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      Direct identification of clinically relevant neoepitopes presented on native human melanoma tissue by mass spectrometry

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          Abstract

          Although mutations may represent attractive targets for immunotherapy, direct identification of mutated peptide ligands isolated from human leucocyte antigens (HLA) on the surface of native tumour tissue has so far not been successful. Using advanced mass spectrometry (MS) analysis, we survey the melanoma-associated immunopeptidome to a depth of 95,500 patient-presented peptides. We thereby discover a large spectrum of attractive target antigen candidates including cancer testis antigens and phosphopeptides. Most importantly, we identify peptide ligands presented on native tumour tissue samples harbouring somatic mutations. Four of eleven mutated ligands prove to be immunogenic by neoantigen-specific T-cell responses. Moreover, tumour-reactive T cells with specificity for selected neoantigens identified by MS are detected in the patient's tumour and peripheral blood. We conclude that direct identification of mutated peptide ligands from primary tumour material by MS is possible and yields true neoepitopes with high relevance for immunotherapeutic strategies in cancer.

          Abstract

          Neoantigens determine anti-cancer immunoreactivity and are important functional targets for immunotherapy. Here, the authors use deep mass spectrometry to characterize neoepitopes from human melanoma tissue and show the presence of tumour-reactive T cells with specificity for selected neoantigens.

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          Most cited references31

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          Predicting immunogenic tumour mutations by combining mass spectrometry and exome sequencing.

          Human tumours typically harbour a remarkable number of somatic mutations. If presented on major histocompatibility complex class I molecules (MHCI), peptides containing these mutations could potentially be immunogenic as they should be recognized as 'non-self' neo-antigens by the adaptive immune system. Recent work has confirmed that mutant peptides can serve as T-cell epitopes. However, few mutant epitopes have been described because their discovery required the laborious screening of patient tumour-infiltrating lymphocytes for their ability to recognize antigen libraries constructed following tumour exome sequencing. We sought to simplify the discovery of immunogenic mutant peptides by characterizing their general properties. We developed an approach that combines whole-exome and transcriptome sequencing analysis with mass spectrometry to identify neo-epitopes in two widely used murine tumour models. Of the >1,300 amino acid changes identified, ∼13% were predicted to bind MHCI, a small fraction of which were confirmed by mass spectrometry. The peptides were then structurally modelled bound to MHCI. Mutations that were solvent-exposed and therefore accessible to T-cell antigen receptors were predicted to be immunogenic. Vaccination of mice confirmed the approach, with each predicted immunogenic peptide yielding therapeutically active T-cell responses. The predictions also enabled the generation of peptide-MHCI dextramers that could be used to monitor the kinetics and distribution of the anti-tumour T-cell response before and after vaccination. These findings indicate that a suitable prediction algorithm may provide an approach for the pharmacodynamic monitoring of T-cell responses as well as for the development of personalized vaccines in cancer patients.
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            Gapped sequence alignment using artificial neural networks: application to the MHC class I system.

            Many biological processes are guided by receptor interactions with linear ligands of variable length. One such receptor is the MHC class I molecule. The length preferences vary depending on the MHC allele, but are generally limited to peptides of length 8-11 amino acids. On this relatively simple system, we developed a sequence alignment method based on artificial neural networks that allows insertions and deletions in the alignment.
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              Cardiovascular toxicity and titin cross-reactivity of affinity-enhanced T cells in myeloma and melanoma.

              An obstacle to cancer immunotherapy has been that the affinity of T-cell receptors (TCRs) for antigens expressed in tumors is generally low. We initiated clinical testing of engineered T cells expressing an affinity-enhanced TCR against HLA-A*01-restricted MAGE-A3. Open-label protocols to test the TCRs for patients with myeloma and melanoma were initiated. The first two treated patients developed cardiogenic shock and died within a few days of T-cell infusion, events not predicted by preclinical studies of the high-affinity TCRs. Gross findings at autopsy revealed severe myocardial damage, and histopathological analysis revealed T-cell infiltration. No MAGE-A3 expression was detected in heart autopsy tissues. Robust proliferation of the engineered T cells in vivo was documented in both patients. A beating cardiomyocyte culture generated from induced pluripotent stem cells triggered T-cell killing, which was due to recognition of an unrelated peptide derived from the striated muscle-specific protein titin. These patients demonstrate that TCR-engineered T cells can have serious and not readily predictable off-target and organ-specific toxicities and highlight the need for improved methods to define the specificity of engineered TCRs.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group
                2041-1723
                21 November 2016
                2016
                : 7
                : 13404
                Affiliations
                [1 ]Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry , Am Klopferspitz 18, Martinsried 82152, Germany
                [2 ]IIIrd Medical Department, Klinikum rechts der Isar, Technische Universität München , Ismaningerstr. 22, Munich 81675, Germany
                [3 ]IInd Medical Department, Klinikum rechts der Isar, Technische Universität München , Ismaningerstr. 22, Munich 81675, Germany
                [4 ]German Cancer Consortium of Translational Cancer Research (DKTK) and German Cancer Research Center (DKFZ) , Heidelberg 69120, Germany
                [5 ]Institute of Pathology, Technische Universität München , Ismaningerstr. 22, Munich 81675, Germany
                [6 ]MRI-TUM-Biobank at the Institute of Pathology, Technische Universität München , Ismaningerstr. 22, Munich 81675, Germany
                [7 ]Surgery Department, Klinikum rechts der Isar, Technische Universität München , Ismaningerstr. 22, Munich, 81675, Germany
                [8 ]Dermatology Department, Klinikum rechts der Isar, Technische Universität München , Biedersteiner Str 29, Munich 80802, Germany
                [9 ]Institute for Medical Microbiology, Immunology and Hygiene, Technische Universität München , Trogerstr. 30, Munich 81675, Germany
                Author notes
                [*]

                These authors contributed equally to this work

                [†]

                These authors jointly supervised this work

                [‡]

                Present address: Department of Oncology, UNIL/CHUV, Ludwig Cancer Research Center, Epalinges 1066, Switzerland

                Article
                ncomms13404
                10.1038/ncomms13404
                5121339
                27869121
                5db29f7e-4c48-4482-a3ee-5943c1a40cf5
                Copyright © 2016, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 09 May 2016
                : 30 September 2016
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