Evidence map›Paper›PMID 38153903›Full record

ArticleBlood2024

Targeting of the CD161 inhibitory receptor enhances T-cell-mediated immunity against hematological malignancies.

Francesca Alvarez Calderon, Byong H Kang, Oleksandr Kyrysyuk, Shiwei Zheng, Hao Wang, Nathan D Mathewson, Adrienne M Luoma, Xiaohan Ning, Jason Pyrdol, Xuan Cao and 4 more

Open access · bronzeAbstract read
In one paragraph

Article in Blood, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.3field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 20 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Have CARs stalled for non-B-cell malignancies? Where are we, and where are we going?Hematology. American Society of Hematology. Education Program · 2025
    Review
  9. Targeting of the CD161 Inhibitory Receptor Enhances Bone-Marrow-Resident Memory CD8Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  10. Article
  11. Article
  12. [Effects of PEG-IFN-α treatment on the expression of CDZhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2025
    Article
  13. Article
  14. Article
  15. Review
  16. Article
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  18. Review
  19. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 6 institutions in 1 country.

Francesca Alvarez CalderonDepartment of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA.ORCID 0000-0001-5620-8431
Byong H KangKoch Institute for Integrative Cancer Research at Massachusetts Institute of Technology, Cambridge, MA.ORCID 0000-0002-1637-2082
Oleksandr KyrysyukDepartment of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA.ORCID 0000-0002-7646-6363
Shiwei ZhengDepartment of Genetics and Genomic Sciences, Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY.ORCID 0000-0001-6682-6743
Hao WangDepartment of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA.ORCID 0000-0001-8729-8556
Nathan D MathewsonDepartment of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA.ORCID 0000-0002-8895-2609
Adrienne M LuomaDepartment of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA.
Xiaohan NingDepartment of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA.
Jason PyrdolDepartment of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA.
Xuan CaoDepartment of Genetics and Genomic Sciences, Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY.ORCID 0000-0003-3754-2623
Mario L SuvàDepartment of Pathology and Center for Cancer Research, Massachusetts General Hospital, Boston, MA.ORCID 0000-0001-9898-5351
Guo-Cheng YuanDepartment of Genetics and Genomic Sciences, Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY.
K Dane WittrupKoch Institute for Integrative Cancer Research at Massachusetts Institute of Technology, Cambridge, MA.
Kai W WucherpfennigDepartment of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA.ORCID 0000-0002-1829-302X
Harvard University · USIcahn School of Medicine at Mount Sinai · USBrigham and Women's Hospital · USMassachusetts Institute of Technology · USBoston Children's Hospital · USBroad Institute · US

Funding

Transcriptional mechanisms and melanomaP01CA163222 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI Kai W Wucherpfennig · 2013 to 2026
$25.3M
Understanding and Overcoming T cell Immunosuppression in GlioblastomaP01CA236749 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI E. Antonio Chiocca · 2020 to 2026
$19.5M
Therapeutic Targeting of Immune Evasion from the MICA - NKG2D PathwayR01CA238039 · NCI · DANA-FARBER CANCER INST · PI Kai W Wucherpfennig · 2019 to 2026
$4.2M
POSTGRADUATE TRAINING IN PEDIATRIC ONCOLOGYT32CA082086 · NCI · UNIVERSITY OF COLORADO DENVER · PI GORE, LIA · 2000 to 2015
$4.1M
Targeting of a Major Immune Evasion Pathway in Triple-negative Breast CancerR01CA251599 · NCI · DANA-FARBER CANCER INST · PI WUCHERPFENNIG, KAI W · 2020 to 2024
$2.4M
Regulators of Cancer Immunotherapy ResponseR01CA234018 · NCI · DANA-FARBER CANCER INST · PI BROWN, MYLES A · 2019 to 2022
$2.3M
NCI NIH HHS L30 CA231679NCI NIH HHS P01 CA163222NCI NIH HHS P01 CA236749NCI NIH HHS R01 CA234018NCI NIH HHS R01 CA238039NCI NIH HHS R01 CA251599NCI NIH HHS T32 CA082086
6 · The paper itself

Abstract

abstractThe CD161 inhibitory receptor is highly upregulated by tumor-infiltrating T cells in multiple human solid tumor types, and its ligand, CLEC2D, is expressed by both tumor cells and infiltrating myeloid cells. Here, we assessed the role of the CD161 receptor in hematological malignancies. Systematic analysis of CLEC2D expression using the Cancer Cell Line Encyclopedia revealed that CLEC2D messenger RNA was most abundant in hematological malignancies, including B-cell and T-cell lymphomas as well as lymphocytic and myelogenous leukemias. CLEC2D protein was detected by flow cytometry on a panel of cell lines representing a diverse set of hematological malignancies. We, therefore, used yeast display to generate a panel of high-affinity, fully human CD161 monoclonal antibodies (mAbs) that blocked CLEC2D binding. These mAbs were specific for CD161 and had a similar affinity for human and nonhuman primate CD161, a property relevant for clinical translation. A high-affinity CD161 mAb enhanced key aspects of T-cell function, including cytotoxicity, cytokine production, and proliferation, against B-cell lines originating from patients with acute lymphoblastic leukemia, diffuse large B-cell lymphoma, and Burkitt lymphoma. In humanized mouse models, this CD161 mAb enhanced T-cell-mediated immunity, resulting in a significant survival benefit. Single cell RNA-seq data demonstrated that CD161 mAb treatment enhanced expression of cytotoxicity genes by CD4 T cells as well as a tissue-residency program by CD4 and CD8 T cells that is associated with favorable survival outcomes in multiple human cancer types. These fully human mAbs, thus, represent potential immunotherapy agents for hematological malignancies.

Indexed as

Hematologic NeoplasmsNeoplasmsAnimalsAntibodies, MonoclonalCD4-Positive T-LymphocytesCD8-Positive T-LymphocytesHumansImmunity, CellularMiceNK Cell Lectin-Like Receptor Subfamily BAntibodies, MonoclonalNK Cell Lectin-Like Receptor Subfamily B

Identifiers

PMID38153903
PMCPMC10972713
OpenAlexW4390333542

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.