A biomathematical model of tumor response to radioimmunotherapy with $\alpha$PDL1 and $\alpha$CTLA4

TL;DR

This paper introduces a biomathematical model that simulates tumor response to combined radiotherapy and immunotherapy, aiding in understanding mechanisms and optimizing treatment strategies.

Contribution

The study develops a novel biomathematical model incorporating immune effects into tumor response to radioimmunotherapy, fitting preclinical data and exploring optimal treatment schedules.

Findings

Model fits preclinical tumor volume data.

Understanding biological delays is crucial for treatment optimization.

Model suggests timing and drug kinetics are key for effective schedules.

Abstract

There is evidence of synergy between radiotherapy and immunotherapy. Radiotherapy can increase liberation of tumor antigens, causing activation of antitumor T-cells. This effect can be boosted with immunotherapy. Radioimmunotherapy has potential to increase tumor control rates. Biomathematical models of response to radioimmunotherapy may help on understanding of the mechanisms affecting response, and assist clinicians on the design of optimal treatment strategies. In this work we present a biomathematical model of tumor response to radioimmunotherapy. The model uses the linear-quadratic response of tumor cells to radiation (or variation of it), and builds on previous developments to include the radiation-induced immune effect. We have focused this study on the combined effect of radiotherapy and $\alpha$PDL1/$\alpha$CTLA4 therapies. The model can fit preclinical data of volume dynamics and control obtained with different dose fractionations and $\alpha$PDL1/$\alpha$CTLA4. A biomathematical study of optimal combination strategies suggests that a good understanding of the involved biological delays, the biokinetics of the immunotherapy drug, and the interplay between them, may be of paramount importance to design optimal radioimmunotherapy schedules. Biomathematical models like the one we present can help to interpret experimental data on the synergy between radiotherapy and immunotherapy, and to assist in the design of more effective treatments.