IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v11y2020i1d10.1038_s41467-020-19119-8.html
   My bibliography  Save this article

Clonal evolution of acute myeloid leukemia revealed by high-throughput single-cell genomics

Author

Listed:
  • Kiyomi Morita

    (The University of Texas MD Anderson Cancer Center
    Graduate School of Medicine, The University of Tokyo)

  • Feng Wang

    (The University of Texas MD Anderson Cancer Center)

  • Katharina Jahn

    (ETH Zurich
    SIB Swiss Institute of Bioinformatics)

  • Tianyuan Hu

    (Baylor College of Medicine)

  • Tomoyuki Tanaka

    (The University of Texas MD Anderson Cancer Center)

  • Yuya Sasaki

    (The University of Texas MD Anderson Cancer Center)

  • Jack Kuipers

    (ETH Zurich
    SIB Swiss Institute of Bioinformatics)

  • Sanam Loghavi

    (The University of Texas MD Anderson Cancer Center)

  • Sa A. Wang

    (The University of Texas MD Anderson Cancer Center)

  • Yuanqing Yan

    (The University of Texas Health Science Center at Houston)

  • Ken Furudate

    (The University of Texas MD Anderson Cancer Center
    Hirosaki University Graduate School of Medicine)

  • Jairo Matthews

    (The University of Texas MD Anderson Cancer Center)

  • Latasha Little

    (The University of Texas MD Anderson Cancer Center)

  • Curtis Gumbs

    (The University of Texas MD Anderson Cancer Center)

  • Jianhua Zhang

    (The University of Texas MD Anderson Cancer Center)

  • Xingzhi Song

    (The University of Texas MD Anderson Cancer Center)

  • Erika Thompson

    (The University of Texas MD Anderson Cancer Center)

  • Keyur P. Patel

    (The University of Texas MD Anderson Cancer Center)

  • Carlos E. Bueso-Ramos

    (The University of Texas MD Anderson Cancer Center)

  • Courtney D. DiNardo

    (The University of Texas MD Anderson Cancer Center)

  • Farhad Ravandi

    (The University of Texas MD Anderson Cancer Center)

  • Elias Jabbour

    (The University of Texas MD Anderson Cancer Center)

  • Michael Andreeff

    (The University of Texas MD Anderson Cancer Center)

  • Jorge Cortes

    (The University of Texas MD Anderson Cancer Center)

  • Kapil Bhalla

    (The University of Texas MD Anderson Cancer Center)

  • Guillermo Garcia-Manero

    (The University of Texas MD Anderson Cancer Center)

  • Hagop Kantarjian

    (The University of Texas MD Anderson Cancer Center)

  • Marina Konopleva

    (The University of Texas MD Anderson Cancer Center)

  • Daisuke Nakada

    (The University of Texas MD Anderson Cancer Center)

  • Nicholas Navin

    (The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center)

  • Niko Beerenwinkel

    (ETH Zurich
    SIB Swiss Institute of Bioinformatics)

  • P. Andrew Futreal

    (The University of Texas MD Anderson Cancer Center)

  • Koichi Takahashi

    (The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center)

Abstract

Clonal diversity is a consequence of cancer cell evolution driven by Darwinian selection. Precise characterization of clonal architecture is essential to understand the evolutionary history of tumor development and its association with treatment resistance. Here, using a single-cell DNA sequencing, we report the clonal architecture and mutational histories of 123 acute myeloid leukemia (AML) patients. The single-cell data reveals cell-level mutation co-occurrence and enables reconstruction of mutational histories characterized by linear and branching patterns of clonal evolution, with the latter including convergent evolution. Through xenotransplantion, we show leukemia initiating capabilities of individual subclones evolving in parallel. Also, by simultaneous single-cell DNA and cell surface protein analysis, we illustrate both genetic and phenotypic evolution in AML. Lastly, single-cell analysis of longitudinal samples reveals underlying evolutionary process of therapeutic resistance. Together, these data unravel clonal diversity and evolution patterns of AML, and highlight their clinical relevance in the era of precision medicine.

Suggested Citation

  • Kiyomi Morita & Feng Wang & Katharina Jahn & Tianyuan Hu & Tomoyuki Tanaka & Yuya Sasaki & Jack Kuipers & Sanam Loghavi & Sa A. Wang & Yuanqing Yan & Ken Furudate & Jairo Matthews & Latasha Little & C, 2020. "Clonal evolution of acute myeloid leukemia revealed by high-throughput single-cell genomics," Nature Communications, Nature, vol. 11(1), pages 1-17, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-19119-8
    DOI: 10.1038/s41467-020-19119-8
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-020-19119-8
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-020-19119-8?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ayşegül Erdem & Silvia Marin & Diego A. Pereira-Martins & Marjan Geugien & Alan Cunningham & Maurien G. Pruis & Isabel Weinhäuser & Albert Gerding & Barbara M. Bakker & Albertus T. J. Wierenga & Eduar, 2022. "Inhibition of the succinyl dehydrogenase complex in acute myeloid leukemia leads to a lactate-fuelled respiratory metabolic vulnerability," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    2. Etienne Sollier & Jack Kuipers & Koichi Takahashi & Niko Beerenwinkel & Katharina Jahn, 2023. "COMPASS: joint copy number and mutation phylogeny reconstruction from amplicon single-cell sequencing data," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. Brooks A. Benard & Logan B. Leak & Armon Azizi & Daniel Thomas & Andrew J. Gentles & Ravindra Majeti, 2021. "Clonal architecture predicts clinical outcomes and drug sensitivity in acute myeloid leukemia," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    4. Peng Dai & Lucia Ruojia Wu & Sherry Xi Chen & Michael Xiangjiang Wang & Lauren Yuxuan Cheng & Jinny Xuemeng Zhang & Pengying Hao & Weijie Yao & Jabra Zarka & Ghayas C. Issa & Lawrence Kwong & David Yu, 2021. "Calibration-free NGS quantitation of mutations below 0.01% VAF," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    5. Haochen Zhang & Elias-Ramzey Karnoub & Shigeaki Umeda & Ronan Chaligné & Ignas Masilionis & Caitlin A. McIntyre & Palash Sashittal & Akimasa Hayashi & Amanda Zucker & Katelyn Mullen & Jungeui Hong & A, 2023. "Application of high-throughput single-nucleus DNA sequencing in pancreatic cancer," Nature Communications, Nature, vol. 14(1), pages 1-14, 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:11:y:2020:i:1:d:10.1038_s41467-020-19119-8. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.