4.6 Article

Multiscale Modelling of Vascular Tumour Growth in 3D: The Roles of Domain Size and Boundary Conditions

期刊

PLOS ONE
卷 6, 期 4, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0014790

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资金

  1. Engineering and Physical Sciences Research Council [EP/D501083/1]
  2. Marie Curie Network MMBNOTT [MEST-CT-2005-020723]
  3. Royal Society
  4. National Institutes of Health [1U54CA143970-01]
  5. BMBF-Funding Initiative
  6. Moffitt Cancer Center PS-OC NIH/National Cancer Institute [U54CA143970]
  7. Engineering and Physical Sciences Research Council [EP/D501083/1] Funding Source: researchfish
  8. EPSRC [EP/D501083/1] Funding Source: UKRI

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We investigate a three-dimensional multiscale model of vascular tumour growth, which couples blood flow, angiogenesis, vascular remodelling, nutrient/growth factor transport, movement of, and interactions between, normal and tumour cells, and nutrient-dependent cell cycle dynamics within each cell. In particular, we determine how the domain size, aspect ratio and initial vascular network influence the tumour's growth dynamics and its long-time composition. We establish whether it is possible to extrapolate simulation results obtained for small domains to larger ones, by constructing a large simulation domain from a number of identical subdomains, each subsystem initially comprising two parallel parent vessels, with associated cells and diffusible substances. We find that the subsystem is not representative of the full domain and conclude that, for this initial vessel geometry, interactions between adjacent subsystems contribute to the overall growth dynamics. We then show that extrapolation of results from a small subdomain to a larger domain can only be made if the subdomain is sufficiently large and is initialised with a sufficiently complex vascular network. Motivated by these results, we perform simulations to investigate the tumour's response to therapy and show that the probability of tumour elimination in a larger domain can be extrapolated from simulation results on a smaller domain. Finally, we demonstrate how our model may be combined with experimental data, to predict the spatio-temporal evolution of a vascular tumour.

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