Predicted number of driver events per tumor strongly correlates with contribution from anthropogenic and lifestyle risk factors

Abstract

I have recently shown that the number of rate-limiting driver events per tumor can be estimated from the age distribution of cancer incidence using the Erlang or gamma probability distribution. Here I show that this number strongly correlates with the proportion of cancer cases due to anthropogenic and lifestyle risk factors, such as air pollution, occupational hazards, ionizing radiation, smoking, alcohol, poor diet, insufficient exercise and obesity, but does not seem to correlate with the proportion of cases due to infection or ultraviolet radiation. The correlation was confirmed for three different countries, three corresponding incidence databases, and three risk estimation studies, as well as for both sexes: USA, CDC WONDER database, Islami et al. study, males [r=0.82, P=0.0006, 13 cancer types], females [r=0.83, P<0.0001, 16 cancer types]; England, ECIS database, Brown et al. study, males [r=0.90, P<0.0001, 16 cancer types], females [r=0.67, P=0.002, 19 cancer types]; Australia, CI5 database, Whiteman et al. study, males [r=0.90, P=0.0004, 10 cancer types], females [r=0.68, P=0.01, 13 cancer types]. It is thus confirmed that predictions based on interpreting the age distribution of cancer incidence as the Erlang probability distribution have biological meaning, validating the underlying Poisson process as the law governing the development of the majority of cancer types, with the possible exception of infection- and UV-induced cancers. It also suggests that the majority of driver events (70-80% in males, 50-70% in females) are induced by anthropogenic carcinogens and the lifestyle, and not by cell divisions or other internal processes.