Mathematical Modeling of Cancer Immunotherapy and Its Synergy with Radiotherapy.
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. Cancer Res; 76(17); 4931-40. ©2016 AACR.
Aix Marseille University, SMARTc Unit, Inserm S 911 CRO2, Marseille, France.
Raphael
R
Serre
MONC team, Inria Bordeaux Sud-Ouest, Institut de Mathématiques de Bordeaux, Talence, France.
Sebastien
S
Benzekry
Department of Radiotherapy Oncology, CHU La Timone, Assistance Publique-Hopitaux Marseille, Marseille, France.
Laetitia
L
Padovani
Novartis Pharma, Basel, Switzerland.
Christophe
C
Meille
Aix 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.
Nicolas
N
André
Aix Marseille University, SMARTc Unit, Inserm S 911 CRO2, Marseille, France.
Joseph
J
Ciccolini
Aix Marseille University, SMARTc Unit, Inserm S 911 CRO2, Marseille, France. Multidisciplinary Oncology & Therapeutic Innovations Unit, Assistance Publique-Hopitaux Marseille, Marseille, France.
Fabrice
F
Barlesi
Department of Radiotherapy Oncology, CHU La Timone, Assistance Publique-Hopitaux Marseille, Marseille, France. dominique.barbolosi@univ-amu.fr xavier.muracciole@ap-hm.fr.
Xavier
X
Muracciole
Aix Marseille University, SMARTc Unit, Inserm S 911 CRO2, Marseille, France. dominique.barbolosi@univ-amu.fr xavier.muracciole@ap-hm.fr.
Dominique
D
Barbolosi
D000818:Animals; D003131:Combined Modality Therapy / Q000379:methods*; D006801:Humans; D007167:Immunotherapy / Q000379:methods*; D008962:Models, Theoretical; D009369:Neoplasms / Q000276:immunology / Q000628:therapy*; D011878:Radiotherapy / Q000379:methods*