1
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Bowen CM, Sinha KM, Vilar E. Current Trends in Vaccine Development for Hereditary Colorectal Cancer Syndromes. Clin Colon Rectal Surg 2024; 37:146-156. [PMID: 38606044 PMCID: PMC11006444 DOI: 10.1055/s-0043-1770383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2024]
Abstract
The coming of age for cancer treatment has experienced exponential growth in the last decade with the addition of immunotherapy as the fourth pillar to the fundamentals of cancer treatment-chemotherapy, surgery, and radiation-taking oncology to an astounding new frontier. In this time, rapid developments in computational biology coupled with immunology have led to the exploration of priming the host immune system through vaccination to prevent and treat certain subsets of cancer such as melanoma and hereditary colorectal cancer. By targeting the immune system through tumor-specific antigens-namely, neoantigens (neoAgs)-the future of cancer prevention may lie within arm's reach by employing neoAg vaccines as an immune-preventive modality for hereditary cancer syndromes like Lynch syndrome. In this review, we discuss the history, current trends, utilization, and future direction of neoAg-based vaccines in the setting of hereditary colorectal cancer.
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Affiliation(s)
- Charles M. Bowen
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Krishna M. Sinha
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Eduardo Vilar
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, Texas
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2
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Ricci AD, Bracco L, Salas-Sarduy E, Ramsey JM, Nolan MS, Lynn MK, Altcheh J, Ballering GE, Torrico F, Kesper N, Villar JC, Marcipar IS, Marco JD, Agüero F. The Trypanosoma cruzi Antigen and Epitope Atlas: antibody specificities in Chagas disease patients across the Americas. Nat Commun 2023; 14:1850. [PMID: 37012236 PMCID: PMC10070320 DOI: 10.1038/s41467-023-37522-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 03/21/2023] [Indexed: 04/05/2023] Open
Abstract
During an infection the immune system produces pathogen-specific antibodies. These antibody repertoires become specific to the history of infections and represent a rich source of diagnostic markers. However, the specificities of these antibodies are mostly unknown. Here, using high-density peptide arrays we examined the human antibody repertoires of Chagas disease patients. Chagas disease is a neglected disease caused by Trypanosoma cruzi, a protozoan parasite that evades immune mediated elimination and mounts long-lasting chronic infections. We describe a proteome-wide search for antigens, characterised their linear epitopes, and show their reactivity on 71 individuals from diverse human populations. Using single-residue mutagenesis we revealed the core functional residues for 232 of these epitopes. Finally, we show the diagnostic performance of identified antigens on challenging samples. These datasets enable the study of the Chagas antibody repertoire at an unprecedented depth and granularity, while also providing a rich source of serological biomarkers.
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Affiliation(s)
- Alejandro D Ricci
- Instituto de Investigaciones Biotecnológicas (IIB) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), San Martín, Buenos Aires, Argentina
- Escuela de Bio y Nanotecnologías (EByN), Universidad de San Martín (UNSAM), San Martín, Buenos Aires, Argentina
| | - Leonel Bracco
- Instituto de Investigaciones Biotecnológicas (IIB) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), San Martín, Buenos Aires, Argentina
- Escuela de Bio y Nanotecnologías (EByN), Universidad de San Martín (UNSAM), San Martín, Buenos Aires, Argentina
| | - Emir Salas-Sarduy
- Instituto de Investigaciones Biotecnológicas (IIB) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), San Martín, Buenos Aires, Argentina
- Escuela de Bio y Nanotecnologías (EByN), Universidad de San Martín (UNSAM), San Martín, Buenos Aires, Argentina
| | - Janine M Ramsey
- Centro Regional de Investigación en Salud Pública, Instituto Nacional de Salud Pública, Tapachula, México
| | - Melissa S Nolan
- Laboratory of Vector-borne and Zoonotic Diseases, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
| | - M Katie Lynn
- Laboratory of Vector-borne and Zoonotic Diseases, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
| | - Jaime Altcheh
- Hospital de Niños "Ricardo Gutierrez", Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
- Instituto Multidisciplinario de Investigaciones en Patologías Pediátricas (IMIPP) - GCBA-CONICET, Buenos Aires, Argentina
| | - Griselda E Ballering
- Hospital de Niños "Ricardo Gutierrez", Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | | | - Norival Kesper
- LIM-49, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brasil
| | - Juan C Villar
- Facultad de Ciencias de la Salud, Universidad Autónoma de Bucaramanga y Fundación Cardioinfantil - Instituto de Cardiología, Bogotá, Colombia
| | - Iván S Marcipar
- Facultad de Ciencias Médicas y Facultad de Ciencias Biológicas, Universidad Nacional del Litoral, Santa Fe, Argentina
| | - Jorge D Marco
- Instituto de Patología Experimental, Universidad Nacional de Salta - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Salta, Argentina
| | - Fernán Agüero
- Instituto de Investigaciones Biotecnológicas (IIB) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), San Martín, Buenos Aires, Argentina.
- Escuela de Bio y Nanotecnologías (EByN), Universidad de San Martín (UNSAM), San Martín, Buenos Aires, Argentina.
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3
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Focused B cell response to recurring gluten motif with implications for epitope spreading in celiac disease. Cell Rep 2022; 41:111541. [DOI: 10.1016/j.celrep.2022.111541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 09/16/2022] [Accepted: 09/29/2022] [Indexed: 11/19/2022] Open
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4
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Nielsen M, Ternette N, Barra C. The interdependence of machine learning and LC-MS approaches for an unbiased understanding of the cellular immunopeptidome. Expert Rev Proteomics 2022; 19:77-88. [PMID: 35390265 DOI: 10.1080/14789450.2022.2064278] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION The comprehensive collection of peptides presented by Major Histocompatibility Complex (MHC) molecules on the cell surface is collectively known as the immunopeptidome. The analysis and interpretation of such data sets holds great promise for furthering our understanding of basic immunology and adaptive immune activation and regulation, and for direct rational discovery of T cell antigens and the design of T-cell based therapeutics and vaccines. These applications are however challenged by the complex nature of immunopeptidome data. AREAS COVERED Here, we describe the benefits and shortcomings of applying liquid chromatography-tandem mass spectrometry (MS) to obtain large scale immunopeptidome data sets and illustrate how the accurate analysis and optimal interpretation of such data is reliant on the availability of refined and highly optimized machine learning approaches. EXPERT OPINION Further we demonstrate how the accuracy of immunoinformatics prediction methods within the field of MHC antigen presentation has benefited greatly from the availability of MS-immunopeptidomics data, and exemplify how optimal antigen discovery is best performed in a synergistic combination of MS experiments and such in silico models trained on large scale immunopeptidomics data.
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Affiliation(s)
- Morten Nielsen
- Department of Health technology, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Nicola Ternette
- Centre for Cellular and Molecular Physiology, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, UK
| | - Carolina Barra
- Department of Health technology, Technical University of Denmark, DK-2800 Lyngby, Denmark
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5
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Ramarathinam SH, Ho BK, Dudek NL, Purcell AW. HLA class II immunopeptidomics reveals that co-inherited HLA-allotypes within an extended haplotype can improve proteome coverage for immunosurveillance. Proteomics 2021; 21:e2000160. [PMID: 34357683 DOI: 10.1002/pmic.202000160] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 08/03/2021] [Accepted: 08/04/2021] [Indexed: 01/05/2023]
Abstract
Human leucocyte antigen (HLA) class II molecules in humans are encoded by three different loci, HLA-DR, -DQ, and -DP. These molecules share approximately 70% sequence similarity and all present peptide ligands to circulating T cells. While the peptide repertoires of numerous HLA-DR, -DQ, and -DP allotypes have been examined, there have been few reports on the combined repertoire of these co-inherited molecules expressed in a single cell as an extended HLA haplotype. Here we describe the endogenous peptide repertoire of a human B lymphoblastoid cell line (C1R) expressing the class II haplotype HLA-DR12/DQ7/DP4. We have identified 71350 unique naturally processed peptides presented collectively by HLA-DR12, HLA-DQ7, or HLA-DP4. The resulting "haplodome" is complemented by the cellular proteome defined by standard LC-MS/MS approaches. This large dataset has shed light on properties of these class II ligands especially the preference for membrane and extracellular source proteins. Our data also provides insights into the co-evolution of these conserved haplotypes of closely linked and co-inherited HLA molecules; which together increase sequence coverage of cellular proteins for immune surveillance with minimal overlap between each co-inherited HLA-class II allomorph.
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Affiliation(s)
- Sri H Ramarathinam
- Department of Biochemistry and Molecular Biology and Infection and Immunity Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia
| | - Bosco K Ho
- Department of Biochemistry and Molecular Biology and Infection and Immunity Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia
| | - Nadine L Dudek
- Department of Biochemistry and Molecular Biology and Infection and Immunity Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia
| | - Anthony W Purcell
- Department of Biochemistry and Molecular Biology and Infection and Immunity Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia
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6
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Liu R, Jiang W, Mellins ED. Yeast display of MHC-II enables rapid identification of peptide ligands from protein antigens (RIPPA). Cell Mol Immunol 2021; 18:1847-1860. [PMID: 34117370 PMCID: PMC8193015 DOI: 10.1038/s41423-021-00717-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 05/25/2021] [Indexed: 11/12/2022] Open
Abstract
CD4+ T cells orchestrate adaptive immune responses via binding of antigens to their receptors through specific peptide/MHC-II complexes. To study these responses, it is essential to identify protein-derived MHC-II peptide ligands that constitute epitopes for T cell recognition. However, generating cells expressing single MHC-II alleles and isolating these proteins for use in peptide elution or binding studies is time consuming. Here, we express human MHC alleles (HLA-DR4 and HLA-DQ6) as native, noncovalent αβ dimers on yeast cells for direct flow cytometry-based screening of peptide ligands from selected antigens. We demonstrate rapid, accurate identification of DQ6 ligands from pre-pro-hypocretin, a narcolepsy-related immunogenic target. We also identify 20 DR4-binding SARS-CoV-2 spike peptides homologous to SARS-CoV-1 epitopes, and one spike peptide overlapping with the reported SARS-CoV-2 epitope recognized by CD4+ T cells from unexposed individuals carrying DR4 subtypes. Our method is optimized for immediate application upon the emergence of novel pathogens.
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Affiliation(s)
- Rongzeng Liu
- Department of Pediatrics-Human Gene Therapy, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Immunology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Immunology, Henan University of Science and Technology School of Medicine, Luoyang, China
| | - Wei Jiang
- Department of Pediatrics-Human Gene Therapy, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Immunology, Stanford University School of Medicine, Stanford, CA, USA.
| | - Elizabeth D Mellins
- Department of Pediatrics-Human Gene Therapy, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Immunology, Stanford University School of Medicine, Stanford, CA, USA.
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7
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Joyce S, Ternette N. Know thy immune self and non-self: Proteomics informs on the expanse of self and non-self, and how and where they arise. Proteomics 2021; 21:e2000143. [PMID: 34310018 PMCID: PMC8865197 DOI: 10.1002/pmic.202000143] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 06/30/2021] [Accepted: 07/19/2021] [Indexed: 12/30/2022]
Abstract
T cells play an important role in the adaptive immune response to a variety of infections and cancers. Initiation of a T cell mediated immune response requires antigen recognition in a process termed MHC (major histocompatibility complex) restri ction. A T cell antigen is a composite structure made up of a peptide fragment bound within the antigen‐binding groove of an MHC‐encoded class I or class II molecule. Insight into the precise composition and biology of self and non‐self immunopeptidomes is essential to harness T cell mediated immunity to prevent, treat, or cure infectious diseases and cancers. T cell antigen discovery is an arduous task! The pioneering work in the early 1990s has made large‐scale T cell antigen discovery possible. Thus, advancements in mass spectrometry coupled with proteomics and genomics technologies make possible T cell antigen discovery with ease, accuracy, and sensitivity. Yet we have only begun to understand the breadth and the depth of self and non‐self immunopeptidomes because the molecular biology of the cell continues to surprise us with new secrets directly related to the source, and the processing and presentation of MHC ligands. Focused on MHC class I molecules, this review, therefore, provides a brief historic account of T cell antigen discovery and, against a backdrop of key advances in molecular cell biologic processes, elaborates on how proteogenomics approaches have revolutionised the field.
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Affiliation(s)
- Sebastian Joyce
- Department of Veterans Affairs, Tennessee Valley Healthcare System and the Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Nicola Ternette
- Centre for Cellular and Molecular Physiology, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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8
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Taylor HB, Klaeger S, Clauser KR, Sarkizova S, Weingarten-Gabbay S, Graham DB, Carr SA, Abelin JG. MS-Based HLA-II Peptidomics Combined With Multiomics Will Aid the Development of Future Immunotherapies. Mol Cell Proteomics 2021; 20:100116. [PMID: 34146720 PMCID: PMC8327157 DOI: 10.1016/j.mcpro.2021.100116] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 06/02/2021] [Accepted: 06/03/2021] [Indexed: 12/25/2022] Open
Abstract
Immunotherapies have emerged to treat diseases by selectively modulating a patient's immune response. Although the roles of T and B cells in adaptive immunity have been well studied, it remains difficult to select targets for immunotherapeutic strategies. Because human leukocyte antigen class II (HLA-II) peptides activate CD4+ T cells and regulate B cell activation, proliferation, and differentiation, these peptide antigens represent a class of potential immunotherapy targets and biomarkers. To better understand the molecular basis of how HLA-II antigen presentation is involved in disease progression and treatment, systematic HLA-II peptidomics combined with multiomic analyses of diverse cell types in healthy and diseased states is required. For this reason, MS-based innovations that facilitate investigations into the interplay between disease pathologies and the presentation of HLA-II peptides to CD4+ T cells will aid in the development of patient-focused immunotherapies.
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Affiliation(s)
- Hannah B Taylor
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Susan Klaeger
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Karl R Clauser
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | | | - Shira Weingarten-Gabbay
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, USA
| | - Daniel B Graham
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA; Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Steven A Carr
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
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9
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Shen L, Zhao ZG, Lainson JC, Brown JR, Sykes KF, Johnston SA, Diehnelt CW. Production of high-complexity frameshift neoantigen peptide microarrays. RSC Adv 2020; 10:29675-29681. [PMID: 35518269 PMCID: PMC9056171 DOI: 10.1039/d0ra05267a] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Accepted: 08/02/2020] [Indexed: 12/22/2022] Open
Abstract
Parallel measurement of large numbers of antigen-antibody interactions are increasingly enabled by peptide microarray technologies. Our group has developed an in situ synthesized peptide microarray of >400 000 frameshift neoantigens using mask-based photolithographic peptide synthesis, to profile patient specific neoantigen reactive antibodies in a single assay. The system produces 208 replicate mircoarrays per wafer and is capable of producing multiple wafers per synthetic lot to routinely synthesize over 300 million peptides simultaneously. In this report, we demonstrate the feasibility of the system for detecting peripheral-blood antibody binding to frameshift neoantigens across multiple synthetic lots.
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Affiliation(s)
- Luhui Shen
- Center for Innovations in Medicine, Biodesign Institute, Arizona State University Tempe AZ USA
| | - Zhan-Gong Zhao
- Center for Innovations in Medicine, Biodesign Institute, Arizona State University Tempe AZ USA
| | - John C Lainson
- Center for Innovations in Medicine, Biodesign Institute, Arizona State University Tempe AZ USA
| | | | | | - Stephen Albert Johnston
- Center for Innovations in Medicine, Biodesign Institute, Arizona State University Tempe AZ USA .,Calviri, Inc. Tempe AZ USA
| | - Chris W Diehnelt
- Center for Innovations in Medicine, Biodesign Institute, Arizona State University Tempe AZ USA
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10
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Wendorff M, Garcia Alvarez HM, Østerbye T, ElAbd H, Rosati E, Degenhardt F, Buus S, Franke A, Nielsen M. Unbiased Characterization of Peptide-HLA Class II Interactions Based on Large-Scale Peptide Microarrays; Assessment of the Impact on HLA Class II Ligand and Epitope Prediction. Front Immunol 2020; 11:1705. [PMID: 32903714 PMCID: PMC7438773 DOI: 10.3389/fimmu.2020.01705] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 06/25/2020] [Indexed: 12/12/2022] Open
Abstract
Human Leukocyte Antigen class II (HLA-II) molecules present peptides to T lymphocytes and play an important role in adaptive immune responses. Characterizing the binding specificity of single HLA-II molecules has profound impacts for understanding cellular immunity, identifying the cause of autoimmune diseases, for immunotherapeutics, and vaccine development. Here, novel high-density peptide microarray technology combined with machine learning techniques were used to address this task at an unprecedented level of high-throughput. Microarrays with over 200,000 defined peptides were assayed with four exemplary HLA-II molecules. Machine learning was applied to mine the signals. The comparison of identified binding motifs, and power for predicting eluted ligands and CD4+ epitope datasets to that obtained using NetMHCIIpan-3.2, confirmed a high quality of the chip readout. These results suggest that the proposed microarray technology offers a novel and unique platform for large-scale unbiased interrogation of peptide binding preferences of HLA-II molecules.
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Affiliation(s)
- Mareike Wendorff
- Genetics & Bioinformatics, Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | | | - Thomas Østerbye
- Department of Immunology and Microbiology, University of Copenhagen, Copenhagen, Denmark
| | - Hesham ElAbd
- Genetics & Bioinformatics, Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Elisa Rosati
- Genetics & Bioinformatics, Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Frauke Degenhardt
- Genetics & Bioinformatics, Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Søren Buus
- Department of Immunology and Microbiology, University of Copenhagen, Copenhagen, Denmark
| | - Andre Franke
- Genetics & Bioinformatics, Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Morten Nielsen
- IIBIO, UNSAM-CONICET, Buenos Aires, Argentina.,Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
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11
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Osterbye T, Nielsen M, Dudek NL, Ramarathinam SH, Purcell AW, Schafer-Nielsen C, Buus S. HLA Class II Specificity Assessed by High-Density Peptide Microarray Interactions. THE JOURNAL OF IMMUNOLOGY 2020; 205:290-299. [PMID: 32482711 DOI: 10.4049/jimmunol.2000224] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 04/22/2020] [Indexed: 01/26/2023]
Abstract
The ability to predict and/or identify MHC binding peptides is an essential component of T cell epitope discovery, something that ultimately should benefit the development of vaccines and immunotherapies. In particular, MHC class I prediction tools have matured to a point where accurate selection of optimal peptide epitopes is possible for virtually all MHC class I allotypes; in comparison, current MHC class II (MHC-II) predictors are less mature. Because MHC-II restricted CD4+ T cells control and orchestrated most immune responses, this shortcoming severely hampers the development of effective immunotherapies. The ability to generate large panels of peptides and subsequently large bodies of peptide-MHC-II interaction data are key to the solution of this problem, a solution that also will support the improvement of bioinformatics predictors, which critically relies on the availability of large amounts of accurate, diverse, and representative data. In this study, we have used rHLA-DRB1*01:01 and HLA-DRB1*03:01 molecules to interrogate high-density peptide arrays, in casu containing 70,000 random peptides in triplicates. We demonstrate that the binding data acquired contains systematic and interpretable information reflecting the specificity of the HLA-DR molecules investigated, suitable of training predictors able to predict T cell epitopes and peptides eluted from human EBV-transformed B cells. Collectively, with a cost per peptide reduced to a few cents, combined with the flexibility of rHLA technology, this poses an attractive strategy to generate vast bodies of MHC-II binding data at an unprecedented speed and for the benefit of generating peptide-MHC-II binding data as well as improving MHC-II prediction tools.
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Affiliation(s)
- Thomas Osterbye
- Department of Immunology and Microbiology, University of Copenhagen, DK-2200 Copenhagen, Denmark;
| | - Morten Nielsen
- Department of Health Technology, Technical University of Denmark, DK-2800 Lyngby, Denmark.,Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, B1650 San Martín, Argentina
| | - Nadine L Dudek
- Infection and Immunity Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia; and
| | - Sri H Ramarathinam
- Infection and Immunity Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia; and
| | - Anthony W Purcell
- Infection and Immunity Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia; and
| | | | - Soren Buus
- Department of Immunology and Microbiology, University of Copenhagen, DK-2200 Copenhagen, Denmark
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