Epstein-Barr virus ensures B cell survival by uniquely modulating apoptosis at early and late times after infection

  1. Alexander M Price
  2. Joanne Dai
  3. Quentin Bazot
  4. Luv Patel
  5. Pavel A Nikitin
  6. Reza Djavadian
  7. Peter S Winter
  8. Cristina A Salinas
  9. Ashley Perkins Barry
  10. Kris C Wood
  11. Eric C Johannsen
  12. Anthony Letai
  13. Martin J Allday
  14. Micah A Luftig  Is a corresponding author
  1. Duke University School of Medicine, United States
  2. Imperial College London, United Kingdom
  3. Harvard Medical School, United States
  4. University of Wisconsin School of Medicine and Public Health, United States
  5. Duke University, United States

Abstract

Latent Epstein-Barr virus (EBV) infection is causally linked to several human cancers. EBV expresses viral oncogenes that promote cell growth and inhibit the apoptotic response to uncontrolled proliferation. The EBV oncoprotein LMP1 constitutively activates NFB and is critical for survival of EBV-immortalized B cells. However, during early infection EBV induces rapid B cell proliferation with low levels of LMP1 and little apoptosis. Therefore, we sought to define the mechanism of survival in the absence of LMP1/NFB early after infection. We used BH3 profiling to query mitochondrial regulation of apoptosis and defined a transition from uninfected B cells (BCL-2) to early-infected (MCL-1/BCL-2) and immortalized cells (BFL-1). This dynamic change in B cell survival mechanisms is unique to virus-infected cells and relies on regulation of MCL-1 mitochondrial localization and BFL-1 transcription by the viral EBNA3A protein. This study defines a new role for EBNA3A in the suppression of apoptosis with implications for EBV lymphomagenesis.

Data availability

The following previously published data sets were used
    1. Zhao B
    2. Zou JY
    3. Wang H
    4. Johannsen E
    5. Aster J
    6. Bernstein B
    7. Kieff E
    (2011) EBNA2 ChIP-Seq
    Publicly available at the NCBI Gene Expression Omnibus (accession no: GSE29498).
    1. Shoresh N
    (2011) Histone modifications in LCLs (ENCODE)
    Publicly available at the NCBI Gene Expression Omnibus (accession no: GSE29611).
    1. Snyder M
    2. Gerstein M
    3. Weissman S
    4. Farnham P
    5. Struhl K
    (2011) TF binding sites in LCLs (ENCODE)
    Publicly available at the NCBI Gene Expression Omnibus (accession no: GSE31477).

Article and author information

Author details

  1. Alexander M Price

    Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, United States
    Competing interests
    No competing interests declared.
  2. Joanne Dai

    Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, United States
    Competing interests
    No competing interests declared.
  3. Quentin Bazot

    Molecular Virology, Division of Infectious Diseases, Department of Medicine, Imperial College London, London, United Kingdom
    Competing interests
    No competing interests declared.
  4. Luv Patel

    Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States
    Competing interests
    No competing interests declared.
  5. Pavel A Nikitin

    Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, United States
    Competing interests
    No competing interests declared.
  6. Reza Djavadian

    McArdle Laboratory for Cancer Research, University of Wisconsin School of Medicine and Public Health, Madison, United States
    Competing interests
    No competing interests declared.
  7. Peter S Winter

    Department of Pharmacology and Cancer Biology, Duke University, Durham, United States
    Competing interests
    No competing interests declared.
  8. Cristina A Salinas

    Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, United States
    Competing interests
    No competing interests declared.
  9. Ashley Perkins Barry

    Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, United States
    Competing interests
    No competing interests declared.
  10. Kris C Wood

    Department of Pharmacology and Cancer Biology, Duke University, Durham, United States
    Competing interests
    No competing interests declared.
  11. Eric C Johannsen

    McArdle Laboratory for Cancer Research, University of Wisconsin School of Medicine and Public Health, Madison, United States
    Competing interests
    No competing interests declared.
  12. Anthony Letai

    Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States
    Competing interests
    Anthony Letai, Is a paid advisor to, and his laboratory receives research sponsorship from, AbbVie, Astra-Zeneca, and Tetralogic..
  13. Martin J Allday

    Molecular Virology, Division of Infectious Diseases, Department of Medicine, Imperial College London, London, United Kingdom
    Competing interests
    No competing interests declared.
  14. Micah A Luftig

    Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, United States
    For correspondence
    micah.luftig@duke.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2964-1907

Funding

National Cancer Institute (R01-CA140337)

  • Micah A Luftig

American Cancer Society (RSG-13-228-01-MPC)

  • Micah A Luftig

Wellcome (099273/Z/12/Z)

  • Quentin Bazot
  • Martin J Allday

National Institute for Dental and Cranofacial Research (R01-DE025994)

  • Joanne Dai
  • Micah A Luftig

National Institute for Allergy and Infectious Diseases (5P30-AI064518)

  • Micah A Luftig

National Cancer Institute (F31-CA180451)

  • Alexander M Price

National Institute for Dental and Cranofacial Research (R01-DE023939)

  • Eric C Johannsen

National Institute for Allergy and Infectious Diseases (T32-AI078985)

  • Reza Djavadian

National Cancer Institute (R01-CA129974)

  • Anthony Letai

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

Copyright

© 2017, Price 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

  • 3,637
    views
  • 723
    downloads
  • 57
    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. Alexander M Price
  2. Joanne Dai
  3. Quentin Bazot
  4. Luv Patel
  5. Pavel A Nikitin
  6. Reza Djavadian
  7. Peter S Winter
  8. Cristina A Salinas
  9. Ashley Perkins Barry
  10. Kris C Wood
  11. Eric C Johannsen
  12. Anthony Letai
  13. Martin J Allday
  14. Micah A Luftig
(2017)
Epstein-Barr virus ensures B cell survival by uniquely modulating apoptosis at early and late times after infection
eLife 6:e22509.
https://doi.org/10.7554/eLife.22509

Share this article

https://doi.org/10.7554/eLife.22509

Further reading

    1. Cancer Biology
    Bruno Bockorny, Lakshmi Muthuswamy ... Senthil K Muthuswamy
    Tools and Resources

    Pancreatic cancer has the worst prognosis of all common tumors. Earlier cancer diagnosis could increase survival rates and better assessment of metastatic disease could improve patient care. As such, there is an urgent need to develop biomarkers to diagnose this deadly malignancy. Analyzing circulating extracellular vesicles (cEVs) using ‘liquid biopsies’ offers an attractive approach to diagnose and monitor disease status. However, it is important to differentiate EV-associated proteins enriched in patients with pancreatic ductal adenocarcinoma (PDAC) from those with benign pancreatic diseases such as chronic pancreatitis and intraductal papillary mucinous neoplasm (IPMN). To meet this need, we combined the novel EVtrap method for highly efficient isolation of EVs from plasma and conducted proteomics analysis of samples from 124 individuals, including patients with PDAC, benign pancreatic diseases and controls. On average, 912 EV proteins were identified per 100 µL of plasma. EVs containing high levels of PDCD6IP, SERPINA12, and RUVBL2 were associated with PDAC compared to the benign diseases in both discovery and validation cohorts. EVs with PSMB4, RUVBL2, and ANKAR were associated with metastasis, and those with CRP, RALB, and CD55 correlated with poor clinical prognosis. Finally, we validated a seven EV protein PDAC signature against a background of benign pancreatic diseases that yielded an 89% prediction accuracy for the diagnosis of PDAC. To our knowledge, our study represents the largest proteomics profiling of circulating EVs ever conducted in pancreatic cancer and provides a valuable open-source atlas to the scientific community with a comprehensive catalogue of novel cEVs that may assist in the development of biomarkers and improve the outcomes of patients with PDAC.

    1. Cancer Biology
    2. Evolutionary Biology
    Lingjie Zhang, Tong Deng ... Chung-I Wu
    Research Article

    Tumorigenesis, like most complex genetic traits, is driven by the joint actions of many mutations. At the nucleotide level, such mutations are cancer-driving nucleotides (CDNs). The full sets of CDNs are necessary, and perhaps even sufficient, for the understanding and treatment of each cancer patient. Currently, only a small fraction of CDNs is known as most mutations accrued in tumors are not drivers. We now develop the theory of CDNs on the basis that cancer evolution is massively repeated in millions of individuals. Hence, any advantageous mutation should recur frequently and, conversely, any mutation that does not is either a passenger or deleterious mutation. In the TCGA cancer database (sample size n=300–1000), point mutations may recur in i out of n patients. This study explores a wide range of mutation characteristics to determine the limit of recurrences (i*) driven solely by neutral evolution. Since no neutral mutation can reach i*=3, all mutations recurring at i≥3 are CDNs. The theory shows the feasibility of identifying almost all CDNs if n increases to 100,000 for each cancer type. At present, only <10% of CDNs have been identified. When the full sets of CDNs are identified, the evolutionary mechanism of tumorigenesis in each case can be known and, importantly, gene targeted therapy will be far more effective in treatment and robust against drug resistance.