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Klein S, Mischke J, Beruldsen F, Prinz I, Antunes DA, Cornberg M, Kraft ARM. Individual Epitope-Specific CD8 + T Cell Immune Responses Are Shaped Differently during Chronic Viral Infection. Pathogens 2023; 12:pathogens12050716. [PMID: 37242386 DOI: 10.3390/pathogens12050716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 05/10/2023] [Accepted: 05/11/2023] [Indexed: 05/28/2023] Open
Abstract
A hallmark in chronic viral infections are exhausted antigen-specific CD8+ T cell responses and the inability of the immune system to eliminate the virus. Currently, there is limited information on the variability of epitope-specific T cell exhaustion within one immune response and the relevance to the T cell receptor (TCR) repertoire. The aim of this study was a comprehensive analysis and comparison of three lymphocytic choriomeningitis virus (LCMV) epitope-specific CD8+ T cell responses (NP396, GP33 and NP205) in a chronic setting with immune intervention, e.g., immune checkpoint inhibitor (ICI) therapy, in regard to the TCR repertoire. These responses, though measured within the same mice, were individual and independent from each other. The massively exhausted NP396-specific CD8+ T cells revealed a significantly reduced TCR repertoire diversity, whereas less-exhausted GP33-specific CD8+ T cell responses were rather unaffected by chronicity in regard to their TCR repertoire diversity. NP205-specific CD8+ T cell responses showed a very special TCR repertoire with a prominent public motif of TCR clonotypes that was present in all NP205-specific responses, which separated this from NP396- and GP33-specific responses. Additionally, we showed that TCR repertoire shifts induced by ICI therapy are heterogeneous on the epitope level, by revealing profound effects in NP396-, less severe and opposed effects in NP205-, and minor effects in GP33-specific responses. Overall, our data revealed individual epitope-specific responses within one viral response that are differently affected by exhaustion and ICI therapy. These individual shapings of epitope-specific T cell responses and their TCR repertoires in an LCMV mouse model indicates important implications for focusing on epitope-specific responses in future evaluations for therapeutic approaches, e.g., for chronic hepatitis virus infections in humans.
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Affiliation(s)
- Sebastian Klein
- Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, 30625 Hannover, Germany
- Twincore Centre for Experimental and Clinical Infection Medicine, 30625 Hannover, Germany
| | - Jasmin Mischke
- Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, 30625 Hannover, Germany
- Twincore Centre for Experimental and Clinical Infection Medicine, 30625 Hannover, Germany
| | - Finn Beruldsen
- Center for Nuclear Receptors and Cell Signaling, Department of Biology and Biochemistry, University of Houston, Houston, TX 77204, USA
| | - Immo Prinz
- Institute of Systems Immunology, University Medical Center Eppendorf, 20251 Hamburg, Germany
- Institute of Immunology, Hannover Medical School, 30625 Hannover, Germany
| | - Dinler A Antunes
- Center for Nuclear Receptors and Cell Signaling, Department of Biology and Biochemistry, University of Houston, Houston, TX 77204, USA
| | - Markus Cornberg
- Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, 30625 Hannover, Germany
- Twincore Centre for Experimental and Clinical Infection Medicine, 30625 Hannover, Germany
- German Centre for Infection Research (DZIF), 30625 Hannover, Germany
- Centre for Individualised Infection Medicine (CIIM), c/o CRC Hannover, 30625 Hannover, Germany
| | - Anke R M Kraft
- Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, 30625 Hannover, Germany
- Twincore Centre for Experimental and Clinical Infection Medicine, 30625 Hannover, Germany
- German Centre for Infection Research (DZIF), 30625 Hannover, Germany
- Centre for Individualised Infection Medicine (CIIM), c/o CRC Hannover, 30625 Hannover, Germany
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2
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Kasmani MY, Zander R, Chung HK, Chen Y, Khatun A, Damo M, Topchyan P, Johnson KE, Levashova D, Burns R, Lorenz UM, Tarakanova VL, Joshi NS, Kaech SM, Cui W. Clonal lineage tracing reveals mechanisms skewing CD8+ T cell fate decisions in chronic infection. J Exp Med 2023; 220:e20220679. [PMID: 36315049 PMCID: PMC9623343 DOI: 10.1084/jem.20220679] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 06/17/2022] [Accepted: 08/08/2022] [Indexed: 11/05/2022] Open
Abstract
Although recent evidence demonstrates heterogeneity among CD8+ T cells during chronic infection, developmental relationships and mechanisms underlying their fate decisions remain incompletely understood. Using single-cell RNA and TCR sequencing, we traced the clonal expansion and differentiation of CD8+ T cells during chronic LCMV infection. We identified immense clonal and phenotypic diversity, including a subset termed intermediate cells. Trajectory analyses and infection models showed intermediate cells arise from progenitor cells before bifurcating into terminal effector and exhausted subsets. Genetic ablation experiments identified that type I IFN drives exhaustion through an IRF7-dependent mechanism, possibly through an IFN-stimulated subset bridging progenitor and exhausted cells. Conversely, Zeb2 was critical for generating effector cells. Intriguingly, some T cell clones exhibited lineage bias. Mechanistically, we identified that TCR avidity correlates with an exhausted fate, whereas SHP-1 selectively restricts low-avidity effector cell accumulation. Thus, our work elucidates novel mechanisms underlying CD8+ T cell fate determination during persistent infection and suggests two potential pathways leading to exhaustion.
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Affiliation(s)
- Moujtaba Y. Kasmani
- Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI
- Blood Research Institute, Versiti Wisconsin, Milwaukee, WI
| | - Ryan Zander
- Blood Research Institute, Versiti Wisconsin, Milwaukee, WI
| | - H. Kay Chung
- NOMIS Center for Immunobiology and Microbial Pathogenesis, Salk Institute for Biological Studies, La Jolla, CA
| | - Yao Chen
- Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI
- Blood Research Institute, Versiti Wisconsin, Milwaukee, WI
| | - Achia Khatun
- Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI
- Blood Research Institute, Versiti Wisconsin, Milwaukee, WI
| | - Martina Damo
- Department of Immunobiology, Yale University School of Medicine, New Haven, CT
| | - Paytsar Topchyan
- Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI
- Blood Research Institute, Versiti Wisconsin, Milwaukee, WI
| | - Kaitlin E. Johnson
- Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI
| | - Darya Levashova
- Department of Microbiology, Immunology, and Cancer Biology, and Carter Immunology Center, University of Virginia, Charlottesville, VA
| | - Robert Burns
- Blood Research Institute, Versiti Wisconsin, Milwaukee, WI
| | - Ulrike M. Lorenz
- Department of Microbiology, Immunology, and Cancer Biology, and Carter Immunology Center, University of Virginia, Charlottesville, VA
| | - Vera L. Tarakanova
- Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI
| | - Nikhil S. Joshi
- Department of Immunobiology, Yale University School of Medicine, New Haven, CT
| | - Susan M. Kaech
- NOMIS Center for Immunobiology and Microbial Pathogenesis, Salk Institute for Biological Studies, La Jolla, CA
| | - Weiguo Cui
- Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI
- Blood Research Institute, Versiti Wisconsin, Milwaukee, WI
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3
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Single-cell immune repertoire sequencing of B and T cells in murine models of infection and autoimmunity. Genes Immun 2022; 23:183-195. [PMID: 36028771 PMCID: PMC9519453 DOI: 10.1038/s41435-022-00180-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 08/04/2022] [Accepted: 08/09/2022] [Indexed: 11/09/2022]
Abstract
Adaptive immune repertoires are composed by the ensemble of B and T-cell receptors within an individual, reflecting both past and current immune responses. Recent advances in single-cell sequencing enable recovery of the complete adaptive immune receptor sequences in addition to transcriptional information. Here, we recovered transcriptome and immune repertoire information for polyclonal T follicular helper cells following lymphocytic choriomeningitis virus (LCMV) infection, CD8+ T cells with binding specificity restricted to two distinct LCMV peptides, and B and T cells isolated from the nervous system in the context of experimental autoimmune encephalomyelitis. We could relate clonal expansion, germline gene usage, and clonal convergence to cell phenotypes spanning activation, memory, naive, antibody secretion, T-cell inflation, and regulation. Together, this dataset provides a resource for immunologists that can be integrated with future single-cell immune repertoire and transcriptome sequencing datasets.
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Kuhn R, Sandu I, Agrafiotis A, Hong KL, Shlesinger D, Neimeier D, Merkler D, Oxenius A, Reddy ST, Yermanos A. Clonally Expanded Virus-Specific CD8 T Cells Acquire Diverse Transcriptional Phenotypes During Acute, Chronic, and Latent Infections. Front Immunol 2022; 13:782441. [PMID: 35185882 PMCID: PMC8847396 DOI: 10.3389/fimmu.2022.782441] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 01/13/2022] [Indexed: 12/13/2022] Open
Abstract
CD8+ T cells play a crucial role in the control and resolution of viral infections and can adopt a wide range of phenotypes and effector functions depending on the inflammatory context and the duration and extent of antigen exposure. Similarly, viral infections can exert diverse selective pressures on populations of clonally related T cells. Technical limitations have nevertheless made it challenging to investigate the relationship between clonal selection and transcriptional phenotypes of virus-specific T cells. We therefore performed single-cell T cell receptor (TCR) repertoire and transcriptome sequencing of virus-specific CD8 T cells in murine models of acute, chronic and latent infection. We observed clear infection-specific populations corresponding to memory, effector, exhausted, and inflationary phenotypes. We further uncovered a mouse-specific and polyclonal T cell response, despite all T cells sharing specificity to a single viral epitope, which was accompanied by stereotypic TCR germline gene usage in all three infection types. Persistent antigen exposure during chronic and latent viral infections resulted in a higher proportion of clonally expanded T cells relative to acute infection. We furthermore observed a relationship between transcriptional heterogeneity and clonal expansion for all three infections, with highly expanded clones having distinct transcriptional phenotypes relative to less expanded clones. Together our work relates clonal selection to gene expression in the context of viral infection and further provides a dataset and accompanying software for the immunological community.
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Affiliation(s)
- Raphael Kuhn
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Ioana Sandu
- Institute of Microbiology, ETH Zurich, Zurich, Switzerland
| | - Andreas Agrafiotis
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Kai-Lin Hong
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Danielle Shlesinger
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Daniel Neimeier
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Doron Merkler
- Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland.,Division of Clinical Pathology, Geneva University Hospital, Geneva, Switzerland
| | | | - Sai T Reddy
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Alexander Yermanos
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.,Institute of Microbiology, ETH Zurich, Zurich, Switzerland.,Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland
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Yermanos A, Agrafiotis A, Kuhn R, Robbiani D, Yates J, Papadopoulou C, Han J, Sandu I, Weber C, Bieberich F, Vazquez-Lombardi R, Dounas A, Neumeier D, Oxenius A, Reddy ST. Platypus: an open-access software for integrating lymphocyte single-cell immune repertoires with transcriptomes. NAR Genom Bioinform 2021; 3:lqab023. [PMID: 33884369 PMCID: PMC8046018 DOI: 10.1093/nargab/lqab023] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 03/05/2021] [Accepted: 03/17/2021] [Indexed: 12/12/2022] Open
Abstract
High-throughput single-cell sequencing (scSeq) technologies are revolutionizing the ability to molecularly profile B and T lymphocytes by offering the opportunity to simultaneously obtain information on adaptive immune receptor repertoires (VDJ repertoires) and transcriptomes. An integrated quantification of immune repertoire parameters, such as germline gene usage, clonal expansion, somatic hypermutation and transcriptional states opens up new possibilities for the high-resolution analysis of lymphocytes and the inference of antigen-specificity. While multiple tools now exist to investigate gene expression profiles from scSeq of transcriptomes, there is a lack of software dedicated to single-cell immune repertoires. Here, we present Platypus, an open-source software platform providing a user-friendly interface to investigate B-cell receptor and T-cell receptor repertoires from scSeq experiments. Platypus provides a framework to automate and ease the analysis of single-cell immune repertoires while also incorporating transcriptional information involving unsupervised clustering, gene expression and gene ontology. To showcase the capabilities of Platypus, we use it to analyze and visualize single-cell immune repertoires and transcriptomes from B and T cells from convalescent COVID-19 patients, revealing unique insight into the repertoire features and transcriptional profiles of clonally expanded lymphocytes. Platypus will expedite progress by facilitating the analysis of single-cell immune repertoire and transcriptome sequencing.
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Affiliation(s)
- Alexander Yermanos
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
- Institute of Microbiology, ETH Zurich, 8093 Zurich, Switzerland
- Department of Pathology and Immunology, University of Geneva, 1211 Geneva, Switzerland
| | - Andreas Agrafiotis
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
| | - Raphael Kuhn
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
| | - Damiano Robbiani
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
| | - Josephine Yates
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
| | - Chrysa Papadopoulou
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
| | - Jiami Han
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
| | - Ioana Sandu
- Institute of Microbiology, ETH Zurich, 8093 Zurich, Switzerland
| | - Cédric Weber
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
| | - Florian Bieberich
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
| | | | - Andreas Dounas
- Institute for Biomedical Engineering, University and ETH Zurich, 8092 Zurich, Switzerland
| | - Daniel Neumeier
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
| | - Annette Oxenius
- Institute of Microbiology, ETH Zurich, 8093 Zurich, Switzerland
| | - Sai T Reddy
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
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Andreatta M, Corria-Osorio J, Müller S, Cubas R, Coukos G, Carmona SJ. Interpretation of T cell states from single-cell transcriptomics data using reference atlases. Nat Commun 2021; 12:2965. [PMID: 34017005 PMCID: PMC8137700 DOI: 10.1038/s41467-021-23324-4] [Citation(s) in RCA: 194] [Impact Index Per Article: 64.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Accepted: 04/22/2021] [Indexed: 02/07/2023] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) has revealed an unprecedented degree of immune cell diversity. However, consistent definition of cell subtypes and cell states across studies and diseases remains a major challenge. Here we generate reference T cell atlases for cancer and viral infection by multi-study integration, and develop ProjecTILs, an algorithm for reference atlas projection. In contrast to other methods, ProjecTILs allows not only accurate embedding of new scRNA-seq data into a reference without altering its structure, but also characterizing previously unknown cell states that "deviate" from the reference. ProjecTILs accurately predicts the effects of cell perturbations and identifies gene programs that are altered in different conditions and tissues. A meta-analysis of tumor-infiltrating T cells from several cohorts reveals a strong conservation of T cell subtypes between human and mouse, providing a consistent basis to describe T cell heterogeneity across studies, diseases, and species.
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Affiliation(s)
- Massimo Andreatta
- Department of Oncology, Lausanne Branch, Ludwig Institute for Cancer Research, CHUV and University of Lausanne, Lausanne, Epalinges, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Jesus Corria-Osorio
- Department of Oncology, Lausanne Branch, Ludwig Institute for Cancer Research, CHUV and University of Lausanne, Lausanne, Epalinges, Switzerland
| | - Sören Müller
- Department of Bioinformatics and Computational Biology, Genentech, South San Francisco, CA, USA
| | - Rafael Cubas
- Department of Translational Oncology, Genentech, South San Francisco, CA, USA
| | - George Coukos
- Department of Oncology, Lausanne Branch, Ludwig Institute for Cancer Research, CHUV and University of Lausanne, Lausanne, Epalinges, Switzerland
| | - Santiago J Carmona
- Department of Oncology, Lausanne Branch, Ludwig Institute for Cancer Research, CHUV and University of Lausanne, Lausanne, Epalinges, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
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7
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Pertseva M, Gao B, Neumeier D, Yermanos A, Reddy ST. Applications of Machine and Deep Learning in Adaptive Immunity. Annu Rev Chem Biomol Eng 2021; 12:39-62. [PMID: 33852352 DOI: 10.1146/annurev-chembioeng-101420-125021] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Adaptive immunity is mediated by lymphocyte B and T cells, which respectively express a vast and diverse repertoire of B cell and T cell receptors and, in conjunction with peptide antigen presentation through major histocompatibility complexes (MHCs), can recognize and respond to pathogens and diseased cells. In recent years, advances in deep sequencing have led to a massive increase in the amount of adaptive immune receptor repertoire data; additionally, proteomics techniques have led to a wealth of data on peptide-MHC presentation. These large-scale data sets are now making it possible to train machine and deep learning models, which can be used to identify complex and high-dimensional patterns in immune repertoires. This article introduces adaptive immune repertoires and machine and deep learning related to biological sequence data and then summarizes the many applications in this field, which span from predicting the immunological status of a host to the antigen specificity of individual receptors and the engineering of immunotherapeutics.
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Affiliation(s)
- Margarita Pertseva
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland; .,Life Science Zurich Graduate School, ETH Zurich and University of Zurich, 8006 Zurich, Switzerland
| | - Beichen Gao
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland;
| | - Daniel Neumeier
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland;
| | - Alexander Yermanos
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland; .,Department of Pathology and Immunology, University of Geneva, 1205 Geneva, Switzerland.,Department of Biology, Institute of Microbiology and Immunology, ETH Zurich, 8093 Zurich, Switzerland
| | - Sai T Reddy
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland;
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Origin and fine-tuning of effector CD8 T cell subpopulations in chronic infection. Curr Opin Virol 2020; 46:27-35. [PMID: 33137688 DOI: 10.1016/j.coviro.2020.10.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 09/27/2020] [Accepted: 10/11/2020] [Indexed: 12/31/2022]
Abstract
Persisting stimulation can skew CD8 T cells towards a hypofunctional state commonly referred to as T cell exhaustion. This functional attenuation likely constitutes a mechanism which evolved to balance T cell mediated viral control versus overwhelming immunopathology. Here, we highlight the recent progress in defining the genetic mechanisms and factors shaping the differentiation of exhausted CD8 T cells. We review how the transcription factor Tox imposes an exhausted phenotype in the Tcf1+ progenitors and how CD4 help fine-tunes the effector subsets that emerge from this progenitor population. Both processes critically shape the spectrum of effector function performed by CD8 T cells and the level of resulting virus control. Finally, we discuss how these insights can be exploited to boost the immune response in chronic infection and cancer.
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