Literature DB >> 31622595

Mathematical modelling of cancer stem cell-targeted immunotherapy.

Daniel Sigal1, Michelle Przedborski2, Darshan Sivaloganathan3, Mohammad Kohandel4.   

Abstract

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.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cancer immunotherapy; Mathematical modeling; Tumor heterogeneity

Year:  2019        PMID: 31622595     DOI: 10.1016/j.mbs.2019.108269

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  2 in total

1.  Dynamics of an Antitumour Model with Pulsed Radioimmunotherapy.

Authors:  Gang Wang; Ming Yi; Sanyi Tang
Journal:  Comput Math Methods Med       Date:  2022-05-29       Impact factor: 2.809

2.  Understanding the effect of measurement time on drug characterization.

Authors:  Hope Murphy; Gabriel McCarthy; Hana M Dobrovolny
Journal:  PLoS One       Date:  2020-05-14       Impact factor: 3.240

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.