English

Dynamical density functional theory based modelling of tissue dynamics: application to tumour growth

Soft Condensed Matter 2018-09-03 v1 Statistical Mechanics Pattern Formation and Solitons

Abstract

We present a theoretical framework based on an extension of dynamical density functional theory (DDFT) for describing the structure and dynamics of cells in living tissues and tumours. DDFT is a microscopic statistical mechanical theory for the time evolution of the density distribution of interacting many-particle systems. The theory accounts for cell pair-interactions, different cell types, phenotypes and cell birth and death processes (including cell division), in order to provide a biophysically consistent description of processes bridging across the scales, including describing the tissue structure down to the level of the individual cells. Analysis of the model is presented for a single species and a two-species cases, the latter aimed at describing competition between tumour and healthy cells. In suitable parameter regimes, model results are consistent with biological observations. Of particular note, divergent tumour growth behaviour, mirroring metastatic and benign growth characteristics, are shown to be dependent on the cell pair-interaction parameters.

Keywords

Cite

@article{arxiv.1807.03261,
  title  = {Dynamical density functional theory based modelling of tissue dynamics: application to tumour growth},
  author = {Hayder M. Al-Saedi and Andrew J. Archer and John Ward},
  journal= {arXiv preprint arXiv:1807.03261},
  year   = {2018}
}

Comments

18 pages, 12 figures

R2 v1 2026-06-23T02:55:19.651Z