Computational Modeling of Cancer Response to Oncolytic Virotherapy: Improving the Effectiveness of Viral Spread and Anti Tumor Efficacy

H. Lefraich ()
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H. Lefraich: University Hassan First, Laboratory (MISI), Faculty of Sciences and techniques, Department of Mathematics and Computer Science

A chapter in Trends in Biomathematics: Stability and Oscillations in Environmental, Social, and Biological Models, 2022, pp 287-309 from Springer

Abstract: Abstract Oncolytic viruses (OV) are genetically engineered viruses that can selectively infect cancer cells, multiply inside them, destroy them and spread to further tumor cells without causing harm to normal healthy cells. They could be used as a therapy approach for cancer treatment that is promising in principle, however the success of oncolytic virotherapy is dampened by the presence of the extracellular matrix (ECM). In fact, the ECM has been recognized as a major barrier for anti-tumor efficacy as it plays a pivotal role in inhibiting virus spread. In this work, we develop a new mathematical model that can improve understanding of the role of viral diffusivity to provide insights that can be useful for the further development of this therapy approach. The spatio-temporal model is formulated in terms of equations that take into account the interaction between uninfected cancer cells, infected cancer cells, extracellular matrix (ECM) and oncolytic virus. Finally, numerical investigations were carried out for different scenarios. For the considered parameter regimes, the numerical simulations show that the viral therapy leads to control and decrease of the overall tumor expansion

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-12515-7_16

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DOI: 10.1007/978-3-031-12515-7_16

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