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Autoreactive CD8+ T cells are restrained by an exhaustion-like program that is maintained by LAG3
Open accessAbstract
Impaired chronic viral and tumor clearance has been attributed to CD8+ T cell exhaustion, a differentiation state in which T cells have reduced and altered effector function that can be partially reversed upon blockade of inhibitory receptors. The role of the exhaustion program and transcriptional networks that control CD8+ T cell function and fate in autoimmunity is not clear. Here we show that intra-islet CD8+ T cells phenotypically, transcriptionally, epigenetically and metabolically possess features of canonically exhausted T cells, yet maintain important differences. This 'restrained' phenotype can be perturbed and disease accelerated by CD8+ T cell-restricted deletion of the inhibitory receptor lymphocyte activating gene 3 (LAG3). Mechanistically, LAG3-deficient CD8+ T cells have enhanced effector-like functions, trafficking to the islets, and have a diminished exhausted phenotype, highlighting a physiological role for an exhaustion program in limiting autoimmunity and implicating LAG3 as a target for autoimmune therapy.
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“T cell exhaustion may play a role in AIDs, 33-35 and exhausted autoantigen-specific CD8 + T cells were detected in murine and human type 1 diabetes (T1D). 35,36”
From Autoantigen-specific CD4+ T cells acquire an exhausted phenotype and persist in human antigen-specific autoimmune diseases (2024) · cites this paper as [36]
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“and exhausted CD8 and CD4 T cells are present in inflamed tissues of T1D 36,62 and systemic lupus erythematosus (SLE) 63 models.”
From Autoantigen-specific CD4+ T cells acquire an exhausted phenotype and persist in human antigen-specific autoimmune diseases (2024) · cites this paper as [36]
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Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
limma powers differential expression analyses for RNA-sequencing and microarray studies
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232
Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., et al. (2019) · Journal of Open Source Software · doi:10.21105/joss.01686 · Cited by 22,138
Comprehensive Integration of Single-Cell Data
Stuart, T., Butler, A., Hoffman, P., Hafemeister, C., Papalexi, E., Mauck, W. M., Hao, Y., Stoeckius, M., Smibert, P., & Satija, R. (2019) · Cell · doi:10.1016/j.cell.2019.05.031 · Cited by 15,453
ggplot2: Elegant Graphics for Data Analysis
Wickham, H. (2009) · doi:10.1007/978-0-387-98141-3 · Cited by 14,447
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn923 · Cited by 14,108
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
Mootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., et al. (2003) · Nature Genetics · doi:10.1038/ng1180 · Cited by 10,197
Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314
voom: precision weights unlock linear model analysis tools for RNA-seq read counts
Law, C. W., Chen, Y., Shi, W., & Smyth, G. K. (2014) · Genome Biology · doi:10.1186/gb-2014-15-2-r29 · Cited by 6,155
Toward understanding the origin and evolution of cellular organisms
Kanehisa, M. (2019) · Protein Science · doi:10.1002/pro.3715 · Cited by 5,509
Dimensionality reduction for visualizing single-cell data using UMAP
Becht, E., McInnes, L., Healy, J., Dutertre, C.-A., Kwok, I. W. H., Ng, L. G., Ginhoux, F., & Newell, E. W. (2019) · Nature Biotechnology · doi:10.1038/nbt.4314 · Cited by 5,358
WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs
Liao, Y., Wang, J., Jaehnig, E. J., Shi, Z., & Zhang, B. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz401 · Cited by 3,144
Smart-seq2 for sensitive full-length transcriptome profiling in single cells
Picelli, S., Björklund, Å. K., Faridani, O. R., Sagasser, S., Winberg, G., & Sandberg, R. (2013) · Nature Methods · doi:10.1038/nmeth.2639 · Cited by 2,358
Miller, B. C., Sen, D. R., Al Abosy, R., Bi, K., Virkud, Y. V., LaFleur, M. W., Yates, K. B., Lako, A., Felt, K., Naik, G. S., et al. (2019) · Nature Immunology · doi:10.1038/s41590-019-0312-6 · Cited by 2,087
Blackburn, S. D., Shin, H., Haining, W. N., Zou, T., Workman, C. J., Polley, A., Betts, M. R., Freeman, G. J., Vignali, D. A. A., & Wherry, E. J. (2009) · Nature Immunology · doi:10.1038/ni.1679 · Cited by 2,062
Self-citationNew approach for understanding genome variations in KEGG
Kanehisa, M. I., Sato, Y., Furumichi, M., Morishima, K., & Tanabe, M. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky962 · Cited by 1,845
Woo, S.-R., Turnis, M. E., Goldberg, M. V., Bankoti, J., Selby, M., Nirschl, C. J., Bettini, M. L., Gravano, D. M., Vogel, P., Liu, C. L., et al. (2012) · Cancer Research · doi:10.1158/0008-5472.can-11-1620 · Cited by 1,647
Self-citationTOX transcriptionally and epigenetically programs CD8+ T cell exhaustion
Khan, O., Giles, J. R., McDonald, S., Manne, S., Ngiow, S. F., Patel, K. P., Werner, M. T., Huang, A. C., Alexander, K. A., Wu, J. E., et al. (2019) · Nature · doi:10.1038/s41586-019-1325-x · Cited by 1,646
Self-citationBlank, C. U., Haining, W. N., Held, W., Hogan, P. G., Kallies, A., Lugli, E., Lynn, R. C., Philip, M., Rao, A., Restifo, N. P., et al. (2019) · Nature Reviews Immunology · doi:10.1038/s41577-019-0221-9 · Cited by 1,603
Self-citationDiffusion pseudotime robustly reconstructs lineage branching
Haghverdi, L., Büttner, M., Wolf, F. A., Buettner, F., & Theis, F. J. (2016) · Nature Methods · doi:10.1038/nmeth.3971 · Cited by 1,385
Epigenetic stability of exhausted T cells limits durability of reinvigoration by PD-1 blockade
Pauken, K. E., Sammons, M. A., Odorizzi, P. M., Manne, S., Godec, J., Khan, O., Drake, A. M., Chen, Z., Sen, D. R., Kurachi, M., et al. (2016) · Science · doi:10.1126/science.aaf2807 · Cited by 1,348
Self-citationMetabolic support of tumour-infiltrating regulatory T cells by lactic acid
Watson, M. J., Vignali, P., Mullett, S. J., Overacre-Delgoffe, A. E., Peralta, R. M., Grebinoski, S., Menk, A. V., Rittenhouse, N., DePeaux, K., Whetstone, R. D., et al. (2021) · Nature · doi:10.1038/s41586-020-03045-2 · Cited by 1,319
Self-citationBeltra, J., Manne, S., Abdel-Hakeem, M. S., Kurachi, M., Giles, J. R., Chen, Z., Casella, V., Ngiow, S. F., Khan, O., Huang, Y., et al. (2020) · Immunity · doi:10.1016/j.immuni.2020.04.014 · Cited by 1,139
Self-citationTOX is a critical regulator of tumour-specific T cell differentiation
Scott, A. C., Dündar, F., Zumbo, P., Chandran, S. S., Klebanoff, C. A., Shakiba, M., Trivedi, P., Menocal, L., Appleby, H., Camara, S., et al. (2019) · Nature · doi:10.1038/s41586-019-1324-y · Cited by 1,106
Stoeckius, M., Zheng, S., Houck-Loomis, B., Hao, S., Yeung, B. Z., Mauck, W. M., Smibert, P., & Satija, R. (2018) · Genome Biology · doi:10.1186/s13059-018-1603-1 · Cited by 1,046
Progenitor and Terminal Subsets of CD8 + T Cells Cooperate to Contain Chronic Viral Infection
Paley, M., Kroy, D. C., Odorizzi, P. M., Johnnidis, J. B., Dolfi, D. V., Barnett, B. E., Bikoff, E. K., Robertson, E. J., Lauer, G. M., Reiner, S. L., et al. (2012) · Science · doi:10.1126/science.1229620 · Cited by 903
Self-citationScharping, N. E., Rivadeneira, D. B., Menk, A. V., Vignali, P. D. A., Ford, B. R., Rittenhouse, N. L., Peralta, R., Wang, Y., Wang, Y., DePeaux, K., et al. (2021) · Nature Immunology · doi:10.1038/s41590-020-00834-9 · Cited by 897
Bengsch, B., Johnson, A. L., Kurachi, M., Odorizzi, P. M., Pauken, K. E., Attanasio, J., Stelekati, E., McLane, L. M., Paley, M. A., Delgoffe, G. M., et al. (2016) · Immunity · doi:10.1016/j.immuni.2016.07.008 · Cited by 868
Self-citationSPICE: Exploration and analysis of post‐cytometric complex multivariate datasets
Roederer, M., Nozzi, J. L., & Nason, M. (2011) · Cytometry Part A · doi:10.1002/cyto.a.21015 · Cited by 822
Prime role for an insulin epitope in the development of type 1 diabetes in NOD mice
Nakayama, M., Abiru, N., Moriyama, H., Babaya, N., Liu, E., Miao, D., Yu, L.-P., Wegmann, D., Hutton, J., Elliott, J., et al. (2005) · Nature · doi:10.1038/nature03523 · Cited by 821
Seo, H., Chen, J., González-Avalos, E., Samaniego-Castruita, D., Das, A., Wang, Y. H., López-Moyado, I. F., Georges, R. O., Zhang, W., Onodera, A., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1905675116 · Cited by 808
Scharping, N. E., Menk, A. V., Moreci, R. S., Whetstone, R. D., Dadey, R., Watkins, S. C., Ferris, R. L., & Delgoffe, G. M. (2016) · Immunity · doi:10.1016/j.immuni.2016.08.009 · Cited by 708
T-cell exhaustion, co-stimulation and clinical outcome in autoimmunity and infection
McKinney, E. F., Lee, J. C., Jayne, D. R. W., Lyons, P. A., & Smith, K. G. C. (2015) · Nature · doi:10.1038/nature14468 · Cited by 685
Immune Landscape of Viral- and Carcinogen-Driven Head and Neck Cancer
Cillo, A. R., Kürten, C. H. L., Tabib, T., Qi, Z., Onkar, S., Wang, T., Liu, A., Duvvuri, U., Kim, S., Soose, R. J., et al. (2020) · Immunity · doi:10.1016/j.immuni.2019.11.014 · Cited by 677
Self-citationDoering, T. A., Crawford, A., Angelosanto, J., Paley, M., Ziegler, C. G. K., & Wherry, E. J. (2012) · Immunity · doi:10.1016/j.immuni.2012.08.021 · Cited by 563
Self-citationSingle-cell RNA-seq reveals TOX as a key regulator of CD8+ T cell persistence in chronic infection
Yao, C., Sun, H.-W., Lacey, N. E., Ji, Y., Moseman, E. A., Shih, H.-Y., Heuston, E. F., Kirby, M., Anderson, S., Cheng, J., et al. (2019) · Nature Immunology · doi:10.1038/s41590-019-0403-4 · Cited by 549
Self-citationWeb‐Based Analysis and Publication of Flow Cytometry Experiments
Kotecha, N., Krutzik, P. O., & Irish, J. M. (2010) · Current Protocols in Cytometry · doi:10.1002/0471142956.cy1017s53 · Cited by 513
HINT: High-quality protein interactomes and their applications in understanding human disease
Das, J., & Yu, H. (2012) · BMC Systems Biology · doi:10.1186/1752-0509-6-92 · Cited by 462
Self-citationChristianson, S. W., Shultz, L. D., & Leiter, E. H. (1993) · Diabetes · doi:10.2337/diab.42.1.44 · Cited by 427
CD39 Expression Defines Cell Exhaustion in Tumor-Infiltrating CD8+ T Cells
Canale, F. P., Ramello, M. C., Núñez, N. G., Furlan, C. L. A., Bossio, S., Serrán, M. G., Tosello, J., del Castillo, A., Ledesma, M., Sedlik, C., et al. (2017) · Cancer Research · doi:10.1158/0008-5472.can-16-2684 · Cited by 418
Kent, S. C., Chen, Y., Bregoli, L., Clemmings, S. M., Kenyon, N. S., Ricordi, C., Hering, B. J., & Hafler, D. A. (2005) · Nature · doi:10.1038/nature03625 · Cited by 409
CD39 Expression Identifies Terminally Exhausted CD8+ T Cells
Gupta, P., Godec, J., Wolski, D., Adland, E., Yates, K. B., Pauken, K. E., Cosgrove, C., Ledderose, C., JUNGER, W. G., Robson, S. C., et al. (2015) · PLoS Pathogens · doi:10.1371/journal.ppat.1005177 · Cited by 384
Self-citationProgression of autoimmune diabetes driven by avidity maturation of a T-cell population
Amrani, A., Verdaguer, J., Serra, P., Tafuro, S., Tan, R., & Santamaría, P. (2000) · Nature · doi:10.1038/35021081 · Cited by 332
Literature-curated protein interaction datasets
Cusick, M. E., Yu, H., Smolyar, A., Venkatesan, K., Carvunis, A., Simonis, N., Rual, J.-F. M., Borick, H., Falter‐Braun, P., Dreze, M., et al. (2008) · Nature Methods · doi:10.1038/nmeth.1284 · Cited by 307
Godec, J., Tan, Y. Q., Liberzon, A., Tamayo, P., Bhattacharya, S., Butte, A. J., Mesirov, J. P., & Haining, W. N. (2016) · Immunity · doi:10.1016/j.immuni.2015.12.006 · Cited by 295
Adverse Events Following Cancer Immunotherapy: Obstacles and Opportunities
Pauken, K. E., Dougan, M., Rose, N. R., Lichtman, A. H., & Sharpe, A. H. (2019) · Trends in Immunology · doi:10.1016/j.it.2019.04.002 · Cited by 280
An autoimmune stem-like CD8 T cell population drives type 1 diabetes
Gearty, S. V., Dündar, F., Zumbo, P., Espinosa-Carrasco, G., Shakiba, M., Sanchez-Rivera, F. J., Socci, N. D., Trivedi, P., Lowe, S. W., Lauer, P., et al. (2022) · Nature · doi:10.1038/s41586-021-04248-x · Cited by 257
Partial exhaustion of CD8 T cells and clinical response to teplizumab in new-onset type 1 diabetes
Long, S. A., Thorpe, J., DeBerg, H. A., Gersuk, V., Eddy, J. A., Harris, K. M., Ehlers, M., Herold, K. C., Nepom, G. T., & Linsley, P. S. (2016) · Science Immunology · doi:10.1126/sciimmunol.aai7793 · Cited by 250
Calvo, T. R., Ekwall, O., Amirian, N., Zapardiel‐Gonzalo, J., & von Herrath, M. G. (2014) · Diabetes · doi:10.2337/db14-0549 · Cited by 241
High Levels of Eomes Promote Exhaustion of Anti-tumor CD8+ T Cells
Li, J., He, Y., Hao, J., Ni, L., & Dong, C. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.02981 · Cited by 229
Responses against islet antigens in NOD mice are prevented by tolerance to proinsulin but not IGRP
Krishnamurthy, B., Dudek, N. L., McKenzie, M. D., Purcell, A. W., Brööks, A. G., Gellert, S. A., Colman, P. G., Harrison, L. C., Lew, A. M., Thomas, H. E., et al. (2006) · Journal of Clinical Investigation · doi:10.1172/jci29602 · Cited by 223
Cutting Edge: Accelerated Autoimmune Diabetes in the Absence of LAG-3
Bettini, M., Szymczak-Workman, A. L., Forbes, K., Castellaw, A. H., Selby, M., Pan, X., Drake, C. G., Korman, A. J., & Vignali, D. A. A. (2011) · The Journal of Immunology · doi:10.4049/jimmunol.1100714 · Cited by 178
Self-citationSmart-seq2 for sensitive full-length transcriptome profiling in single cells
Picelli, S., Björklund, Å. K., Faridani, O. R., Sagasser, S., Winberg, G., & Sandberg, R. (2013) · F1000Research · doi:10.7490/f1000research.1094785.1 · Cited by 173
LAG3 limits regulatory T cell proliferation and function in autoimmune diabetes
Zhang, Q., Chikina, M. D., Szymczak-Workman, A. L., Horne, W. T., Kolls, J. K., Vignali, K. M., Normolle, D. P., Bettini, M., Workman, C. J., & Vignali, D. A. A. (2017) · Science Immunology · doi:10.1126/sciimmunol.aah4569 · Cited by 170
Self-citationAutoreactive CD8+ T cell exhaustion distinguishes subjects with slow type 1 diabetes progression
Wiedeman, A. E., Muir, V. S., Rosasco, M. G., DeBerg, H. A., Presnell, S., Haas, B., Dufort, M. J., Speake, C., Greenbaum, C. J., Serti, E., et al. (2019) · Journal of Clinical Investigation · doi:10.1172/jci126595 · Cited by 168
Sato, Y., Endo, H., Okuyama, H., Takeda, T., Iwahashi, H., Imagawa, A., Yamagata, K., Shimomura, I., & Inoue, M. (2011) · Journal of Biological Chemistry · doi:10.1074/jbc.m110.194738 · Cited by 164
Kidney-infiltrating T cells in murine lupus nephritis are metabolically and functionally exhausted
Tilstra, J. S., Avery, L., Menk, A. V., Gordon, R. A., Smita, S., Kane, L. P., Chikina, M., Delgoffe, G. M., & Shlomchik, M. J. (2018) · Journal of Clinical Investigation · doi:10.1172/jci120859 · Cited by 149
Zakharov, P. N., Hu, H., Wan, X., & Unanue, E. R. (2020) · Journal of Experimental Medicine · doi:10.1084/jem.20192362 · Cited by 149
Chen, Y., Mathews, C. E., & Driver, J. P. (2018) · Frontiers in Endocrinology · doi:10.3389/fendo.2018.00051 · Cited by 142
T Cell Islet Accumulation in Type 1 Diabetes Is a Tightly Regulated, Cell-Autonomous Event
Lennon, G. P., Bettini, M., Burton, A. R., Vincent, E., Arnold, P. Y., Santamaría, P., & Vignali, D. A. A. (2009) · Immunity · doi:10.1016/j.immuni.2009.07.008 · Cited by 137
Self-citationThe NOD Mouse: A Model for Insulin‐Dependent Diabetes Mellitus
Leiter, E. H. (1997) · Current Protocols in Immunology · doi:10.1002/0471142735.im1509s24 · Cited by 128
Transcriptional regulatory network for the establishment of CD8+ T cell exhaustion
Seo, W., Jerin, C., & Nishikawa, H. (2021) · Experimental & Molecular Medicine · doi:10.1038/s12276-021-00568-0 · Cited by 125
Increased Numbers of Low-Oxygenated Pancreatic Islets After Intraportal Islet Transplantation
Olsson, R. F., Olerud, J., Pettersson, U., & Carlsson, P. (2011) · Diabetes · doi:10.2337/db09-0490 · Cited by 124
Impact of Oxygen on Pancreatic Islet Survival
Komatsu, H., KANDEEL, F. R., & Mullen, Y. (2018) · Pancreas · doi:10.1097/mpa.0000000000001050 · Cited by 122
Abdelsamed, H. A., Zebley, C. C., Nguyen, H., Rutishauser, R. L., Fan, Y., Ghoneim, H. E., Crawford, J. C., Alfei, F., Alli, S., Ribeiro, S. P., et al. (2020) · Nature Immunology · doi:10.1038/s41590-020-0633-5 · Cited by 121
The NKG2A immune checkpoint — a new direction in cancer immunotherapy
Creelan, B., & Antonia, S. J. (2019) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-019-0182-8 · Cited by 119
β-Cell–Specific CD8 T Cell Phenotype in Type 1 Diabetes Reflects Chronic Autoantigen Exposure
Skowera, A., Ladell, K., McLaren, J. E., Dolton, G. M., Matthews, K. K., Emma Gostick, D., Kronenberg‐Versteeg, D., Eichmann, M., Knight, R. R., Heck, S., et al. (2014) · Diabetes · doi:10.2337/db14-0332 · Cited by 118
Resistance to PD1 blockade in the absence of metalloprotease-mediated LAG3 shedding
Andrews, L. P., Somasundaram, A., Moskovitz, J. M., Szymczak-Workman, A. L., Liu, C., Cillo, A. R., Huang, L., Normolle, D. P., Moynihan, K. D., Taniuchi, I., et al. (2020) · Science Immunology · doi:10.1126/sciimmunol.abc2728 · Cited by 87
Self-citationOlsson, R. F., & Carlsson, P. (2011) · Diabetes · doi:10.2337/db09-0877 · Cited by 85
Remodeling T cell compartments during anti-CD3 immunotherapy of type 1 diabetes
Long, S. A., Thorpe, J., Herold, K. C., Ehlers, M. R., Sanda, S., Lim, N., Linsley, P. S., Nepom, G. T., & Harris, K. M. (2017) · Cellular Immunology · doi:10.1016/j.cellimm.2017.07.007 · Cited by 84
Kuric, E., Seiron, P., Krogvold, L., Edwin, B., Buanes, T., Hanssen, K. F., Skog, O., Dahl-Jørgensen, K., & Korsgren, O. (2017) · The American Journal of Pathology · doi:10.1016/j.ajpath.2016.11.002 · Cited by 80
Autoreactive T effector memory differentiation mirrors β cell function in type 1 diabetes
Yeo, L., Woodwyk, A., Sood, S., Lorenc, A., Eichmann, M., Pujol‐Autonell, I., Melchiotti, R., Skowera, A., Fidanis, E., Dolton, G. M., et al. (2018) · Journal of Clinical Investigation · doi:10.1172/jci120555 · Cited by 68
Inhibitory receptor agonists: the future of autoimmune disease therapeutics?
Grebinoski, S., & Vignali, D. A. (2020) · Current Opinion in Immunology · doi:10.1016/j.coi.2020.06.001 · Cited by 58
Self-citationEffector-Memory T Cells Develop in Islets and Report Islet Pathology in Type 1 Diabetes
Chee, J., Ko, H., Skowera, A., Jhala, G., Catterall, T., Graham, K. L., Sutherland, R. M., Thomas, H. E., Lew, A. M., Peakman, M., et al. (2013) · The Journal of Immunology · doi:10.4049/jimmunol.1302100 · Cited by 55
Understanding adverse events of immunotherapy: A mechanistic perspective
Burke, K. P., Grebinoski, S., Sharpe, A. H., & Vignali, D. A. A. (2020) · The Journal of Experimental Medicine · doi:10.1084/jem.20192179 · Cited by 47
Self-citationPrasad, S., Xu, D., & Miller, S. D. (2012) · The Review of Diabetic Studies · doi:10.1900/rds.2012.9.319 · Cited by 35
Fewer LAG-3+ T Cells in Relapsing-Remitting Multiple Sclerosis and Type 1 Diabetes
Jones, B. E., Maerz, M. D., Bahnson, H. T., Somasundaram, A., McCarthy, L. H., Speake, C., & Buckner, J. H. (2022) · The Journal of Immunology · doi:10.4049/jimmunol.2100850 · Cited by 34
Heterogeneity and clonality of kidney-infiltrating T cells in murine lupus nephritis
Smita, S., Chikina, M. D., Shlomchik, M. J., & Tilstra, J. S. (2022) · JCI Insight · doi:10.1172/jci.insight.156048 · Cited by 24
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Metadata
- Authors
- Grebinoski, S., Zhang, Q., Cillo, A. R., Manne, S., Xiao, H., Brunazzi, E. A., Tabib, T., Cardello, C., Lian, C. G., Murphy, G. F., Lafyatis, R., Wherry, E. J., Das, J., Workman, C. J., & Vignali, D. A. A.
- Affiliations
- University of Pittsburgh (US)
- Boston Children's Hospital (US)
- University of Pennsylvania (US)
- Brigham and Women's Hospital (US)
- Parker Institute for Cancer Immunotherapy (US)
- Corresponding author
- Vignali, Dario A. A.
- ORCID
- Venue
- Nature Immunology
- Published
- 2022-05-26
- Volume
- 23
- Issue
- 6
- Pages
- 868-877
- ISSN
- 1529-2908 (ISSN-L)
- 1529-2916
- PMC
- PMC9179227
- OpenAlex
- W4281565387
- Cited by
- 107
- References
- 84
- Citations by year
- 2026: 20 · 2025: 21 · 2024: 38 · 2023: 25 · 2022: 3
- FWCI
- 8.50
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature Immunology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (DK089125)
- U.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases (AI144422, AI108545, AI147638, AI089443, AI105343, AI117950, AI082630, AI112521, AI115712)
- U.S. Department of Health & Human Services | NIH | NCI | Division of Cancer Epidemiology and Genetics, National Cancer Institute (CA210944)
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Keywords
- CD8+ T cell exhaustion, LAG-3, type 1 diabetes, autoimmunity, pancreatic islets, T cell metabolism, T cell migration, inhibitory receptors, nonobese diabetic mouse, T cell fate
- MeSH terms
- Humans, Neoplasms, Phenotype, Autoimmunity, CD8-Positive T-Lymphocytes
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