Methematical Modeling of Carcinogenesis

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Niwa et al.analyzed the frequency of germline mutation at the pathernally serived allele of a hypervariable minisatellite locus for F1 mice which were born between the father mice which irradiated ^<252>Cf and unirradiated mother mice. A significant excess risk due to the irradiation, extended in the generation inherited unstable because of the radiation exposure of the cell was detected for spermatid stage. The dose response of ^<252>Cf radiation for induction of germline mutation was linear up to 0.7Gy for spermatid stage germ line cells. They concluded that DNA damage is not the direct cause of mutations at this locus, but it may induce genetic instability which in turn induces recombination at the hypervariable minisatellite locus. (Niwa et al., J.Radiation Research 37,1996).Regarding the carcinogenesis as a series of events of mutation of one cell, proliferation of the mutation cell, the appearance of the malignant cell and the formation and the growth of tumor, Ohtaki developed t … More he mathematical model which was called "Premutation" -Mutation model. In this model, it is assumed that only the first step of carcinogenesis may have the exposure dependency and the length of the tumor growth period is formulated as a random variable which may very over individuals. The model was applied to the cancer incidence data in the Atomic bomb Survivors in Hiroshima and Nagasaki which were published from Radiation Effects Reasearch Foundation and to the mice's carcinogenesis data, and the dose-response relationship was analyzed statistically (Ohtaki, Hiroshima Medical Journal 49,1996).Matsuura et al.analyzed the data of the mortality rate among Atomic bomb Survivors living in Hiroshima Prefecture. Assuming linear dose-response relationship between the exposed radiation dose and motality risk from various cancers, and appling the technique of the dynamic cohort study, they analyzed the data. As a result, statistically significant excess risk among exposed population was detected for mortality from leukemia, the lung cancer, colon cancer, and breast cancer. (Matsuura et al., Journal of Radiation Research, in press). Less