TY - CHAP
T1 - Spatio-Temporal-Structural Approaches in Cancer and Immunity Focussed on Oncolytic Viral Therapies
AU - Hodgkinson, Arran
AU - Trucu, Dumitru
N1 - Copyright © 2025 by World Scientific Publishing Europe Ltd.
PY - 2024/12
Y1 - 2024/12
N2 - Although much progress has been made in the targeted treatment of cancer cells, for which mathematical modelling has played an active role, resistance phenomena continue to confound success in this field. Within this context, oncolytic viruses have demonstrated promising outcomes by targeting cancerous cells in situ, but interacting negatively with the innate immune interferon (IFN) response, which acts to reduce viral replication and persistence. Building on existing work in spatiotemporal-structural modelling, we take the case of IFN-mediated, temporally local, acquired resistance to oncolytic viral (OV) therapies for use in oncology. Building a spatio-temporal-structural model of the cell-scale dynamics of OV uptake and IFN-based innate immune signalling, within its spatial context, we study and compare two scenarios: one in which cells are incapable of mounting such an immune response and one in which they are capable. In the former case, the cancer cell population proceeds asymptotically towards zero, with the OV multiplying within the cell and causing almost complete lysis among the population. In the latter case, the onset of infection causes IFN to be secreted from infected cells and, upon binding to neighbouring cells, causes the shutdown of the cells’ replicative structures and protects sufficient numbers of cells from OV lysis to allow a regrowth of the population or (resistance phenomena). In all, the heterogeneity and correlated behaviours modelled through spatio-temporal-structural modelling techniques allows for distributed dynamics among a cell population and, in so doing, demonstrates predictive potential beyond its immediate uses and into more complex biological phenomena.
AB - Although much progress has been made in the targeted treatment of cancer cells, for which mathematical modelling has played an active role, resistance phenomena continue to confound success in this field. Within this context, oncolytic viruses have demonstrated promising outcomes by targeting cancerous cells in situ, but interacting negatively with the innate immune interferon (IFN) response, which acts to reduce viral replication and persistence. Building on existing work in spatiotemporal-structural modelling, we take the case of IFN-mediated, temporally local, acquired resistance to oncolytic viral (OV) therapies for use in oncology. Building a spatio-temporal-structural model of the cell-scale dynamics of OV uptake and IFN-based innate immune signalling, within its spatial context, we study and compare two scenarios: one in which cells are incapable of mounting such an immune response and one in which they are capable. In the former case, the cancer cell population proceeds asymptotically towards zero, with the OV multiplying within the cell and causing almost complete lysis among the population. In the latter case, the onset of infection causes IFN to be secreted from infected cells and, upon binding to neighbouring cells, causes the shutdown of the cells’ replicative structures and protects sufficient numbers of cells from OV lysis to allow a regrowth of the population or (resistance phenomena). In all, the heterogeneity and correlated behaviours modelled through spatio-temporal-structural modelling techniques allows for distributed dynamics among a cell population and, in so doing, demonstrates predictive potential beyond its immediate uses and into more complex biological phenomena.
U2 - 10.1142/9781800614383_0007
DO - 10.1142/9781800614383_0007
M3 - Chapter (peer-reviewed)
SN - 9781800614376
SP - 181
EP - 212
BT - Modelling and Computational Approaches for Multi-Scale Phenomena in Cancer Research
A2 - Eftimie, Raluca
A2 - Trucu, Dumitru
PB - World Scientific
CY - Singapore
ER -