Computational Modelling of Cancer Development and Growth: Modelling at Multiple Scales and Multiscale Modelling

Zuzanna Szymańska, Maciej Cytowski, Elaine Mitchell, Cicely K. Macnamara, Mark Chaplain (Lead / Corresponding author)

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)


In this paper, we present two mathematical models related to different aspects and scales of cancer growth. The first model is a stochastic spatiotemporal model of both a synthetic gene regulatory network (the example of a three-gene repressilator is given) and an actual gene regulatory network, the NF-[Formula: see text]B pathway. The second model is a force-based individual-based model of the development of a solid avascular tumour with specific application to tumour cords, i.e. a mass of cancer cells growing around a central blood vessel. In each case, we compare our computational simulation results with experimental data. In the final discussion section, we outline how to take the work forward through the development of a multiscale model focussed at the cell level. This would incorporate key intracellular signalling pathways associated with cancer within each cell (e.g. p53-Mdm2, NF-[Formula: see text]B) and through the use of high-performance computing be capable of simulating up to [Formula: see text] cells, i.e. the tissue scale. In this way, mathematical models at multiple scales would be combined to formulate a multiscale computational model.

Original languageEnglish
Pages (from-to)1366-1403
Number of pages38
JournalBulletin of Mathematical Biology
Issue number5
Early online date20 Jun 2017
Publication statusPublished - 1 May 2018


  • Computational simulations
  • Gene regulatory network
  • Individual-based model
  • Multiscale cancer modelling
  • Spatial stochastic model

ASJC Scopus subject areas

  • General Neuroscience
  • Immunology
  • General Mathematics
  • General Biochemistry,Genetics and Molecular Biology
  • General Environmental Science
  • Pharmacology
  • General Agricultural and Biological Sciences
  • Computational Theory and Mathematics


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