A stochastic carcinogenesis model incorporating multiple types of genomic instability fitted to colon cancer data

Little, Mark, Vineis, Paolo and Li, Guangquan (2008) A stochastic carcinogenesis model incorporating multiple types of genomic instability fitted to colon cancer data. Journal of Theoretical Biology, 254 (2). pp. 229-238. ISSN 0022-5193

Full text not available from this repository. (Request a copy)
Official URL: http://dx.doi.org/10.1016/j.jtbi.2008.05.027

Abstract

A generalization of the two-mutation stochastic carcinogenesis model of Moolgavkar, Venzon and Knudson and certain models constructed by Little [Little, M.P. (1995). Are two mutations sufficient to cause cancer? Some generalizations of the two-mutation model of carcinogenesis of Moolgavkar, Venzon, and Knudson, and of the multistage model of Armitage and Doll. Biometrics 51, 1278–1291] and Little and Wright [Little, M.P., Wright, E.G. (2003). A stochastic carcinogenesis model incorporating genomic instability fitted to colon cancer data. Math. Biosci. 183, 111–134] is developed; the model incorporates multiple types of progressive genomic instability and an arbitrary number of mutational stages. The model is fitted to US Caucasian colon cancer incidence data. On the basis of the comparison of fits to the population-based data, there is little evidence to support the hypothesis that the model with more than one type of genomic instability fits better than models with a single type of genomic instability. Given the good fit of the model to this large dataset, it is unlikely that further information on presence of genomic instability or of types of genomic instability can be extracted from age-incidence data by extensions of this model.

Item Type: Article
Subjects: G100 Mathematics
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Ellen Cole
Date Deposited: 12 Jul 2013 10:53
Last Modified: 13 Oct 2019 00:24
URI: http://nrl.northumbria.ac.uk/id/eprint/13216

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics