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      Understanding the Dynamics of T-Cell Activation in Health and Disease Through the Lens of Computational Modeling

      , PhD 1 , , PhD 1 , , PhD 1

      JCO clinical cancer informatics

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          Abstract

          T cells in the immune system are activated by binding to foreign peptides (from an external pathogen) or mutant peptide (derived from endogenous proteins) displayed on the surface of a diseased cell. This triggers a series of intracellular signaling pathways, which ultimately dictate the response of the T cell. The insights from computational models have greatly improved our understanding of the mechanisms that control T-cell activation. In this review, we focus on the use of ordinary differential equation–based mechanistic models to study T-cell activation. We highlight several examples that demonstrate the models’ utility in answering specific questions related to T-cell activation signaling, from antigen discrimination to the feedback mechanisms that initiate transcription factor activation. In addition, we describe other modeling approaches that can be combined with mechanistic models to bridge time scales and better understand how intracellular signaling events, which occur on the order of seconds to minutes, influence phenotypic responses of T-cell activation, which occur on the order of hours to days. Overall, through concrete examples, we emphasize how computational modeling can be used to enable the rational design and optimization of immunotherapies.

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          Most cited references 80

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          The basic principles of chimeric antigen receptor design.

          Chimeric antigen receptors (CAR) are recombinant receptors that provide both antigen-binding and T-cell-activating functions. A multitude of CARs has been reported over the past decade, targeting an array of cell surface tumor antigens. Their biologic functions have dramatically changed following the introduction of tripartite receptors comprising a costimulatory domain, termed second-generation CARs. These have recently shown clinical benefit in patients treated with CD19-targeted autologous T cells. CARs may be combined with costimulatory ligands, chimeric costimulatory receptors, or cytokines to further enhance T-cell potency, specificity, and safety. CARs represent a new class of drugs with exciting potential for cancer immunotherapy. CARs are a new class of drugs with great potential for cancer immunotherapy. Upon their expression in T lymphocytes, CARs direct potent, targeted immune responses that have recently shown encouraging clinical outcomes in a subset of patients with B-cell malignancies. This review focuses on the design of CARs, including the requirements for optimal antigen recognition and different modalities to provide costimulatory support to targeted T cells, which include the use of second- and third generation CARs, costimulatory ligands, chimeric costimulatory receptors, and cytokines. ©2013 AACR.
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            Kinetic proofreading: a new mechanism for reducing errors in biosynthetic processes requiring high specificity.

             John Hopfield (1974)
            The specificity with which the genetic code is read in protein synthesis, and with which other highly specific biosynthetic reactions take place, can be increased above the level available from free energy differences in intermediates or kinetic barriers by a process defined here as kinetic proofreading. A simple kinetic pathway is described which results in this proofreading when the reaction is strongly but nonspecifically driven, e.g., by phosphate hydrolysis. Protein synthesis, amino acid recognition, and DNA replication, all exhibit the features of this model. In each case, known reactions which otherwise appear to be useless or deleterious complications are seen to be essential to the proofreading function.
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              Engineered T cells: the promise and challenges of cancer immunotherapy.

              The immune system evolved to distinguish non-self from self to protect the organism. As cancer is derived from our own cells, immune responses to dysregulated cell growth present a unique challenge. This is compounded by mechanisms of immune evasion and immunosuppression that develop in the tumour microenvironment. The modern genetic toolbox enables the adoptive transfer of engineered T cells to create enhanced anticancer immune functions where natural cancer-specific immune responses have failed. Genetically engineered T cells, so-called 'living drugs', represent a new paradigm in anticancer therapy. Recent clinical trials using T cells engineered to express chimeric antigen receptors (CARs) or engineered T cell receptors (TCRs) have produced stunning results in patients with relapsed or refractory haematological malignancies. In this Review we describe some of the most recent and promising advances in engineered T cell therapy with a particular emphasis on what the next generation of T cell therapy is likely to entail.
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                Author and article information

                Journal
                101708809
                46709
                JCO Clin Cancer Inform
                JCO Clin Cancer Inform
                JCO clinical cancer informatics
                2473-4276
                2 June 2019
                January 2019
                26 June 2019
                : 3
                : 1-8
                Affiliations
                [1 ]University of Southern California, Los Angeles, CA
                Author notes

                AUTHOR CONTRIBUTIONS

                Conception and design: All authors

                Financial support: Jennifer A. Rohrs, Pin Wang

                Administrative support: Pin Wang

                Data analysis and interpretation: Pin Wang, Stacey D. Finley

                Manuscript writing: All authors

                Final approval of manuscript: All authors

                Accountable for all aspects of the work: All authors

                CORRESPONDING AUTHOR Stacey D. Finley, PhD, 1042 Downey Way, DRB 140, Los Angeles, CA 90089; sfinley@ 123456usc.edu .
                Article
                NIHMS1032908
                10.1200/CCI.18.00057
                6593125
                30689404

                Creative Commons Attribution Non-Commercial No Derivatives 4.0 License

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