Gene–Environment Interactions in Cancer

Do They Exist?

Authors

  • KARI HEMMINKI,

    1. Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany
    2. Center for Family Medicine, Karolinska Institute, 141 83 Huddinge, Sweden
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  • ASTA FÖRSTI,

    1. Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany
    2. Center for Family Medicine, Karolinska Institute, 141 83 Huddinge, Sweden
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  • JUSTO LORENZO BERMEJO

    1. Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany
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Address for correspondence: Kari Hemminki, Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, D-69120, Heidelberg, Germany. Voice: 49-6221-421800; fax: 49-6221-421810.
 e-mail: k.hemminki@dkfz.de

Abstract

Abstract: Single nucleotide polymorphisms (SNPs) are extensively used in case–control studies of practically all cancer types. In addition to the pure genetic studies, gene–environment studies, which simultaneously consider environmental factors, have been increasingly conducted. All SNP studies aim at the identification of the role of inherited cancer susceptibility genes. However, being genetic markers, they are applicable only on heritable conditions, which is often a neglected fact. Based on the data on the heritability of cancer and the importance of environmental factors in cancer etiology, we discuss the likelihood of successful gene–environment studies. The available evidence is not conclusive, but it consistently points to a minor heritable etiology in cancer, which will hamper the success of SNP-based association studies. We use simulation techniques to examine which situations would favor the application of a gene–environment approach instead of the traditional environmental approach in case–control studies. The results show that well-chosen candidate gene with a relatively low allele frequency may improve the power to detect environmental determinants of a disease. However, this advantage is lost when the number of underlying genes increases. We are concerned about an indiscriminate use of genetic tools for cancers, which are mainly environmental in origin. The likelihood of success for SNP-based gene–environment studies increases if established environmental risk factors are tested on proven candidate genes. Enhancing the likelihood that the disease causation is genetic, for example, by selecting familial cases, may increase the power of the studies, and the rareness of those cases calls for collaborative networks.

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