Abstract

In the radiation protection approach to risk assessment, it is assumed that cancer induction follows low-level radiation exposure in a probabilistic way. The stochastic model underlying all present risk assessment methods derives risks from cancer incidence frequencies in exposed populations and associates disease outcomes totally with the level of exposure to an environmental source. Exposure is the risk factor that affects the probability of the disease outcome. But cancer risk also reflects pre-existing underlying genetic predisposition (genetic risk factors) in individuals who are exposed. The distribution of genetic risk factors in time and space is governed by the biological and social processes involved in reproduction (biological risk factors). To include both genetic and biological risk factors in cancer risk assessment, a genetic cancer risk factors model must be developed. We tested the plausibility of the genetic cancer risk factors model by surveying all genetic disorders associated with cancer in the Online Mendelian Inheritance in Man database, determined the gene map location, if known, and attached DNA sequence information if it was available. We found 641 genetic disorders associated with cancer, of which 495 have been mapped into about 120 clusters on the human genome, and of which DNA sequence data are at least partially available for 253. From the molecular variants of various cancer risk genes that have been described, and from the breeding patterns that determine carrier frequencies in the population, we deduce that significant numbers of members of the population may carry such genes. If such carriers differ in radiogenic cancer risk from non-carriers in the population, then their variability needs to be taken into account in risk assessment models.

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