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Daniels J, Doukas PG, Escala MEM, Ringbloom KG, Shih DJH, Yang J, Tegtmeyer K, Park J, Thomas JJ, Selli ME, Altunbulakli C, Gowthaman R, Mo SH, Jothishankar B, Pease DR, Pro B, Abdulla FR, Shea C, Sahni N, Gru AA, Pierce BG, Louissaint A, Guitart J, Choi J. Cellular origins and genetic landscape of cutaneous gamma delta T cell lymphomas. Nat Commun 2020; 11:1806. [PMID: 32286303 PMCID: PMC7156460 DOI: 10.1038/s41467-020-15572-7] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Accepted: 03/10/2020] [Indexed: 12/14/2022] Open
Abstract
Primary cutaneous γδ T cell lymphomas (PCGDTLs) represent a heterogeneous group of uncommon but aggressive cancers. Herein, we perform genome-wide DNA, RNA, and T cell receptor (TCR) sequencing on 29 cutaneous γδ lymphomas. We find that PCGDTLs are not uniformly derived from Vδ2 cells. Instead, the cell-of-origin depends on the tissue compartment from which the lymphomas are derived. Lymphomas arising from the outer layer of skin are derived from Vδ1 cells, the predominant γδ cell in the epidermis and dermis. In contrast, panniculitic lymphomas arise from Vδ2 cells, the predominant γδ T cell in the fat. We also show that TCR chain usage is non-random, suggesting common antigens for Vδ1 and Vδ2 lymphomas respectively. In addition, Vδ1 and Vδ2 PCGDTLs harbor similar genomic landscapes with potentially targetable oncogenic mutations in the JAK/STAT, MAPK, MYC, and chromatin modification pathways. Collectively, these findings suggest a paradigm for classifying, staging, and treating these diseases.
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MESH Headings
- Amino Acid Sequence
- Antigens, CD1d/metabolism
- Chromatin Assembly and Disassembly
- Epitopes/immunology
- Genome, Human
- HEK293 Cells
- Humans
- Lymph Nodes/pathology
- Lymphoma, T-Cell, Cutaneous/genetics
- Lymphoma, T-Cell, Cutaneous/pathology
- Models, Biological
- Mutation/genetics
- Phenotype
- Principal Component Analysis
- Receptors, Antigen, T-Cell, gamma-delta/metabolism
- Signal Transduction
- Skin/pathology
- Skin Neoplasms/genetics
- Skin Neoplasms/pathology
- Transcription, Genetic
- Transcriptome/genetics
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Affiliation(s)
- Jay Daniels
- Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Biochemistry and Molecular Genetics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Peter G Doukas
- Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Maria E Martinez Escala
- Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Kimberly G Ringbloom
- Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - David J H Shih
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jingyi Yang
- Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Kyle Tegtmeyer
- Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Joonhee Park
- Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Jane J Thomas
- Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Mehmet E Selli
- Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Can Altunbulakli
- Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Ragul Gowthaman
- University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD, USA
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD, USA
| | - Samuel H Mo
- University of Illinois College of Medicine, Chicago, IL, USA
| | - Balaji Jothishankar
- Department of Medicine, Section of Dermatology, University of Chicago Pritzker School of Medicine, Chicago, IL, USA
| | - David R Pease
- Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Barbara Pro
- Division of Hematology/Oncology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Farah R Abdulla
- Division of Dermatology, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Christopher Shea
- Department of Medicine, Section of Dermatology, University of Chicago Pritzker School of Medicine, Chicago, IL, USA
| | - Nidhi Sahni
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX, USA
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston, TX, USA
| | - Alejandro A Gru
- Department of Pathology, University of Virginia Health System, Charlottesville, VA, USA
- Department of Dermatology, University of Virginia Health System, Charlottesville, VA, USA
| | - Brian G Pierce
- University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD, USA
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD, USA
| | - Abner Louissaint
- Department of Pathology, Massachusetts General Hospital, Boston, MA, USA.
| | - Joan Guitart
- Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
| | - Jaehyuk Choi
- Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
- Department of Biochemistry and Molecular Genetics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
- Center for Genetic Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA.
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
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How an alloreactive T-cell receptor achieves peptide and MHC specificity. Proc Natl Acad Sci U S A 2017; 114:E4792-E4801. [PMID: 28572406 DOI: 10.1073/pnas.1700459114] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
T-cell receptor (TCR) allorecognition is often presumed to be relatively nonspecific, attributable to either a TCR focus on exposed major histocompatibility complex (MHC) polymorphisms or the degenerate recognition of allopeptides. However, paradoxically, alloreactivity can proceed with high peptide and MHC specificity. Although the underlying mechanisms remain unclear, the existence of highly specific alloreactive TCRs has led to their use as immunotherapeutics that can circumvent central tolerance and limit graft-versus-host disease. Here, we show how an alloreactive TCR achieves peptide and MHC specificity. The HCV1406 TCR was cloned from T cells that expanded when a hepatitis C virus (HCV)-infected HLA-A2- individual received an HLA-A2+ liver allograft. HCV1406 was subsequently shown to recognize the HCV nonstructural protein 3 (NS3):1406-1415 epitope with high specificity when presented by HLA-A2. We show that NS3/HLA-A2 recognition by the HCV1406 TCR is critically dependent on features unique to both the allo-MHC and the NS3 epitope. We also find cooperativity between structural mimicry and a crucial peptide "hot spot" and demonstrate its role, along with the MHC, in directing the specificity of allorecognition. Our results help explain the paradox of specificity in alloreactive TCRs and have implications for their use in immunotherapy and related efforts to manipulate TCR recognition, as well as alloreactivity in general.
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Hoffmann T, Marion A, Antes I. DynaDom: structure-based prediction of T cell receptor inter-domain and T cell receptor-peptide-MHC (class I) association angles. BMC STRUCTURAL BIOLOGY 2017; 17:2. [PMID: 28148269 PMCID: PMC5289058 DOI: 10.1186/s12900-016-0071-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2016] [Accepted: 12/29/2016] [Indexed: 11/22/2022]
Abstract
Background T cell receptor (TCR) molecules are involved in the adaptive immune response as they distinguish between self- and foreign-peptides, presented in major histocompatibility complex molecules (pMHC). Former studies showed that the association angles of the TCR variable domains (Vα/Vβ) can differ significantly and change upon binding to the pMHC complex. These changes can be described as a rotation of the domains around a general Center of Rotation, characterized by the interaction of two highly conserved glutamine residues. Methods We developed a computational method, DynaDom, for the prediction of TCR Vα/Vβ inter-domain and TCR/pMHC orientations in TCRpMHC complexes, which allows predicting the orientation of multiple protein-domains. In addition, we implemented a new approach to predict the correct orientation of the carboxamide endgroups in glutamine and asparagine residues, which can also be used as an external, independent tool. Results The approach was evaluated for the remodeling of 75 and 53 experimental structures of TCR and TCRpMHC (class I) complexes, respectively. We show that the DynaDom method predicts the correct orientation of the TCR Vα/Vβ angles in 96 and 89% of the cases, for the poses with the best RMSD and best interaction energy, respectively. For the concurrent prediction of the TCR Vα/Vβ and pMHC orientations, the respective rates reached 74 and 72%. Through an exhaustive analysis, we could show that the pMHC placement can be further improved by a straightforward, yet very time intensive extension of the current approach. Conclusions The results obtained in the present remodeling study prove the suitability of our approach for interdomain-angle optimization. In addition, the high prediction rate obtained specifically for the energetically highest ranked poses further demonstrates that our method is a powerful candidate for blind prediction. Therefore it should be well suited as part of any accurate atomistic modeling pipeline for TCRpMHC complexes and potentially other large molecular assemblies. Electronic supplementary material The online version of this article (doi:10.1186/s12900-016-0071-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Thomas Hoffmann
- Department of Biosciences and Center for Integrated Protein Science Munich, Technische Universität München, Emil-Erlenmeyer-Forum 8, 85354, Freising, Germany
| | - Antoine Marion
- Department of Biosciences and Center for Integrated Protein Science Munich, Technische Universität München, Emil-Erlenmeyer-Forum 8, 85354, Freising, Germany
| | - Iris Antes
- Department of Biosciences and Center for Integrated Protein Science Munich, Technische Universität München, Emil-Erlenmeyer-Forum 8, 85354, Freising, Germany.
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Root-Bernstein R. Autoimmunity and the microbiome: T-cell receptor mimicry of "self" and microbial antigens mediates self tolerance in holobionts: The concepts of "holoimmunity" (TcR-mediated tolerance for the holobiont) and "holoautoimmunity" (loss of tolerance for the holobiont) are introduced. Bioessays 2016; 38:1068-1083. [PMID: 27594308 PMCID: PMC7161894 DOI: 10.1002/bies.201600083] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
I propose a T-cell receptor (TcR)-based mechanism by which immunity mediates both "genetic self" and "microbial self" thereby, connecting microbiome disease with autoimmunity. The hypothesis is based on simple principles. First, TcR are selected to avoid strong cross-reactivity with "self," resulting in selection for a TcR repertoire mimicking "genetic self." Second, evolution has selected for a "microbial self" that mimics "genetic self" so as to share tolerance. In consequence, our TcR repertoire also mimics microbiome antigenicity, providing a novel mechanism for modulating tolerance to it. Also, the microbiome mimics the TcR repertoire, acting as a secondary immune system. I call this TcR-microbiome mimicry "holoimmunity" to denote immune tolerance to the "holobiont self." Logically, microbiome-host mimicry means that autoimmunity directed at host antigens will also attack components of the microbiome, and conversely, an immunological attack on the microbiome may cross-react with host antigens producing "holoautoimmunity."
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Abstract
T-cell receptor (TCR) binding to peptide/MHC determines specificity and initiates signaling in antigen-specific cellular immune responses. Structures of TCR-pMHC complexes have provided enormous insight to cellular immune functions, permitted a rational understanding of processes such as pathogen escape, and led to the development of novel approaches for the design of vaccines and other therapeutics. As production, crystallization, and structure determination of TCR-pMHC complexes can be challenging, there is considerable interest in modeling new complexes. Here we describe a rapid approach to TCR-pMHC modeling that takes advantage of structural features conserved in known complexes, such as the restricted TCR binding site and the generally conserved diagonal docking mode. The approach relies on the powerful Rosetta suite and is implemented using the PyRosetta scripting environment. We show how the approach can recapitulate changes in TCR binding angles and other structural details, and highlight areas where careful evaluation of parameters is needed and alternative choices might be made. As TCRs are highly sensitive to subtle structural perturbations, there is room for improvement. Our method nonetheless generates high-quality models that can be foundational for structure-based hypotheses regarding TCR recognition.
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Affiliation(s)
- Timothy P Riley
- Department of Chemistry and Biochemistry, University of Notre Dame, 251 Nieuwland Science Hall, Notre Dame, IN, 46556, USA
- Harper Cancer Research Institute, University of Notre Dame, 251 Nieuwland Science Hall, Notre Dame, IN, 46556, USA
| | - Nishant K Singh
- Department of Chemistry and Biochemistry, University of Notre Dame, 251 Nieuwland Science Hall, Notre Dame, IN, 46556, USA
- Harper Cancer Research Institute, University of Notre Dame, 251 Nieuwland Science Hall, Notre Dame, IN, 46556, USA
| | - Brian G Pierce
- Institute for Bioscience and Biotechnology Research, University of Maryland, 9600 Gudelsky Drive, Rockville, MD, 20850, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, 01605, USA
| | - Brian M Baker
- Department of Chemistry and Biochemistry, University of Notre Dame, 251 Nieuwland Science Hall, Notre Dame, IN, 46556, USA.
- Harper Cancer Research Institute, University of Notre Dame, 251 Nieuwland Science Hall, Notre Dame, IN, 46556, USA.
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