 studies)) and pneumonia (relative risk = 1.57, 95% CI: 1.22, 2.01 (12 studies)) were also associated with lung cancer risk. Among never smokers, elevated risks were observed for emphysema, pneumonia, and tuberculosis. These results suggest that previous lung diseases influence lung cancer risk independently of tobacco use and that these diseases are important for assessing individual risk.

Increased risk of lung cancer in individuals with a family history of the disease: a pooled analysis from the International Lung Cancer Consortium

BACKGROUND AND METHODS

Familial aggregation of lung cancer exists after accounting for cigarette smoking. However, the extent to which family history affects risk by smoking status, histology, relative type and ethnicity is not well described. This pooled analysis included 24 case-control studies in the International Lung Cancer Consortium. Each study collected age of onset/interview, gender, race/ethnicity, cigarette smoking, histology and first-degree family history of lung cancer. Data from 24,380 lung cancer cases and 23,305 healthy controls were analysed. Unconditional logistic regression models and generalised estimating equations were used to estimate odds ratios and 95% confidence intervals.

RESULTS

Individuals with a first-degree relative with lung cancer had a 1.51-fold increase in the risk of lung cancer, after adjustment for smoking and other potential confounders (95% CI: 1.39, 1.63). The association was strongest for those with a family history in a sibling, after adjustment (odds ratios (OR) = 1.82, 95% CI: 1.62, 2.05). No modifying effect by histologic type was found. Never smokers showed a lower association with positive familial history of lung cancer (OR = 1.25, 95% CI: 1.03, 1.52), slightly stronger for those with an affected sibling (OR = 1.44, 95% CI: 1.07, 1.93), after adjustment.

CONCLUSIONS

The occurrence of lung cancer among never smokers and similar magnitudes of the effect of family history on lung cancer risk across histological types suggests familial aggregation of lung cancer is independent of those risks associated with cigarette smoking. While the role of genetic variation in the aetiology of lung cancer remains to be fully characterised, family history assessment is immediately available and those with a positive history represent a higher risk group.

Response to inhibition of smoothened in diverse epithelial cancer cells that lack smoothened or patched 1 mutations

Hedgehog (HH) pathway Smoothened (Smo) inhibitors are active against Gorlin syndrome-associated basal cell carcinoma (BCC) and medulloblastoma where Patched (Ptch) mutations occur. We interrogated 705 epithelial cancer cell lines for growth response to the Smo inhibitor cyclopamine and for expressed HH pathway-regulated species in a linked genetic database. Ptch and Smo mutations that respectively conferred Smo inhibitor response or resistance were undetected. Previous studies revealed HH pathway activation in lung cancers. Therefore, findings were validated using lung cancer cell lines, transgenic and transplantable murine lung cancer models, and human normal-malignant lung tissue arrays in addition to testing other Smo inhibitors. Cyclopamine sensitivity most significantly correlated with high cyclin E (P=0.000009) and low insulin-like growth factor binding protein 6 (IGFBP6) (P=0.000004) levels. Gli family members were associated with response. Cyclopamine resistance occurred with high GILZ (P=0.002) expression. Newer Smo inhibitors exhibited a pattern of sensitivity similar to cyclopamine. Gain of cyclin E or loss of IGFBP6 in lung cancer cells significantly increased Smo inhibitor response. Cyclin E-driven transgenic lung cancers expressed a gene profile implicating HH pathway activation. Cyclopamine treatment significantly reduced proliferation of murine and human lung cancers. Smo inhibition reduced lung cancer formation in a syngeneic mouse model. In human normal-malignant lung tissue arrays cyclin E, IGFBP6, Gli1 and GILZ were each differentially expressed. Together, these findings indicate that Smo inhibitors should be considered in cancers beyond those with activating HH pathway mutations. This includes tumors that express genes indicating basal HH pathway activation.

Natural and orthogonal interaction framework for modeling gene-environment interactions with application to lung cancer

OBJECTIVES

We aimed at extending the Natural and Orthogonal Interaction (NOIA) framework, developed for modeling gene-gene interactions in the analysis of quantitative traits, to allow for reduced genetic models, dichotomous traits, and gene-environment interactions. We evaluate the performance of the NOIA statistical models using simulated data and lung cancer data.

METHODS

The NOIA statistical models are developed for additive, dominant, and recessive genetic models as well as for a binary environmental exposure. Using the Kronecker product rule, a NOIA statistical model is built to model gene-environment interactions. By treating the genotypic values as the logarithm of odds, the NOIA statistical models are extended to the analysis of case-control data.

RESULTS

Our simulations showed that power for testing associations while allowing for interaction using the NOIA statistical model is much higher than using functional models for most of the scenarios we simulated. When applied to lung cancer data, much smaller p values were obtained using the NOIA statistical model for either the main effects or the SNP-smoking interactions for some of the SNPs tested.

CONCLUSION

The NOIA statistical models are usually more powerful than the functional models in detecting main effects and interaction effects for both quantitative traits and binary traits.

Evidence for the ubiquitin protease UBP43 as an antineoplastic target

New pharmacologic targets are needed for lung cancer. One candidate pathway to target is composed of the E1-like ubiquitin-activating enzyme (UBE1L) that associates with interferon-stimulated gene 15 (ISG15), which complexes with and destabilizes cyclin D1. Ubiquitin protease 43 (UBP43/USP18) removes ISG15 from conjugated proteins. This study reports that gain of UBP43 stabilized cyclin D1, but not other D-type cyclins or cyclin E. This depended on UBP43 enzymatic activity; an enzymatically inactive UBP43 did not affect cyclin D1 stability. As expected, small interfering RNAs that reduced UBP43 expression also decreased cyclin D1 levels and increased apoptosis in a panel of lung cancer cell lines. Forced cyclin D1 expression rescued UBP43 apoptotic effects, which highlighted the importance of cyclin D1 in conferring this. Short hairpin RNA-mediated reduction of UBP43 significantly increased apoptosis and reduced murine lung cancer growth in vitro and in vivo after transplantation of these cells into syngeneic mice. These cells also exhibited increased response to all-trans-retinoic acid, interferon, or cisplatin treatments. Notably, gain of UBP43 expression antagonized these effects. Normal-malignant human lung tissue arrays were examined independently for UBP43, cyclin D1, and cyclin E immunohistochemical expression. UBP43 was significantly (P < 0.01) increased in the malignant versus normal lung. A direct relationship was found between UBP43 and cyclin D1 (but not cyclin E) expression. Differential UBP43 expression was independently detected in a normal-malignant tissue array with diverse human cancers. Taken together, these findings uncovered UBP43 as a previously unrecognized antineoplastic target.

Analysis of the Distribution and Temporal Trends of Grade and Stage in Urothelial Bladder Cancer in Northern New England from 1994 to 2004

We investigate the distribution of bladder tumor category and stage in Northern New England by geographic region, smoking status and over time. 1091 incident bladder cancer cases from the New England Bladder Cancer Study (NEBCS), a large population-based case-control study carried out in Maine, New Hampshire and Vermont (2001-2004), and 680 bladder cancer cases from previous case-control studies in New Hampshire (1994-2000) were used in the analysis. Of 1091 incident bladder cancer cases from the NEBCS, 26.7% of tumors were papillary urothelial neoplasms of low malignant potential (PUNLMP), 26.8% low-grade papillary urothelial carcinomas (PUC-LG), 31.3% high-grade papillary urothelial carcinomas (PUC-HG), 9.1% non-papillary urothelial carcinomas (non-PUC), and 4.3% carcinoma in situ (CIS). Approximately 70% of cases were non-invasive (Tis/Ta), and all PUNLMP cases were of the Ta category. By contrast, half of all PUC-HG carcinomas were invasive. Short-term time trend analysis within the NEBCS (2001-2004) indicated an increase in the percentage of PUNLMP (p-trend<0.0001) paralleled by a decrease in PUC-LG (p-trend=0.02), and for PUC-LG an increase in the percentage of non-invasive tumors (p-trend 0.04). Our findings suggest possible short-term trends with an increase in the percentage of PUNLMP and a change in the percentage of PUC-LG towards non-invasive disease.

Asthma and lung cancer risk: a systematic investigation by the International Lung Cancer Consortium

Asthma has been hypothesized to be associated with lung cancer (LC) risk. We conducted a pooled analysis of 16 studies in the International Lung Cancer Consortium (ILCCO) to quantitatively assess this association and compared the results with 36 previously published studies. In total, information from 585 444 individuals was used. Study-specific measures were combined using random effects models. A meta-regression and subgroup meta-analyses were performed to identify sources of heterogeneity. The overall LC relative risk (RR) associated with asthma was 1.28 [95% confidence intervals (CIs) = 1.16-1.41] but with large heterogeneity (I(2) = 73%, P < 0.001) between studies. Among ILCCO studies, an increased risk was found for squamous cell (RR = 1.69, 95%, CI = 1.26-2.26) and for small-cell carcinoma (RR = 1.71, 95% CI = 0.99-2.95) but was weaker for adenocarcinoma (RR = 1.09, 95% CI = 0.88-1.36). The increased LC risk was strongest in the 2 years after asthma diagnosis (RR = 2.13, 95% CI = 1.09-4.17) but subjects diagnosed with asthma over 10 years prior had no or little increased LC risk (RR = 1.10, 95% CI = 0.94-1.30). Because the increased incidence of LC was chiefly observed in small cell and squamous cell lung carcinomas, primarily within 2 years of asthma diagnosis and because the association was weak among never smokers, we conclude that the association may not reflect a causal effect of asthma on the risk of LC.

A case-control study of polymorphisms in xenobiotic and arsenic metabolism genes and arsenic-related bladder cancer in New Hampshire

Arsenic is associated with bladder cancer risk even at low exposure levels. Genetic variation in enzymes involved in xenobiotic and arsenic metabolism may modulate individual susceptibility to arsenic-related bladder cancer. Through a population-based case-control study in NH (832 cases and 1191 controls), we investigated gene-environment interactions between arsenic metabolic gene polymorphisms and arsenic exposure in relation to bladder cancer risk. Toenail arsenic concentrations were used to classify subjects into low and high exposure groups. Single nucleotide polymorphisms (SNPs) in GSTP1, GSTO2, GSTZ1, AQP3, AS3MT and the deletion status of GSTM1 and GSTT1 were determined. We found evidence of genotype-arsenic interactions in the high exposure group; GSTP1 Ile105Val homozygous individuals had an odds ratio (OR) of 5.4 [95% confidence interval (CI): 1.5-20.2; P for interaction=0.03] and AQP3 Phe130Phe carriers had an OR=2.2 (95% CI: 0.8-6.1; P for interaction=0.10). Bladder cancer risk overall was associated with GSTO2 Asn142Asp (homozygous; OR=1.4; 95% CI: 1.0-1.9; P for trend=0.06) and GSTZ1 Glu32Lys (homozygous; OR=1.3; 95% CI: 0.9-1.8; P for trend=0.06). Our findings suggest that susceptibility to bladder cancer may relate to variation in genes involved in arsenic metabolism and oxidative stress response and potential gene-environment interactions requiring confirmation in other populations.

Indoor and Outdoor Air Pollution and Lung Cancer in New Hampshire and Vermont

Indoor and outdoor air pollution is known to contribute to increased lung cancer incidence. This study is the first to address the contribution of home heating fuel and geographical course particulate matter (PM₁₀) concentrations to lung cancer rates in New Hampshire, U.S. First, Pearson correlation analysis and Geographically weighted regression were used to investigate spatial relationships between outdoor PM₁₀ and lung cancer rates. While the aforementioned analyses did not indicate a significant contribution of PM₁₀ to lung cancer in the state, there was a trend towards a significant association in the northern and southwestern regions of the state. Second, case-control data were used to estimate the contributions of indoor pollution and second hand smoke to risk of lung cancer with adjustment for confounders. Increased risk was found among those who used wood or coal to heat their homes for more than 10 winters before the age of 18, with a significant increase in risk per winter. Resulting data suggest that further investigation of the relationship between heating-related air pollution levels and lung cancer risk is needed.

SLC39A2 and FSIP1 polymorphisms as potential modifiers of arsenic-related bladder cancer

Arsenic is a carcinogen that contaminates drinking water worldwide. Accumulating evidence suggests that both exposure and genetic factors may influence susceptibility to arsenic-induced malignancies. We sought to identify novel susceptibility loci for arsenic-related bladder cancer in a US population with low to moderate drinking water levels of arsenic. We first screened a subset of bladder cancer cases using a panel of approximately 10,000 non-synonymous single nucleotide polymorphisms (SNPs). Top ranking hits on the SNP array then were considered for further analysis in our population-based case-control study (n = 832 cases and 1,191 controls). SNPs in the fibrous sheath interacting protein 1 (FSIP1) gene (rs10152640) and the solute carrier family 39, member 2 (SLC39A2) in the ZIP gene family of metal transporters (rs2234636) were detected as potential hits in the initial scan and validated in the full case-control study. The adjusted odds ratio (OR) for the FSIP1 polymorphism was 2.57 [95% confidence interval (CI) 1.13, 5.85] for heterozygote variants (AG) and 12.20 (95% CI 2.51, 59.30) for homozygote variants (GG) compared to homozygote wild types (AA) in the high arsenic group (greater than the 90th percentile), and unrelated in the low arsenic group (equal to or below the 90th percentile) (P for interaction = 0.002). For the SLC39A2 polymorphism, the adjusted ORs were 2.96 (95% CI 1.23, 7.15) and 2.91 (95% CI 1.00, 8.52) for heterozygote (TC) and homozygote (CC) variants compared to homozygote wild types (TT), respectively, and close to one in the low arsenic group (P for interaction = 0.03). Our findings suggest novel variants that may influence risk of arsenic-associated bladder cancer and those who may be at greatest risk from this widespread exposure.

Abstract 1655: The ubiquitin protease UBP43 is a target for lung cancer therapy and prevention

Lung cancer is the leading cause of cancer mortality for women and men in the United States. Given this, there is a need to find new targets to combat lung cancer. This study explores the E1-like ubiquitin-activating enzyme (UBE1L) that associates with the interferon-stimulated gene 15 (ISG15), which complexes with cyclin D1 and other specific proteins. The ubiquitin protease UBP43 removes ISG15 from conjugated proteins. The UBE1L-ISG15-UBP43 pathway was previously proposed to inhibit lung carcinogenesis by repressing cyclin D1 expression. Our prior work is extended here by reporting that UBP43 is enzymatically active in cells. Also, gain of UBP43 expression specifically stabilizes cyclin D1 while UBP43 knock-down destabilizes cyclin D1, but not cyclin E or other D-type cyclins. This occurs by regulating ISG15 complexes with cyclin D1. UBP43 effects on cyclin D1 were not antagonized by cycloheximide treatment. Whether the deconjugase UBP43 was a lung cancer target was independently addressed through engineered gain and loss of UBP43 expression in lung cancer cells. UBP43 knock-down triggered apoptosis in these cells. In contrast, UBP43 over-expression promoted lung cancer cell growth by inhibiting apoptosis. That cyclin D1 plays a key role in conferring these effects was shown by engineered loss of UBP43 along with forced cyclin D1 expression. Cyclin D1 antagonized effects of loss of UBP43. Engineered UBP43 knock-down in lung cancer cells significantly increased apoptosis (P &lt; 0.05), reduced growth (P &lt; 0.05) and inhibited lung cancer formation (P &lt; 0.05) in FVB mice injected via tail veins with syngeneic lung cancer cells. In marked contrast, forced UBP43 over-expression in lung cancer cells antagonized the effects of interferon, cisplatin and all-trans-retinoic acid, indicating that UBP43 can regulate response to anti-neoplastic agents. To ascertain the clinical impact of this pathway, a paired normal-malignant human lung tissue array from 74 cases was examined for immunohistochemical expression profiles of UBP43 and cyclin D1 proteins. Notably, UBP43 was significantly increased in the malignant as compared to the adjacent normal lung tissues (P = 0.04 for adenocarcinoma and P = 0.02 for squamous cell carcinoma). Intriguingly, a direct relationship was found between UBP43 and cyclin D1, validating clinical relevance. Thus, UBP43 knock-down appears to exert its anti-neoplastic effects by destabilizing cyclin D1. Taken together, these findings establish that the deconjugase UBP43 is a tractable target for lung cancer therapy and prevention.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 1655. doi:10.1158/1538-7445.AM2011-1655

Abstract 1615: Gene expression profile predicts response to smoothened inhibitors in epithelial cancers

The hedgehog (HH) signaling pathway is important for embryonic development as it controls cell fate and proliferation. Deregulation of the HH pathway is linked to the onset and maintenance of multiple cancers. Clinical trials revealed promising effects of targeting the HH pathway with smoothened (Smo) inhibitors, particularly in basal cell carcinomas and medulloblastomas where HH pathway activation occurs. This study sought to uncover a gene signature that would predict response to Smo inhibitors, such as cyclopamine or SANT-1. A panel of 705 human cancer cell lines from diverse epithelial cancers was interrogated for sensitivity to cyclopamine. A subset of cancer cell lines exhibited substantial growth inhibition across a broad array of epithelial cancers. Sensitivity was significantly linked to high Gli1, high cyclin E, and low insulin-like growth factor binding protein 6 (IGFBP6) expression levels (P &lt; 0.05). Cyclin E overexpression and IGFBP6 knockdown conferred increased sensitivity to either cyclopamine or SANT-1 Smo inhibitors in lung cancer cell lines. This functionally validated the importance of this gene signature. To ascertain the biological impact of this profile, cyclin E transgenic mice that spontaneously developed premalignant and malignant lung lesions were studied. These lung cancers expressed the gene signature profile that predicts sensitivity to Smo inhibitors. As expected, cyclopamine treatment of these transgenic mice caused substantial immunohistochemical repression of cyclin D1 and Ki-67 in both premalignant and malignant lung lesions. To confirm and extend these findings, cyclopamine antineoplastic effects were examined using a previously described murine syngeneic and transplantable lung cancer model. Cyclopamine treatment significantly repressed lung cancer formation in these mice (P &lt; 0.01). Notably, a subset of examined human lung cancers was found to express the same gene signature that predicted response to Smo inhibitors. Taken together, these findings reveal a gene expression profile that predicts response of diverse epithelial cancers to Smo inhibitors. Future work should discern whether this same gene signature also predicts response to HH inhibitors in epithelial cancers of patients.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 1615. doi:10.1158/1538-7445.AM2011-1615

In-home coal and wood use and lung cancer risk: a pooled analysis of the International Lung Cancer Consortium

BACKGROUND

Domestic fuel combustion from cooking and heating is an important public health issue because roughly 3 billion people are exposed worldwide. Recently, the International Agency for Research on Cancer classified indoor emissions from household coal combustion as a human carcinogen (group 1) and from biomass fuel (primarily wood) as a probable human carcinogen (group 2A).

OBJECTIVES

We pooled seven studies from the International Lung Cancer Consortium (5,105 cases and 6,535 controls) to provide further epidemiological evaluation of the association between in-home solid-fuel use, particularly wood, and lung cancer risk.

METHODS

Using questionnaire data, we classified subjects as predominant solid-fuel users (e.g., coal, wood) or nonsolid-fuel users (e.g., oil, gas, electricity). Unconditional logistic regression was used to estimate the odds ratios (ORs) and to compute 95% confidence intervals (CIs), adjusting for age, sex, education, smoking status, race/ethnicity, and study center.

RESULTS

Compared with nonsolid-fuel users, predominant coal users (OR = 1.64; 95% CI, 1.49-1.81), particularly coal users in Asia (OR = 4.93; 95% CI, 3.73-6.52), and predominant wood users in North American and European countries (OR = 1.21; 95% CI, 1.06-1.38) experienced higher risk of lung cancer. The results were similar in never-smoking women and other subgroups.

CONCLUSIONS

Our results are consistent with previous observations pertaining to in-home coal use and lung cancer risk, support the hypothesis of a carcinogenic potential of in-home wood use, and point to the need for more detailed study of factors affecting these associations.

A robust multifactor dimensionality reduction method for detecting gene-gene interactions with application to the genetic analysis of bladder cancer susceptibility

A central goal of human genetics is to identify susceptibility genes for common human diseases. An important challenge is modelling gene-gene interaction or epistasis that can result in nonadditivity of genetic effects. The multifactor dimensionality reduction (MDR) method was developed as a machine learning alternative to parametric logistic regression for detecting interactions in the absence of significant marginal effects. The goal of MDR is to reduce the dimensionality inherent in modelling combinations of polymorphisms using a computational approach called constructive induction. Here, we propose a Robust Multifactor Dimensionality Reduction (RMDR) method that performs constructive induction using a Fisher's Exact Test rather than a predetermined threshold. The advantage of this approach is that only statistically significant genotype combinations are considered in the MDR analysis. We use simulation studies to demonstrate that this approach will increase the success rate of MDR when there are only a few genotype combinations that are significantly associated with case-control status. We show that there is no loss of success rate when this is not the case. We then apply the RMDR method to the detection of gene-gene interactions in genotype data from a population-based study of bladder cancer in New Hampshire.

A novel survival multifactor dimensionality reduction method for detecting gene-gene interactions with application to bladder cancer prognosis

The widespread use of high-throughput methods of single nucleotide polymorphism (SNP) genotyping has created a number of computational and statistical challenges. The problem of identifying SNP-SNP interactions in case-control studies has been studied extensively, and a number of new techniques have been developed. Little progress has been made, however, in the analysis of SNP-SNP interactions in relation to time-to-event data, such as patient survival time or time to cancer relapse. We present an extension of the two class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of survival analysis. The proposed Survival MDR (Surv-MDR) method handles survival data by modifying MDR's constructive induction algorithm to use the log-rank test. Surv-MDR replaces balanced accuracy with log-rank test statistics as the score to determine the best models. We simulated datasets with a survival outcome related to two loci in the absence of any marginal effects. We compared Surv-MDR with Cox-regression for their ability to identify the true predictive loci in these simulated data. We also used this simulation to construct the empirical distribution of Surv-MDR's testing score. We then applied Surv-MDR to genetic data from a population-based epidemiologic study to find prognostic markers of survival time following a bladder cancer diagnosis. We identified several two-loci SNP combinations that have strong associations with patients' survival outcome. Surv-MDR is capable of detecting interaction models with weak main effects. These epistatic models tend to be dropped by traditional Cox regression approaches to evaluating interactions. With improved efficiency to handle genome wide datasets, Surv-MDR will play an important role in a research strategy that embraces the complexity of the genotype-phenotype mapping relationship since epistatic interactions are an important component of the genetic basis of disease.

A simple and computationally efficient sampling approach to covariate adjustment for multifactor dimensionality reduction analysis of epistasis

Epistasis or gene-gene interaction is a fundamental component of the genetic architecture of complex traits such as disease susceptibility. Multifactor dimensionality reduction (MDR) was developed as a nonparametric and model-free method to detect epistasis when there are no significant marginal genetic effects. However, in many studies of complex disease, other covariates like age of onset and smoking status could have a strong main effect and may potentially interfere with MDR's ability to achieve its goal. In this paper, we present a simple and computationally efficient sampling method to adjust for covariate effects in MDR. We use simulation to show that after adjustment, MDR has sufficient power to detect true gene-gene interactions. We also compare our method with the state-of-art technique in covariate adjustment. The results suggest that our proposed method performs similarly, but is more computationally efficient. We then apply this new method to an analysis of a population-based bladder cancer study in New Hampshire.

Identification of methylated genes associated with aggressive bladder cancer

Approximately 500,000 individuals diagnosed with bladder cancer in the U.S. require routine cystoscopic follow-up to monitor for disease recurrences or progression, resulting in over $2 billion in annual expenditures. Identification of new diagnostic and monitoring strategies are clearly needed, and markers related to DNA methylation alterations hold great promise due to their stability, objective measurement, and known associations with the disease and with its clinical features. To identify novel epigenetic markers of aggressive bladder cancer, we utilized a high-throughput DNA methylation bead-array in two distinct population-based series of incident bladder cancer (n = 73 and n = 264, respectively). We then validated the association between methylation of these candidate loci with tumor grade in a third population (n = 245) through bisulfite pyrosequencing of candidate loci. Array based analyses identified 5 loci for further confirmation with bisulfite pyrosequencing. We identified and confirmed that increased promoter methylation of HOXB2 is significantly and independently associated with invasive bladder cancer and methylation of HOXB2, KRT13 and FRZB together significantly predict high-grade non-invasive disease. Methylation of these genes may be useful as clinical markers of the disease and may point to genes and pathways worthy of additional examination as novel targets for therapeutic treatment.

Replication of lung cancer susceptibility loci at chromosomes 15q25, 5p15, and 6p21: a pooled analysis from the International Lung Cancer Consortium

BACKGROUND

Genome-wide association studies have identified three chromosomal regions at 15q25, 5p15, and 6p21 as being associated with the risk of lung cancer. To confirm these associations in independent studies and investigate heterogeneity of these associations within specific subgroups, we conducted a coordinated genotyping study within the International Lung Cancer Consortium based on independent studies that were not included in previous genome-wide association studies.

METHODS

Genotype data for single-nucleotide polymorphisms at chromosomes 15q25 (rs16969968, rs8034191), 5p15 (rs2736100, rs402710), and 6p21 (rs2256543, rs4324798) from 21 case-control studies for 11 645 lung cancer case patients and 14 954 control subjects, of whom 85% were white and 15% were Asian, were pooled. Associations between the variants and the risk of lung cancer were estimated by logistic regression models. All statistical tests were two-sided.

RESULTS

Associations between 15q25 and the risk of lung cancer were replicated in white ever-smokers (rs16969968: odds ratio [OR] = 1.26, 95% confidence interval [CI] = 1.21 to 1.32, P(trend) = 2 x 10(-26)), and this association was stronger for those diagnosed at younger ages. There was no association in never-smokers or in Asians between either of the 15q25 variants and the risk of lung cancer. For the chromosome 5p15 region, we confirmed statistically significant associations in whites for both rs2736100 (OR = 1.15, 95% CI = 1.10 to 1.20, P(trend) = 1 x 10(-10)) and rs402710 (OR = 1.14, 95% CI = 1.09 to 1.19, P(trend) = 5 x 10(-8)) and identified similar associations in Asians (rs2736100: OR = 1.23, 95% CI = 1.12 to 1.35, P(trend) = 2 x 10(-5); rs402710: OR = 1.15, 95% CI = 1.04 to 1.27, P(trend) = .007). The associations between the 5p15 variants and lung cancer differed by histology; odds ratios for rs2736100 were highest in adenocarcinoma and for rs402710 were highest in adenocarcinoma and squamous cell carcinomas. This pattern was observed in both ethnic groups. Neither of the two variants on chromosome 6p21 was associated with the risk of lung cancer.

CONCLUSIONS

In this international genetic association study of lung cancer, previous associations found in white populations were replicated and new associations were identified in Asian populations. Future genetic studies of lung cancer should include detailed stratification by histology.

MicroRNA-31 functions as an oncogenic microRNA in mouse and human lung cancer cells by repressing specific tumor suppressors

MicroRNAs (miRNAs) regulate gene expression. It has been suggested that obtaining miRNA expression profiles can improve classification, diagnostic, and prognostic information in oncology. Here, we sought to comprehensively identify the miRNAs that are overexpressed in lung cancer by conducting miRNA microarray expression profiling on normal lung versus adjacent lung cancers from transgenic mice. We found that miR-136, miR-376a, and miR-31 were each prominently overexpressed in murine lung cancers. Real-time RT-PCR and in situ hybridization (ISH) assays confirmed these miRNA expression profiles in paired normal-malignant lung tissues from mice and humans. Engineered knockdown of miR-31, but not other highlighted miRNAs, substantially repressed lung cancer cell growth and tumorigenicity in a dose-dependent manner. Using a bioinformatics approach, we identified miR-31 target mRNAs and independently confirmed them as direct targets in human and mouse lung cancer cell lines. These targets included the tumor-suppressive genes large tumor suppressor 2 (LATS2) and PP2A regulatory subunit B alpha isoform (PPP2R2A), and expression of each was augmented by miR-31 knockdown. Their engineered repression antagonized miR-31-mediated growth inhibition. Notably, miR-31 and these target mRNAs were inversely expressed in mouse and human lung cancers, underscoring their biologic relevance. The clinical relevance of miR-31 expression was further independently and comprehensively validated using an array containing normal and malignant human lung tissues. Together, these findings revealed that miR-31 acts as an oncogenic miRNA (oncomir) in lung cancer by targeting specific tumor suppressors for repression.

MicroRNA-31 functions as an oncogenic microRNA in mouse and human lung cancer cells by repressing specific tumor suppressors

MicroRNAs (miRNAs) regulate gene expression. It has been suggested that obtaining miRNA expression profiles can improve classification, diagnostic, and prognostic information in oncology. Here, we sought to comprehensively identify the miRNAs that are overexpressed in lung cancer by conducting miRNA microarray expression profiling on normal lung versus adjacent lung cancers from transgenic mice. We found that miR-136, miR-376a, and miR-31 were each prominently overexpressed in murine lung cancers. Real-time RT-PCR and in situ hybridization (ISH) assays confirmed these miRNA expression profiles in paired normal-malignant lung tissues from mice and humans. Engineered knockdown of miR-31, but not other highlighted miRNAs, substantially repressed lung cancer cell growth and tumorigenicity in a dose-dependent manner. Using a bioinformatics approach, we identified miR-31 target mRNAs and independently confirmed them as direct targets in human and mouse lung cancer cell lines. These targets included the tumor-suppressive genes large tumor suppressor 2 (LATS2) and PP2A regulatory subunit B alpha isoform (PPP2R2A), and expression of each was augmented by miR-31 knockdown. Their engineered repression antagonized miR-31-mediated growth inhibition. Notably, miR-31 and these target mRNAs were inversely expressed in mouse and human lung cancers, underscoring their biologic relevance. The clinical relevance of miR-31 expression was further independently and comprehensively validated using an array containing normal and malignant human lung tissues. Together, these findings revealed that miR-31 acts as an oncogenic miRNA (oncomir) in lung cancer by targeting specific tumor suppressors for repression.

Implications of LINE1 methylation for bladder cancer risk in women

PURPOSE

Epigenetic alterations including changes to cellular DNA methylation levels contribute to carcinogenesis and may serve as powerful biomarkers of the disease. This investigation sought to determine whether hypomethylation at the long interspersed nuclear elements (LINE1), reflective of the level of global DNA methylation, in peripheral blood-derived DNA is associated with increased risk of bladder cancer.

EXPERIMENTAL DESIGN

LINE1 methylation was measured from blood-derived DNA obtained from participants of a population-based incident case-control study of bladder cancer in New Hampshire. Bisulfite-modified DNA was pyrosequenced to determine LINE1 methylation status; a total of 285 cases and 465 controls were evaluated for methylation.

RESULTS

Being in the lowest LINE1 methylation decile was associated with a 1.8-fold increased risk of bladder cancer [95% confidence interval (95% CI), 1.12-2.90] in models controlling for gender, age, and smoking, and the association was stronger in women than in men (odds ratio, 2.48; 95% CI, 1.19-5.17 in women; and odds ratio, 1.47; 95% CI, 0.79-2.74 in men). Among controls, women were more likely to have lower LINE1 methylation than men (P = 0.04), and levels of arsenic in the 90th percentile were associated with reduced LINE1 methylation (P = 0.04).

CONCLUSIONS

LINE1 hypomethylation may be an important biomarker of bladder cancer risk, especially among women.

International Lung Cancer Consortium: coordinated association study of 10 potential lung cancer susceptibility variants

BACKGROUND

Analysis of candidate genes in individual studies has had only limited success in identifying particular gene variants that are conclusively associated with lung cancer risk. In the International Lung Cancer Consortium (ILCCO), we conducted a coordinated genotyping study of 10 common variants selected because of their prior evidence of an association with lung cancer. These variants belonged to candidate genes from different cancer-related pathways including inflammation (IL1B), folate metabolism (MTHFR), regulatory function (AKAP9 and CAMKK1), cell adhesion (SEZL6) and apoptosis (FAS, FASL, TP53, TP53BP1 and BAT3).

METHODS

Genotype data from 15 ILCCO case-control studies were available for a total of 8431 lung cancer cases and 11 072 controls of European descent and Asian ethnic groups. Unconditional logistic regression was used to model the association between each variant and lung cancer risk.

RESULTS

Only the association between a non-synonymous variant of TP53BP1 (rs560191) and lung cancer risk was significant (OR = 0.91, P = 0.002). This association was more striking for squamous cell carcinoma (OR = 0.86, P = 6 x 10(-4)). No heterogeneity by center, ethnicity, smoking status, age group or sex was observed. In order to confirm this association, we included results for this variant from a set of independent studies (9966 cases/11,722 controls) and we reported similar results. When combining all these studies together, we reported an overall OR = 0.93 (0.89-0.97) (P = 0.001). This association was significant only for squamous cell carcinoma [OR = 0.89 (0.85-0.95), P = 1 x 10(-4)].

CONCLUSION

This study suggests that rs560191 is associated to lung cancer risk and further highlights the value of consortia in replicating or refuting published genetic associations.