Mathematical modelling of cancer stem cell-targeted immunotherapy.
Cancer immunotherapy
Mathematical modeling
Tumor heterogeneity
Journal
Mathematical biosciences
ISSN: 1879-3134
Titre abrégé: Math Biosci
Pays: United States
ID NLM: 0103146
Informations de publication
Date de publication:
12 2019
12 2019
Historique:
received:
15
07
2019
revised:
17
09
2019
accepted:
05
10
2019
pubmed:
18
10
2019
medline:
8
8
2020
entrez:
18
10
2019
Statut:
ppublish
Résumé
The cancer stem cell hypothesis states that tumors are heterogeneous and comprised of several different cell types that have a range of reproductive potentials. Cancer stem cells (CSCs), represent one class of cells that has both reproductive potential and the ability to differentiate. These cells are thought to drive the progression of aggressive and recurring cancers since they give rise to all other constituent cells within a tumor. With the development of immunotherapy in the last decade, the specific targeting of CSCs has become feasible and presents a novel therapeutic approach. In this paper, we construct a mathematical model to study how specific components of the immune system, namely dendritic cells and cytotoxic T-cells interact with different cancer cell types (CSCs and non-CSCs). Using a system of ordinary differential equations, we model the effects of immunotherapy, specifically dendritic cell vaccines and T-cell adoptive therapy, on tumor growth, with and without chemotherapy. The model reproduces several results observed in the literature, including temporal measurements of tumor size from in vivo experiments, and it is used to predict the optimal treatment schedule when combining different treatment modalities. Importantly, the model also demonstrates that chemotherapy increases tumorigenicity whereas CSC-targeted immunotherapy decreases it.
Identifiants
pubmed: 31622595
pii: S0025-5564(19)30510-3
doi: 10.1016/j.mbs.2019.108269
pii:
doi:
Substances chimiques
Cancer Vaccines
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
108269Informations de copyright
Copyright © 2019 Elsevier Inc. All rights reserved.