Derivation and travelling wave analysis of phenotype-structured haptotaxis models of cancer invasion

Tommaso Lorenzi, Fiona R. Macfarlane*, Kevin J. Painter

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


We formulate haptotaxis models of cancer invasion wherein the infiltrating cancer cells can occupy a spectrum of states in phenotype space, ranging from ‘fully mesenchymal’ to ‘fully epithelial’. The more mesenchymal cells are those that display stronger haptotaxis responses and have greater capacity to modify the extracellular matrix (ECM) through enhanced secretion of matrix-degrading enzymes (MDEs). However, as a trade-off, they have lower proliferative capacity than the more epithelial cells. The framework is multiscale in that we start with an individual- based model that tracks the dynamics of single cells, which is based on a branching random walk over a lattice representing both physical and phenotype space. We formally derive the corresponding continuum model, which takes the form of a coupled system comprising a partial integro-differential equation for the local cell population density function, a partial differential equation for the MDE concentration and an infinite-dimensional ordinary differential equation for the ECM density. Despite the intricacy of the model, we show, through formal asymptotic techniques, that for certain parameter regimes it is possible to carry out a detailed travelling wave analysis and obtain invading fronts with spatial structuring of phenotypes. Precisely, the most mesenchymal cells dominate the leading edge of the invasion wave and the most epithelial (and most proliferative) dominate the rear, representing a bulk tumour population. As such, the model recapitulates similar observations into a front to back structuring of invasion waves into leader-type and follower-type cells, witnessed in an increasing number of experimental studies over recent years.
Original languageEnglish
Number of pages33
JournalEuropean Journal of Mathematics
Early online date27 Feb 2024
Publication statusE-pub ahead of print - 27 Feb 2024


  • Individual-based models
  • Partial integro-differential equation
  • Travelling wave analysis
  • Phenotypic diversity
  • Haptotaxis models of cancer invasion


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