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Cancer risk: Many factors contribute

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Science  13 Feb 2015:
Vol. 347, Issue 6223, pp. 728-729
DOI: 10.1126/science.aaa6094

In their Report “Variation in cancer risk among tissues can be explained by the number of stem cell divisions” (2 January, p. 78), C. Tomasetti and B. Vogelstein found a high correlation between the number of lifetime stem cell divisions of a given tissue and the lifetime risk of cancer in that tissue. Based on the finding that 65% of the variation in cancer risk among different tissues can be explained by the number of stem cell divisions in those tissues, the authors concluded that “these results suggest that only a third of the variation in cancer risk among tissues is attributable to environmental factors or inherited predispositions.” This conclusion presumes that the total contribution of different components to variation in cancer risk among tissues adds up to 100%. However, most cancers are caused by multiple overlapping factors, and the attributable fractions for individual factors can add up to more than 100%. Furthermore, Tomasetti and Vogelstein suggest using the extra risk score (ERS) to direct allocation of primary versus secondary prevention for different cancers. However, although the ERS indicates how important the stochastic effects of DNA replication are for the variation in cancer rates across organs, it does not inform about the preventability of a certain cancer in the population. As shown in Figure 1 in the Report, a wide variation in cancer rates exists even within highly proliferative tissues, indicating a substantial role of non-stochastic factors in carcinogenesis (such as sun exposure for melanoma, tobacco for lung cancer, viruses and obesity for hepatocellular carcinoma, and obesity and tobacco for pancreatic ductal adenocarcinoma) and an enormous potential for primary prevention. The proportion of cancer cases that can be potentially prevented by environmental (mainly lifestyle) modification should be estimated on the basis of the comparison of cancer rates across populations with different risk factor profiles (1, 2), rather than the comparison of cancer rates across tissues within individuals.

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