Immune checkpoint inhibitors (ICIs) have demonstrated significant clinical impact in improving overall survival of several malignancies associated with poor outcomes; however, only 20-40% of patients will show long-lasting survival. Further clarification of factors related to treatment response can support improvements in clinical outcome and guide the development of novel immune checkpoint therapies. In this article, we have provided an overview of the pharmacokinetic (PK) aspects related to current ICIs, which include target-mediated drug disposition and time-varying drug clearance. In response to the variation in treatment exposure of ICIs and the significant healthcare costs associated with these agents, arguments for both dose individualization and generalization are provided. We address important issues related to the efficacy and safety, the pharmacodynamics (PD), of ICIs, including exposure-response relationships related to clinical outcome. The unique PK and PD aspects of ICIs give rise to issues of confounding and suboptimal surrogate endpoints that complicate interpretation of exposure-response analysis. Biomarkers to identify patients benefiting from treatment with ICIs have been brought forward. However, validated biomarkers to monitor treatment response are currently lacking.

Recent clinical evidence revealed that the use of beta-blockers such as propranolol, prior to diagnosis or concurrently with chemotherapy, could increase relapse-free and overall survival in breast cancer patients. We therefore hypothesized that propranolol may be able to increase the efficacy of chemotherapy either through direct effects on cancer cells or via anti-angiogenic mechanisms. In vitro proliferation assay showed that propranolol (from 50-100 μM) induces dose-dependent anti-proliferative effects in a panel of 9 human cancer and “normal” cell lines. Matrigel assays revealed that propranolol displays potent anti-angiogenic properties at non-toxic concentrations (<50 μM) but exert no vascular-disrupting activity. Combining chemotherapeutic drugs, such as 5-fluorouracil (5-FU) or paclitaxel, with propranolol at the lowest effective concentration resulted in synergistic, additive or antagonistic effects on cell proliferation in vitro depending on the cell type and the dose of chemotherapy used. Interestingly, breast cancer and vascular endothelial cells were among the most responsive to these combinations. Furthermore, Matrigel assays indicated that low concentrations of propranolol (10 – 50 μM) potentiated the anti-angiogenic effects of 5-FU and paclitaxel. Using an orthotopic xenograft model of triple-negative breast cancer, based on injection of luciferase-expressing MDA-MB-231 cells in the mammary fat pad of nude mice, we showed that propranolol, when used alone, induced only transient anti-tumor effects, if at all, and did not increase median survival. However, the combination of propranolol with chemotherapy resulted in more profound and sustained anti-tumor effects and significantly increased the survival benefits induced by chemotherapy alone (+19% and +79% in median survival for the combination as compared with 5-FU alone and paclitaxel alone, respectively; p<0.05). Collectively our results show that propranolol can potentiate the anti-angiogenic effects and anti-tumor efficacy of chemotherapy. The current study, together with retrospective clinical data, strongly suggests that the use of propranolol concurrently with chemotherapy may improve the outcome of breast cancer patients, thus providing a strong rationale for the evaluation of this drug combination in prospective clinical studies.

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 linearquadratic 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 offtarget 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. Ó2016 AACR.