AR-V7 exhibits non-canonical mechanisms of nuclear import and chromatin engagement in castrate-resistant prostate cancer

Abstract

Expression of the AR splice variant, AR-V7, in prostate cancer is correlated with poor patient survival and resistance to AR targeted therapies and taxanes. Currently, there is no specific inhibitor of AR-V7, while the molecular mechanisms regulating its biological function are not well elucidated. Here we report that AR-V7 has unique biological features that functionally differentiate it from canonical AR-fl or from the second most prevalent variant, AR-v567. First, AR-V7 exhibits fast nuclear import kinetics via a pathway distinct from the nuclear localization signal dependent importin-a/b pathway used by AR-fl and AR-v567. We also show that the dimerization box domain, known to mediate AR dimerization and transactivation, is required for AR-V7 nuclear import but not for AR-fl. Once in the nucleus, AR-V7 is transcriptionally active, yet exhibits unusually high intranuclear mobility and transient chromatin interactions, unlike the stable chromatin association of liganded AR-fl. The high intranuclear mobility of AR-V7 together with its high transcriptional output, suggest a Hit-and-Run mode of transcription. Our findings reveal unique mechanisms regulating AR-V7 activity, offering the opportunity to develop selective therapeutic interventions.

Data availability

All data generated or analysed during this study are included in the manuscript. Source data files have been provided for figure 6.

Article and author information

Author details

  1. Seaho Kim

    Department of Medicine, Weill Cornell Medical College, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. CheukMan C Au

    Department of Medicine, Weill Cornell Medical College, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Mohd Azrin Bin Jamalruddin

    Department of Medicine, Weill Cornell Medical College, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Naira Essam Abou-Ghali

    Department of Medicine, Weill Cornell Medical College, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Eiman Mukhtar

    Department of Medicine, Weill Cornell Medical College, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Luigi Portella

    Department of Medicine, Weill Cornell Medical College, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Adeline Berger

    Department of Pathology, Weill Cornell Medical College, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Daniel Worroll III

    Department of Medicine, Weill Cornell Medical College, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7351-676X
  9. Prerna Vatsa

    Department of Medicine, Weill Cornell Medical College, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. David S Rickman

    Department of Pathology, Weill Cornell Medical College, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. David M Nanus

    Department of Medicine, Weill Cornell Medical College, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Paraskevi Giannakakou

    Department of Medicine, Weill Cornell Medical College, New York, United States
    For correspondence
    pag2015@med.cornell.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7378-262X

Funding

National Cancer Institute (NIH T32 CA203702)

  • Seaho Kim

National Cancer Institute (NIH T32 CA062948)

  • CheukMan C Au

National Cancer Institute (R01CA137020)

  • Paraskevi Giannakakou

National Cancer Institute (R21CA216800)

  • Paraskevi Giannakakou

National Cancer Institute (R01CA228512)

  • Paraskevi Giannakakou

National Cancer Institute (R01CA179100)

  • David S Rickman
  • Paraskevi Giannakakou

U.S. Department of Defense (W81XWH-17-1-0162)

  • Adeline Berger

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Erica A Golemis, Fox Chase Cancer Center, United States

Publication history

  1. Preprint posted: June 3, 2021 (view preprint)
  2. Received: August 27, 2021
  3. Accepted: July 17, 2022
  4. Accepted Manuscript published: July 18, 2022 (version 1)

Copyright

© 2022, Kim et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Seaho Kim
  2. CheukMan C Au
  3. Mohd Azrin Bin Jamalruddin
  4. Naira Essam Abou-Ghali
  5. Eiman Mukhtar
  6. Luigi Portella
  7. Adeline Berger
  8. Daniel Worroll III
  9. Prerna Vatsa
  10. David S Rickman
  11. David M Nanus
  12. Paraskevi Giannakakou
(2022)
AR-V7 exhibits non-canonical mechanisms of nuclear import and chromatin engagement in castrate-resistant prostate cancer
eLife 11:e73396.
https://doi.org/10.7554/eLife.73396

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    Sequencing of cell-free DNA (cfDNA) is currently being used to detect cancer by searching both for mutational and non-mutational alterations. Recent work has shown that the length distribution of cfDNA fragments from a cancer patient can inform tumor load and type. Here, we propose non-negative matrix factorization (NMF) of fragment length distributions as a novel and completely unsupervised method for studying fragment length patterns in cfDNA. Using shallow whole-genome sequencing (sWGS) of cfDNA from a cohort of patients with metastatic castration-resistant prostate cancer (mCRPC), we demonstrate how NMF accurately infers the true tumor fragment length distribution as an NMF component - and that the sample weights of this component correlate with ctDNA levels (r=0.75). We further demonstrate how using several NMF components enables accurate cancer detection on data from various early stage cancers (AUC = 0.96). Finally, we show that NMF, when applied across genomic regions, can be used to discover fragment length signatures associated with open chromatin.

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