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Updated: Dec 25, 2025
Paramyxoviruses for Tumor-targeted Immunomodulation: Design and Evaluation Ex Vivo
Published on: January 7, 2019
Application of control theory in a delayed-infection and immune-evading oncolytic virotherapy
Taeyong Lee1, Adrianne L Jenner2, Peter S Kim3
1Department of Mathematics, College of Science, Yonsei University, Seoul, Korea.
Abstract:
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.
Insights
Optimizing oncolytic virotherapy, this study reveals that coated viruses with controlled infectivity and clearance are more effective. A bimodal mixture of coated viruses is crucial for minimizing tumor volume and overcoming immune responses.
Area of Science:
- Oncology
- Virology
- Mathematical Biology
Background:
- Oncolytic virotherapy uses engineered viruses to target and destroy cancer cells.
- Clinical trials show promise, but optimizing viral perturbations remains a challenge.
- Understanding virus-host interactions, including immune evasion, is key to improving efficacy.
Purpose of the Study:
- To determine optimal treatment protocols for coated oncolytic viruses.
- To model the interaction between tumors and immune-evading, coated oncolytic viruses.
- To investigate the impact of viral coating and immune clearance on treatment outcomes.
Main Methods:
- Derivation of a system of partial differential equations to model tumor-virus dynamics.
- Simulation of coated virus behavior, including degradation and infectivity.
- Analysis of various immune response scenarios and their effect on viral clearance.
Main Results:
- Inhibited viral clearance and infectivity enhance the effectiveness of coated viruses over uncoated ones.
- A hierarchical coating that degrades over time requires a specific initial distribution for optimal tumor reduction.
- A bimodal mixture of thickly and thinly coated viruses is necessary to achieve minimal tumor volume.
Conclusions:
- Controlled viral properties, such as coating and infectivity, significantly impact oncolytic virotherapy success.
- Viral coating strategies, particularly bimodal mixtures, offer a promising avenue for enhanced cancer treatment.
- Immune response modulation is critical for maximizing the therapeutic potential of oncolytic viruses.
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