IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-28910-8.html
   My bibliography  Save this article

S6K1-mediated phosphorylation of PDK1 impairs AKT kinase activity and oncogenic functions

Author

Listed:
  • Qiwei Jiang

    (Sun Yat-sen University
    Sun Yat-sen University)

  • Xiaomei Zhang

    (Sun Yat-sen University)

  • Xiaoming Dai

    (Harvard Medical School)

  • Shiyao Han

    (Sun Yat-sen University)

  • Xueji Wu

    (Sun Yat-sen University)

  • Lei Wang

    (Sun Yat-sen University)

  • Wenyi Wei

    (Harvard Medical School)

  • Ning Zhang

    (Sun Yat-sen University)

  • Wei Xie

    (Sun Yat-sen University)

  • Jianping Guo

    (Sun Yat-sen University)

Abstract

Functioning as a master kinase, 3-phosphoinositide-dependent protein kinase 1 (PDK1) plays a fundamental role in phosphorylating and activating protein kinases A, B and C (AGC) family kinases, including AKT. However, upstream regulation of PDK1 remains largely elusive. Here we report that ribosomal protein S6 kinase beta 1 (S6K1), a member of AGC kinases and downstream target of mechanistic target of rapamycin complex 1 (mTORC1), directly phosphorylates PDK1 at its pleckstrin homology (PH) domain, and impairs PDK1 interaction with and activation of AKT. Mechanistically, S6K1-mediated phosphorylation of PDK1 augments its interaction with 14-3-3 adaptor protein and homo-dimerization, subsequently dissociating PDK1 from phosphatidylinositol 3,4,5 triphosphate (PIP3) and retarding its interaction with AKT. Pathologically, tumor patient-associated PDK1 mutations, either attenuating S6K1-mediated PDK1 phosphorylation or impairing PDK1 interaction with 14-3-3, result in elevated AKT kinase activity and oncogenic functions. Taken together, our findings not only unravel a delicate feedback regulation of AKT signaling via S6K1-mediated PDK1 phosphorylation, but also highlight the potential strategy to combat mutant PDK1-driven cancers.

Suggested Citation

  • Qiwei Jiang & Xiaomei Zhang & Xiaoming Dai & Shiyao Han & Xueji Wu & Lei Wang & Wenyi Wei & Ning Zhang & Wei Xie & Jianping Guo, 2022. "S6K1-mediated phosphorylation of PDK1 impairs AKT kinase activity and oncogenic functions," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28910-8
    DOI: 10.1038/s41467-022-28910-8
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-28910-8
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-022-28910-8?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
    ---><---

    References listed on IDEAS

    as
    1. Jordi Barretina & Giordano Caponigro & Nicolas Stransky & Kavitha Venkatesan & Adam A. Margolin & Sungjoon Kim & Christopher J.Wilson & Joseph Lehár & Gregory V. Kryukov & Dmitriy Sonkin & Anupama Red, 2012. "Addendum: The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity," Nature, Nature, vol. 492(7428), pages 290-290, December.
    2. Jinfang Zhang & Xia Bu & Haizhen Wang & Yasheng Zhu & Yan Geng & Naoe Taira Nihira & Yuyong Tan & Yanpeng Ci & Fei Wu & Xiangpeng Dai & Jianping Guo & Yu-Han Huang & Caoqi Fan & Shancheng Ren & Yingha, 2018. "Cyclin D–CDK4 kinase destabilizes PD-L1 via cullin 3–SPOP to control cancer immune surveillance," Nature, Nature, vol. 553(7686), pages 91-95, January.
    3. Jordi Barretina & Giordano Caponigro & Nicolas Stransky & Kavitha Venkatesan & Adam A. Margolin & Sungjoon Kim & Christopher J. Wilson & Joseph Lehár & Gregory V. Kryukov & Dmitriy Sonkin & Anupama Re, 2012. "The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity," Nature, Nature, vol. 483(7391), pages 603-607, March.
    4. Peter Blume-Jensen & Tony Hunter, 2001. "Oncogenic kinase signalling," Nature, Nature, vol. 411(6835), pages 355-365, May.
    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. Junyi Chen & Xiaoying Wang & Anjun Ma & Qi-En Wang & Bingqiang Liu & Lang Li & Dong Xu & Qin Ma, 2022. "Deep transfer learning of cancer drug responses by integrating bulk and single-cell RNA-seq data," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Omar Alhalabi & Jianfeng Chen & Yuxue Zhang & Yang Lu & Qi Wang & Sumankalai Ramachandran & Rebecca Slack Tidwell & Guangchun Han & Xinmiao Yan & Jieru Meng & Ruiping Wang & Anh G. Hoang & Wei-Lien Wa, 2022. "MTAP deficiency creates an exploitable target for antifolate therapy in 9p21-loss cancers," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    3. Yan Li & Chen Xu & Bing Wang & Fujiang Xu & Fahan Ma & Yuanyuan Qu & Dongxian Jiang & Kai Li & Jinwen Feng & Sha Tian & Xiaohui Wu & Yunzhi Wang & Yang Liu & Zhaoyu Qin & Yalan Liu & Jing Qin & Qi Son, 2022. "Proteomic characterization of gastric cancer response to chemotherapy and targeted therapy reveals potential therapeutic strategies," Nature Communications, Nature, vol. 13(1), pages 1-26, December.
    4. Aina Maria Mas & Enrique Goñi & Igor Ruiz de los Mozos & Aida Arcas & Luisa Statello & Jovanna González & Lorea Blázquez & Wei Ting Chelsea Lee & Dipika Gupta & Álvaro Sejas & Shoko Hoshina & Alexandr, 2023. "ORC1 binds to cis-transcribed RNAs for efficient activation of replication origins," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    5. Nicolae Sapoval & Amirali Aghazadeh & Michael G. Nute & Dinler A. Antunes & Advait Balaji & Richard Baraniuk & C. J. Barberan & Ruth Dannenfelser & Chen Dun & Mohammadamin Edrisi & R. A. Leo Elworth &, 2022. "Current progress and open challenges for applying deep learning across the biosciences," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    6. G. Gambardella & G. Viscido & B. Tumaini & A. Isacchi & R. Bosotti & D. di Bernardo, 2022. "A single-cell analysis of breast cancer cell lines to study tumour heterogeneity and drug response," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    7. Seungyeul Yoo & Abhilasha Sinha & Dawei Yang & Nasser K. Altorki & Radhika Tandon & Wenhui Wang & Deebly Chavez & Eunjee Lee & Ayushi S. Patel & Takashi Sato & Ranran Kong & Bisen Ding & Eric E. Schad, 2022. "Integrative network analysis of early-stage lung adenocarcinoma identifies aurora kinase inhibition as interceptor of invasion and progression," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    8. Shi, Chengchun & Xu, Tianlin & Bergsma, Wicher & Li, Lexin, 2021. "Double generative adversarial networks for conditional independence testing," LSE Research Online Documents on Economics 112550, London School of Economics and Political Science, LSE Library.
    9. Alon Stern & Mariam Fokra & Boris Sarvin & Ahmad Abed Alrahem & Won Dong Lee & Elina Aizenshtein & Nikita Sarvin & Tomer Shlomi, 2023. "Inferring mitochondrial and cytosolic metabolism by coupling isotope tracing and deconvolution," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    10. Sandor Spisak & David Chen & Pornlada Likasitwatanakul & Paul Doan & Zhixin Li & Pratyusha Bala & Laura Vizkeleti & Viktoria Tisza & Pushpamali Silva & Marios Giannakis & Brian Wolpin & Jun Qi & Nilay, 2024. "Identifying regulators of aberrant stem cell and differentiation activity in colorectal cancer using a dual endogenous reporter system," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    11. Mariela Cortés-López & Laura Schulz & Mihaela Enculescu & Claudia Paret & Bea Spiekermann & Mathieu Quesnel-Vallières & Manuel Torres-Diz & Sebastian Unic & Anke Busch & Anna Orekhova & Monika Kuban &, 2022. "High-throughput mutagenesis identifies mutations and RNA-binding proteins controlling CD19 splicing and CART-19 therapy resistance," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    12. Yanli Liu & Zhong Wu & Jin Zhou & Dinesh K. A. Ramadurai & Katelyn L. Mortenson & Estrella Aguilera-Jimenez & Yifei Yan & Xiaojun Yang & Alison M. Taylor & Katherine E. Varley & Jason Gertz & Peter S., 2021. "A predominant enhancer co-amplified with the SOX2 oncogene is necessary and sufficient for its expression in squamous cancer," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    13. Xiao-Song Wang & Sanghoon Lee & Han Zhang & Gong Tang & Yue Wang, 2022. "An integral genomic signature approach for tailored cancer therapy using genome-wide sequencing data," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    14. Sayantani Ghosh Dastidar & Bony Kumar & Bo Lauckner & Damien Parrello & Danielle Perley & Maria Vlasenok & Antariksh Tyagi & Nii Koney-Kwaku Koney & Ata Abbas & Sergei Nechaev, 2023. "Transcriptional responses of cancer cells to heat shock-inducing stimuli involve amplification of robust HSF1 binding," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    15. Sumana Srivatsa & Hesam Montazeri & Gaia Bianco & Mairene Coto-Llerena & Mattia Marinucci & Charlotte K. Y. Ng & Salvatore Piscuoglio & Niko Beerenwinkel, 2022. "Discovery of synthetic lethal interactions from large-scale pan-cancer perturbation screens," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    16. Cemal Erdem & Sean M. Gross & Laura M. Heiser & Marc R. Birtwistle, 2023. "MOBILE pipeline enables identification of context-specific networks and regulatory mechanisms," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    17. Smriti Chawla & Anja Rockstroh & Melanie Lehman & Ellca Ratther & Atishay Jain & Anuneet Anand & Apoorva Gupta & Namrata Bhattacharya & Sarita Poonia & Priyadarshini Rai & Nirjhar Das & Angshul Majumd, 2022. "Gene expression based inference of cancer drug sensitivity," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    18. Adrià Fernández-Torras & Miquel Duran-Frigola & Martino Bertoni & Martina Locatelli & Patrick Aloy, 2022. "Integrating and formatting biomedical data as pre-calculated knowledge graph embeddings in the Bioteque," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    19. Jun Lu, 2022. "Bayesian Low-Rank Interpolative Decomposition for Complex Datasets," Studies in Engineering and Technology, Redfame publishing, vol. 9(1), pages 112-112, December.
    20. Kerryn Elliott & Vinod Kumar Singh & Martin Boström & Erik Larsson, 2023. "Base-resolution UV footprinting by sequencing reveals distinctive damage signatures for DNA-binding proteins," Nature Communications, Nature, vol. 14(1), pages 1-10, 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_s41467-022-28910-8. 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.

    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.