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

TL;DR

This paper develops a dynamical density functional theory framework to model tissue and tumor dynamics, capturing cell interactions, types, and processes like division and death, aligning with biological observations.

Contribution

It introduces a biophysically consistent DDFT-based model for tissue and tumor dynamics, incorporating multiple cell types and interactions, bridging microscopic and macroscopic scales.

Findings

Model reproduces tumor growth behaviors similar to metastatic and benign cases.

Tumor growth divergence depends on cell interaction parameters.

Model aligns with biological observations in suitable regimes.

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.