Targeting stem cells with oncolytic viruses: a mathematical modelling approach

Intratumoural epigenetic heterogeneity, which affects the outcome of many cancer treatments, results from stem cell-differentiated cell hierarchy. Cancer stem cells, also known as tumour-initiating cells, are a pluripotent subpopulation of tumour cells capable of creating a tumour clone through self-renewal and differentiation. Oncolytic viral therapy is a category of cancer therapeutics with high specificity in targeting cancer cells while leaving normal cells unharmed. More recently, oncolytic viruses have been developed that target tumour initiating cells with some promising results. The question is what values for virus infectivity and stem cell specificity result in the best clinical outcome. To address this question, we model interactions between uninfected and infected cancer cells, within a stem cell-differentiated cell hierarchy, during oncolytic viral therapy. We calculate the basic reproduction number and use it to constrain the infectivity rates of initiating and differentiated cancer cells. Long-term tumour shrinkage is observable when this constraint is met; otherwise, treatment fails. Our results suggest that stem cell specificity of an oncolytic virus depends both on the average infectivity and mitotic rates of infected cells. There is a positive correlation between the average infectivity rate and stem cell specificity for nonmitotic infected cells: when average infectivity is high, an oncolytic virus with higher stem cell specificity leads to smaller tumours. In contrast, when average infectivity is low, the minimum tumour size is obtained when an oncolytic virus with higher potency targeting differentiated cells is used. For the perfect stem cell targeting regimen, we derive the condition that leads to the minimum tumour size.

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Publication Details

Journal
Mathematical Biosciences & Engineering
Published
2025-01-01
DOI
https://doi.org/10.3934/mbe.2025090
Primary Topic
Virus-based gene therapy research
Type
article
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article

Targeting stem cells with oncolytic viruses: a mathematical modelling approach

Kamran Kaveh, James Watmough, Sana Jahedi
Mathematical Biosciences & Engineering
Virus-based gene therapy research
article

Targeting stem cells with oncolytic viruses: a mathematical modelling approach

Kamran Kaveh, James Watmough, Sana Jahedi
article en

Abstract

Intratumoural epigenetic heterogeneity, which affects the outcome of many cancer treatments, results from stem cell-differentiated cell hierarchy. Cancer stem cells, also known as tumour-initiating cells, are a pluripotent subpopulation of tumour cells capable of creating a tumour clone through self-renewal and differentiation. Oncolytic viral therapy is a category of cancer therapeutics with high specificity in targeting cancer cells while leaving normal cells unharmed. More recently, oncolytic viruses have been developed that target tumour initiating cells with some promising results. The question is what values for virus infectivity and stem cell specificity result in the best clinical outcome. To address this question, we model interactions between uninfected and infected cancer cells, within a stem cell-differentiated cell hierarchy, during oncolytic viral therapy. We calculate the basic reproduction number and use it to constrain the infectivity rates of initiating and differentiated cancer cells. Long-term tumour shrinkage is observable when this constraint is met; otherwise, treatment fails. Our results suggest that stem cell specificity of an oncolytic virus depends both on the average infectivity and mitotic rates of infected cells. There is a positive correlation between the average infectivity rate and stem cell specificity for nonmitotic infected cells: when average infectivity is high, an oncolytic virus with higher stem cell specificity leads to smaller tumours. In contrast, when average infectivity is low, the minimum tumour size is obtained when an oncolytic virus with higher potency targeting differentiated cells is used. For the perfect stem cell targeting regimen, we derive the condition that leads to the minimum tumour size.

Mathematical Biosciences & EngineeringVol. 22(9)
University of New Brunswick (CA), University of Minnesota (US), Oakland University (US), University of Maryland, College Park (US)
Openalex Percentile: Top 79%
Virus-based gene therapy research
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