Display Settings:

Format

Send to:

Choose Destination
    J Theor Biol. 2008 Sep 21;254(2):229-38. Epub 2008 May 29.

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

    Source

    Department of Epidemiology and Public Health, Imperial College Faculty of Medicine, London W21PG, UK. mark.little@imperial.ac.uk

    Erratum in

    • J Theor Biol. 2008 Nov 21;255(2):268.

    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.

    PMID:
    18640693
    [PubMed - indexed for MEDLINE]

      Supplemental Content

      Icon for Elsevier Science

      Save items

      loading

      Recent activity

      Your browsing activity is empty.

      Activity recording is turned off.

      Turn recording back on

      See more...
      Write to the Help Desk