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      Comparative analysis of TCR and CAR signaling informs CAR designs with superior antigen sensitivity and in vivo function

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          Abstract

          Chimeric antigen receptor (CAR)–modified T cell therapy is effective in treating lymphomas, leukemias, and multiple myeloma in which the tumor cells express high amounts of target antigen. However, achieving durable remission for these hematological malignancies and extending CAR T cell therapy to patients with solid tumors will require receptors that can recognize and eliminate tumor cells with a low density of target antigen. Although CARs were designed to mimic T cell receptor (TCR) signaling, TCRs are at least 100-fold more sensitive to antigen. To design a CAR with improved antigen sensitivity, we directly compared TCR and CAR signaling in primary human T cells. Global phosphoproteomic analysis revealed that key T cell signaling proteins—such as CD3δ, CD3ε, and CD3γ, which comprise a portion of the T cell co-receptor, as well as the TCR adaptor protein LAT—were either not phosphorylated or were only weakly phosphorylated by CAR stimulation. Modifying a commonplace 4-1BB/CD3ζ CAR sequence to better engage CD3ε and LAT using embedded CD3ε or GRB2 domains resulted in enhanced T cell activation in vitro in settings of a low density of antigen, and improved efficacy in in vivo models of lymphoma, leukemia, and breast cancer. These CARs represent examples of alterations in receptor design that were guided by in-depth interrogation of T cell signaling.

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          Most cited references76

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          MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

          Efficient analysis of very large amounts of raw data for peptide identification and protein quantification is a principal challenge in mass spectrometry (MS)-based proteomics. Here we describe MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. Using correlation analysis and graph theory, MaxQuant detects peaks, isotope clusters and stable amino acid isotope-labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space. By integrating multiple mass measurements and correcting for linear and nonlinear mass offsets, we achieve mass accuracy in the p.p.b. range, a sixfold increase over standard techniques. We increase the proportion of identified fragmentation spectra to 73% for SILAC peptide pairs via unambiguous assignment of isotope and missed-cleavage state and individual mass precision. MaxQuant automatically quantifies several hundred thousand peptides per SILAC-proteome experiment and allows statistically robust identification and quantification of >4,000 proteins in mammalian cell lysates.
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            The Perseus computational platform for comprehensive analysis of (prote)omics data.

            A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.
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              Axicabtagene Ciloleucel CAR T-Cell Therapy in Refractory Large B-Cell Lymphoma

              In a phase 1 trial, axicabtagene ciloleucel (axi-cel), an autologous anti-CD19 chimeric antigen receptor (CAR) T-cell therapy, showed efficacy in patients with refractory large B-cell lymphoma after the failure of conventional therapy.
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                Author and article information

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                Journal
                Science Signaling
                Sci. Signal.
                American Association for the Advancement of Science (AAAS)
                1945-0877
                1937-9145
                August 24 2021
                August 24 2021
                August 24 2021
                August 24 2021
                : 14
                : 697
                : eabe2606
                Affiliations
                [1 ]Program in Immunology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
                [2 ]Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
                [3 ]Department of Biophysics, University of Michigan, Ann Arbor, MI 48109, USA.
                [4 ]Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
                [5 ]Cape Town HVTN Immunology Laboratory, Hutchinson Centre Research Institute of South Africa, NPC (HCRISA), Cape Town 8001, South Africa.
                [6 ]Department of Medicine, University of Washington School of Medicine, Seattle, WA 98195, USA.
                Article
                10.1126/scisignal.abe2606
                34429382
                c8feb2ef-e026-4ed5-a219-9e31e0e8661f
                © 2021

                https://www.sciencemag.org/about/science-licenses-journal-article-reuse

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