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Combination therapy for cancer with oncolytic virus and checkpoint inhibitor: A mathematical model
1Mathematical Bioscience Institute & Department of Mathematics, Ohio State University, Columbus, OH, United States of America.
Abstract:
Oncolytic virus (OV) is a replication competent virus that selectively invades cancer cells; as these cells die under the viral burden, the released virus particles proceed to infect other cancer cells. Oncolytic viruses are designed to also be able to stimulate the anticancer immune response. Thus, one may represent an OV by two parameters: its replication potential and its immunogenicity. In this paper we consider a combination therapy with OV and a checkpoint inhibitor, anti-PD-1. We evaluate the efficacy of the combination therapy in terms of the tumor volume at some later time, for example, 6 months from initial treatment. Since T cells kill not only virus-free cancer cells but also virus-infected cancer cells, the following question arises: Does increasing the amount of the checkpoint inhibitor always improve the efficacy? We address this question, by a mathematical model consisting of a system of partial differential equations. We use the model to construct, by simulations, an efficacy map in terms of the doses of the checkpoint inhibitor and the OV injection. We show that there are regions in the map where an increase in the checkpoint inhibitor actually decreases the efficacy of the treatment. We also construct efficacy maps with checkpoint inhibitor vs. the replication potential of the virus that show the same antagonism, namely, an increase in the checkpoint inhibitor may actually decrease the efficacy. These results have implications for clinical trials.
Insights
Combining oncolytic viruses (OVs) with checkpoint inhibitors like anti-PD-1 shows complex efficacy. Mathematical modeling reveals that increasing anti-PD-1 dosage can sometimes decrease treatment effectiveness against cancer.
Area of Science:
- Oncology
- Virology
- Immunology
- Mathematical Biology
Background:
- Oncolytic viruses (OVs) are engineered to selectively infect and kill cancer cells while stimulating an anticancer immune response.
- Combination therapy with OVs and checkpoint inhibitors, such as anti-PD-1, is a promising strategy in cancer treatment.
- The interplay between OV replication, immunogenicity, and immune checkpoint blockade requires detailed investigation.
Purpose of the Study:
- To evaluate the efficacy of combination therapy using oncolytic viruses and anti-PD-1 checkpoint inhibitors.
- To address whether increasing anti-PD-1 dosage consistently improves treatment efficacy in mathematical models.
- To explore the relationship between OV properties (replication potential, immunogenicity) and combination therapy outcomes.
Main Methods:
- Development of a mathematical model comprising a system of partial differential equations to simulate treatment dynamics.
- Construction of efficacy maps through simulations, correlating treatment parameters (OV dose, anti-PD-1 dose) with tumor volume.
- Analysis of efficacy maps to identify potential antagonistic effects between OV and anti-PD-1.
Main Results:
- Simulation results reveal specific regions in the efficacy map where higher doses of anti-PD-1 lead to decreased treatment efficacy.
- Efficacy maps comparing anti-PD-1 dosage against OV replication potential demonstrate similar antagonistic effects.
- The study identifies a non-linear relationship where increased checkpoint inhibition does not always equate to improved outcomes.
Conclusions:
- The combination of oncolytic viruses and checkpoint inhibitors can exhibit complex, non-intuitive efficacy profiles.
- Mathematical modeling is crucial for understanding these dynamics and predicting optimal therapeutic strategies.
- Findings have significant implications for the design and interpretation of clinical trials involving OV and anti-PD-1 therapies.
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