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      Specific MHC-I Peptides Are Induced Using PROTACs

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          Abstract

          Peptides presented by the class-I major histocompatibility complex (MHC-I) are important targets for immunotherapy. The identification of these peptide targets greatly facilitates the generation of T-cell-based therapeutics. Herein, we report the capability of proteolysis targeting chimera (PROTAC) compounds to induce the presentation of specific MHC class-I peptides derived from endogenous cellular proteins. Using LC-MS/MS, we identified several BET-derived MHC-I peptides induced by treatment with three BET-directed PROTAC compounds. To understand our ability to tune this process, we measured the relative rate of presentation of these peptides under varying treatment conditions using label-free mass spectrometry quantification. We found that the rate of peptide presentation reflected the rate of protein degradation, indicating a direct relationship between PROTAC treatment and peptide presentation. We additionally analyzed the effect of PROTAC treatment on the entire immunopeptidome and found many new peptides that were displayed in a PROTAC-specific fashion: we determined that these identifications map to the BET pathway, as well as, potential off-target or unique-to-PROTAC pathways. This work represents the first evidence of the use of PROTAC compounds to induce the presentation of MHC-I peptides from endogenous cellular proteins, highlighting the capability of PROTAC compounds for the discovery and generation of new targets for immunotherapy.

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          Most cited references 46

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          Large-scale gene function analysis with the PANTHER classification system.

          The PANTHER (protein annotation through evolutionary relationship) classification system (http://www.pantherdb.org/) is a comprehensive system that combines gene function, ontology, pathways and statistical analysis tools that enable biologists to analyze large-scale, genome-wide data from sequencing, proteomics or gene expression experiments. The system is built with 82 complete genomes organized into gene families and subfamilies, and their evolutionary relationships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models or HMMs). Genes are classified according to their function in several different ways: families and subfamilies are annotated with ontology terms (Gene Ontology (GO) and PANTHER protein class), and sequences are assigned to PANTHER pathways. The PANTHER website includes a suite of tools that enable users to browse and query gene functions, and to analyze large-scale experimental data with a number of statistical tests. It is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. In the 2013 release of PANTHER (v.8.0), in addition to an update of the data content, we redesigned the website interface to improve both user experience and the system's analytical capability. This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system.
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            Selective inhibition of BET bromodomains

            Epigenetic proteins are intently pursued targets in ligand discovery. To date, successful efforts have been limited to chromatin modifying enzymes, or so-called epigenetic “writers” and “erasers”. Potent inhibitors of histone binding modules have not yet been described. Here we report a cell-permeable small molecule (JQ1) which binds competitively to acetyl-lysine recognition motifs, or bromodomains. High potency and specificity toward a subset of human bromodomains is explained by co-crystal structures with BRD4, revealing excellent shape complementarity with the acetyl-lysine binding cavity. Recurrent translocation of BRD4 is observed in a genetically-defined, incurable subtype of human squamous carcinoma. Competitive binding by JQ1 displaces the BRD4 fusion oncoprotein from chromatin, prompting squamous differentiation and specific anti-proliferative effects in BRD4-dependent cell lines and patient-derived xenograft models. These data establish proof of concept for targeting protein-protein interactions of epigenetic “readers” and provide a versatile chemical scaffold for the development of chemical probes more broadly throughout the bromodomain family.
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              PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements

              The PANTHER database (Protein ANalysis THrough Evolutionary Relationships, http://pantherdb.org) contains comprehensive information on the evolution and function of protein-coding genes from 104 completely sequenced genomes. PANTHER software tools allow users to classify new protein sequences, and to analyze gene lists obtained from large-scale genomics experiments. In the past year, major improvements include a large expansion of classification information available in PANTHER, as well as significant enhancements to the analysis tools. Protein subfamily functional classifications have more than doubled due to progress of the Gene Ontology Phylogenetic Annotation Project. For human genes (as well as a few other organisms), PANTHER now also supports enrichment analysis using pathway classifications from the Reactome resource. The gene list enrichment tools include a new ‘hierarchical view’ of results, enabling users to leverage the structure of the classifications/ontologies; the tools also allow users to upload genetic variant data directly, rather than requiring prior conversion to a gene list. The updated coding single-nucleotide polymorphisms (SNP) scoring tool uses an improved algorithm. The hidden Markov model (HMM) search tools now use HMMER3, dramatically reducing search times and improving accuracy of E-value statistics. Finally, the PANTHER Tree-Attribute Viewer has been implemented in JavaScript, with new views for exploring protein sequence evolution.
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                22 November 2018
                2018
                : 9
                Affiliations
                Discovery Chemistry and Technology, AbbVie North Chicago, IL, United States
                Author notes

                Edited by: Christian Kurts, Universität Bonn, Germany

                Reviewed by: Alessio Ciulli, University of Dundee, United Kingdom; Loredana Saveanu, Institut National de la Santé et de la Recherche Médicale (INSERM), FranceClaire Whitworth, University of Dundee, United Kingdom, in collaboration with AC

                *Correspondence: Melanie J. Patterson Melanie.Patterson@ 123456abbvie.com

                This article was submitted to Antigen Presenting Cell Biology, a section of the journal Frontiers in Immunology

                Article
                10.3389/fimmu.2018.02697
                6262898
                Copyright © 2018 Jensen, Potts, Ready and Patterson.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Page count
                Figures: 7, Tables: 0, Equations: 0, References: 47, Pages: 13, Words: 9702
                Categories
                Immunology
                Original Research

                Immunology

                bet, immunopeptides, hla, mhc-i, protac

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