Abstract LB-441: The genome wide gene-environment interaction analysis for asbestos exposure on lung cancer susceptibility

Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030 USA.
Carcinogenesis (Impact Factor: 5.33). 05/2012; 33(8):1531-7. DOI: 10.1093/carcin/bgs188
Source: PubMed


Asbestos exposure is a known risk factor for lung cancer. Although recent genome-wide association studies (GWASs) have identified some novel loci for lung cancer risk, few addressed genome-wide gene-environment interactions. To determine gene-asbestos interactions in lung cancer risk, we conducted genome-wide gene-environment interaction analyses at levels of single nucleotide polymorphisms (SNPs), genes and pathways, using our published Texas lung cancer GWAS dataset. This dataset included 317 498 SNPs from 1154 lung cancer cases and 1137 cancer-free controls. The initial SNP-level P-values for interactions between genetic variants and self-reported asbestos exposure were estimated by unconditional logistic regression models with adjustment for age, sex, smoking status and pack-years. The P-value for the most significant SNP rs13383928 was 2.17×10(-6), which did not reach the genome-wide statistical significance. Using a versatile gene-based test approach, we found that the top significant gene was C7orf54, located on 7q32.1 (P = 8.90×10(-5)). Interestingly, most of the other significant genes were located on 11q13. When we used an improved gene-set-enrichment analysis approach, we found that the Fas signaling pathway and the antigen processing and presentation pathway were most significant (nominal P < 0.001; false discovery rate < 0.05) among 250 pathways containing 17 572 genes. We believe that our analysis is a pilot study that first describes the gene-asbestos interaction in lung cancer risk at levels of SNPs, genes and pathways. Our findings suggest that immune function regulation-related pathways may be mechanistically involved in asbestos-associated lung cancer risk.

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    • "The same considerations apply to pathway- or gene-set analyses, where the association signals from the genes in a pathway are combined. A similar situation appears in interaction analyses where the objective is to identify pairs of genes contributing to a trait in a way that deviates from the simple addition of their independent effects [9, 10]. This type of analysis can be done at the individual SNP level but this is very sensitive to small variations in the study, and analysis at the gene or pathway level has been advocated as more reproducible [9–11]. "
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    ABSTRACT: Background Some association studies, as the implemented in VEGAS, ALIGATOR, i-GSEA4GWAS, GSA-SNP and other software tools, use genes as the unit of analysis. These genes include the coding sequence plus flanking sequences. Polymorphisms in the flanking sequences are of interest because they involve cis-regulatory elements or they inform on untyped genetic variants trough linkage disequilibrium. Gene extensions have customarily been defined as ± 50 Kb. This approach is not fully satisfactory because genetic relationships between neighbouring sequences are a function of genetic distances, which are only poorly replaced by physical distances. Results Standardized recombination rates (SRR) from the deCODE recombination map were used as units of genetic distances. We searched for a SRR producing flanking sequences near the ± 50 Kb offset that has been common in previous studies. A SRR ≥ 2 was selected because it led to gene extensions with median length = 45.3 Kb and the simplicity of an integer value. As expected, boundaries of the genes defined with the ± 50 Kb and with the SRR ≥2 rules were rarely concordant. The impact of these differences was illustrated with the interpretation of top association signals from two large studies including many hits and their detailed analysis based in different criteria. The definition based in genetic distance was more concordant with the results of these studies than the based in physical distance. In the analysis of 18 top disease associated loci form the first study, the SRR ≥2 genes led to a fully concordant interpretation in 17 loci; the ± 50 Kb genes only in 6. Interpretation of the 43 putative functional genes of the second study based in the SRR ≥2 definition only missed 4 of the genes, whereas the based in the ± 50 Kb definition missed 10 genes. Conclusions A gene definition based on genetic distance led to results more concordant with expert detailed analyses than the commonly used based in physical distance. The genome coordinates for each gene are provided to maintain a simple use of the new definitions. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-408) contains supplementary material, which is available to authorized users.
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    ABSTRACT: Lung cancer (LC) is a highly prevalent malignancy mainly caused by long-term exposure to tobacco smoke, although other substances in the workplace can also cause LC. This paper reviews carcinogens in the workplace linked with occupational LC, including asbestos, radon, silica, nickel, beryllium, chromium and polycyclic aromatic hydrocarbons (PAH). In LC of occupational origin, diagnosis can be difficult due to co-exposure to various carcinogens. The present review is intended to provide additional information that may help in the diagnostic approach and discusses controversial issues on certain substances like silica, beryllium or PAH as etiological factors of LC. Finally, occupational LC preventive measures are discussed.
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    ABSTRACT: This chapter focuses specifically on asbestos-induced chronic inflammation and carcinogenesis, discussing possible mechanisms of action of asbestos exposure, and concluding with suggestions on potential therapeutic targets. The chemical composition of asbestos-like fibers can play an important role in determining the inflammatory and carcinogenic potential. Asbestos exposure has been associated with a group of diseases collectively referred to as asbestos-related diseases (ARDs), which can be divided into malignant and benign. The best recognized asbestos-associated malignancies are malignant mesothelioma (MM), lung cancer, and laryngeal cancer. Given the established role of chronic inflammation in asbestos-related cancers and the long latency time between fiber exposure and cancer formation, asbestos-induced inflammation is an appealing therapeutic target for cancer prevention. By a greater understanding of asbestos-induced chronic inflammation, we expect increased efforts in the chemoprevention of asbestos-induced malignancies in the near future.
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