방사선의학 웹진

바로가기  >

Abstract

Combining radiotherapy with immune checkpoint blockade may offer considerable therapeutic impact if the immunosuppressive nature of the tumor microenvironment (TME) can be relieved. In this study, we used mathematical models, which can illustrate the potential synergism between immune checkpoint inhibitors and radiotherapy. A discrete-time pharmacodynamic model of the combination of radiotherapy with inhibitors of the PD1-PDL1 axis and/or the CTLA4 pathway is described. This mathematical framework describes how a growing tumor first elicits and then inhibits an antitumor immune response. This antitumor immune response is described by a primary and a secondary (or memory) response. The primary immune response appears first and is inhibited by the PD1-PDL1 axis, whereas the secondary immune response happens next and is inhibited by the CTLA4 pathway. The effects of irradiation are described by a modified version of the linear-quadratic model. This modeling offers an explanation for the reported biphasic relationship between the size of a tumor and its immunogenicity, as measured by the abscopal effect (an off-target immune response). Furthermore, it explains why discontinuing immunotherapy may result in either tumor recurrence or a durably sustained response. Finally, it describes how synchronizing immunotherapy and radiotherapy can produce synergies. The ability of the model to forecast pharmacodynamic endpoints was validated retrospectively by checking that it could describe data from experimental studies, which investigated the combination of radiotherapy with immune checkpoint inhibitors. In summary, a model such as this could be further used as a simulation tool to facilitate decision making about optimal scheduling of immunotherapy with radiotherapy and perhaps other types of anticancer therapies. 

​Major Findings

To help the design and efficacy analysis of combined anticancer therapies, this article proposes a set of mathematical equations that describe the pharmacodynamics of radiotherapy in combination with two paradigmatic immunotherapies, namely the blockers of the PD1–PDL1 axis and of the CTLA4 pathway. These equations explain several experimental results reported in preclinical and clinical settings. Together with published pharmacokinetic models, they pave the way for the efficient in silico design and optimization of combined anticancer therapies mixing immunotherapy and radiotherapy; this approach is currently under active investigation because of its strong potential synergism.​ 

​Author information​

Serre R1, Benzekry S2, Padovani L3, Meille C4, André N5, Ciccolini J1, Barlesi F6, Muracciole X7, Barbolosi D8.

1Aix Marseille University, SMARTc Unit, Inserm S 911 CRO2, Marseille, France.

2MONC team, Inria Bordeaux Sud-Ouest, Institut de Mathématiques de Bordeaux, Talence, France.

3Department of Radiotherapy Oncology, CHU La Timone, Assistance Publique-Hopitaux Marseille, Marseille, France.

4Novartis Pharma, Basel, Switzerland.

5Aix Marseille University, SMARTc Unit, Inserm S 911 CRO2, Marseille, France. Department of Pediatric Hematology and Oncology, CHU La Timone, Assistance Publique-Hopitaux Marseille, Marseille, France. Centre d'Essais Précoces Cancérologie Marseille (CEPCM), CHU La Timone, Assistance Publique-Hopitaux Marseille, Marseille, France.

6Aix Marseille University, SMARTc Unit, Inserm S 911 CRO2, Marseille, France. Multidisciplinary Oncology & Therapeutic Innovations Unit, Assistance Publique-Hopitaux Marseille, Marseille, France.

7Department of Radiotherapy Oncology, CHU La Timone, Assistance Publique-Hopitaux Marseille, Marseille, France. dominique.barbolosi@univ-amu.fr xavier.muracciole@ap-hm.fr.

8Aix Marseille University, SMARTc Unit, Inserm S 911 CRO2, Marseille, France. dominique.barbolosi@univ-amu.fr xavier.muracciole@ap-hm.fr.