title: A stochastic carcinogenesis model incorporating genomic instability fitted to colon cancer data.
abstract: A generalization of the two-mutation stochastic carcinogenesis model of Moolgavkar, Venzon and Knudson and certain models constructed by Little is developed; the model incorporates progressive genomic instability and an arbitrary number of mutational stages. This model is shown to have the property that, at least in the case when the parameters of the model are eventually constant, the excess relative and absolute cancer rates following changes in any of the parameters will eventually tend to zero. It is also shown that when the parameters governing the processes of cell division, death, or additional mutation (whether of the normal sort or that resulting in genomic destabilization) at the penultimate stage are subject to perturbations, there are relatively large fluctuations in the hazard function for the model, which start almost as soon as the parameters are changed. The model is fitted to US Caucasian colon cancer incidence data. A model with five stages and two levels of genomic destabilization fits the data well. Comparison with patterns of excess risk in the Japanese atomic bomb survivor colon cancer incidence data indicate that radiation might act on early mutation rates in the model; a major role for radiation in initiating genomic destabilization is less likely.
authors.affiliation: Department of Epidemiology and Public Health, Imperial College Faculty of Medicine, London, UK. mark.little@imperial.ac.uk
authors.forename: M P
authors.initials: MP
authors.lastname: Little
authors.forename: E G
authors.initials: EG
authors.lastname: Wright
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D003110:Colonic Neoplasms / Q000453:epidemiology / Q000235:genetics*; D005260:Female; D006801:Humans; D015994:Incidence; D007223:Infant; D007564:Japan; D008297:Male; D008875:Middle Aged; D008957:Models, Genetic; D016016:Proportional Hazards Models; D013269:Stochastic Processes; D014481:United States