Literature DB >> 27302167

Mathematical Modeling of Cancer Immunotherapy and Its Synergy with Radiotherapy.

Raphael Serre1, Sebastien Benzekry2, Laetitia Padovani3, Christophe Meille4, Nicolas André5, Joseph Ciccolini1, Fabrice Barlesi6, Xavier Muracciole7, Dominique Barbolosi8.   

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. Cancer Res; 76(17); 4931-40. ©2016 AACR. ©2016 American Association for Cancer Research.

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Year:  2016        PMID: 27302167     DOI: 10.1158/0008-5472.CAN-15-3567

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  37 in total

1.  Immunologic Consequences of Sequencing Cancer Radiotherapy and Surgery.

Authors:  Juan Carlos López Alfonso; Jan Poleszczuk; Rachel Walker; Sungjune Kim; Shari Pilon-Thomas; Jose J Conejo-Garcia; Hatem Soliman; Brian Czerniecki; Louis B Harrison; Heiko Enderling
Journal:  JCO Clin Cancer Inform       Date:  2019-04

2.  Irradiation enhances dendritic cell potential antitumor activity by inducing tumor cell expressing TNF-α.

Authors:  Lijia Chang; Zhengzheng Zhang; Fang Chen; Wen Zhang; Shuang Song; Shuxia Song
Journal:  Med Oncol       Date:  2017-02-13       Impact factor: 3.064

3.  The Immune Checkpoint Kick Start: Optimization of Neoadjuvant Combination Therapy Using Game Theory.

Authors:  Jeffrey West; Mark Robertson-Tessi; Kimberly Luddy; Derek S Park; Drew F K Williamson; Cathal Harmon; Hung T Khong; Joel Brown; Alexander R A Anderson
Journal:  JCO Clin Cancer Inform       Date:  2019-02

4.  Durvalumab after chemoradiotherapy in stage III non-small cell lung cancer.

Authors:  Pascale Tomasini; Laurent Greillier; Arnaud Boyer; Arnaud Jeanson; Fabrice Barlesi
Journal:  J Thorac Dis       Date:  2018-04       Impact factor: 2.895

5.  Optimization of combination therapy for chronic myeloid leukemia with dosing constraints.

Authors:  Helen Moore; Lewis Strauss; Urszula Ledzewicz
Journal:  J Math Biol       Date:  2018-07-10       Impact factor: 2.259

Review 6.  Mathematical modeling of tumor-immune cell interactions.

Authors:  Grace E Mahlbacher; Kara C Reihmer; Hermann B Frieboes
Journal:  J Theor Biol       Date:  2019-03-02       Impact factor: 2.691

Review 7.  Molecular imaging and radionuclide therapy of pheochromocytoma and paraganglioma in the era of genomic characterization of disease subgroups.

Authors:  David Taïeb; Abhishek Jha; Giorgio Treglia; Karel Pacak
Journal:  Endocr Relat Cancer       Date:  2019-11       Impact factor: 5.678

Review 8.  New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling.

Authors:  Keesha E Erickson; Oleksii S Rukhlenko; Richard G Posner; William S Hlavacek; Boris N Kholodenko
Journal:  Semin Cancer Biol       Date:  2018-03-05       Impact factor: 15.707

Review 9.  Addressing current challenges in cancer immunotherapy with mathematical and computational modelling.

Authors:  Anna Konstorum; Anthony T Vella; Adam J Adler; Reinhard C Laubenbacher
Journal:  J R Soc Interface       Date:  2017-06       Impact factor: 4.118

10.  A tumor-immune interaction model for hepatocellular carcinoma based on measured lymphocyte counts in patients undergoing radiotherapy.

Authors:  Wonmo Sung; Clemens Grassberger; Aimee Louise McNamara; Lucas Basler; Stefanie Ehrbar; Stephanie Tanadini-Lang; Theodore S Hong; Harald Paganetti
Journal:  Radiother Oncol       Date:  2020-07-15       Impact factor: 6.280

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