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Wei F, Kouro T, Nakamura Y, Ueda H, Iiizumi S, Hasegawa K, Asahina Y, Kishida T, Morinaga S, Himuro H, Horaguchi S, Tsuji K, Mano Y, Nakamura N, Kawamura T, Sasada T. Enhancing Mass spectrometry-based tumor immunopeptide identification: machine learning filter leveraging HLA binding affinity, aliphatic index and retention time deviation. Comput Struct Biotechnol J 2024; 23:859-869. [PMID: 38356658 PMCID: PMC10864759 DOI: 10.1016/j.csbj.2024.01.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/31/2024] [Accepted: 01/31/2024] [Indexed: 02/16/2024] Open
Abstract
Accurately identifying neoantigens is crucial for developing effective cancer vaccines and improving tumor immunotherapy. Mass spectrometry-based immunopeptidomics has emerged as a promising approach to identifying human leukocyte antigen (HLA) peptides presented on the surface of cancer cells, but false-positive identifications remain a significant challenge. In this study, liquid chromatography-tandem mass spectrometry-based proteomics and next-generation sequencing were utilized to identify HLA-presenting neoantigenic peptides resulting from non-synonymous single nucleotide variations in tumor tissues from 18 patients with renal cell carcinoma or pancreatic cancer. Machine learning was utilized to evaluate Mascot identifications through the prediction of MS/MS spectral consistency, and four descriptors for each candidate sequence: the max Mascot ion score, predicted HLA binding affinity, aliphatic index and retention time deviation, were selected as important features in filtering out identifications with inadequate fragmentation consistency. This suggests that incorporating rescoring filters based on peptide physicochemical characteristics could enhance the identification rate of MS-based immunopeptidomics compared to the traditional Mascot approach predominantly used for proteomics, indicating the potential for optimizing neoantigen identification pipelines as well as clinical applications.
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Affiliation(s)
- Feifei Wei
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Cancer Vaccine and Immunotherapy Center, Kanagawa Cancer Center, Yokohama, Japan
| | - Taku Kouro
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Cancer Vaccine and Immunotherapy Center, Kanagawa Cancer Center, Yokohama, Japan
| | - Yuko Nakamura
- Isotope Science Center, The University of Tokyo, Tokyo, Japan
| | - Hiroki Ueda
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Susumu Iiizumi
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Research & Early Development Division, BrightPath Biotherapeutics Co., Ltd., Kawasaki, Japan
| | - Kyoko Hasegawa
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Research & Early Development Division, BrightPath Biotherapeutics Co., Ltd., Kawasaki, Japan
| | - Yuki Asahina
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
| | - Takeshi Kishida
- Department of Urology, Kanagawa Cancer Center, Yokohama, Japan
| | - Soichiro Morinaga
- Department of Hepato-Biliary and Pancreatic Surgery, Kanagawa Cancer Center, Yokohama, Japan
| | - Hidetomo Himuro
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Cancer Vaccine and Immunotherapy Center, Kanagawa Cancer Center, Yokohama, Japan
| | - Shun Horaguchi
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Cancer Vaccine and Immunotherapy Center, Kanagawa Cancer Center, Yokohama, Japan
- Department of Pediatric Surgery, Nihon University School of Medicine, Tokyo, Japan
| | - Kayoko Tsuji
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Cancer Vaccine and Immunotherapy Center, Kanagawa Cancer Center, Yokohama, Japan
| | - Yasunobu Mano
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Cancer Vaccine and Immunotherapy Center, Kanagawa Cancer Center, Yokohama, Japan
| | - Norihiro Nakamura
- Research & Early Development Division, BrightPath Biotherapeutics Co., Ltd., Kawasaki, Japan
| | | | - Tetsuro Sasada
- Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan
- Cancer Vaccine and Immunotherapy Center, Kanagawa Cancer Center, Yokohama, Japan
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2
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Zhu X, Ma E, Ning K, Feng X, Quan W, Wang F, Zhu C, Ma Y, Dong Y, Jiang Q. A comparative analysis of TCR immune repertoire in COVID-19 patients. Hum Immunol 2024; 85:110795. [PMID: 38582657 DOI: 10.1016/j.humimm.2024.110795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 03/22/2024] [Accepted: 03/25/2024] [Indexed: 04/08/2024]
Abstract
The coronavirus disease 2019 (COVID-19) has merged as a global health threat since its outbreak in December 2019. Despite widespread recognition, there has been a paucity of studies focusing on the T cell receptor (TCR) bias in adaptive immunity induced by SARS-CoV-2. This research conducted a comparative analysis of the TCR immune repertoire to identify notable αβ TCR bias sequences associated with the SARS-CoV-2 virus antigen. The present study encompassed 73 symptomatic COVID-19 patients, categorized as moderate/mild or severe/critical, along with 9 healthy controls. Our findings revealed specific TCR chains prominently utilized by moderate and severe patients, identified as TRAV30-J34-TRBV3-1-J2-7 and TRAV12-3-J6-TRBV28-J1-1, respectively. Additionally, our research explored critical TCR preferences in the bronchoalveolar lavage fluid (BALF) of COVID-19 patients at various disease stages. Indeed, monitoring the dynamics of immune repertoire changes in COVID-19 patients could serve as a crucial biomarker for predicting disease progression and recovery. Furthermore, the study explored TCR bias in both peripheral blood mononuclear cells (PBMCs) and BALF. The most common αβ VJ pair observed in BALF was TRAV12-3-J18-TRBV7-6-J2-7. In addition, a comparative analysis with the VDJdb database indicated that the HLA-A*02:01 allele exhibited the widest distribution and highest frequency in COVID-19 patients across different periods. This comprehensive examination provided a global characterization of the TCR immune repertoire in COVID-19 patients, contributing significantly to our understanding of TCR bias induced by SARS-CoV-2.
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MESH Headings
- Humans
- COVID-19/immunology
- SARS-CoV-2/immunology
- Male
- Female
- Middle Aged
- Receptors, Antigen, T-Cell, alpha-beta/genetics
- Receptors, Antigen, T-Cell, alpha-beta/immunology
- Receptors, Antigen, T-Cell, alpha-beta/metabolism
- Adult
- Bronchoalveolar Lavage Fluid/immunology
- Aged
- Receptors, Antigen, T-Cell/immunology
- Receptors, Antigen, T-Cell/genetics
- Receptors, Antigen, T-Cell/metabolism
- Adaptive Immunity/immunology
- Severity of Illness Index
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Affiliation(s)
- Xiao Zhu
- School of Computer and Control Engineering, Yantai University, Yantai, Shandong, China; Lead Contact.
| | - Enze Ma
- School of Computer Science and Information Engineering, Harbin Normal University, Harbin, Heilongjiang, China
| | - Ke Ning
- School of Computer Science and Information Engineering, Harbin Normal University, Harbin, Heilongjiang, China
| | - Xiangyan Feng
- Department of Hematology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China.
| | - Wei Quan
- School of Computer and Control Engineering, Yantai University, Yantai, Shandong, China
| | - Fei Wang
- School of Computer and Control Engineering, Yantai University, Yantai, Shandong, China
| | - Chaoqun Zhu
- School of Computer and Control Engineering, Yantai University, Yantai, Shandong, China
| | - Yuanjun Ma
- School of Computer and Control Engineering, Yantai University, Yantai, Shandong, China
| | - Yucui Dong
- Department of Immunology, Binzhou Medical University, Yantai, Shandong, China
| | - Qinghua Jiang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, China.
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3
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Karnaukhov VK, Le Gac AL, Bilonda Mutala L, Darbois A, Perrin L, Legoux F, Walczak AM, Mora T, Lantz O. Innate-like T cell subset commitment in the murine thymus is independent of TCR characteristics and occurs during proliferation. Proc Natl Acad Sci U S A 2024; 121:e2311348121. [PMID: 38530897 PMCID: PMC10998581 DOI: 10.1073/pnas.2311348121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 02/09/2024] [Indexed: 03/28/2024] Open
Abstract
How T-cell receptor (TCR) characteristics determine subset commitment during T-cell development is still unclear. Here, we addressed this question for innate-like T cells, mucosal-associated invariant T (MAIT) cells, and invariant natural killer T (iNKT) cells. MAIT and iNKT cells have similar developmental paths, leading in mice to two effector subsets, cytotoxic (MAIT1/iNKT1) and IL17-secreting (MAIT17/iNKT17). For iNKT1 vs iNKT17 fate choice, an instructive role for TCR affinity was proposed but recent data argue against this model. Herein, we examined TCR role in MAIT and iNKT subset commitment through scRNAseq and TCR repertoire analysis. In our dataset of thymic MAIT cells, we found pairs of T-cell clones with identical amino acid TCR sequences originating from distinct precursors, one of which committed to MAIT1 and the other to MAIT17 fates. Quantitative in silico simulations indicated that the number of such cases is best explained by lineage choice being independent of TCR characteristics. Comparison of TCR features of MAIT1 and MAIT17 clonotypes demonstrated that the subsets cannot be distinguished based on TCR sequence. To pinpoint the developmental stage associated with MAIT sublineage choice, we demonstrated that proliferation takes place both before and after MAIT fate commitment. Altogether, we propose a model of MAIT cell development in which noncommitted, intermediate-stage MAIT cells undergo a first round of proliferation, followed by TCR characteristics-independent commitment to MAIT1 or MAIT17 lineage, followed by an additional round of proliferation. Reanalyzing a published iNKT TCR dataset, we showed that this model is also relevant for iNKT cell development.
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Affiliation(s)
- Vadim K. Karnaukhov
- Institut Curie, Paris Sciences & Lettres University, Inserm U932, Immunity and Cancer, Paris75005, France
- Laboratoire de Physique de l’École Normale Supérieure, Paris Sciences & Lettres University, CNRS, Sorbonne Université and Université Paris Cité, Paris75005, France
| | - Anne-Laure Le Gac
- Institut Curie, Paris Sciences & Lettres University, Inserm U932, Immunity and Cancer, Paris75005, France
| | - Linda Bilonda Mutala
- Institut Curie, Paris Sciences & Lettres University, Inserm U932, Immunity and Cancer, Paris75005, France
| | - Aurélie Darbois
- Institut Curie, Paris Sciences & Lettres University, Inserm U932, Immunity and Cancer, Paris75005, France
| | - Laetitia Perrin
- Institut Curie, Paris Sciences & Lettres University, Inserm U932, Immunity and Cancer, Paris75005, France
| | - Francois Legoux
- Institut Curie, Paris Sciences & Lettres University, Inserm U932, Immunity and Cancer, Paris75005, France
- INSERM Equipe de Recherche Labellisée 1305, CNRSUMR6290, Université de Rennes, Institut de Génétique & Développement de Rennes35000, France
| | - Aleksandra M. Walczak
- Laboratoire de Physique de l’École Normale Supérieure, Paris Sciences & Lettres University, CNRS, Sorbonne Université and Université Paris Cité, Paris75005, France
| | - Thierry Mora
- Laboratoire de Physique de l’École Normale Supérieure, Paris Sciences & Lettres University, CNRS, Sorbonne Université and Université Paris Cité, Paris75005, France
| | - Olivier Lantz
- Institut Curie, Paris Sciences & Lettres University, Inserm U932, Immunity and Cancer, Paris75005, France
- Laboratoire d’Immunologie Clinique, Département de médecine diagnostique et théranostique, Institut Curie, Paris75005, France
- Centre d’Investigation Clinique en Biothérapie Gustave-Roussy Institut Curie (CIC-BT1428), Paris75005, France
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4
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De Boer RJ, Kesmir C, Perelson AS, Borghans JAM. Is the exquisite specificity of lymphocytes generated by thymic selection or due to evolution? Front Immunol 2024; 15:1266349. [PMID: 38605941 PMCID: PMC11008227 DOI: 10.3389/fimmu.2024.1266349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 03/11/2024] [Indexed: 04/13/2024] Open
Abstract
We have previously argued that the antigen receptors of T and B lymphocytes evolved to be sufficiently specific to avoid massive deletion of clonotypes by negative selection. Their optimal 'specificity' level, i.e., probability of binding any particular epitope, was shown to be inversely related to the number of self-antigens that the cells have to be tolerant to. Experiments have demonstrated that T lymphocytes also become more specific during negative selection in the thymus, because cells expressing the most crossreactive receptors have the highest likelihood of binding a self-antigen, and hence to be tolerized (i.e., deleted, anergized, or diverted into a regulatory T cell phenotype). Thus, there are two -not mutually exclusive- explanations for the exquisite specificity of T cells, one involving evolution and the other thymic selection. To better understand the impact of both, we extend a previously developed mathematical model by allowing for T cells with very different binding probabilities in the pre-selection repertoire. We confirm that negative selection tends to tolerize the most crossreactive clonotypes. As a result, the average level of specificity in the functional post-selection repertoire depends on the number of self-antigens, even if there is no evolutionary optimization of binding probabilities. However, the evolutionary optimal range of binding probabilities in the pre-selection repertoire also depends on the number of self-antigens. Species with more self antigens need more specific pre-selection repertoires to avoid excessive loss of T cells during thymic selection, and hence mount protective immune responses. We conclude that both evolution and negative selection are responsible for the high level of specificity of lymphocytes.
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Affiliation(s)
- Rob J. De Boer
- Theoretical Biology and Bioinformatics, Utrecht University, Utrecht, Netherlands
| | - Can Kesmir
- Theoretical Biology and Bioinformatics, Utrecht University, Utrecht, Netherlands
| | - Alan S. Perelson
- Department of Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM, United States
| | - José A. M. Borghans
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht, Netherlands
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5
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Li X, Zhang Y, Guo S, Wu Z, Wang H, Huang Y, Wang Y, Qiu M, Lang J, Xiao Y, Zhu Y, Jin G, Hu L, Kong X. Global analysis of T-cell groups reveals immunological features and common antigen targets of digestive tract tumors. J Cancer Res Clin Oncol 2024; 150:129. [PMID: 38488909 PMCID: PMC10943170 DOI: 10.1007/s00432-024-05645-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 02/05/2024] [Indexed: 03/17/2024]
Abstract
BACKGROUND T cells are key players in the tumor immune microenvironment (TIME), as they can recognize and eliminate cancer cells that express neoantigens derived from somatic mutations. However, the diversity and specificity of T-cell receptors (TCRs) that recognize neoantigens are largely unknown, due to the high variability of TCR sequences among individuals. METHODS To address this challenge, we applied GLIPH2, a novel algorithm that groups TCRs based on their predicted antigen specificity and HLA restriction, to cluster the TCR repertoire of 1,702 patients with digestive tract cancer. The patients were divided into five groups based on whether they carried tumor-infiltrating or clonal-expanded TCRs and calculated their TCR diversity. The prognosis, tumor subtype, gene mutation, gene expression, and immune microenvironment of these groups were compared. Viral specificity inference and immunotherapy relevance analysis performed for the TCR groups. RESULTS This approach reduced the complexity of TCR sequences to 249 clonally expanded and 150 tumor-infiltrating TCR groups, which revealed distinct patterns of TRBV usage, HLA association, and TCR diversity. In gastric adenocarcinoma (STAD), patients with tumor-infiltrating TCRs (Patients-TI) had significantly worse prognosis than other patients (Patients-nonTI). Patients-TI had richer CD8+ T cells in the immune microenvironment, and their gene expression features were positively correlated with immunotherapy response. We also found that tumor-infiltrating TCR groups were associated with four distinct tumor subtypes, 26 common gene mutations, and 39 gene expression signatures. We discovered that tumor-infiltrating TCRs had cross-reactivity with viral antigens, indicating a possible link between viral infections and tumor immunity. CONCLUSION By applying GLIPH2 to TCR sequences from digestive tract tumors, we uncovered novel insights into the tumor immune landscape and identified potential candidates for shared TCRs and neoantigens.
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Affiliation(s)
- Xiaoxue Li
- Shanghai Institute of Nutrition and Health, CAS Key Laboratory of Tissue Microenvironment and Tumor, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Chinese Academy of Sciences (CAS), Beijing, China
| | - Yuchao Zhang
- Shanghai Institute of Nutrition and Health, CAS Key Laboratory of Tissue Microenvironment and Tumor, Chinese Academy of Sciences, Shanghai, China
| | - Shiwei Guo
- Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Shanghai, China
| | - Zhenchuan Wu
- Anda Biology Medicine Development (Shenzhen) Co., Ltd., Shenzhen, China
| | - Hailong Wang
- Anda Biology Medicine Development (Shenzhen) Co., Ltd., Shenzhen, China
| | - Yi Huang
- Shanghai Institute of Nutrition and Health, CAS Key Laboratory of Tissue Microenvironment and Tumor, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Chinese Academy of Sciences (CAS), Beijing, China
| | - Yue Wang
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
| | - Mengni Qiu
- Shanghai Institute of Nutrition and Health, CAS Key Laboratory of Tissue Microenvironment and Tumor, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Chinese Academy of Sciences (CAS), Beijing, China
| | - Jingyu Lang
- Shanghai Institute of Nutrition and Health, CAS Key Laboratory of Tissue Microenvironment and Tumor, Chinese Academy of Sciences, Shanghai, China
| | - Yichuan Xiao
- Shanghai Institute of Nutrition and Health, CAS Key Laboratory of Tissue Microenvironment and Tumor, Chinese Academy of Sciences, Shanghai, China
| | - Yufei Zhu
- Shanghai Institute of Nutrition and Health, CAS Key Laboratory of Tissue Microenvironment and Tumor, Chinese Academy of Sciences, Shanghai, China
| | - Gang Jin
- Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Shanghai, China.
| | - Landian Hu
- Anda Biology Medicine Development (Shenzhen) Co., Ltd., Shenzhen, China.
| | - Xiangyin Kong
- Shanghai Institute of Nutrition and Health, CAS Key Laboratory of Tissue Microenvironment and Tumor, Chinese Academy of Sciences, Shanghai, China.
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
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6
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Porcheddu V, Lhomme G, Giraudet R, Correia E, Maillère B. The self-reactive FVIII T cell repertoire in healthy individuals relies on a short set of epitopes and public clonotypes. Front Immunol 2024; 15:1345195. [PMID: 38510258 PMCID: PMC10951066 DOI: 10.3389/fimmu.2024.1345195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 01/31/2024] [Indexed: 03/22/2024] Open
Abstract
Non-mutated FVIII-specific CD4 T cell epitopes have been recently found to contribute to the development of inhibitors in patients with hemophilia A (HA), while auto-reactive CD4 T cells specific to FVIII circulate in the blood of healthy individuals at a frequency close to the foreign protein ovalbumin. Thus, although FVIII is a self-protein, the central tolerance raised against FVIII appears to be low. In this study, we conducted a comprehensive analysis of the FVIII CD4 T cell repertoire in 29 healthy donors. Sequencing of the CDR3β TCR region from isolated FVIII-specific CD4 T cells revealed a limited usage and pairing of TRBV and TRBJ genes as well as a mostly hydrophobic composition of the CDR3β region according to their auto-reactivity. The FVIII repertoire is dominated by a few clonotypes, with only 13 clonotypes accounting for half of the FVIII response. Through a large-scale epitope mapping of the full-length FVIII sequence, we identified 18 immunodominant epitopes located in the A1, A3, C1, and C2 domains and covering half of the T cell response. These epitopes exhibited a broad specificity for HLA-DR or DP molecules or both. T cell priming with this reduced set of peptides revealed that highly expanded clonotypes specific to these epitopes were responsible individually for up to 32% of the total FVIII repertoire. These FVIII T cell epitopes and clonotypes were shared among HLA-unrelated donors tested and previously reported HA patients. Our study highlights the role of the auto-reactive T cell response against FVIII in HA and its similarity to the response observed in healthy individuals. Thus, it provides valuable insights for the development of new tolerance induction and deimmunization strategies.
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Affiliation(s)
- Valeria Porcheddu
- Université de Paris-Saclay, Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Institut national de recherche pour l’agriculture, l’alimentation et l’environnement (INRAE), Département Médicaments et Technologies pour la Santé, Service d’Ingénierie Moléculaire pour la Santé (SIMoS), Gif-sur-Yvette, France
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7
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Fang J, Lei J, He B, Wu Y, Chen P, Sun Z, Wu N, Huang Y, Wei P, Yin L, Chen Y. Decoding the transcriptional heterogeneity, differentiation lineage, clinical significance in tissue-resident memory CD8 T cell of the small intestine by single-cell analysis. J Transl Med 2024; 22:203. [PMID: 38403590 PMCID: PMC10895748 DOI: 10.1186/s12967-024-04978-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 02/11/2024] [Indexed: 02/27/2024] Open
Abstract
Resident memory T (Trm) cells which are specifically located in non-lymphoid tissues showed distinct phenotypes and functions compared to circulating memory T cells and were vital for the initiation of robust immune response within tissues. However, the heterogeneity in the transcriptional features, development pathways, and cancer response of Trm cells in the small intestine was not demonstrated. Here, we integrated scRNA-seq and scTCR-seq data pan-tissue T cells to explore the heterogeneity of Trm cells and their development pathways. Trm were enriched in tissue-specific immune response and those in the DUO specially interacted with B cells via TNF and MHC-I signatures. T cell lineage analyses demonstrated that Trm might be derived from the T_CD4/CD8 subset within the same organ or migrated from spleen and mesenteric lymph nodes. We compared the immune repertoire of Trm among organs and implied that clonotypes in both DUO and ILE were less expanded and hydrophilic TRB CDR3s were enriched in the DUO. We further demonstrated that Trm in the intestine infiltrated the colorectal cancer and several effector molecules were highly expressed. Finally, the TCGA dataset of colorectal cancer implied that the infiltration of Trm from the DUO and the ILE was beneficial for overall survival and the response to immune checkpoint blockade.
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Affiliation(s)
- Jialing Fang
- State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Department of Clinical Oncology, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Jun Lei
- State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Department of Clinical Oncology, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China
- Department of Laboratory Medicine, Xixi Hospital of Hangzhou, Hangzhou, China
| | - Boxiao He
- State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Department of Clinical Oncology, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Yankang Wu
- State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Department of Clinical Oncology, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Peng Chen
- State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Department of Clinical Oncology, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Zaiqiao Sun
- State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Department of Clinical Oncology, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Ning Wu
- Department of Immunology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yafei Huang
- Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Pengcheng Wei
- School of Medicine, Guangxi University, Nanning, 530004, China
- Department of Immunology and Genomic Medicine, National Jewish Health, Denver, CO, 80206, USA
| | - Lei Yin
- State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Department of Clinical Oncology, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China.
| | - Yongshun Chen
- State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Department of Clinical Oncology, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China.
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8
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Akama-Garren EH, Yin X, Prestwood TR, Ma M, Utz PJ, Carroll MC. T cell help shapes B cell tolerance. Sci Immunol 2024; 9:eadj7029. [PMID: 38363829 DOI: 10.1126/sciimmunol.adj7029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 12/29/2023] [Indexed: 02/18/2024]
Abstract
T cell help is a crucial component of the normal humoral immune response, yet whether it promotes or restrains autoreactive B cell responses remains unclear. Here, we observe that autoreactive germinal centers require T cell help for their formation and persistence. Using retrogenic chimeras transduced with candidate TCRs, we demonstrate that a follicular T cell repertoire restricted to a single autoreactive TCR, but not a foreign antigen-specific TCR, is sufficient to initiate autoreactive germinal centers. Follicular T cell specificity influences the breadth of epitope spreading by regulating wild-type B cell entry into autoreactive germinal centers. These results demonstrate that TCR-dependent T cell help can promote loss of B cell tolerance and that epitope spreading is determined by TCR specificity.
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Affiliation(s)
- Elliot H Akama-Garren
- Program in Cellular and Molecular Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
- Harvard-MIT Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA
| | - Xihui Yin
- Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Tyler R Prestwood
- Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Minghe Ma
- Program in Cellular and Molecular Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Paul J Utz
- Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Michael C Carroll
- Program in Cellular and Molecular Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
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9
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Yasumizu Y, Takeuchi D, Morimoto R, Takeshima Y, Okuno T, Kinoshita M, Morita T, Kato Y, Wang M, Motooka D, Okuzaki D, Nakamura Y, Mikami N, Arai M, Zhang X, Kumanogoh A, Mochizuki H, Ohkura N, Sakaguchi S. Single-cell transcriptome landscape of circulating CD4 + T cell populations in autoimmune diseases. CELL GENOMICS 2024; 4:100473. [PMID: 38359792 PMCID: PMC10879034 DOI: 10.1016/j.xgen.2023.100473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 09/07/2023] [Accepted: 12/05/2023] [Indexed: 02/17/2024]
Abstract
CD4+ T cells are key mediators of various autoimmune diseases; however, their role in disease progression remains unclear due to cellular heterogeneity. Here, we evaluated CD4+ T cell subpopulations using decomposition-based transcriptome characterization and canonical clustering strategies. This approach identified 12 independent gene programs governing whole CD4+ T cell heterogeneity, which can explain the ambiguity of canonical clustering. In addition, we performed a meta-analysis using public single-cell datasets of over 1.8 million peripheral CD4+ T cells from 953 individuals by projecting cells onto the reference and cataloging cell frequency and qualitative alterations of the populations in 20 diseases. The analyses revealed that the 12 transcriptional programs were useful in characterizing each autoimmune disease and predicting its clinical status. Moreover, genetic variants associated with autoimmune diseases showed disease-specific enrichment within the 12 gene programs. The results collectively provide a landscape of single-cell transcriptomes of CD4+ T cell subpopulations involved in autoimmune disease.
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Affiliation(s)
- Yoshiaki Yasumizu
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan; Department of Neurology, Graduate School of Medicine, Osaka University, Osaka, Japan; Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Osaka, Japan
| | - Daiki Takeuchi
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan; Faculty of Medicine, Osaka University, Osaka, Japan
| | - Reo Morimoto
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | - Yusuke Takeshima
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | - Tatsusada Okuno
- Department of Neurology, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Makoto Kinoshita
- Department of Neurology, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Takayoshi Morita
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Yasuhiro Kato
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Osaka, Japan; Department of Immunopathology, Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | - Min Wang
- Clinical Immunology Center, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Rheumatology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Daisuke Motooka
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Osaka, Japan; Genome Information Research Center, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
| | - Daisuke Okuzaki
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Osaka, Japan; Genome Information Research Center, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
| | - Yamami Nakamura
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | - Norihisa Mikami
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | - Masaya Arai
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | - Xuan Zhang
- Department of Rheumatology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Atsushi Kumanogoh
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Osaka, Japan; Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Osaka, Japan; Department of Immunopathology, Immunology Frontier Research Center, Osaka University, Osaka, Japan; Center for Infectious Diseases for Education and Research, Osaka University, Osaka, Japan
| | - Hideki Mochizuki
- Department of Neurology, Graduate School of Medicine, Osaka University, Osaka, Japan; Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Osaka, Japan
| | - Naganari Ohkura
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan; Department of Frontier Research in Tumor Immunology, Graduate School of Medicine, Osaka University, Osaka, Japan.
| | - Shimon Sakaguchi
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan; Department of Experimental Immunology, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan.
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10
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Lagattuta KA, Park HL, Rumker L, Ishigaki K, Nathan A, Raychaudhuri S. The genetic basis of autoimmunity seen through the lens of T cell functional traits. Nat Commun 2024; 15:1204. [PMID: 38331990 PMCID: PMC10853555 DOI: 10.1038/s41467-024-45170-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 01/15/2024] [Indexed: 02/10/2024] Open
Abstract
Autoimmune disease heritability is enriched in T cell-specific regulatory regions of the genome. Modern-day T cell datasets now enable association studies between single nucleotide polymorphisms (SNPs) and a myriad of molecular phenotypes, including chromatin accessibility, gene expression, transcriptional programs, T cell antigen receptor (TCR) amino acid usage, and cell state abundances. Such studies have identified hundreds of quantitative trait loci (QTLs) in T cells that colocalize with genetic risk for autoimmune disease. The key challenge facing immunologists today lies in synthesizing these results toward a unified understanding of the autoimmune T cell: which genes, cell states, and antigens drive tissue destruction?
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Affiliation(s)
- Kaitlyn A Lagattuta
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Hannah L Park
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Laurie Rumker
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Kazuyoshi Ishigaki
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Laboratory for Human Immunogenetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Aparna Nathan
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
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11
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Anang DC, Walter HAW, Lim J, Niewold ITG, van der Weele L, Aronica E, Eftimov F, Raaphorst J, van Schaik BDC, van Kampen AHC, van der Kooi AJ, de Vries N. TCRβ clones in muscle tissue share structural features in patients with idiopathic inflammatory myopathy and are associated with disease activity. Front Immunol 2024; 14:1279055. [PMID: 38268914 PMCID: PMC10806010 DOI: 10.3389/fimmu.2023.1279055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 12/13/2023] [Indexed: 01/26/2024] Open
Abstract
Objectives To characterize the T cell receptor (TCRβ) repertoire in peripheral blood and muscle tissues of treatment naïve patients with newly diagnosed idiopathic inflammatory myopathies (IIMs). Methods High throughput RNA sequencing of the TCRβ chain was performed in peripheral blood and muscle tissue in twenty newly-diagnosed treatment-naïve IIM patients (9 DM, 5 NM/OM, 5 IMNM and 1 ASyS) and healthy controls. Results thereof were correlated with markers of disease activity. Results Muscle tissue of IIM patients shows more expansion of TCRβ clones and decreased diversity when compared to peripheral blood of IIM as well as healthy controls (both p=0.0001). Several expanded TCRβ clones in muscle are tissue restricted and cannot be retrieved in peripheral blood. These clones have significantly longer CDR3 regions when compared to clones (also) found in circulation (p=0.0002), while their CDR3 region is more hydrophobic (p<0.01). Network analysis shows that clonal TCRβ signatures are shared between patients. Increased clonal expansion in muscle tissue is significantly correlated with increased CK levels (p=0.03), while it tends to correlate with decreased muscle strength (p=0.08). Conclusion Network analysis of clones in muscle of IIM patients shows shared clusters of sequences across patients. Muscle-restricted CDR3 TCRβ clones show specific structural features in their T cell receptor. Our results indicate that clonal TCRβ expansion in muscle tissue might be associated with disease activity. Collectively, these findings support a role for specific clonal T cell responses in muscle tissue in the pathogenesis of the IIM subtypes studied.
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Affiliation(s)
- Dornatien C. Anang
- Department of Rheumatology and Clinical Immunology, Amsterdam Rheumatology and Immunology Center, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
- Department of Experimental Immunology, Amsterdam Infection and Immunity Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
- Department of Genome Analysis, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Hannah A. W. Walter
- Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Johan Lim
- Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Ilse T. G. Niewold
- Department of Rheumatology and Clinical Immunology, Amsterdam Rheumatology and Immunology Center, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
- Department of Genome Analysis, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Linda van der Weele
- Department of Rheumatology and Clinical Immunology, Amsterdam Rheumatology and Immunology Center, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
- Department of Experimental Immunology, Amsterdam Infection and Immunity Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Eleonora Aronica
- Department of (Neuro) Pathology, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Filip Eftimov
- Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Joost Raaphorst
- Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Barbera D. C. van Schaik
- Bioinformatics Laboratory, Department of Epidemiology and Data Science, Amsterdam Public Health Institute, Amsterdam Infection and Immunity Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Antoine H. C. van Kampen
- Bioinformatics Laboratory, Department of Epidemiology and Data Science, Amsterdam Public Health Institute, Amsterdam Infection and Immunity Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Anneke J. van der Kooi
- Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Niek de Vries
- Department of Rheumatology and Clinical Immunology, Amsterdam Rheumatology and Immunology Center, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
- Department of Experimental Immunology, Amsterdam Infection and Immunity Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
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12
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Firdessa Fite R, Bechi Genzano C, Mallone R, Creusot RJ. Epitope-based precision immunotherapy of Type 1 diabetes. Hum Vaccin Immunother 2023; 19:2154098. [PMID: 36656048 PMCID: PMC9980607 DOI: 10.1080/21645515.2022.2154098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Antigen-specific immunotherapies (ASITs) address important clinical needs in treating autoimmune diseases. However, Type 1 diabetes is a heterogeneous disease wherein patient characteristics influence responsiveness to ASITs. Targeting not only disease-relevant T cell populations, but also specific groups of patients using precision medicine is a new goal toward achieving effective treatment. HLA-restricted peptides provide advantages over protein as antigens, however, methods for profiling antigen-specific T cells need to improve in sensitivity, depth, and throughput to facilitate epitope selection. Delivery approaches are highly diverse, illustrating the many ways relevant antigen-presenting cell populations and anatomical locations can be targeted for tolerance induction. The role of persistence of antigen presentation in promoting durable antigen-specific tolerance requires further investigation. Based on the outcome of ASIT trials, the field is moving toward using patient-specific variations to improve efficacy, but challenges still lie on the path to delivering more effective and safer treatment to the T1D patient population.
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Affiliation(s)
- Rebuma Firdessa Fite
- Columbia Center for Translational Immunology, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Camillo Bechi Genzano
- Columbia Center for Translational Immunology, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Roberto Mallone
- Université Paris Cité, Institut Cochin, CNRS, INSERM, Paris, France.,Assistance Publique Hôpitaux de Paris, Service de Diabétologie et Immunologie Clinique, Cochin Hospital, Hôpitaux Universitaires de Paris Centre-Université de Paris, Paris, France
| | - Remi J Creusot
- Columbia Center for Translational Immunology, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
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13
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Borna Š, Lee E, Nideffer J, Ramachandran A, Wang B, Baker J, Mavers M, Lakshmanan U, Narula M, Garrett AKH, Schulze J, Olek S, Marois L, Gernez Y, Bhatia M, Chong HJ, Walter J, Kitcharoensakkul M, Lang A, Cooper MA, Bertaina A, Roncarolo MG, Meffre E, Bacchetta R. Identification of unstable regulatory and autoreactive effector T cells that are expanded in patients with FOXP3 mutations. Sci Transl Med 2023; 15:eadg6822. [PMID: 38117899 PMCID: PMC11070150 DOI: 10.1126/scitranslmed.adg6822] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 11/17/2023] [Indexed: 12/22/2023]
Abstract
Studies of the monogenic autoimmune disease immunodysregulation polyendocrinopathy enteropathy X-linked syndrome (IPEX) have elucidated the essential function of the transcription factor FOXP3 and thymic-derived regulatory T cells (Tregs) in controlling peripheral tolerance. However, the presence and the source of autoreactive T cells in IPEX remain undetermined. Here, we investigated how FOXP3 deficiency affects the T cell receptor (TCR) repertoire and Treg stability in vivo and compared T cell abnormalities in patients with IPEX with those in patients with autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy syndrome (APECED). To study Tregs independently of their phenotype and to analyze T cell autoreactivity, we combined Treg-specific demethylation region analyses, single-cell multiomic profiling, and bulk TCR sequencing. We found that patients with IPEX, unlike patients with APECED, have expanded autoreactive T cells originating from both autoreactive effector T cells (Teffs) and Tregs. In addition, a fraction of the expanded Tregs from patients with IPEX lost their phenotypic and functional markers, including CD25 and FOXP3. Functional experiments with CRISPR-Cas9-mediated FOXP3 knockout Tregs and Tregs from patients with IPEX indicated that the patients' Tregs gain a TH2-skewed Teff-like function, which is consistent with immune dysregulation observed in these patients. Analyses of FOXP3 mutation-carrier mothers and a patient with IPEX after hematopoietic stem cell transplantation indicated that Tregs expressing nonmutated FOXP3 prevent the accumulation of autoreactive Teffs and unstable Tregs. These findings could be directly used for diagnostic and prognostic purposes and for monitoring the effects of immunomodulatory treatments.
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Affiliation(s)
- Šimon Borna
- Department of Pediatrics, Division of Hematology, Oncology, Stem Cell Transplantation and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Esmond Lee
- Department of Pediatrics, Division of Hematology, Oncology, Stem Cell Transplantation and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Jason Nideffer
- Department of Pediatrics, Division of Hematology, Oncology, Stem Cell Transplantation and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Akshaya Ramachandran
- Department of Pediatrics, Division of Hematology, Oncology, Stem Cell Transplantation and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Bing Wang
- Department of Pediatrics, Division of Hematology, Oncology, Stem Cell Transplantation and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Jeanette Baker
- Department of Medicine, Division of Blood and Marrow Transplantation, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Melissa Mavers
- Department of Pediatrics, Division of Hematology, Oncology, Stem Cell Transplantation and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Uma Lakshmanan
- Department of Pediatrics, Division of Hematology, Oncology, Stem Cell Transplantation and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Mansi Narula
- Department of Pediatrics, Division of Hematology, Oncology, Stem Cell Transplantation and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Amy Kang-hee Garrett
- Department of Pediatrics, Division of Hematology, Oncology, Stem Cell Transplantation and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | | | - Sven Olek
- Ivana Turbachova Laboratory for Epigenetics, Precision for Medicine GmbH, Berlin, 12489, Germany
| | - Louis Marois
- Department of Medicine, Immunology and Allergy Service, CHU de Québec – Laval University, Quebec, G1V 4G2, Canada
| | - Yael Gernez
- Department of Pediatrics, Division of Allergy, Rheumatology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Monica Bhatia
- Columbia University Irving Medical Center, NY, NY 10032, USA
| | - Hey Jin Chong
- Division of Allergy and Immunology, University of Pittsburgh Medical Center Children’s Hospital of Pittsburgh, Pittsburgh, 15224, Pa, USA
| | - Jolan Walter
- Division of Allergy and Immunology, Department of Pediatrics, Johns Hopkins All Children’s Hospital, University of South Florida, St. Petersburg, 33701, FL, USA
| | - Maleewan Kitcharoensakkul
- Divisions of Rheumatology/Immunology, and Allergy and Pulmonary Medicine, Department of Pediatrics, Washington University in St. Louis, St. Louis, Missouri, 63110, USA
| | - Abigail Lang
- Department of Pediatrics, Division of Allergy and Immunology, Ann and Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, 60611, USA
- Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Megan A. Cooper
- Department of pediatrics, division of Rheumatology and Immunology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, 63110, USA
| | - Alice Bertaina
- Department of Pediatrics, Division of Hematology, Oncology, Stem Cell Transplantation and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
- Center for Definitive and Curative Medicine (CDCM), Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Maria Grazia Roncarolo
- Department of Pediatrics, Division of Hematology, Oncology, Stem Cell Transplantation and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
- Center for Definitive and Curative Medicine (CDCM), Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Eric Meffre
- Department of Medicine, Division of Immunology and Rheumatology, Stanford University School of Medicine, 269 Campus Drive West, Stanford, CA 94305, USA
| | - Rosa Bacchetta
- Department of Pediatrics, Division of Hematology, Oncology, Stem Cell Transplantation and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
- Center for Definitive and Curative Medicine (CDCM), Stanford University School of Medicine, Stanford, CA 94305, USA
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14
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Textor J, Buytenhuijs F, Rogers D, Gauthier ÈM, Sultan S, Wortel IMN, Kalies K, Fähnrich A, Pagel R, Melichar HJ, Westermann J, Mandl JN. Machine learning analysis of the T cell receptor repertoire identifies sequence features of self-reactivity. Cell Syst 2023; 14:1059-1073.e5. [PMID: 38061355 DOI: 10.1016/j.cels.2023.11.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 09/01/2023] [Accepted: 11/09/2023] [Indexed: 12/23/2023]
Abstract
The T cell receptor (TCR) determines specificity and affinity for both foreign and self-peptides presented by the major histocompatibility complex (MHC). Although the strength of TCR interactions with self-pMHC impacts T cell function, it has been challenging to identify TCR sequence features that predict T cell fate. To discern patterns distinguishing TCRs from naive CD4+ T cells with low versus high self-reactivity, we used data from 42 mice to train a machine learning (ML) algorithm that identifies population-level differences between TCRβ sequence sets. This approach revealed that weakly self-reactive T cell populations were enriched for longer CDR3β regions and acidic amino acids. We tested our ML predictions of self-reactivity using retrogenic mice with fixed TCRβ sequences. Extrapolating our analyses to independent datasets, we predicted high self-reactivity for regulatory T cells and slightly reduced self-reactivity for T cells responding to chronic infections. Our analyses suggest a potential trade-off between TCR repertoire diversity and self-reactivity. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Johannes Textor
- Data Science Group, Institute for Computing and Information Sciences, Radboud University, Nijmegen 6525 EC, the Netherlands; Medical BioSciences, Radboudumc, Nijmegen 6525 GA, the Netherlands.
| | - Franka Buytenhuijs
- Data Science Group, Institute for Computing and Information Sciences, Radboud University, Nijmegen 6525 EC, the Netherlands
| | - Dakota Rogers
- Department of Physiology, McGill University, Montreal, QC H3G 0B1, Canada; McGill Research Centre on Complex Traits, McGill University, Montreal, QC H3G 0B1, Canada
| | - Ève Mallet Gauthier
- Immunology-Oncology Unit, Maisonneuve-Rosemont Hospital Research Center, Montreal, QC H1T 2M4, Canada; Department of Microbiology, Infectious Diseases, and Immunology, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Shabaz Sultan
- Data Science Group, Institute for Computing and Information Sciences, Radboud University, Nijmegen 6525 EC, the Netherlands; Medical BioSciences, Radboudumc, Nijmegen 6525 GA, the Netherlands
| | - Inge M N Wortel
- Data Science Group, Institute for Computing and Information Sciences, Radboud University, Nijmegen 6525 EC, the Netherlands; Medical BioSciences, Radboudumc, Nijmegen 6525 GA, the Netherlands
| | - Kathrin Kalies
- Institut für Anatomie, Universität zu Lübeck, 23562 Lübeck, Germany
| | - Anke Fähnrich
- Institut für Anatomie, Universität zu Lübeck, 23562 Lübeck, Germany
| | - René Pagel
- Institut für Anatomie, Universität zu Lübeck, 23562 Lübeck, Germany
| | - Heather J Melichar
- Immunology-Oncology Unit, Maisonneuve-Rosemont Hospital Research Center, Montreal, QC H1T 2M4, Canada; Department of Medicine, Université de Montréal, Montréal, QC H1T 2M4, Canada; Department of Microbiology & Immunology, McGill University, Montreal, QC H3A 1A3, Canada; Rosalind and Morris Goodman Cancer Institute, McGill University, Montreal, QC H3A 1A3, Canada
| | | | - Judith N Mandl
- Department of Physiology, McGill University, Montreal, QC H3G 0B1, Canada; Department of Microbiology & Immunology, McGill University, Montreal, QC H3A 1A3, Canada; McGill Research Centre on Complex Traits, McGill University, Montreal, QC H3G 0B1, Canada.
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15
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Shah RK, Cygan E, Kozlik T, Colina A, Zamora AE. Utilizing immunogenomic approaches to prioritize targetable neoantigens for personalized cancer immunotherapy. Front Immunol 2023; 14:1301100. [PMID: 38149253 PMCID: PMC10749952 DOI: 10.3389/fimmu.2023.1301100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Accepted: 11/29/2023] [Indexed: 12/28/2023] Open
Abstract
Advancements in sequencing technologies and bioinformatics algorithms have expanded our ability to identify tumor-specific somatic mutation-derived antigens (neoantigens). While recent studies have shown neoantigens to be compelling targets for cancer immunotherapy due to their foreign nature and high immunogenicity, the need for increasingly accurate and cost-effective approaches to rapidly identify neoantigens remains a challenging task, but essential for successful cancer immunotherapy. Currently, gene expression analysis and algorithms for variant calling can be used to generate lists of mutational profiles across patients, but more care is needed to curate these lists and prioritize the candidate neoantigens most capable of inducing an immune response. A growing amount of evidence suggests that only a handful of somatic mutations predicted by mutational profiling approaches act as immunogenic neoantigens. Hence, unbiased screening of all candidate neoantigens predicted by Whole Genome Sequencing/Whole Exome Sequencing may be necessary to more comprehensively access the full spectrum of immunogenic neoepitopes. Once putative cancer neoantigens are identified, one of the largest bottlenecks in translating these neoantigens into actionable targets for cell-based therapies is identifying the cognate T cell receptors (TCRs) capable of recognizing these neoantigens. While many TCR-directed screening and validation assays have utilized bulk samples in the past, there has been a recent surge in the number of single-cell assays that provide a more granular understanding of the factors governing TCR-pMHC interactions. The goal of this review is to provide an overview of existing strategies to identify candidate neoantigens using genomics-based approaches and methods for assessing neoantigen immunogenicity. Additionally, applications, prospects, and limitations of some of the current single-cell technologies will be discussed. Finally, we will briefly summarize some of the recent models that have been used to predict TCR antigen specificity and analyze the TCR receptor repertoire.
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Affiliation(s)
- Ravi K. Shah
- Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Erin Cygan
- Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Tanya Kozlik
- Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Alfredo Colina
- Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Anthony E. Zamora
- Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, United States
- Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI, United States
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16
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Mitchell AM, Baschal EE, McDaniel KA, Fleury T, Choi H, Pyle L, Yu L, Rewers MJ, Nakayama M, Michels AW. Tracking DNA-based antigen-specific T cell receptors during progression to type 1 diabetes. SCIENCE ADVANCES 2023; 9:eadj6975. [PMID: 38064552 PMCID: PMC10708189 DOI: 10.1126/sciadv.adj6975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 11/09/2023] [Indexed: 12/18/2023]
Abstract
T cells targeting self-proteins are important mediators in autoimmune diseases. T cells express unique cell-surface receptors (TCRs) that recognize peptides presented by major histocompatibility molecules. TCRs have been identified from blood and pancreatic islets of individuals with type 1 diabetes (T1D). Here, we tracked ~1700 known antigen-specific TCR sequences, islet antigen or viral reactive, in bulk TCRβ sequencing from longitudinal blood DNA samples in at-risk cases who progressed to T1D, age/sex/human leukocyte antigen-matched controls, and a new-onset T1D cohort. Shared and frequent antigen-specific TCRβ sequences were identified in all three cohorts, and viral sequences were present across all ages. Islet sequences had different patterns of accumulation based upon antigen specificity in the at-risk cases. Furthermore, 73 islet-antigen TCRβ sequences were present in higher frequencies and numbers in T1D samples relative to controls. The total number of these disease-associated TCRβ sequences inversely correlated with age at clinical diagnosis, indicating the potential to use disease-relevant TCR sequences as biomarkers in autoimmune disorders.
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Affiliation(s)
- Angela M. Mitchell
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO, USA
| | - Erin E. Baschal
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO, USA
| | - Kristen A. McDaniel
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO, USA
| | - Theodore Fleury
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO, USA
| | - Hyelin Choi
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO, USA
| | - Laura Pyle
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO, USA
- Department of Biostatistics and Informatics, University of Colorado School of Public Health, Aurora, CO, USA
| | - Liping Yu
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO, USA
- Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO, USA
| | - Marian J. Rewers
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO, USA
- Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO, USA
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Maki Nakayama
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO, USA
- Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO, USA
- Department of Immunology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Aaron W. Michels
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO, USA
- Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO, USA
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
- Department of Immunology, University of Colorado School of Medicine, Aurora, CO, USA
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17
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Liu Z, Zhou J, Wu S, Chen Z, Wu S, Chen L, Zhu X, Li Z. Why Treg should be the focus of cancer immunotherapy: The latest thought. Biomed Pharmacother 2023; 168:115142. [PMID: 37806087 DOI: 10.1016/j.biopha.2023.115142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Revised: 06/26/2023] [Accepted: 07/07/2023] [Indexed: 10/10/2023] Open
Abstract
Regulatory T cells are a subgroup of T cells with immunomodulatory functions. Different from most cytotoxic T cells and helper T cells, they play a supporting role in the immune system. What's more, regulatory T cells often play an immunosuppressive role, which mainly plays a role in maintaining the stability of the immune system and regulating the immune response in the body. However, recent studies have shown that not only playing a role in autoimmune diseases, organ transplantation, and other aspects, regulatory T cells can also play a role in the immune escape of tumors in the body, through various mechanisms to help tumor cells escape from the demic immune system, weakening the anti-cancer effect in the body. For a better understanding of the role that regulatory T cells can play in cancer, and to be able to use regulatory T cells for tumor immunotherapy more quickly. This review focuses on the research progress of various mechanisms of regulatory T cells in the tumor environment, the related research of tumor cells acting on regulatory T cells, and the existing various therapeutic methods acting on regulatory T cells.
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Affiliation(s)
- Ziyu Liu
- The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, China
| | - Jiajun Zhou
- Kidney Department, The First Affiliated Hospital of Wannan Medical College, Wuhu, China
| | - Shihui Wu
- The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, China
| | - Zhihong Chen
- The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, China
| | - Shuhong Wu
- The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, China
| | - Ling Chen
- The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, China
| | - Xiao Zhu
- The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, China; Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou Medical College, Hangzhou, China.
| | - Zesong Li
- Guangdong Provincial Key Laboratory of Systems Biology and Synthetic Biology for Urogenital Tumors, Shenzhen Key Laboratory of Genitourinary Tumor, Department of Urology, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital (Shenzhen Institute of Translational Medicine), Shenzhen, China.
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18
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Zhao W, Lei J, Ke S, Chen Y, Xiao J, Tang Z, Wang L, Ren Y, Alnaggar M, Qiu H, Shi W, Yin L, Chen Y. Fecal microbiota transplantation plus tislelizumab and fruquintinib in refractory microsatellite stable metastatic colorectal cancer: an open-label, single-arm, phase II trial (RENMIN-215). EClinicalMedicine 2023; 66:102315. [PMID: 38024475 PMCID: PMC10679864 DOI: 10.1016/j.eclinm.2023.102315] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 10/18/2023] [Accepted: 10/30/2023] [Indexed: 12/01/2023] Open
Abstract
Background Immunotherapy has revolutionized the treatment of cancer. However, microsatellite stable (MSS) metastatic colorectal cancer (mCRC) shows a low response to PD-1 inhibitors. Antiangiogenic therapy can enhance anti-PD-1 efficacy, but it still cannot meet clinical needs. Increasing evidence supported a close relationship between gut microbiome and anti-PD-1 efficacy. This study aimed to explore the efficacy and safety of the combination of fecal microbiota transplantation (FMT) and tislelizumab and fruquintinib in refractory MSS mCRC. Methods In the phase II trial, MSS mCRC patients were administered FMT plus tislelizumab and fruquintinib as a third-line or above treatment. The primary endpoint was progression-free survival (PFS). Secondary endpoints were overall survival (OS), objective response rate (ORR), disease control rate (DCR), duration of response (DoR), clinical benefit rate (CBR), safety and quality of life. Feces and peripheral blood were collected for exploratory biomarker analysis. This study is registered with Chictr.org.cn, identifier ChiCTR2100046768. Findings From May 10, 2021 to January 17, 2022, 20 patients were enrolled. Median follow-up was 13.7 months. Median PFS was 9.6 months (95% CI 4.1-15.1). Median OS was 13.7 months (95% CI 9.3-17.7). Median DoR was 8.1 months (95% CI 1.7-10.6). ORR was 20% (95% CI 5.7-43.7). DCR was 95% (95% CI 75.1-99.9). CBR was 60% (95% CI 36.1-80.9). Nineteen patients (95%) experienced at least one treatment-related adverse event (TRAE). Six patients (30%) had grade 3-4 TRAEs, with the most common being albuminuria (10%), urine occult blood (10%), fecal occult blood (10%), hypertension (5%), hyperglycemia (5%), liver dysfunction (5%), hand-foot skin reaction (5%), and hypothyroidism (5%). No treatment-related deaths occurred. Responders had a high-abundance of Proteobacteria and Lachnospiraceae family and a low-abundance of Actinobacteriota and Bifidobacterium. The treatment did not change the structure of peripheral blood TCR repertoire. However, the expanded TCRs exhibited the characteristics of antigen-driven responses in responders. Interpretation FMT plus tislelizumab and fruquintinib as third-line or above treatment showed improved survival and manageable safety in refractory MSS mCRC, suggesting a valuable new treatment option for this patient population. Funding This study was supported by the National Natural Science Foundation of China (82102954 to Wensi Zhao) and the Special Project of Central Government for Local Science and Technology Development of Hubei Province (ZYYD2020000169 to Yongshun Chen).
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Affiliation(s)
- Wensi Zhao
- Department of Clinical Oncology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Jun Lei
- Department of Clinical Oncology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Shaobo Ke
- Department of Clinical Oncology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Yuan Chen
- Department of Clinical Oncology, Qianjiang Central Hospital, Qianjiang, China
| | - Jiping Xiao
- Department of Abdominal Tumor Surgery, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Huangshi, China
| | - Ze Tang
- Department of Abdominal & Pelvic Medical Oncology, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Huangshi, China
| | - Li Wang
- Department of Oncology, Xiaochang First People's Hospital, China
| | - Yiping Ren
- Department of Clinical Oncology, Jingshan Union Hospital of Huazhong University of Science and Technology, Jingshan, China
| | - Mohammed Alnaggar
- Department of Internal Medicine, Clinic Medical College, Hubei University of Science and Technology, Xianning, China
| | - Hu Qiu
- Department of Clinical Oncology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Wei Shi
- Department of Clinical Oncology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Lei Yin
- State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Wuhan University, Wuhan, China
| | - Yongshun Chen
- Department of Clinical Oncology, Renmin Hospital of Wuhan University, Wuhan, China
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19
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Chen DG, Xie J, Su Y, Heath JR. T cell receptor sequences are the dominant factor contributing to the phenotype of CD8 + T cells with specificities against immunogenic viral antigens. Cell Rep 2023; 42:113279. [PMID: 37883974 PMCID: PMC10729740 DOI: 10.1016/j.celrep.2023.113279] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 08/23/2023] [Accepted: 09/29/2023] [Indexed: 10/28/2023] Open
Abstract
Antigen-specific CD8+ T cells mediate pathogen clearance. T cell phenotype is influenced by T cell receptor (TCR) sequences and environmental signals. Quantitative comparisons of these factors in human disease, while challenging to obtain, can provide foundational insights into basic T cell biology. Here, we investigate the phenotype kinetics of 679 CD8+ T cell clonotypes, each with specificity against one of three immunogenic viral antigens. Data were collected from a longitudinal study of 68 COVID-19 patients with antigens from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), cytomegalovirus (CMV), and influenza. Each antigen is associated with a different type of immune activation during COVID-19. We find TCR sequence to be by far the most important factor in shaping T cell phenotype and persistence for populations specific to any of these antigens. Our work demonstrates the important relationship between TCR sequence and T cell phenotype and persistence and helps explain why T cell phenotype often appears to be determined early in an infection.
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Affiliation(s)
- Daniel G Chen
- Institute of Systems Biology, Seattle, WA 98109, USA; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA; Clinical Research Division, Program in Immunology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Jingyi Xie
- Institute of Systems Biology, Seattle, WA 98109, USA; Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA 98105, USA
| | - Yapeng Su
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA; Clinical Research Division, Program in Immunology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - James R Heath
- Institute of Systems Biology, Seattle, WA 98109, USA; Department of Bioengineering, University of Washington, Seattle, WA 98105, USA.
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20
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Vogel K, Arra A, Lingel H, Bretschneider D, Prätsch F, Schanze D, Zenker M, Balk S, Bruder D, Geffers R, Hachenberg T, Arens C, Brunner-Weinzierl MC. Bifidobacteria shape antimicrobial T-helper cell responses during infancy and adulthood. Nat Commun 2023; 14:5943. [PMID: 37741816 PMCID: PMC10517955 DOI: 10.1038/s41467-023-41630-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 09/11/2023] [Indexed: 09/25/2023] Open
Abstract
Microbial infections early in life are challenging for the unexperienced immune system. The SARS-CoV-2 pandemic again has highlighted that neonatal, infant, child, and adult T-helper(Th)-cells respond differently to infections, and requires further understanding. This study investigates anti-bacterial T-cell responses against Staphylococcus aureus aureus, Staphylococcus epidermidis and Bifidobacterium longum infantis in early stages of life and adults and shows age and pathogen-dependent mechanisms. Beside activation-induced clustering, T-cells stimulated with Staphylococci become Th1-type cells; however, this differentiation is mitigated in Bifidobacterium-stimulated T-cells. Strikingly, prestimulation of T-cells with Bifidobacterium suppresses the activation of Staphylococcus-specific T-helper cells in a cell-cell dependent manner by inducing FoxP3+CD4+ T-cells, increasing IL-10 and galectin-1 secretion and showing a CTLA-4-dependent inhibitory capacity. Furthermore Bifidobacterium dampens Th responses of severely ill COVID-19 patients likely contributing to resolution of harmful overreactions of the immune system. Targeted, age-specific interventions may enhance infection defence, and specific immune features may have potential cross-age utilization.
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Affiliation(s)
- Katrin Vogel
- Department of Experimental Paediatrics, University Hospital, Otto-von-Guericke University, Magdeburg, Germany
| | - Aditya Arra
- Department of Experimental Paediatrics, University Hospital, Otto-von-Guericke University, Magdeburg, Germany
| | - Holger Lingel
- Department of Experimental Paediatrics, University Hospital, Otto-von-Guericke University, Magdeburg, Germany
| | | | - Florian Prätsch
- Department of Anaesthesiology and Intensive Care Medicine, University Hospital, Otto-von-Guericke-University, Magdeburg, Germany
| | - Denny Schanze
- Institute of Human Genetics, University Hospital, Otto-von-Guericke University, Magdeburg, Germany
| | - Martin Zenker
- Institute of Human Genetics, University Hospital, Otto-von-Guericke University, Magdeburg, Germany
| | - Silke Balk
- Department of Experimental Paediatrics, University Hospital, Otto-von-Guericke University, Magdeburg, Germany
| | - Dunja Bruder
- Infection Immunology Group, Institute of Medical Microbiology and Hospital Hygiene, Health Campus Immunology, Infectiology and Inflammation, Otto-von-Guericke University, Magdeburg, Germany
- Immune Regulation Group, Helmholtz Centre for Infection Research, Braunschweig, Germany
| | - Robert Geffers
- Genome Analytics, Helmholtz Centre for Infection Research, Braunschweig, Germany
| | - Thomas Hachenberg
- Department of Anaesthesiology and Intensive Care Medicine, University Hospital, Otto-von-Guericke-University, Magdeburg, Germany
| | - Christoph Arens
- Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital, Otto-von-Guericke University, Magdeburg, Germany
- Justus-Liebig-University Gießen, University Hospital of Gießen and Marburg (UKGM), Gießen Campus, Department of Otorhinolaryngology, Head/Neck Surgery and Plastic Surgery, Gießen, Germany
| | - Monika C Brunner-Weinzierl
- Department of Experimental Paediatrics, University Hospital, Otto-von-Guericke University, Magdeburg, Germany.
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21
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Aran A, Lázaro G, Marco V, Molina E, Abancó F, Peg V, Gión M, Garrigós L, Pérez-García J, Cortés J, Martí M. Analysis of tumor infiltrating CD4+ and CD8+ CDR3 sequences reveals shared features putatively associated to the anti-tumor immune response. Front Immunol 2023; 14:1227766. [PMID: 37600765 PMCID: PMC10436466 DOI: 10.3389/fimmu.2023.1227766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 07/20/2023] [Indexed: 08/22/2023] Open
Abstract
Introduction Tumor-infiltrating lymphocytes (TILs) have predictive and prognostic value in breast cancer (BC) and exert a protective function against tumor growth, indicating that it is susceptible to treatment using adoptive cell transfer of TILs or T cell receptor (TCR)-based therapies. TCR can be used to identify naturally tumor-reactive T cells, but little is known about the differences in the TCR repertoires of CD4+ and CD8+ TILs. Methods TCR high-throughput sequencing was performed using TILs derived from the initial cultures of 11 BC biopsies and expanded and sorted CD4+ and CD8+ TILs as well as using PBMCs from healthy donors expanded and sorted using the same methodology. Results Physicochemical TCR differences between T cell subsets were observed, as CD4+ TILs presented larger N(D)Nnt TRB sequences and with a higher usage of positively charged residues, although only the latest was also observed in peripheral T cells from healthy individuals. Moreover, in CD4+ TILs, a more restricted TCR repertoire with a higher abundance of similar sequences containing certain amino acid motifs was observed. Discussion Some differences between CD4+ and CD8+ TCRs were intrinsic to T cell subsets as can also be observed in peripheral T cells from healthy individuals, while other were only found in TILs samples and therefore may be tumor-driven. Notably, the higher similarity among CD4+ TCRs suggests a higher TCR promiscuity in this subset.
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Affiliation(s)
- Andrea Aran
- Immunology Unit, Department of Cell Biology, Physiology, and Immunology, Institut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
| | - Gonzalo Lázaro
- Immunology Unit, Department of Cell Biology, Physiology, and Immunology, Institut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
| | - Vicente Marco
- Pathology, Hospital Quironsalud Barcelona, Barcelona, Spain
| | - Elisa Molina
- Immunology Unit, Department of Cell Biology, Physiology, and Immunology, Institut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
| | - Ferran Abancó
- Immunology Unit, Department of Cell Biology, Physiology, and Immunology, Institut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
| | - Vicente Peg
- Pathology Department, Vall d’Hebron University Hospital, Barcelona, Spain
- Department of Morphological Sciences, Universidad Autónoma de Barcelona, Bellaterra, Spain
- Spanish Biomedical Research Network Centre in Oncology (CIBERONC), Madrid, Spain
| | - María Gión
- Medical Oncology Department, Ramón y Cajal University Hospital, Madrid, Spain
| | - Laia Garrigós
- International Breast Cancer Center (IBCC), Pangaea Oncology, Quironsalud Group, Barcelona, Spain
| | - José Pérez-García
- International Breast Cancer Center (IBCC), Pangaea Oncology, Quironsalud Group, Barcelona, Spain
- Medical Scientia Innovation Research (MedSIR), Barcelona, Spain
| | - Javier Cortés
- International Breast Cancer Center (IBCC), Pangaea Oncology, Quironsalud Group, Barcelona, Spain
- Medical Scientia Innovation Research (MedSIR), Barcelona, Spain
- Department of Medicine, Faculty of Biomedical and Health Sciences, Universidad Europea de Madrid, Madrid, Spain
| | - Mercè Martí
- Immunology Unit, Department of Cell Biology, Physiology, and Immunology, Institut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Biosensing and Bioanalysis Group, Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Spain
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22
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Lagattuta KA, Nathan A, Rumker L, Birnbaum ME, Raychaudhuri S. The T cell receptor sequence influences the likelihood of T cell memory formation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.20.549939. [PMID: 37502994 PMCID: PMC10370203 DOI: 10.1101/2023.07.20.549939] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
T cell differentiation depends on activation through the T cell receptor (TCR), whose amino acid sequence varies cell to cell. Particular TCR amino acid sequences nearly guarantee Mucosal-Associated Invariant T (MAIT) and Natural Killer T (NKT) cell fates. To comprehensively define how TCR amino acids affects all T cell fates, we analyze the paired αβTCR sequence and transcriptome of 819,772 single cells. We find that hydrophobic CDR3 residues promote regulatory T cell transcriptional states in both the CD8 and CD4 lineages. Most strikingly, we find a set of TCR sequence features, concentrated in CDR2α, that promotes positive selection in the thymus as well as transition from naïve to memory in the periphery. Even among T cells that recognize the same antigen, these TCR sequence features help to explain which T cells form immunological memory, which is essential for effective pathogen response.
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Affiliation(s)
- Kaitlyn A. Lagattuta
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Aparna Nathan
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Laurie Rumker
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Michael E. Birnbaum
- Koch Institute for Integrative Cancer Research, Cambridge, MA, USA
- Department of Biomedical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
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23
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Mora T, Walczak AM. Towards a quantitative theory of tolerance. Trends Immunol 2023; 44:512-518. [PMID: 37263823 DOI: 10.1016/j.it.2023.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 04/24/2023] [Accepted: 04/28/2023] [Indexed: 06/03/2023]
Abstract
A cornerstone of the classical view of tolerance is the elimination of self-reactive T cells via negative selection in the thymus. However, high-throughput T cell receptor (TCR) sequencing data have so far failed to detect substantial signatures of negative selection in the observed repertoires. In addition, quantitative estimates as well as recent experiments suggest that the elimination of self-reactive T cells is at best incomplete. We discuss several recent theoretical ideas that might explain tolerance while being consistent with these observations, including collective decision-making through quorum sensing, and sensitivity to change through dynamic tuning and adaptation. We propose that a unified quantitative theory of tolerance should combine these elements to help to explain the plasticity of the immune system and its robustness to autoimmunity.
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Affiliation(s)
- Thierry Mora
- Laboratoire de Physique de l'Ecole Normale Supérieure, Centre National de la Recherche Scientifique (CNRS), Université Paris Sciences et Lettres (PSL University), Sorbonne Université, and Université Paris-Cité, 75005 Paris, France.
| | - Aleksandra M Walczak
- Laboratoire de Physique de l'Ecole Normale Supérieure, Centre National de la Recherche Scientifique (CNRS), Université Paris Sciences et Lettres (PSL University), Sorbonne Université, and Université Paris-Cité, 75005 Paris, France.
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24
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Park JS, Perl A. Endosome Traffic Modulates Pro-Inflammatory Signal Transduction in CD4 + T Cells-Implications for the Pathogenesis of Systemic Lupus Erythematosus. Int J Mol Sci 2023; 24:10749. [PMID: 37445926 DOI: 10.3390/ijms241310749] [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: 05/05/2023] [Revised: 06/10/2023] [Accepted: 06/26/2023] [Indexed: 07/15/2023] Open
Abstract
Endocytic recycling regulates the cell surface receptor composition of the plasma membrane. The surface expression levels of the T cell receptor (TCR), in concert with signal transducing co-receptors, regulate T cell responses, such as proliferation, differentiation, and cytokine production. Altered TCR expression contributes to pro-inflammatory skewing, which is a hallmark of autoimmune diseases, such as systemic lupus erythematosus (SLE), defined by a reduced function of regulatory T cells (Tregs) and the expansion of CD4+ helper T (Th) cells. The ensuing secretion of inflammatory cytokines, such as interferon-γ and interleukin (IL)-4, IL-17, IL-21, and IL-23, trigger autoantibody production and tissue infiltration by cells of the adaptive and innate immune system that induce organ damage. Endocytic recycling influences immunological synapse formation by CD4+ T lymphocytes, signal transduction from crosslinked surface receptors through recruitment of adaptor molecules, intracellular traffic of organelles, and the generation of metabolites to support growth, cytokine production, and epigenetic control of DNA replication and gene expression in the cell nucleus. This review will delineate checkpoints of endosome traffic that can be targeted for therapeutic interventions in autoimmune and other disease conditions.
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Affiliation(s)
- Joy S Park
- Department of Medicine, Norton College of Medicine, State University of New York, Upstate Medical University, Syracuse, NY 13210, USA
- Department of Biochemistry and Molecular Biology, Norton College of Medicine, State University of New York, Upstate Medical University, Syracuse, NY 13210, USA
| | - Andras Perl
- Department of Medicine, Norton College of Medicine, State University of New York, Upstate Medical University, Syracuse, NY 13210, USA
- Department of Biochemistry and Molecular Biology, Norton College of Medicine, State University of New York, Upstate Medical University, Syracuse, NY 13210, USA
- Department of Microbiology and Immunology, Norton College of Medicine, State University of New York, Upstate Medical University, Syracuse, NY 13210, USA
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25
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Billiet L, De Cock L, Sanchez Sanchez G, Mayer RL, Goetgeluk G, De Munter S, Pille M, Ingels J, Jansen H, Weening K, Pascal E, Raes K, Bonte S, Kerre T, Vandamme N, Seurinck R, Roels J, Lavaert M, Van Nieuwerburgh F, Leclercq G, Taghon T, Impens F, Menten B, Vermijlen D, Vandekerckhove B. Single-cell profiling identifies a novel human polyclonal unconventional T cell lineage. J Exp Med 2023; 220:e20220942. [PMID: 36939517 PMCID: PMC10037106 DOI: 10.1084/jem.20220942] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 12/22/2022] [Accepted: 02/27/2023] [Indexed: 03/21/2023] Open
Abstract
In the human thymus, a CD10+ PD-1+ TCRαβ+ differentiation pathway diverges from the conventional single positive T cell lineages at the early double-positive stage. Here, we identify the progeny of this unconventional lineage in antigen-inexperienced blood. These unconventional T cells (UTCs) in thymus and blood share a transcriptomic profile, characterized by hallmark transcription factors (i.e., ZNF683 and IKZF2), and a polyclonal TCR repertoire with autoreactive features, exhibiting a bias toward early TCRα chain rearrangements. Single-cell RNA sequencing confirms a common developmental trajectory between the thymic and blood UTCs and clearly delineates this unconventional lineage in blood. Besides MME+ recent thymic emigrants, effector-like clusters are identified in this heterogeneous lineage. Expression of Helios and KIR and a decreased CD8β expression are characteristics of this lineage. This UTC lineage could be identified in adult blood and intestinal tissues. In summary, our data provide a comprehensive characterization of the polyclonal unconventional lineage in antigen-inexperienced blood and identify the adult progeny.
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Affiliation(s)
- Lore Billiet
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Laurenz De Cock
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Guillem Sanchez Sanchez
- Department of Pharmacotherapy and Pharmaceutics, Université Libre de Bruxelles, Brussels, Belgium
- Institute for Medical Immunology, Université Libre de Bruxelles, Brussels, Belgium
- Université Libre de Bruxelles Center for Research in Immunology, Université Libre de Bruxelles, Brussels, Belgium
- WELBIO Department, WEL Research Institute, Wavre, Belgium
| | - Rupert L. Mayer
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium
- VIB Proteomics Core, VIB, Ghent, Belgium
| | - Glenn Goetgeluk
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Stijn De Munter
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Melissa Pille
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Joline Ingels
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Hanne Jansen
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Karin Weening
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Eva Pascal
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Killian Raes
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Sarah Bonte
- Cancer Research Institute Ghent, Ghent, Belgium
- Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
- Data Mining and Modeling for Biomedicine, VIB-UGent Center for Inflammation Research, Ghent, Belgium
| | - Tessa Kerre
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
- Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
| | - Niels Vandamme
- VIB Single Cell Core, VIB, Ghent, Belgium
- Data Mining and Modeling for Biomedicine, VIB-UGent Center for Inflammation Research, Ghent, Belgium
| | - Ruth Seurinck
- Data Mining and Modeling for Biomedicine, VIB-UGent Center for Inflammation Research, Ghent, Belgium
| | - Jana Roels
- VIB Single Cell Core, VIB, Ghent, Belgium
- Data Mining and Modeling for Biomedicine, VIB-UGent Center for Inflammation Research, Ghent, Belgium
| | - Marieke Lavaert
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Filip Van Nieuwerburgh
- Cancer Research Institute Ghent, Ghent, Belgium
- Department of Pharmaceutics, Ghent University, Ghent, Belgium
| | - Georges Leclercq
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Tom Taghon
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Francis Impens
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium
- VIB Proteomics Core, VIB, Ghent, Belgium
| | - Björn Menten
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - David Vermijlen
- Department of Pharmacotherapy and Pharmaceutics, Université Libre de Bruxelles, Brussels, Belgium
- Institute for Medical Immunology, Université Libre de Bruxelles, Brussels, Belgium
- Université Libre de Bruxelles Center for Research in Immunology, Université Libre de Bruxelles, Brussels, Belgium
- WELBIO Department, WEL Research Institute, Wavre, Belgium
| | - Bart Vandekerckhove
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
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26
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Ausserwöger H, Krainer G, Welsh TJ, Thorsteinson N, de Csilléry E, Sneideris T, Schneider MM, Egebjerg T, Invernizzi G, Herling TW, Lorenzen N, Knowles TPJ. Surface patches induce nonspecific binding and phase separation of antibodies. Proc Natl Acad Sci U S A 2023; 120:e2210332120. [PMID: 37011217 PMCID: PMC10104583 DOI: 10.1073/pnas.2210332120] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 02/06/2023] [Indexed: 04/05/2023] Open
Abstract
Nonspecific interactions are a key challenge in the successful development of therapeutic antibodies. The tendency for nonspecific binding of antibodies is often difficult to reduce by rational design, and instead, it is necessary to rely on comprehensive screening campaigns. To address this issue, we performed a systematic analysis of the impact of surface patch properties on antibody nonspecificity using a designer antibody library as a model system and single-stranded DNA as a nonspecificity ligand. Using an in-solution microfluidic approach, we find that the antibodies tested bind to single-stranded DNA with affinities as high as KD = 1 µM. We show that DNA binding is driven primarily by a hydrophobic patch in the complementarity-determining regions. By quantifying the surface patches across the library, the nonspecific binding affinity is shown to correlate with a trade-off between the hydrophobic and total charged patch areas. Moreover, we show that a change in formulation conditions at low ionic strengths leads to DNA-induced antibody phase separation as a manifestation of nonspecific binding at low micromolar antibody concentrations. We highlight that phase separation is driven by a cooperative electrostatic network assembly mechanism of antibodies with DNA, which correlates with a balance between positive and negative charged patches. Importantly, our study demonstrates that both nonspecific binding and phase separation are controlled by the size of the surface patches. Taken together, these findings highlight the importance of surface patches and their role in conferring antibody nonspecificity and its macroscopic manifestation in phase separation.
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Affiliation(s)
- Hannes Ausserwöger
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Georg Krainer
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Timothy J. Welsh
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Nels Thorsteinson
- Research and Development, Chemical Computing Group, Montreal, QuebecH3A 2R7, Canada
| | - Ella de Csilléry
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Tomas Sneideris
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Matthias M. Schneider
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Thomas Egebjerg
- Global Research Technologies, Novo Nordisk A/S2760Måløv, Denmark
| | | | - Therese W. Herling
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Nikolai Lorenzen
- Global Research Technologies, Novo Nordisk A/S2760Måløv, Denmark
| | - Tuomas P. J. Knowles
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
- Department of Physics, Cavendish Laboratory, University of Cambridge, CambridgeCB3 0HE, United Kingdom
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27
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Camaglia F, Ryvkin A, Greenstein E, Reich-Zeliger S, Chain B, Mora T, Walczak AM, Friedman N. Quantifying changes in the T cell receptor repertoire during thymic development. eLife 2023; 12:81622. [PMID: 36661220 PMCID: PMC9934861 DOI: 10.7554/elife.81622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 01/18/2023] [Indexed: 01/21/2023] Open
Abstract
One of the feats of adaptive immunity is its ability to recognize foreign pathogens while sparing the self. During maturation in the thymus, T cells are selected through the binding properties of their antigen-specific T-cell receptor (TCR), through the elimination of both weakly (positive selection) and strongly (negative selection) self-reactive receptors. However, the impact of thymic selection on the TCR repertoire is poorly understood. Here, we use transgenic Nur77-mice expressing a T-cell activation reporter to study the repertoires of thymic T cells at various stages of their development, including cells that do not pass selection. We combine high-throughput repertoire sequencing with statistical inference techniques to characterize the selection of the TCR in these distinct subsets. We find small but significant differences in the TCR repertoire parameters between the maturation stages, which recapitulate known differentiation pathways leading to the CD4+ and CD8+ subtypes. These differences can be simulated by simple models of selection acting linearly on the sequence features. We find no evidence of specific sequences or sequence motifs or features that are suppressed by negative selection. These results favour a collective or statistical model for T-cell self non-self discrimination, where negative selection biases the repertoire away from self recognition, rather than ensuring lack of self-reactivity at the single-cell level.
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Affiliation(s)
- Francesco Camaglia
- Laboratoire de physique de l’École normale supérieure, CNRS, PSL University, Sorbonne Université, and Université de ParisParisFrance
| | - Arie Ryvkin
- Department of Immunology, Weizmann Institute of ScienceRehovotIsrael
| | - Erez Greenstein
- Department of Immunology, Weizmann Institute of ScienceRehovotIsrael
| | | | - Benny Chain
- Division of Infection and Immunity, University College LondonLondonUnited Kingdom
| | - Thierry Mora
- Laboratoire de physique de l’École normale supérieure, CNRS, PSL University, Sorbonne Université, and Université de ParisParisFrance
| | - Aleksandra M Walczak
- Laboratoire de physique de l’École normale supérieure, CNRS, PSL University, Sorbonne Université, and Université de ParisParisFrance
| | - Nir Friedman
- Department of Immunology, Weizmann Institute of ScienceRehovotIsrael
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28
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Ishina IA, Zakharova MY, Kurbatskaia IN, Mamedov AE, Belogurov AA, Gabibov AG. MHC Class II Presentation in Autoimmunity. Cells 2023; 12:314. [PMID: 36672249 PMCID: PMC9856717 DOI: 10.3390/cells12020314] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 01/10/2023] [Accepted: 01/12/2023] [Indexed: 01/17/2023] Open
Abstract
Antigen presentation by major histocompatibility complex class II (MHC-II) molecules is crucial for eliciting an efficient immune response by CD4+ T cells and maintaining self-antigen tolerance. Some MHC-II alleles are known to be positively or negatively associated with the risk of the development of different autoimmune diseases (ADs), including those characterized by the emergence of autoreactive T cells. Apparently, the MHC-II presentation of self-antigens contributes to the autoimmune T cell response, initiated through a breakdown of central tolerance to self-antigens in the thymus. The appearance of autoreactive T cell might be the result of (i) the unusual interaction between T cell receptors (TCRs) and self-antigens presented on MHC-II; (ii) the posttranslational modifications (PTMs) of self-antigens; (iii) direct loading of the self-antigen to classical MHC-II without additional nonclassical MHC assistance; (iv) the proinflammatory environment effect on MHC-II expression and antigen presentation; and (v) molecular mimicry between foreign and self-antigens. The peculiarities of the processes involved in the MHC-II-mediated presentation may have crucial importance in the elucidation of the mechanisms of triggering and developing ADs as well as for clarification on the protective effect of MHC-II alleles that are negatively associated with ADs.
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Affiliation(s)
- Irina A. Ishina
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, 117997 Moscow, Russia
| | - Maria Y. Zakharova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, 117997 Moscow, Russia
| | - Inna N. Kurbatskaia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, 117997 Moscow, Russia
| | - Azad E. Mamedov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, 117997 Moscow, Russia
| | - Alexey A. Belogurov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, 117997 Moscow, Russia
- Department of Biological Chemistry, Evdokimov Moscow State University of Medicine and Dentistry, 127473 Moscow, Russia
| | - Alexander G. Gabibov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, 117997 Moscow, Russia
- Department of Life Sciences, Higher School of Economics, 101000 Moscow, Russia
- Department of Chemistry, Lomonosov Moscow State University, 119991 Moscow, Russia
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29
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Abstract
Inflammation is a biological process that dynamically alters the surrounding microenvironment, including participating immune cells. As a well-protected organ surrounded by specialized barriers and with immune privilege properties, the central nervous system (CNS) tightly regulates immune responses. Yet in neuroinflammatory conditions, pathogenic immunity can disrupt CNS structure and function. T cells in particular play a key role in promoting and restricting neuroinflammatory responses, while the inflamed CNS microenvironment can influence and reshape T cell function and identity. Still, the contraction of aberrant T cell responses within the CNS is not well understood. Using autoimmunity as a model, here we address the contribution of CD4 T helper (Th) cell subsets in promoting neuropathology and disease. To address the mechanisms antagonizing neuroinflammation, we focus on the control of the immune response by regulatory T cells (Tregs) and describe the counteracting processes that preserve their identity under inflammatory challenges. Finally, given the influence of the local microenvironment on immune regulation, we address how CNS-intrinsic signals reshape T cell function to mitigate abnormal immune T cell responses.
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Affiliation(s)
- Nail Benallegue
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA 19104
- Nantes Université, CHU Nantes, INSERM, Center for Research in Transplantation and Translational Immunology, UMR 1064, F-44000, Nantes, France
| | - Hania Kebir
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Jorge I. Alvarez
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA 19104
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30
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Mulinacci G, Palermo A, Gerussi A, Asselta R, Gershwin ME, Invernizzi P. New insights on the role of human leukocyte antigen complex in primary biliary cholangitis. Front Immunol 2022; 13:975115. [PMID: 36119102 PMCID: PMC9471323 DOI: 10.3389/fimmu.2022.975115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 08/11/2022] [Indexed: 01/04/2023] Open
Abstract
Primary Biliary Cholangitis (PBC) is a rare autoimmune cholangiopathy. Genetic studies have shown that the strongest statistical association with PBC has been mapped in the human leukocyte antigen (HLA) locus, a highly polymorphic area that mostly contribute to the genetic variance of the disease. Furthermore, PBC presents high variability throughout different population groups, which may explain the different geoepidemiology of the disease. A major role in defining HLA genetic contribution has been given by genome-wide association studies (GWAS) studies; more recently, new technologies have been developed to allow a deeper understanding. The study of the altered peptides transcribed by genetic alterations also allowed the development of novel therapeutic strategies in the context of immunotolerance. This review summarizes what is known about the immunogenetics of PBC with a focus on the HLA locus, the different distribution of HLA alleles worldwide, and how HLA modifications are associated with the pathogenesis of PBC. Novel therapeutic strategies are also outlined.
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Affiliation(s)
- Giacomo Mulinacci
- Division of Gastroenterology, Center for Autoimmune Liver Diseases, Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
- European Reference Network on Hepatological Diseases (ERN RARE-LIVER), San Gerardo Hospital, Monza, Italy
| | - Andrea Palermo
- Division of Gastroenterology, Center for Autoimmune Liver Diseases, Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
- European Reference Network on Hepatological Diseases (ERN RARE-LIVER), San Gerardo Hospital, Monza, Italy
| | - Alessio Gerussi
- Division of Gastroenterology, Center for Autoimmune Liver Diseases, Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
- European Reference Network on Hepatological Diseases (ERN RARE-LIVER), San Gerardo Hospital, Monza, Italy
| | - Rosanna Asselta
- Department of Biomedical Sciences, Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS) Humanitas Research Hospital, Milan, Italy
- Department of Biomedical Sciences, Humanitas University, Milan, Italy
| | - Merrill Eric Gershwin
- Division of Rheumatology, Allergy and Clinical Immunology, University of California, Davis, Davis, CA, United States
| | - Pietro Invernizzi
- Division of Gastroenterology, Center for Autoimmune Liver Diseases, Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
- European Reference Network on Hepatological Diseases (ERN RARE-LIVER), San Gerardo Hospital, Monza, Italy
- *Correspondence: Pietro Invernizzi,
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31
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Katayama Y, Yokota R, Akiyama T, Kobayashi TJ. Machine Learning Approaches to TCR Repertoire Analysis. Front Immunol 2022; 13:858057. [PMID: 35911778 PMCID: PMC9334875 DOI: 10.3389/fimmu.2022.858057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 06/07/2022] [Indexed: 11/13/2022] Open
Abstract
Sparked by the development of genome sequencing technology, the quantity and quality of data handled in immunological research have been changing dramatically. Various data and database platforms are now driving the rapid progress of machine learning for immunological data analysis. Of various topics in immunology, T cell receptor repertoire analysis is one of the most important targets of machine learning for assessing the state and abnormalities of immune systems. In this paper, we review recent repertoire analysis methods based on machine learning and deep learning and discuss their prospects.
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Affiliation(s)
- Yotaro Katayama
- Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
- *Correspondence: Yotaro Katayama,
| | - Ryo Yokota
- National Research Institute of Police Science, Kashiwa, Chiba, Japan
| | - Taishin Akiyama
- Laboratory for Immune Homeostasis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Graduate School of Medical Life Science, Yokohama City University, Yokohama, Japan
| | - Tetsuya J. Kobayashi
- Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
- Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
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