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      The Optimal Radiation Dose to Induce Robust Systemic Anti-Tumor Immunity

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          Abstract

          The synergy of radiation and the immune system is currently receiving significant attention in oncology as numerous studies have shown that cancer irradiation can induce strong anti-tumor immune responses. It remains unclear, however, what are the best radiation fractionation protocols to maximize the therapeutic benefits of this synergy. Here, we present a novel mathematical model that can be used to predict and dissect the complexity of the immune-mediated response at multiple tumor sites after applying focal irradiation and systemic immunotherapy. We successfully calibrate the proposed framework with published experimental data, in which two tumors were grown in mice at two spatially-separated sites from which only one was irradiated using various radiation fractionation protocols with and without concurrent systemic immunotherapy. The proposed model is calibrated to fit the temporal dynamics of tumor volume at both sites and can predict changes in immune infiltration in the non-irradiated tumors. The model was then used to investigate additional radiation fractionation protocols. Model simulations suggest that the optimal radiation doses per fraction to maximize anti-tumor immunity are between 10 and 13 Gy, at least for the experimental setting used for model calibration. This work provides the framework for evaluating radiation fractionation protocols for radiation-induced immune-mediated systemic anti-tumor responses.

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          Most cited references24

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          Combining radiotherapy and cancer immunotherapy: a paradigm shift.

          The therapeutic application of ionizing radiation has been largely based on its cytocidal power combined with the ability to selectively target tumors. Radiotherapy effects on survival of cancer patients are generally interpreted as the consequence of improved local control of the tumor, directly decreasing systemic spread. Experimental data from multiple cancer models have provided sufficient evidence to propose a paradigm shift, whereby some of the effects of ionizing radiation are recognized as contributing to systemic antitumor immunity. Recent examples of objective responses achieved by adding radiotherapy to immunotherapy in metastatic cancer patients support this view. Therefore, the traditional palliative role of radiotherapy in metastatic disease is evolving into that of a powerful adjuvant for immunotherapy. This combination strategy adds to the current anticancer arsenal and offers opportunities to harness the immune system to extend survival, even among metastatic and heavily pretreated cancer patients. We briefly summarize key evidence supporting the role of radiotherapy as an immune adjuvant. A critical appraisal of the current status of knowledge must include potential immunosuppressive effects of radiation that can hamper its capacity to convert the irradiated tumor into an in situ, individualized vaccine. Moreover, we discuss some of the current challenges to translate this knowledge to the clinic as more trials testing radiation with different immunotherapies are proposed.
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            Local radiotherapy and granulocyte-macrophage colony-stimulating factor to generate abscopal responses in patients with metastatic solid tumours: a proof-of-principle trial.

            An abscopal response describes radiotherapy-induced immune-mediated tumour regression at sites distant to the irradiated field. Granulocyte-macrophage colony-stimulating factor is a potent stimulator of dendritic cell maturation. We postulated that the exploitation of the pro-immunogenic effects of radiotherapy with granulocyte-macrophage colony-stimulating factor might result in abscopal responses among patients with metastatic cancer.
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              Nonlinear dynamics of immunogenic tumors: parameter estimation and global bifurcation analysis.

              We present a mathematical model of the cytotoxic T lymphocyte response to the growth of an immunogenic tumor. The model exhibits a number of phenomena that are seen in vivo, including immunostimulation of tumor growth, "sneaking through" of the tumor, and formation of a tumor "dormant state". The model is used to describe the kinetics of growth and regression of the B-lymphoma BCL1 in the spleen of mice. By comparing the model with experimental data, numerical estimates of parameters describing processes that cannot be measured in vivo are derived. Local and global bifurcations are calculated for realistic values of the parameters. For a large set of parameters we predict that the course of tumor growth and its clinical manifestation have a recurrent profile with a 3- to 4-month cycle, similar to patterns seen in certain leukemias.
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                Author and article information

                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                29 October 2018
                November 2018
                : 19
                : 11
                : 3377
                Affiliations
                [1 ]Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Ks. Trojdena 4, 02-109 Warsaw, Poland
                [2 ]Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL 33612, USA; heiko.enderling@ 123456moffitt.org
                [3 ]Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL 33612, USA
                Author notes
                [* ]Correspondence: jpoleszczuk@ 123456ibib.waw.pl ; Tel.: +48-22-592-59-00 (ext. 307)
                Author information
                https://orcid.org/0000-0001-8758-7200
                https://orcid.org/0000-0002-9696-6410
                Article
                ijms-19-03377
                10.3390/ijms19113377
                6275030
                30380596
                3e70d104-836e-430b-b403-ea4773f9fa43
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 13 September 2018
                : 23 October 2018
                Categories
                Article

                Molecular biology
                abscopal effect,radiotherapy,immunotherapy,mathematical model
                Molecular biology
                abscopal effect, radiotherapy, immunotherapy, mathematical model

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