Multiple tumor suppressors regulate a HIF-dependent negative feedback loop via ISGF3 in human clear cell renal cancer

  1. Lili Liao
  2. Zongzhi Z Liu
  3. Lauren Langbein
  4. Weijia Cai
  5. Eun-Ah Cho
  6. Jie Na
  7. Xiaohua Niu
  8. Wei Jiang
  9. Zhijiu Zhong
  10. Wesley L Cai
  11. Geetha Jagannathan
  12. Essel Dulaimi
  13. Joseph R Testa
  14. Robert G Uzzo
  15. Yuxin Wang
  16. George R Stark
  17. Jianxin Sun
  18. Stephen C Peiper
  19. Yaomin Xu  Is a corresponding author
  20. Qin Yan  Is a corresponding author
  21. Haifeng Yang  Is a corresponding author
  1. Thomas Jefferson University, United States
  2. Yale University, United States
  3. Mayo Clinic, United States
  4. The Sixth Affiliated Hospital of Guangzhou Medical University, China
  5. Fox Chase Cancer Center, United States
  6. Lerner Research Institute, Cleveland Clinic, United States
  7. Vanderbilt University, United States

Abstract

Whereas VHL inactivation is a primary event in clear cell renal cell carcinoma (ccRCC), the precise mechanism(s) of how this interacts with the secondary mutations in tumor suppressor genes, including PBRM1, KDM5C/JARID1C, SETD2, and/orBAP1, remains unclear. Gene expression analyses reveal that VHL, PBRM1, or KDM5C share a common regulation of interferon response expression signature. Loss of HIF2a, PBRM1, or KDM5C in VHL-/-cells reduces the expression of interferon stimulated gene factor 3 (ISGF3), a transcription factor that regulates the interferon signature. Moreover, loss of SETD2 or BAP1 also reduces the ISGF3 level. Finally, ISGF3 is strongly tumor-suppressive in a xenograft model as its loss significantly enhances tumor growth. Conversely, reactivation of ISGF3 retards tumor growth by PBRM1-deficient ccRCC cells. Thus after VHL inactivation, HIF induces ISGF3, which is reversed by the loss of secondary tumor suppressors, suggesting that this is a key negative feedback loop in ccRCC.

Data availability

Microarray data have been deposited inn GEO under the accession code GSE108229.

The following data sets were generated

Article and author information

Author details

  1. Lili Liao

    Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Zongzhi Z Liu

    Department of Pathology, Yale University, New Haven, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Lauren Langbein

    Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3007-5287
  4. Weijia Cai

    Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Eun-Ah Cho

    Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Jie Na

    Department of Health Sciences Research, Mayo Clinic, Rochester, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Xiaohua Niu

    Department of Gastrointestinal Surgery, The Sixth Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
    Competing interests
    The authors declare that no competing interests exist.
  8. Wei Jiang

    Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Zhijiu Zhong

    Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Wesley L Cai

    Department of Pathology, Yale University, New Haven, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Geetha Jagannathan

    Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Essel Dulaimi

    Fox Chase Cancer Center, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  13. Joseph R Testa

    Fox Chase Cancer Center, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  14. Robert G Uzzo

    Fox Chase Cancer Center, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  15. Yuxin Wang

    Department of Cancer Biology, Lerner Research Institute, Cleveland Clinic, Cleveland, United States
    Competing interests
    The authors declare that no competing interests exist.
  16. George R Stark

    Department of Cancer Biology, Lerner Research Institute, Cleveland Clinic, Cleveland, United States
    Competing interests
    The authors declare that no competing interests exist.
  17. Jianxin Sun

    Department of Medicine, Thomas Jefferson University, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  18. Stephen C Peiper

    Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  19. Yaomin Xu

    Department of Biostatistics, Vanderbilt University, Nashville, United States
    For correspondence
    yaomin.xu@vanderbilt.edu
    Competing interests
    The authors declare that no competing interests exist.
  20. Qin Yan

    Department of Pathology, Yale University, New Haven, United States
    For correspondence
    qin.yan@yale.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4077-453X
  21. Haifeng Yang

    Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, United States
    For correspondence
    Haifeng.yang@jefferson.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0892-9055

Funding

National Cancer Institute (R01 CA155015)

  • Haifeng Yang

National Cancer Institute (P30CA056036)

  • Haifeng Yang

Department of Defence (W81XWH-16-1-0326)

  • Qin Yan

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

Ethics

Animal experimentation: All animal experiments were conducted in accordance with protocol 01462-935A approved by the IACUC of Thomas Jefferson University and protocol 2015-11286 approved by the IACUC of Yale University.

Reviewing Editor

  1. Irwin Davidson, Institut de Génétique et de Biologie Moléculaire et Cellulaire, France

Publication history

  1. Received: April 27, 2018
  2. Accepted: October 22, 2018
  3. Accepted Manuscript published: October 25, 2018 (version 1)
  4. Version of Record published: November 13, 2018 (version 2)
  5. Version of Record updated: April 21, 2021 (version 3)

Copyright

© 2018, Liao 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. Lili Liao
  2. Zongzhi Z Liu
  3. Lauren Langbein
  4. Weijia Cai
  5. Eun-Ah Cho
  6. Jie Na
  7. Xiaohua Niu
  8. Wei Jiang
  9. Zhijiu Zhong
  10. Wesley L Cai
  11. Geetha Jagannathan
  12. Essel Dulaimi
  13. Joseph R Testa
  14. Robert G Uzzo
  15. Yuxin Wang
  16. George R Stark
  17. Jianxin Sun
  18. Stephen C Peiper
  19. Yaomin Xu
  20. Qin Yan
  21. Haifeng Yang
(2018)
Multiple tumor suppressors regulate a HIF-dependent negative feedback loop via ISGF3 in human clear cell renal cancer
eLife 7:e37925.
https://doi.org/10.7554/eLife.37925

Further reading

    1. Cancer Biology
    2. Computational and Systems Biology
    Iurii Petrov, Andrey Alexeyenko
    Research Article Updated

    Late advances in genome sequencing expanded the space of known cancer driver genes several-fold. However, most of this surge was based on computational analysis of somatic mutation frequencies and/or their impact on the protein function. On the contrary, experimental research necessarily accounted for functional context of mutations interacting with other genes and conferring cancer phenotypes. Eventually, just such results become ‘hard currency’ of cancer biology. The new method, NEAdriver employs knowledge accumulated thus far in the form of global interaction network and functionally annotated pathways in order to recover known and predict novel driver genes. The driver discovery was individualized by accounting for mutations’ co-occurrence in each tumour genome – as an alternative to summarizing information over the whole cancer patient cohorts. For each somatic genome change, probabilistic estimates from two lanes of network analysis were combined into joint likelihoods of being a driver. Thus, ability to detect previously unnoticed candidate driver events emerged from combining individual genomic context with network perspective. The procedure was applied to 10 largest cancer cohorts followed by evaluating error rates against previous cancer gene sets. The discovered driver combinations were shown to be informative on cancer outcome. This revealed driver genes with individually sparse mutation patterns that would not be detectable by other computational methods and related to cancer biology domains poorly covered by previous analyses. In particular, recurrent mutations of collagen, laminin, and integrin genes were observed in the adenocarcinoma and glioblastoma cancers. Considering constellation patterns of candidate drivers in individual cancer genomes opens a novel avenue for personalized cancer medicine.