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Cited by 677T-cell and B-cell ImmunologyCancer Immunotherapy and BiomarkersPsoriasis: Treatment and Pathogenesis

Runx3 programs CD8+ T cell residency in non-lymphoid tissues and tumours

Open access
Milner, J. Justin, Toma, Clara, Yu, Bingfei, Zhang, Kai, Omilusik, Kyla, Phan, Anthony T., Wang, Dapeng, Getzler, Adam J. +5 more·2017·Nature
DOI 10.1038/nature24993PMC PMC5747964
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Abstract

Tissue-resident memory CD8+ T (T RM) cells are found at common sites of pathogen exposure, where they elicit rapid and robust protective immune responses. However, the molecular signals that control T RM cell differentiation and homeostasis are not fully understood. Here we show that mouse T RM precursor cells represent a unique CD8+ T cell subset that is distinct from the precursors of circulating memory cell populations at the levels of gene expression and chromatin accessibility. Using computational and pooled in vivo RNA interference screens, we identify the transcription factor Runx3 as a key regulator of T RM cell differentiation and homeostasis. Runx3 was required to establish T RM cell populations in diverse tissue environments, and supported the expression of crucial tissue-residency genes while suppressing genes associated with tissue egress and recirculation. Furthermore, we show that human and mouse tumour-infiltrating lymphocytes share a core tissue-residency gene-expression signature with T RM cells that is associated with Runx3 activity. In a mouse model of adoptive T cell therapy for melanoma, Runx3-deficient CD8+ tumour-infiltrating lymphocytes failed to accumulate in tumours, resulting in greater rates of tumour growth and mortality. Conversely, overexpression of Runx3 enhanced tumour-specific CD8+ T cell abundance, delayed tumour growth, and prolonged survival. In addition to establishing Runx3 as a central regulator of T RM cell differentiation, these results provide insight into the signals that promote T cell residency in non-lymphoid sites, which could be used to enhance vaccine efficacy or adoptive cell therapy treatments that target cancer.

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  • TRM cells can be identified by upregulation of specific transcription factors such as HOBIT, RUNX3, and BLIMP-1, which lead to transcriptional reprogramming to downregulate tissue egress genes and upregulate tissue retention markers.

    “Additionally, T RM cells can be identified by the upregulation of specific transcription factors such as HOBIT (homolog of Blimp-1 in T cells), RUNX3 (runt-related transcription factor 3), and BLIMP-1 (B lymphocyte-induced maturation protein-1), which lead to transcriptional reprogramming to downregulate tissue egress genes and upregulate tissue retention markers. 295-298”

    From Autoimmune Myocarditis, Old Dogs and New Tricks. (2024) · cites this paper as [296]

    The main text (page unavailable) identifies Hobit, Blimp-1, and Runx3 as regulators of tissue-resident memory CD8+ T-cell formation, and reports that Runx3 promotes residency-associated genes while suppressing egress genes. It does not establish that all three act through the stated gene program. It also says Runx3 expression is relatively uniform in circulating and resident CD8+ T cells, contrary to identifying resident cells by Runx3 upregulation. (LLM, conf=0.90)

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Research works printed but not linked: 33

  1. [1]Jiang X Skin infection generates non-migratory memory CD8+ T(RM) cells providing global skin immunity Nature 483 227 231 2012 22388819 PMC3437663
  2. [2]Schenkel JM Resident memory CD8 T cells trigger protective innate and adaptive immune responses Science 346 98 101 2014 25170049 PMC4449618
  3. [3]Chang JT Wherry EJ Goldrath AW Molecular regulation of effector and memory T cell differentiation Nat Immunol 15 1104 1115 2014 25396352 PMC4386685
  4. [4]Mueller SN Gebhardt T Carbone FR Heath WR Memory T cell subsets, migration patterns, and tissue residence Annu Rev Immunol 31 137 161 2013 23215646
  5. [6]Mackay LK Hobit and Blimp1 instruct a universal transcriptional program of tissue residency in lymphocytes Science 352 459 463 2016 27102484
  6. [7]Wakim LM The molecular signature of tissue resident memory CD8 T cells isolated from the brain J Immunol 189 3462 3471 2012 22922816 PMC3884813
  7. [8]Masopust D Vezys V Wherry EJ Barber DL Ahmed R Cutting edge: gut microenvironment promotes differentiation of a unique memory CD8 T cell population J Immunol 176 2079 2083 2006 16455963
  8. [9]Sheridan BS Oral infection drives a distinct population of intestinal resident memory CD8+ T cells with enhanced protective function Immunity 40 747 757 2014 24792910 PMC4045016
  9. [11]Boddupalli CS ABC transporters and NR4A1 identify a quiescent subset of tissue-resident memory T cells J Clin Invest 126 3905 3916 2016 27617863 PMC5096804
  10. [12]Mackay LK T-box Transcription Factors Combine with the Cytokines TGF-β and IL-15 to Control Tissue-Resident Memory T Cell Fate Immunity 43 1101 1111 2015 26682984
  11. [13]Laidlaw BJ CD4+ T cell help guides formation of CD103+ lung-resident memory CD8+ T cells during influenza viral infection Immunity 41 633 645 2014 25308332 PMC4324721
  12. [14]Yu B Epigenetic landscapes reveal transcription factors that regulate CD8+ T cell differentiation Nat Immunol 2017 PMC5395420 28288100
  13. [16]Chen R In vivo RNA interference screens identify regulators of antiviral CD4+ and CD8+ T cell differentiation Immunity 41 325 338 2014 25148027 PMC4160313
  14. [17]Skon CN Transcriptional downregulation of S1pr1 is required for the establishment of resident memory CD8+ T cells Nat Immunol 14 1285 1293 2013 24162775 PMC3844557
  15. [18]Taniuchi I Differential requirements for Runx proteins in CD4 repression and epigenetic silencing during T lymphocyte development Cell 111 621 633 2002 12464175
  16. [19]Cruz-Guilloty F Runx3 and T-box proteins cooperate to establish the transcriptional program of effector CTLs J Exp Med 206 51 59 2009 19139168 PMC2626671
  17. [20]Shan Q The transcription factor Runx3 guards cytotoxic CD8+ effector T cells against deviation towards follicular helper T cell lineage Nat Immunol 18 931 939 2017 28604718 PMC5564218
  18. [21]Reis BS Rogoz A Costa-Pinto FA Taniuchi I Mucida D Mutual expression of the transcription factors Runx3 and ThPOK regulates intestinal CD4+ T cell immunity Nat Immunol 14 271 280 2013 23334789 PMC3804366
  19. [22]Grueter B Runx3 regulates integrin αE/CD103 and CD4 expression during development of CD4−/CD8+ T cells J Immunol 175 1694 1705 2005 16034110
  20. [23]Lotem J Runx3-mediated transcriptional program in cytotoxic lymphocytes PloS one 8 e80467 2013 24236182 PMC3827420
  21. [24]Reis BS van Konijnenburg DPH Grivennikov SI Mucida D Transcription factor T-bet regulates intraepithelial lymphocyte functional maturation Immunity 41 244 256 2014 25148025 PMC4287410
  22. [25]Djenidi F CD8+ CD103+ Tumor–Infiltrating Lymphocytes Are Tumor-Specific Tissue-Resident Memory T Cells and a Prognostic Factor for Survival in Lung Cancer Patients J Immunol 194 3475 3486 2015 25725111
  23. [26]Ganesan AP Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer Nat Immunol 18 940 950 2017 28628092 PMC6036910
  24. [27]Doedens AL Molecular programming of tumor-infiltrating CD8+ T cells and IL15 resistance Cancer Immunol Res 4 799 811 2016 27485135 PMC5010943
  25. [28]Gooden MJ de Bock GH Leffers N Daemen T Nijman HW The prognostic influence of tumour-infiltrating lymphocytes in cancer: a systematic review with meta-analysis Br J Cancer 105 93 103 2011 21629244 PMC3137407
  26. [29]Singer M A distinct gene module for dysfunction uncoupled from activation in tumor-infiltrating T cells Cell 166 1500 1511 2016 27610572 PMC5019125
  27. [30]Tirosh I Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq Science 352 189 196 2016 27124452 PMC4944528
  28. [32]Benck CJ Martinov T Fife BT Chatterjea D Isolation of Infiltrating Leukocytes from Mouse Skin Using Enzymatic Digest and Gradient Separation J Vis Exp e53638 2016 26863129 PMC4781699
  29. [33]Knott SR A computational algorithm to predict shRNA potency Mol Cell 56 796 807 2014 25435137 PMC4272634
  30. [34]Pear WS Efficient and rapid induction of a chronic myelogenous leukemia-like myeloproliferative disease in mice receiving P210 bcr/abl-transduced bone marrow Blood 92 3780 3792 1998 9808572
  31. [35]Best JA Transcriptional insights into the CD8+ T cell response to infection and memory T cell formation Nat Immunol 14 404 412 2013 23396170 PMC3689652
  32. [36]Trapnell C Pachter L Salzberg SL TopHat: discovering splice junctions with RNA-Seq Bioinformatics 25 1105 1111 2009 19289445 PMC2672628
  33. [37]Anders S Pyl PT Huber W HTSeq–a Python framework to work with high-throughput sequencing data Bioinformatics 31 166 169 2015 25260700 PMC4287950

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Authors
Milner, J. J., Toma, C., Yu, B., Zhang, K., Omilusik, K., Phan, A. T., Wang, D., Getzler, A. J., Nguyen, T., Crotty, S., Wang, W., Pipkin, M. E., & Goldrath, A. W.
Affiliations
  • University of California San Diego (US)
  • Scripps Research Institute (US)
  • La Jolla Institute for Immunology (US)
Corresponding author
  • Pipkin, Matthew E.
  • Goldrath, Ananda W.
ORCID
Venue
Nature
Publisher
Springer Science and Business Media LLC
Published
2017-12-06
Volume
552
Issue
7684
Pages
253-257
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
DOI
10.1038/nature24993
PMC
PMC5747964
OpenAlex
W2774264760
Cited by
677
References
3
Citations by year
2026: 81 · 2025: 77 · 2024: 82 · 2023: 76 · 2022: 79 · 2021: 101 · 2020: 75 · 2019: 62 · 2018: 44
FWCI
21.68
Type
journal article
Language
en
Update notices
erratum (2018-01-10)
Open access
Licence
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
  • National Institutes of Health (1s10od016262-01)
  • National Human Genome Research Institute (R01HG009626)
  • National Institute of Allergy and Infectious Diseases (R01AI095634, U19AI109976, R37AI067545)
  • National Center for Research Resources (S10RR027366)
Topics
  • Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
  • Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
  • Life Sciences › Immunology and Microbiology › Immunology › Psoriasis: Treatment and Pathogenesis
Keywords
RUNX3, tissue-resident memory T cells, CD8+ T cells, tumor-infiltrating lymphocytes, transcriptional regulation, chromatin accessibility, adoptive T cell therapy, melanoma, cancer immunotherapy, T cell differentiation
MeSH terms
Animals, Cell Differentiation, Chromatin, Disease Models, Animal, Female, Gene Expression Regulation, Homeostasis, Humans, Immunologic Memory, Male, Melanoma, Organ Specificity, Survival Analysis, T-Lymphocyte Subsets, Lymphocytes, Tumor-Infiltrating, CD8-Positive T-Lymphocytes, Adoptive Transfer, Cell Proliferation, Core Binding Factor Alpha 3 Subunit, Mice

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