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Application of control theory in a delayed-infection and immune-evading oncolytic virotherapy

1 Department of Mathematics, College of Science, Yonsei University, Seoul, Korea
2 Département de mathématiques et de statistique, Université de Montréal, Montréal, Canada
3 School of Mathematics and Statistics, University of Sydney, Sydney, Australia
4 Department of Computer Science & Engineering, Yonsei University, Seoul, Korea

#,ΦThese authors contributed equally to this work.

Special Issues: Mathematical modeling of tumor heterogeneity

Oncolytic virotherapy is a promising cancer treatment that harnesses the power of viruses. Through genetic engineering, these viruses are cultivated to infect and destroy cancer cells. While this therapy has shown success in a range of clinical trials, an open problem in the field is to determine more effective perturbations of these viruses. In this work, we use a controlled therapy approach to determine the optimal treatment protocol for a delayed infection from an immune-evading, coated virus. We derive a system of partial differential equations to model the interaction between a growing tumour and this coated oncolytic virus. Using this system, we show that viruses with inhibited viral clearance and infectivity are more effective than uncoated viruses. We then consider a hierarchical level of coating that degrades over time and determine a nontrivial initial distribution of coating levels needed to produce the lowest tumour volume. Interestingly, we find that a bimodal mixture of thickly coated and thinly coated virus is necessary to achieve a minimum tumour size. Throughout this article we also consider the effects of immune clearance of the virus. We show how different immune responses instigate significantly different treatment outcomes.
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Keywords virus; oncolytic virotherapy; cancer; optimal control; partial differential equations

Citation: Taeyong Lee, Adrianne L. Jenner, Peter S. Kim, Jeehyun Lee. Application of control theory in a delayed-infection and immune-evading oncolytic virotherapy. Mathematical Biosciences and Engineering, 2020, 17(3): 2361-2383. doi: 10.3934/mbe.2020126

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