IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-28682-1.html
   My bibliography  Save this article

Phosphoproteomic profiling of T cell acute lymphoblastic leukemia reveals targetable kinases and combination treatment strategies

Author

Listed:
  • Valentina Cordo’

    (Princess Máxima Center for Pediatric Oncology)

  • Mariska T. Meijer

    (Princess Máxima Center for Pediatric Oncology)

  • Rico Hagelaar

    (Princess Máxima Center for Pediatric Oncology)

  • Richard R. Goeij-de Haas

    (Amsterdam University Medical Centers, VU University
    Amsterdam University Medical Centers, VU University)

  • Vera M. Poort

    (Princess Máxima Center for Pediatric Oncology)

  • Alex A. Henneman

    (Amsterdam University Medical Centers, VU University
    Amsterdam University Medical Centers, VU University)

  • Sander R. Piersma

    (Amsterdam University Medical Centers, VU University
    Amsterdam University Medical Centers, VU University)

  • Thang V. Pham

    (Amsterdam University Medical Centers, VU University
    Amsterdam University Medical Centers, VU University)

  • Koichi Oshima

    (Columbia University Medical Center)

  • Adolfo A. Ferrando

    (Columbia University Medical Center)

  • Guido J. R. Zaman

    (Oncolines B.V.)

  • Connie R. Jimenez

    (Amsterdam University Medical Centers, VU University
    Amsterdam University Medical Centers, VU University)

  • Jules P. P. Meijerink

    (Princess Máxima Center for Pediatric Oncology
    Acerta Pharma (member of the AstraZeneca group))

Abstract

Protein kinase inhibitors are amongst the most successful cancer treatments, but targetable kinases activated by genomic abnormalities are rare in T cell acute lymphoblastic leukemia. Nevertheless, kinases can be activated in the absence of genetic defects. Thus, phosphoproteomics can provide information on pathway activation and signaling networks that offer opportunities for targeted therapy. Here, we describe a mass spectrometry-based global phosphoproteomic profiling of 11 T cell acute lymphoblastic leukemia cell lines to identify targetable kinases. We report a comprehensive dataset consisting of 21,000 phosphosites on 4,896 phosphoproteins, including 217 kinases. We identify active Src-family kinases signaling as well as active cyclin-dependent kinases. We validate putative targets for therapy ex vivo and identify potential combination treatments, such as the inhibition of the INSR/IGF-1R axis to increase the sensitivity to dasatinib treatment. Ex vivo validation of selected drug combinations using patient-derived xenografts provides a proof-of-concept for phosphoproteomics-guided design of personalized treatments.

Suggested Citation

  • Valentina Cordo’ & Mariska T. Meijer & Rico Hagelaar & Richard R. Goeij-de Haas & Vera M. Poort & Alex A. Henneman & Sander R. Piersma & Thang V. Pham & Koichi Oshima & Adolfo A. Ferrando & Guido J. R, 2022. "Phosphoproteomic profiling of T cell acute lymphoblastic leukemia reveals targetable kinases and combination treatment strategies," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28682-1
    DOI: 10.1038/s41467-022-28682-1
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-28682-1
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-28682-1?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. Martin Frejno & Chen Meng & Benjamin Ruprecht & Thomas Oellerich & Sebastian Scheich & Karin Kleigrewe & Enken Drecoll & Patroklos Samaras & Alexander Hogrebe & Dominic Helm & Julia Mergner & Jana Zec, 2020. "Proteome activity landscapes of tumor cell lines determine drug responses," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
    2. Giulia Franciosa & Jos G. A. Smits & Sonia Minuzzo & Ana Martinez-Val & Stefano Indraccolo & Jesper V. Olsen, 2021. "Proteomics of resistance to Notch1 inhibition in acute lymphoblastic leukemia reveals targetable kinase signatures," Nature Communications, Nature, vol. 12(1), pages 1-19, December.
    3. Gannie Tzoneva & Chelsea L. Dieck & Koichi Oshima & Alberto Ambesi-Impiombato & Marta Sánchez-Martín & Chioma J. Madubata & Hossein Khiabanian & Jiangyan Yu & Esme Waanders & Ilaria Iacobucci & Maria , 2018. "Clonal evolution mechanisms in NT5C2 mutant-relapsed acute lymphoblastic leukaemia," Nature, Nature, vol. 553(7689), pages 511-514, January.
    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. Kun Zhang & Pengfei Wang & Wei Huang & Shi-Hao Tang & Hanzhong Xue & Hao Wu & Ying Zhang & Yu Rong & Shan-Shan Dong & Jia-Bin Chen & Yan Zou & Ding Tian & Na Yang & Yifan Liang & Chungui Liu & Dongyan, 2024. "Integrated landscape of plasma metabolism and proteome of patients with post-traumatic deep vein thrombosis," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    2. Merve Öztürk & Anja Freiwald & Jasmin Cartano & Ramona Schmitt & Mario Dejung & Katja Luck & Bassem Al-Sady & Sigurd Braun & Michal Levin & Falk Butter, 2022. "Proteome effects of genome-wide single gene perturbations," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    3. Amanda C. Lorentzian & Jenna Rever & Enes K. Ergin & Meiyun Guo & Neha M. Akella & Nina Rolf & C. James Lim & Gregor S. D. Reid & Christopher A. Maxwell & Philipp F. Lange, 2023. "Targetable lesions and proteomes predict therapy sensitivity through disease evolution in pediatric acute lymphoblastic leukemia," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    4. Florian P. Bayer & Manuel Gander & Bernhard Kuster & Matthew The, 2023. "CurveCurator: a recalibrated F-statistic to assess, classify, and explore significance of dose–response curves," Nature Communications, Nature, vol. 14(1), pages 1-11, 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_s41467-022-28682-1. 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.