Common Genetic Polymorphisms Modify the Effect of Smoking on Absolute Risk of Bladder Cancer

Universidad de Oviedo, Oviedo, Spain
Cancer Research (Impact Factor: 9.33). 03/2013; 73(7). DOI: 10.1158/0008-5472.CAN-12-2388
Source: PubMed


Bladder cancer results from the combined effects of environmental and genetic factors, smoking being the strongest risk factor. Evaluating absolute risks resulting from the joint effects of smoking and genetic factors is critical to assess the public health relevance of genetic information. Analyses included up to 3,942 cases and 5,680 controls of European background in seven studies. We tested for multiplicative and additive interactions between smoking and 12 susceptibility loci, individually and combined as a polygenic risk score (PRS). Thirty-year absolute risks and risk differences by levels of the PRS were estimated for U.S. males aged 50 years. Six of 12 variants showed significant additive gene-environment interactions, most notably NAT2 (P = 7 × 10(-4)) and UGT1A6 (P = 8 × 10(-4)). The 30-year absolute risk of bladder cancer in U.S. males was 6.2% for all current smokers. This risk ranged from 2.9% for current smokers in the lowest quartile of the PRS to 9.9% for current smokers in the upper quartile. Risk difference estimates indicated that 8,200 cases would be prevented if elimination of smoking occurred in 100,000 men in the upper PRS quartile compared with 2,000 cases prevented by a similar effort in the lowest PRS quartile (Padditive = 1 × 10(-4)). Thus, the potential impact of eliminating smoking on the number of bladder cancer cases prevented is larger for individuals at higher than lower genetic risk. Our findings could have implications for targeted prevention strategies. However, other smoking-related diseases, as well as practical and ethical considerations, need to be considered before any recommendations could be made. Cancer Res; 73(7); 1-10. ©2012 AACR.

25 Reads
  • Source
    • "In a recent paper published in Cancer Research, Garcia-Closas and colleagues55 examined how genetic variants were recently identified in GWAS for bladder cancer interaction with smoking status to influence bladder cancer risk. The authors identified a new high-risk subgroup of individuals – current smokers carrying the highest genetic risk burden – who could be targeted for behavioral interventions and/or early detection protocols. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Cancer risk prediction models are important in identifying individuals at high risk of developing cancer, which could result in targeted screening and interventions to maximize the treatment benefit and minimize the burden of cancer. The cancer-associated genetic variants identified in genome-wide or candidate gene association studies have been shown to collectively enhance cancer risk prediction, improve our understanding of carcinogenesis, and possibly result in the development of targeted treatments for patients. In this article, we review the cancer risk prediction models that have been developed for popular cancers and assess their applicability, strengths, and weaknesses. We also discuss the factors to be considered for future development and improvement of models for cancer risk prediction.
    Cancer informatics 09/2014; 13(Suppl 2):19-28. DOI:10.4137/CIN.S13788
  • Source
    • "Prostate cancer, urothelial carcinoma and renal cancer are common cancer types and major cause of cancer-related death worldwide [1,2]. Smoking, diet and environmental factors have been reported to contribute to the carcinogenesis of these malignancies [3,4]. However, the fact that a small fraction of people exposed to these carcinogens eventually develop urinary cancers suggests that individual genetic predisposition factors may contribute to carcinogenesis. "
    [Show abstract] [Hide abstract]
    ABSTRACT: AbstractBackgroundThe Cytochrome P450 1B1 (CYP1B1) is a key P450 enzyme involved in the metabolism of exogenous and endogenous substrates. Previous studies have reported the existence of CYP1B1 L432V missense polymorphism in prostate, bladder and renal cancers. However, the effects of this polymorphism on the risk of these cancers remain conflicting. Therefore, we performed a meta-analysis to assess the association between L432V polymorphism and the susceptibility of urinary cancers.MethodsWe searched the PubMed database without limits on language for studies exploring the relationship of CYP1B1 L432V polymorphism and urinary cancers. Article search was supplemented by screening the references of retrieved studies manually. Odds ratios (OR) and 95% confidence intervals (95% CI) were calculated to evaluate the strength of these associations. Simultaneously, publication bias was estimated by funnel plot and Begg’s test with Stata 11 software.ResultsWe observed a significant association between CYP1B1 L432V polymorphism and urinary cancers. The overall OR (95% CI) of CC versus CG was 0.937 (0.881-0.996), the overall OR (95% CI) of CC versus CG + GG was 0.942 (0.890-0.997). Furthermore, we identified reduced risk for CC versus other phenotypes in both prostate and overall urinary cancers, when studies were limited to Caucasian or Asian patients.ConclusionsThis meta-analysis suggests that the CYP1B1 L432V polymorphism is associated with urinary cancer risk.Virtual SlidesThe virtual slide(s) for this article can be found here:
    Diagnostic Pathology 06/2014; 9(1):113. DOI:10.1186/1746-1596-9-113 · 2.60 Impact Factor
  • Source
    • "In addition to these strong environmental risk factors, recent genome-wide association studies have identified several highly significant genetic factors with small effects [5,6]. Some of these have been shown to modify the effects of smoking on risk of bladder cancer [7]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: 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. 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. 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.
    BioData Mining 04/2014; 7(1):5. DOI:10.1186/1756-0381-7-5 · 2.02 Impact Factor
Show more