ERG signaling in prostate cancer is driven through PRMT5-dependent methylation of the androgen receptor

  1. Zineb Mounir
  2. Joshua M Korn
  3. Thomas Westerling
  4. Fallon Lin
  5. Christina A Kirby
  6. Markus Schirle
  7. Gregg McAllister
  8. Greg Hoffman
  9. Nadire Ramadan
  10. Anke Hartung
  11. Yan Feng
  12. David Randal Kipp
  13. Christopher Quinn
  14. Michelle Fodor
  15. Jason Baird
  16. Marie Schoumacher
  17. Ronald Meyer
  18. James Deeds
  19. Gilles Buchwalter
  20. Travis Stams
  21. Nicholas Keen
  22. William R Sellers
  23. Myles Brown
  24. Raymond A Pagliarini  Is a corresponding author
  1. Genentech, United States
  2. Novartis Institutes for BioMedical Research, United States
  3. Harvard Medical School, United States
  4. Novartis Institutes for Biomedical Research, United States
  5. Organovo, United States
  6. NIBR, United States
  7. Laboratoires Servier, France
  8. Celgene Avilomics Research, United States

Abstract

The TMPRSS2:ERG gene fusion is common in androgen receptor (AR) positive prostate cancers, yet its function remains poorly understood. From a screen for functionally relevant ERG interactors, we identify the arginine methyltransferase PRMT5. ERG recruits PRMT5 to AR-target genes, where PRMT5 methylates AR on arginine 761. This attenuates AR recruitment and transcription of genes expressed in differentiated prostate epithelium. The AR-inhibitory function of PRMT5 is restricted to TMPRSS2:ERG-positive prostate cancer cells. Mutation of this methylation site on AR results in a transcriptionally hyperactive AR, suggesting that the proliferative effects of ERG and PRMT5 are mediated through attenuating AR's ability to induce genes normally involved in lineage differentiation. This provides a rationale for targeting PRMT5 in TMPRSS2:ERG positive prostate cancers. Moreover, methylation of AR at arginine 761 highlights a mechanism for how the ERG oncogene may coax AR towards inducing proliferation versus differentiation.

Article and author information

Author details

  1. Zineb Mounir

    Genentech, South San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Joshua M Korn

    Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Thomas Westerling

    Department of Medical Oncology, Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Fallon Lin

    Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Christina A Kirby

    Center for Proteomic Chemistry, Novartis Institutes for BioMedical Research, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Markus Schirle

    Developmental and Molecular Pathways, Novartis Institutes for Biomedical Research, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Gregg McAllister

    Developmental and Molecular Pathways, Novartis Institutes for Biomedical Research, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Greg Hoffman

    Developmental and Molecular Pathways, Novartis Institutes for Biomedical Research, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Nadire Ramadan

    Developmental and Molecular Pathways, Novartis Institutes for Biomedical Research, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Anke Hartung

    Organovo, San Diego, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Yan Feng

    Developmental and Molecular Pathways, Novartis Institutes for Biomedical Research, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. David Randal Kipp

    Oncology, NIBR, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  13. Christopher Quinn

    Oncology, NIBR, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  14. Michelle Fodor

    Oncology, NIBR, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  15. Jason Baird

    Oncology, NIBR, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  16. Marie Schoumacher

    Laboratoires Servier, Neuilly-sur-Seine, France
    Competing interests
    The authors declare that no competing interests exist.
  17. Ronald Meyer

    Department of Oncology, Novartis Institutes for Biomedical Research, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  18. James Deeds

    Department of Oncology, Novartis Institutes for Biomedical Research, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  19. Gilles Buchwalter

    Celgene Avilomics Research, Bedford, United States
    Competing interests
    The authors declare that no competing interests exist.
  20. Travis Stams

    Center for Proteomic Chemistry, Novartis Institutes for Biomedical Research, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  21. Nicholas Keen

    Department of Oncology, Novartis Institutes for Biomedical Research, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  22. William R Sellers

    Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  23. Myles Brown

    Department of Medical Oncology, Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  24. Raymond A Pagliarini

    Celgene Avilomics Research, Bedford, United States
    For correspondence
    raymond.pagliarini@novartis.com
    Competing interests
    The authors declare that no competing interests exist.

Reviewing Editor

  1. Scott A Armstrong, Memorial Sloan Kettering Cancer Center, United States

Version history

  1. Received: December 21, 2015
  2. Accepted: May 6, 2016
  3. Accepted Manuscript published: May 16, 2016 (version 1)
  4. Accepted Manuscript updated: May 18, 2016 (version 2)
  5. Version of Record published: June 15, 2016 (version 3)

Copyright

© 2016, Mounir 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

  • 4,003
    views
  • 1,042
    downloads
  • 60
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

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. Zineb Mounir
  2. Joshua M Korn
  3. Thomas Westerling
  4. Fallon Lin
  5. Christina A Kirby
  6. Markus Schirle
  7. Gregg McAllister
  8. Greg Hoffman
  9. Nadire Ramadan
  10. Anke Hartung
  11. Yan Feng
  12. David Randal Kipp
  13. Christopher Quinn
  14. Michelle Fodor
  15. Jason Baird
  16. Marie Schoumacher
  17. Ronald Meyer
  18. James Deeds
  19. Gilles Buchwalter
  20. Travis Stams
  21. Nicholas Keen
  22. William R Sellers
  23. Myles Brown
  24. Raymond A Pagliarini
(2016)
ERG signaling in prostate cancer is driven through PRMT5-dependent methylation of the androgen receptor
eLife 5:e13964.
https://doi.org/10.7554/eLife.13964

Share this article

https://doi.org/10.7554/eLife.13964

Further reading

    1. Cancer Biology
    Chenxi Gao, Huaibin Ge ... Jing Hu
    Research Article

    BRAFV600E mutation is a driver mutation in the serrated pathway to colorectal cancers. BRAFV600E drives tumorigenesis through constitutive downstream extracellular signal-regulated kinase (ERK) activation, but high-intensity ERK activation can also trigger tumor suppression. Whether and how oncogenic ERK signaling can be intrinsically adjusted to a ‘just-right’ level optimal for tumorigenesis remains undetermined. In this study, we found that FAK (Focal adhesion kinase) expression was reduced in BRAFV600E-mutant adenomas/polyps in mice and patients. In Vil1-Cre;BRAFLSL-V600E/+;Ptk2fl/fl mice, Fak deletion maximized BRAFV600E’s oncogenic activity and increased cecal tumor incidence to 100%. Mechanistically, our results showed that Fak loss, without jeopardizing BRAFV600E-induced ERK pathway transcriptional output, reduced EGFR (epidermal growth factor receptor)-dependent ERK phosphorylation. Reduction in ERK phosphorylation increased the level of Lgr4, promoting intestinal stemness and cecal tumor formation. Our findings show that a ‘just-right’ ERK signaling optimal for BRAFV600E-induced cecal tumor formation can be achieved via Fak loss-mediated downregulation of ERK phosphorylation.

    1. Cancer Biology
    2. Computational and Systems Biology
    Marie Breeur, George Stepaniants ... Vivian Viallon
    Research Article

    Untargeted metabolomic profiling through liquid chromatography-mass spectrometry (LC-MS) measures a vast array of metabolites within biospecimens, advancing drug development, disease diagnosis, and risk prediction. However, the low throughput of LC-MS poses a major challenge for biomarker discovery, annotation, and experimental comparison, necessitating the merging of multiple datasets. Current data pooling methods encounter practical limitations due to their vulnerability to data variations and hyperparameter dependence. Here, we introduce GromovMatcher, a flexible and user-friendly algorithm that automatically combines LC-MS datasets using optimal transport. By capitalizing on feature intensity correlation structures, GromovMatcher delivers superior alignment accuracy and robustness compared to existing approaches. This algorithm scales to thousands of features requiring minimal hyperparameter tuning. Manually curated datasets for validating alignment algorithms are limited in the field of untargeted metabolomics, and hence we develop a dataset split procedure to generate pairs of validation datasets to test the alignments produced by GromovMatcher and other methods. Applying our method to experimental patient studies of liver and pancreatic cancer, we discover shared metabolic features related to patient alcohol intake, demonstrating how GromovMatcher facilitates the search for biomarkers associated with lifestyle risk factors linked to several cancer types.