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Consensus report of the 8 and 9th Weinman Symposia on Gene x Environment Interaction in carcinogenesis: novel opportunities for precision medicine

The relative contribution of intrinsic genetic factors and extrinsic environmental ones to cancer aetiology and natural history is a lengthy and debated issue. Gene-environment interactions (G x E) arise when the combined presence of both a germline genetic variant and a known environmental factor m...

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Published in:Cell death and differentiation 2018-11, Vol.25 (11), p.1885-1904
Main Authors: Carbone, Michele, Amelio, Ivano, Affar, El Bachir, Brugarolas, James, Cannon-Albright, Lisa A, Cantley, Lewis C, Cavenee, Webster K, Chen, Zhijian, Croce, Carlo M, Andrea, Alan D', Gandara, David, Giorgi, Carlotta, Jia, Wei, Lan, Qing, Mak, Tak Wah, Manley, James L, Mikoshiba, Katsuhiko, Onuchic, Jose N, Pass, Harvey I, Pinton, Paolo, Prives, Carol, Rothman, Nathaniel, Sebti, Said M, Turkson, James, Wu, Xifeng, Yang, Haining, Yu, Herbert, Melino, Gerry
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Language:English
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Summary:The relative contribution of intrinsic genetic factors and extrinsic environmental ones to cancer aetiology and natural history is a lengthy and debated issue. Gene-environment interactions (G x E) arise when the combined presence of both a germline genetic variant and a known environmental factor modulates the risk of disease more than either one alone. A panel of experts discussed our current understanding of cancer aetiology, known examples of G × E interactions in cancer, and the expanded concept of G × E interactions to include somatic cancer mutations and iatrogenic environmental factors such as anti-cancer treatment. Specific genetic polymorphisms and genetic mutations increase susceptibility to certain carcinogens and may be targeted in the near future for prevention and treatment of cancer patients with novel molecularly based therapies. There was general consensus that a better understanding of the complexity and numerosity of G × E interactions, supported by adequate technological, epidemiological, modelling and statistical resources, will further promote our understanding of cancer and lead to novel preventive and therapeutic approaches.
ISSN:1350-9047
1476-5403
DOI:10.1038/s41418-018-0213-5