A feedback loop between the androgen receptor and 6-phosphogluoconate dehydrogenase (6PGD) drives prostate cancer growth

  1. Joanna L Gillis
  2. Josephine A Hinneh
  3. Natalie K Ryan
  4. Swati Irani
  5. Max Moldovan
  6. Lake-Ee Quek
  7. Raj K Shrestha
  8. Adrienne R Hanson
  9. Jianling Xie
  10. Andrew J Hoy
  11. Jeff Holst
  12. Margaret M Centenera
  13. Ian G Mills
  14. David J Lynn
  15. Luke A Selth  Is a corresponding author
  16. Lisa M Butler  Is a corresponding author
  1. University of Adelaide, Australia
  2. South Australian Health and Medical Research Institute, Australia
  3. University of Sydney, Australia
  4. Flinders University, Australia
  5. University of New South Wales, Australia
  6. Queen's University Belfast, United Kingdom

Abstract

Alterations to the androgen receptor (AR) signalling axis and cellular metabolism are hallmarks of prostate cancer. This study provides insight into both hallmarks by uncovering a novel link between AR and the pentose phosphate pathway (PPP). Specifically, we identify 6-phosphogluoconate dehydrogenase (6PGD) as an androgen-regulated gene that is upregulated in prostate cancer. AR increased the expression of 6PGD indirectly via activation of sterol regulatory element binding protein 1 (SREBP1). Accordingly, loss of 6PGD, AR or SREBP1 resulted in suppression of PPP activity, as revealed by 1,2-13C2 glucose metabolic flux analysis. Knockdown of 6PGD also impaired growth and elicited death of prostate cancer cells, at least in part due to increased oxidative stress. We investigated the therapeutic potential of targeting 6PGD using two specific inhibitors, physcion and S3, and observed substantial anti-cancer activity in multiple models of prostate cancer, including aggressive, therapy-resistant models of castration-resistant disease as well as prospectively-collected patient-derived tumour explants. Targeting of 6PGD was associated with two important tumour-suppressive mechanisms: first, increased activity of the AMP-activated protein kinase (AMPK), which repressed anabolic growth-promoting pathways regulated by ACC1 and mTOR; and second, enhanced AR ubiquitylation, associated with a reduction in AR protein levels and activity. Supporting the biological relevance of positive feedback between AR and PGD, pharmacological co-targeting of both factors was more effective in suppressing the growth of prostate cancer cells than single agent therapies. Collectively, this work provides new insight into the dysregulated metabolism of prostate cancer and provides impetus for further investigation of co-targeting AR and the PPP as a novel therapeutic strategy.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figure 1.Sequencing data have been deposited in GEO under accession code GSE152254

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Joanna L Gillis

    Medicine, University of Adelaide, Adelaide, Australia
    Competing interests
    The authors declare that no competing interests exist.
  2. Josephine A Hinneh

    Medicine, University of Adelaide, Adelaide, Australia
    Competing interests
    The authors declare that no competing interests exist.
  3. Natalie K Ryan

    Medicine, University of Adelaide, Adelaide, Australia
    Competing interests
    The authors declare that no competing interests exist.
  4. Swati Irani

    Medicine, University of Adelaide, Adelaide, Australia
    Competing interests
    The authors declare that no competing interests exist.
  5. Max Moldovan

    Precision Medicine, South Australian Health and Medical Research Institute, Adelaide, Australia
    Competing interests
    The authors declare that no competing interests exist.
  6. Lake-Ee Quek

    Charles Perkins Centre, University of Sydney, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.
  7. Raj K Shrestha

    Medicine, University of Adelaide, Adelaide, Australia
    Competing interests
    The authors declare that no competing interests exist.
  8. Adrienne R Hanson

    Flinders University, Bedford Park, Australia
    Competing interests
    The authors declare that no competing interests exist.
  9. Jianling Xie

    Flinders University, Bedford Park, Australia
    Competing interests
    The authors declare that no competing interests exist.
  10. Andrew J Hoy

    Charles Perkins Centre, University of Sydney, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3922-1137
  11. Jeff Holst

    School of Medical Sciences, University of New South Wales, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0377-9318
  12. Margaret M Centenera

    Medicine, University of Adelaide, Adelaide, Australia
    Competing interests
    The authors declare that no competing interests exist.
  13. Ian G Mills

    Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  14. David J Lynn

    Precision Medicine, South Australian Health and Medical Research Institute, Adelaide, Australia
    Competing interests
    The authors declare that no competing interests exist.
  15. Luke A Selth

    Flinders University, Bedford Park, Australia
    For correspondence
    luke.selth@flinders.edu.au
    Competing interests
    The authors declare that no competing interests exist.
  16. Lisa M Butler

    Medicine, University of Adelaide, Adelaide, Australia
    For correspondence
    lisa.butler@adelaide.edu.au
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2698-3220

Funding

Cancer Australia (1138766)

  • Margaret M Centenera
  • Ian G Mills
  • David J Lynn
  • Lisa M Butler

Movember Foundation (MRTA3)

  • Andrew J Hoy
  • Margaret M Centenera
  • Luke A Selth
  • Lisa M Butler

Prostate Cancer Foundation of Australia (MRTA3)

  • Andrew J Hoy
  • Margaret M Centenera
  • Luke A Selth
  • Lisa M Butler

Cancer Council South Australia (Principal Cancer Research Fellowships)

  • Luke A Selth
  • Lisa M Butler

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

Reviewing Editor

  1. Ivan Topisirovic, Jewish General Hospital, Canada

Ethics

Human subjects: Prostate cancer tissue was obtained with informed written consent through the Australian Prostate Cancer BioResource from men undergoing radical prostatectomy at St Andrew's Hospital (Adelaide, Australia). Ethical approval for the use of human prostate tumours was obtained from the Ethics Committees of the University of Adelaide (Adelaide, Australia) and St Andrew's Hospital (Adelaide, Australia). All experiments were performed in accordance with the guidelines of the National Health and Medical Research Council (Australia).

Version history

  1. Received: August 29, 2020
  2. Preprint posted: September 3, 2020 (view preprint)
  3. Accepted: August 11, 2021
  4. Accepted Manuscript published: August 12, 2021 (version 1)
  5. Version of Record published: September 3, 2021 (version 2)

Copyright

© 2021, Gillis 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.

Metrics

  • 2,275
    Page views
  • 329
    Downloads
  • 12
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Joanna L Gillis
  2. Josephine A Hinneh
  3. Natalie K Ryan
  4. Swati Irani
  5. Max Moldovan
  6. Lake-Ee Quek
  7. Raj K Shrestha
  8. Adrienne R Hanson
  9. Jianling Xie
  10. Andrew J Hoy
  11. Jeff Holst
  12. Margaret M Centenera
  13. Ian G Mills
  14. David J Lynn
  15. Luke A Selth
  16. Lisa M Butler
(2021)
A feedback loop between the androgen receptor and 6-phosphogluoconate dehydrogenase (6PGD) drives prostate cancer growth
eLife 10:e62592.
https://doi.org/10.7554/eLife.62592

Share this article

https://doi.org/10.7554/eLife.62592

Further reading

    1. Cancer Biology
    2. Computational and Systems Biology
    Bingrui Li, Fernanda G Kugeratski, Raghu Kalluri
    Research Article

    Non-invasive early cancer diagnosis remains challenging due to the low sensitivity and specificity of current diagnostic approaches. Exosomes are membrane-bound nanovesicles secreted by all cells that contain DNA, RNA, and proteins that are representative of the parent cells. This property, along with the abundance of exosomes in biological fluids makes them compelling candidates as biomarkers. However, a rapid and flexible exosome-based diagnostic method to distinguish human cancers across cancer types in diverse biological fluids is yet to be defined. Here, we describe a novel machine learning-based computational method to distinguish cancers using a panel of proteins associated with exosomes. Employing datasets of exosome proteins from human cell lines, tissue, plasma, serum, and urine samples from a variety of cancers, we identify Clathrin Heavy Chain (CLTC), Ezrin, (EZR), Talin-1 (TLN1), Adenylyl cyclase-associated protein 1 (CAP1), and Moesin (MSN) as highly abundant universal biomarkers for exosomes and define three panels of pan-cancer exosome proteins that distinguish cancer exosomes from other exosomes and aid in classifying cancer subtypes employing random forest models. All the models using proteins from plasma, serum, or urine-derived exosomes yield AUROC scores higher than 0.91 and demonstrate superior performance compared to Support Vector Machine, K Nearest Neighbor Classifier and Gaussian Naive Bayes. This study provides a reliable protein biomarker signature associated with cancer exosomes with scalable machine learning capability for a sensitive and specific non-invasive method of cancer diagnosis.

    1. Cancer Biology
    Carolyn M Jablonowski, Waise Quarni ... Jun Yang
    Research Article

    Dysregulated pre-mRNA splicing and metabolism are two hallmarks of MYC-driven cancers. Pharmacological inhibition of both processes has been extensively investigated as potential therapeutic avenues in preclinical and clinical studies. However, how pre-mRNA splicing and metabolism are orchestrated in response to oncogenic stress and therapies is poorly understood. Here, we demonstrate that jumonji domain containing 6, arginine demethylase, and lysine hydroxylase, JMJD6, acts as a hub connecting splicing and metabolism in MYC-driven human neuroblastoma. JMJD6 cooperates with MYC in cellular transformation of murine neural crest cells by physically interacting with RNA binding proteins involved in pre-mRNA splicing and protein homeostasis. Notably, JMJD6 controls the alternative splicing of two isoforms of glutaminase (GLS), namely kidney-type glutaminase (KGA) and glutaminase C (GAC), which are rate-limiting enzymes of glutaminolysis in the central carbon metabolism in neuroblastoma. Further, we show that JMJD6 is correlated with the anti-cancer activity of indisulam, a ‘molecular glue’ that degrades splicing factor RBM39, which complexes with JMJD6. The indisulam-mediated cancer cell killing is at least partly dependent on the glutamine-related metabolic pathway mediated by JMJD6. Our findings reveal a cancer-promoting metabolic program is associated with alternative pre-mRNA splicing through JMJD6, providing a rationale to target JMJD6 as a therapeutic avenue for treating MYC-driven cancers.