Spatial stochastic models for cancer initiation and progression

Bull Math Biol. 2006 Oct;68(7):1573-99. doi: 10.1007/s11538-005-9046-8.

Abstract

The multistage carcinogenesis hypothesis has been formulated by a number of authors as a stochastic process. However, most previous models assumed "perfect mixing" in the population of cells, and included no information about spatial locations. In this work, we studied the role of spatial dynamics in carcinogenesis. We formulated a 1D spatial generalization of a constant population (Moran) birth-death process, and described the dynamics analytically. We found that in the spatial model, the probability of fixation of advantageous and disadvantageous mutants is lower, and the rate of generation of double-hit mutants (the so-called tunneling rate) is higher, compared to those for the space-free model. This means that the results previously obtained for space-free models give an underestimation for rates of cancer initiation in the case where the first event is the generation of a double-hit mutant, e.g. the inactivation of a tumor-suppressor gene.

MeSH terms

  • Algorithms
  • Cell Death
  • Cell Division
  • Cell Proliferation
  • Disease Progression
  • Genes, Tumor Suppressor
  • Humans
  • Kinetics
  • Models, Biological*
  • Mutation / genetics
  • Neoplasms / etiology
  • Neoplasms / genetics
  • Neoplasms / pathology*
  • Probability
  • Stochastic Processes*