Mathematical modelling of cancer stem cell-targeted immunotherapy.


Journal

Mathematical biosciences
ISSN: 1879-3134
Titre abrégé: Math Biosci
Pays: United States
ID NLM: 0103146

Informations de publication

Date de publication:
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

108269

Informations de copyright

Copyright © 2019 Elsevier Inc. All rights reserved.

Auteurs

Daniel Sigal (D)

Schulich School of Medicine and Dentistry, University of Western Ontario, ON N6A 3K7 Canada.

Michelle Przedborski (M)

Department of Applied Mathematics, University of Waterloo, ON N2L 3G1.

Darshan Sivaloganathan (D)

Lewis-Sigler Institute for Integrative Genomics, Princeton University, NJ 08544 Canada.

Mohammad Kohandel (M)

Department of Applied Mathematics, University of Waterloo, ON N2L 3G1. Electronic address: kohandel@uwaterloo.ca.

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