Modelling the Immune Response to Cancer: An Individual-Based Approach Accounting for the Difference in Movement Between Inactive and Activated T Cells
Authored by Tommaso Lorenzi, Mark A J Chaplain, Fiona R Macfarlane
Date Published: 2018
DOI: 10.1007/s11538-018-0412-8
Sponsors:
United Kingdom Engineering and Physical Sciences Research Council (EPSRC)
Platforms:
No platforms listed
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
Model code not found
Abstract
A growing body of experimental evidence indicates that immune cells move
in an unrestricted search pattern if they are in the pre-activated
state, whilst they tend to stay within a more restricted area upon
activation induced by the presence of tumour antigens. This change in
movement is not often considered in the existing mathematical models of
the interactions between immune cells and cancer cells. With the aim to
fill such a gap in the existing literature, in this work we present a
spatially structured individual-based model of tumour-immune competition
that takes explicitly into account the difference in movement between
inactive and activated immune cells. In our model, a L,vy walk is used
to capture the movement of inactive immune cells, whereas Brownian
motion is used to describe the movement of antigen-activated immune
cells. The effects of activation of immune cells, the proliferation of
cancer cells and the immune destruction of cancer cells are also
modelled. We illustrate the ability of our model to reproduce
qualitatively the spatial trajectories of immune cells observed in
experimental data of single-cell tracking. Computational simulations of
our model further clarify the conditions for the onset of a successful
immune action against cancer cells and may suggest possible targets to
improve the efficacy of cancer immunotherapy. Overall, our theoretical
work highlights the importance of taking into account spatial
interactions when modelling the immune response to cancer cells.
Tags
individual-based models
Migration
lymphocytes
Brownian motion
Dendritic cells
Vaccination
Mathematical-model
Recognition
Ligand
Induction
Solid tumor
Destruction
Cancer-immune competition
Spatial movement
Levy walk
Metastatic melanoma
Immunotherapy
Tumors