IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-29175-x.html
   My bibliography  Save this article

Single-cell RNA sequencing coupled to TCR profiling of large granular lymphocyte leukemia T cells

Author

Listed:
  • Shouguo Gao

    (National Institutes of Health)

  • Zhijie Wu

    (National Institutes of Health)

  • Bradley Arnold

    (National Institutes of Health)

  • Carrie Diamond

    (National Institutes of Health)

  • Sai Batchu

    (National Institutes of Health)

  • Valentina Giudice

    (National Institutes of Health)

  • Lemlem Alemu

    (National Institutes of Health)

  • Diego Quinones Raffo

    (National Institutes of Health)

  • Xingmin Feng

    (National Institutes of Health)

  • Sachiko Kajigaya

    (National Institutes of Health)

  • John Barrett

    (National Institutes of Health)

  • Sawa Ito

    (University of Pittsburgh)

  • Neal S. Young

    (National Institutes of Health)

Abstract

T-cell large granular lymphocyte leukemia (T-LGLL) is a lymphoproliferative disease and bone marrow failure syndrome which responds to immunosuppressive therapies. We show single-cell TCR coupled with RNA sequencing of CD3+ T cells from 13 patients, sampled before and after alemtuzumab treatments. Effector memory T cells and loss of T cell receptor (TCR) repertoire diversity are prevalent in T-LGLL. Shared TCRA and TCRB clonotypes are absent. Deregulation of cell survival and apoptosis gene programs, and marked downregulation of apoptosis genes in CD8+ clones, are prominent features of T-LGLL cells. Apoptosis genes are upregulated after alemtuzumab treatment, especially in responders than non-responders; baseline expression levels of apoptosis genes are predictive of hematologic response. Alemtuzumab does not attenuate TCR clonality, and TCR diversity is further skewed after treatment. Inferences made from analysis of single cell data inform understanding of the pathophysiologic mechanisms of clonal expansion and persistence in T-LGLL.

Suggested Citation

  • Shouguo Gao & Zhijie Wu & Bradley Arnold & Carrie Diamond & Sai Batchu & Valentina Giudice & Lemlem Alemu & Diego Quinones Raffo & Xingmin Feng & Sachiko Kajigaya & John Barrett & Sawa Ito & Neal S. Y, 2022. "Single-cell RNA sequencing coupled to TCR profiling of large granular lymphocyte leukemia T cells," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29175-x
    DOI: 10.1038/s41467-022-29175-x
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-29175-x
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-29175-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Shinya Tasaki & Katsuya Suzuki & Yoshiaki Kassai & Masaru Takeshita & Atsuko Murota & Yasushi Kondo & Tatsuya Ando & Yusuke Nakayama & Yuumi Okuzono & Maiko Takiguchi & Rina Kurisu & Takahiro Miyazaki, 2018. "Multi-omics monitoring of drug response in rheumatoid arthritis in pursuit of molecular remission," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alexander Platzer & Thomas Nussbaumer & Thomas Karonitsch & Josef S Smolen & Daniel Aletaha, 2019. "Analysis of gene expression in rheumatoid arthritis and related conditions offers insights into sex-bias, gene biotypes and co-expression patterns," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-23, July.
    2. Jia You & Yu Guo & Yi Zhang & Ju-Jiao Kang & Lin-Bo Wang & Jian-Feng Feng & Wei Cheng & Jin-Tai Yu, 2023. "Plasma proteomic profiles predict individual future health risk," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. Niki Karagianni & Ksanthi Kranidioti & Nikolaos Fikas & Maria Tsochatzidou & Panagiotis Chouvardas & Maria C Denis & George Kollias & Christoforos Nikolaou, 2019. "An integrative transcriptome analysis framework for drug efficacy and similarity reveals drug-specific signatures of anti-TNF treatment in a mouse model of inflammatory polyarthritis," PLOS Computational Biology, Public Library of Science, vol. 15(5), pages 1-25, May.
    4. Xia Qing & Thompson Jeffrey A. & Koestler Devin C., 2021. "Batch effect reduction of microarray data with dependent samples using an empirical Bayes approach (BRIDGE)," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 20(4-6), pages 101-119, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29175-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.