Evidence map›Paper›PMID 35015834›Full record

ArticleBlood2022

Genomic landscape of TCRαβ and TCRγδ T-large granular lymphocyte leukemia.

HeeJin Cheon, Jeffrey C Xing, Katharine B Moosic, Johnson Ung, Vivian W Chan, David S Chung, Mariella F Toro, Omar Elghawy, John S Wang, Cait E Hamele and 6 more

Open access · hybridAbstract read
In one paragraph

Article in Blood, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
8.7field-weighted citation impact, top 2% 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

45 citing papers in PubMed, 58 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. How Genomic and Structural Context Could Shape JAK-STAT Variant Pathogenicity.Twin research and human genetics : the official journal of the International Society for Twin Studies · 2026
    Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 3 institutions in 1 country.

HeeJin CheonDepartment of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, Charlottesville, VA.ORCID 0000-0003-0149-9651
Jeffrey C XingDepartment of Medicine, University of Virginia Cancer Center, Charlottesville, VA.ORCID 0000-0003-0696-1390
Katharine B MoosicDepartment of Medicine, University of Virginia Cancer Center, Charlottesville, VA.ORCID 0000-0001-6736-4392
Johnson UngDepartment of Medicine, University of Virginia Cancer Center, Charlottesville, VA.ORCID 0000-0002-3275-0530
Vivian W ChanDepartment of Medicine, University of Virginia Cancer Center, Charlottesville, VA.ORCID 0000-0002-6834-3013
David S ChungDepartment of Medicine, University of Virginia Cancer Center, Charlottesville, VA.ORCID 0000-0002-3861-7693
Mariella F ToroDepartment of Medicine, University of Virginia Cancer Center, Charlottesville, VA.
Omar ElghawyDepartment of Medicine, University of Virginia Cancer Center, Charlottesville, VA.
John S WangDepartment of Medicine, University of Virginia Cancer Center, Charlottesville, VA.
Cait E HameleDepartment of Medicine, University of Virginia Cancer Center, Charlottesville, VA.ORCID 0000-0003-0077-7840
Ross C HardisonDepartment of Biochemistry and Molecular Biology, Center for Computational Biology & Bioinformatics, The Pennsylvania State University, State College, PA.ORCID 0000-0003-4084-7516
Thomas L OlsonDepartment of Medicine, University of Virginia Cancer Center, Charlottesville, VA.ORCID 0000-0001-7906-205X
Su-Fern TanDepartment of Medicine, University of Virginia Cancer Center, Charlottesville, VA.
David J FeithDepartment of Medicine, University of Virginia Cancer Center, Charlottesville, VA.ORCID 0000-0003-4981-1691
Aakrosh RatanCenter for Public Health Genomics, University of Virginia, Charlottesville, VA; and.ORCID 0000-0002-0782-3056
Thomas P LoughranDepartment of Medicine, University of Virginia Cancer Center, Charlottesville, VA.
University of Virginia Cancer CenterPennsylvania State University · USUniversity of Virginia · US

Funding

Women's Oncology Program - WONP30CA044579 · NCI · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI Dina Gould Halme · 1987 to 2026
$72.1M
Cancer Research Training Program: From Molecular Mechanisms to Therapeutic StrategiesT32CA009109 · NCI · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI Andrew Carl Dudley, Melanie R Rutkowski · 1985 to 2026
$13.9M
MEDICAL SCIENTIST TRAINING PROGRAMT32GM007267 · NIGMS · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI GARCIA-BLANCO, MARIANO A. · 1985 to 2024
$13.4M
Genomic Architecture of LGL LeukemiaR01CA178393 · NCI · UNIVERSITY OF VIRGINIA · PI Thomas P. Loughran, Aakrosh Ratan · 2016 to 2026
$6.5M
Transdisciplinary Big Data Science Training at UVaT32LM012416 · NLM · UNIVERSITY OF VIRGINIA · PI BROWN, DONALD E, LOUGHRAN, THOMAS P. · 2016 to 2020
$1.3M
Integrative network modeling of regulatory modules in Large Granular Lymphocyte LeukemiaF30CA225046 · NCI · UNIVERSITY OF VIRGINIA · PI XING, JEFFREY CHUNLONG · 2018 to 2021
$185k
NCI NIH HHS F30 CA225046NCI NIH HHS P30 CA044579NCI NIH HHS R01 CA178393NCI NIH HHS T32 CA009109NIGMS NIH HHS T32 GM007267NLM NIH HHS T32 LM012416
6 · The paper itself

Abstract

Large granular lymphocyte (LGL) leukemia comprises a group of rare lymphoproliferative disorders whose molecular landscape is incompletely defined. We leveraged paired whole-exome and transcriptome sequencing in the largest LGL leukemia cohort to date, which included 105 patients (93 T-cell receptor αβ [TCRαβ] T-LGL and 12 TCRγδ T-LGL). Seventy-six mutations were observed in 3 or more patients in the cohort, and out of those, STAT3, KMT2D, PIK3R1, TTN, EYS, and SULF1 mutations were shared between both subtypes. We identified ARHGAP25, ABCC9, PCDHA11, SULF1, SLC6A15, DDX59, DNMT3A, FAS, KDM6A, KMT2D, PIK3R1, STAT3, STAT5B, TET2, and TNFAIP3 as recurrently mutated putative drivers using an unbiased driver analysis approach leveraging our whole-exome cohort. Hotspot mutations in STAT3, PIK3R1, and FAS were detected, whereas truncating mutations in epigenetic modifying enzymes such as KMT2D and TET2 were observed. Moreover, STAT3 mutations co-occurred with mutations in chromatin and epigenetic modifying genes, especially KMT2D and SETD1B (P < .01 and P < .05, respectively). STAT3 was mutated in 50.5% of the patients. Most common Y640F STAT3 mutation was associated with lower absolute neutrophil count values, and N647I mutation was associated with lower hemoglobin values. Somatic activating mutations (Q160P, D170Y, L287F) in the STAT3 coiled-coil domain were characterized. STAT3-mutant patients exhibited increased mutational burden and enrichment of a mutational signature associated with increased spontaneous deamination of 5-methylcytosine. Finally, gene expression analysis revealed enrichment of interferon-γ signaling and decreased phosphatidylinositol 3-kinase-Akt signaling for STAT3-mutant patients. These findings highlight the clinical and molecular heterogeneity of this rare disorder.

Indexed as

Amino Acid Transport Systems, NeutralLeukemia, Large Granular LymphocyticExomeEye ProteinsGenomicsHumansMutationNerve Tissue ProteinsReceptors, Antigen, T-Cell, alpha-betaReceptors, Antigen, T-Cell, gamma-deltaRNA HelicasesSTAT3 Transcription FactorAmino Acid Transport Systems, NeutralDDX59 protein, humanEye ProteinsEYS protein, humanNerve Tissue ProteinsReceptors, Antigen, T-Cell, alpha-betaReceptors, Antigen, T-Cell, gamma-deltaRNA HelicasesSLC6A15 protein, humanSTAT3 Transcription Factor

Identifiers

PMID35015834
PMCPMC9121841
OpenAlexW4205129887

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.