Characterization of the mechanism by which the RB/E2F pathway controls expression of the cancer genomic DNA deaminase APOBEC3B

  1. Pieter A Roelofs
  2. Chai Yeen Goh
  3. Boon Haow Chua
  4. Matthew C Jarvis
  5. Teneale A Stewart
  6. Jennifer L McCann
  7. Rebecca M McDougle
  8. Michael A Carpenter
  9. John WM Martens
  10. Paul N Span
  11. Dennis Kappei
  12. Reuben S Harris  Is a corresponding author
  1. University of Minnesota, United States
  2. National University of Singapore, Singapore
  3. Howard Hughes Medical Institute, University of Minnesota, United States
  4. Erasmus MC Cancer Institute, Erasmus University Medical Center, Netherlands
  5. Radboud University Medical Center, Netherlands [NL]

Abstract

APOBEC3B (A3B)-catalyzed DNA cytosine deamination contributes to the overall mutational landscape in breast cancer. Molecular mechanisms responsible for A3B upregulation in cancer are poorly understood. Here, we show that a single E2F cis-element mediates repression in normal cells and that expression is activated by its mutational disruption in a reporter construct or the endogenous A3B gene. The same E2F site is required for A3B induction by polyomavirus T antigen indicating a shared molecular mechanism. Proteomic and biochemical experiments demonstrate binding of wildtype but not mutant E2F promoters by repressive PRC1.6/E2F6 and DREAM/E2F4 complexes. Knockdown and overexpression studies confirm involvement of these repressive complexes in regulating A3B expression. Altogether, these studies demonstrate that A3B expression is suppressed in normal cells by repressive E2F complexes and that viral or mutational disruption of this regulatory network triggers overexpression in breast cancer and provides fuel for tumor evolution.

Data availability

Raw mass spectrometry data will be accessible through the ProteomeXchange Consortium via the PRIDE (Vizcaino et al., 2016) partner repository with the dataset identifier PXD020473. Additional data generated or analysed during this study are included in the manuscript and supporting files.

Article and author information

Author details

  1. Pieter A Roelofs

    Biochemistry, University of Minnesota, Minneapolis, United States
    Competing interests
    No competing interests declared.
  2. Chai Yeen Goh

    Translational Medicine, National University of Singapore, Singapore, Singapore
    Competing interests
    No competing interests declared.
  3. Boon Haow Chua

    Translational Medicine, National University of Singapore, Singapore, Singapore
    Competing interests
    No competing interests declared.
  4. Matthew C Jarvis

    Microbiology and Immunology, University of Minnesota, Minneapolis, United States
    Competing interests
    No competing interests declared.
  5. Teneale A Stewart

    Biochemistry, University of Minnesota, Minneapolis, United States
    Competing interests
    No competing interests declared.
  6. Jennifer L McCann

    Microbiology and Immunology, University of Minnesota, Minneapolis, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0458-1335
  7. Rebecca M McDougle

    Biochemistry, University of Minnesota, Minneapolis, United States
    Competing interests
    No competing interests declared.
  8. Michael A Carpenter

    Biochemistry, Howard Hughes Medical Institute, University of Minnesota, Minneapolis, United States
    Competing interests
    No competing interests declared.
  9. John WM Martens

    Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, Netherlands
    Competing interests
    No competing interests declared.
  10. Paul N Span

    Radboud University Medical Center, Nijmegen, Netherlands [NL]
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1930-6638
  11. Dennis Kappei

    Translational Medicine, National University of Singapore, Singapore, Singapore
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3582-2253
  12. Reuben S Harris

    Biochemistry, Howard Hughes Medical Institute, University of Minnesota, Minneapolis, United States
    For correspondence
    rsh@umn.edu
    Competing interests
    Reuben S Harris, RSH is a co-founder, shareholder, and consultant of ApoGen Biotechnologies Inc..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9034-9112

Funding

National Cancer Institute (P01-CA234228)

  • Reuben S Harris

KWF Kankerbestrijding (KWF10270)

  • John WM Martens
  • Paul N Span
  • Reuben S Harris

National Research Foundation Singapore (NMRC/OFYIRG/055/2017)

  • Dennis Kappei

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

Copyright

© 2020, Roelofs 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

  • 2,893
    views
  • 330
    downloads
  • 26
    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. Pieter A Roelofs
  2. Chai Yeen Goh
  3. Boon Haow Chua
  4. Matthew C Jarvis
  5. Teneale A Stewart
  6. Jennifer L McCann
  7. Rebecca M McDougle
  8. Michael A Carpenter
  9. John WM Martens
  10. Paul N Span
  11. Dennis Kappei
  12. Reuben S Harris
(2020)
Characterization of the mechanism by which the RB/E2F pathway controls expression of the cancer genomic DNA deaminase APOBEC3B
eLife 9:e61287.
https://doi.org/10.7554/eLife.61287

Share this article

https://doi.org/10.7554/eLife.61287

Further reading

    1. Cancer Biology
    Thi Mong Quynh Pham, Thanh Nhan Nguyen ... Le Son Tran
    Research Article

    In the realm of cancer immunotherapy, the meticulous selection of neoantigens plays a fundamental role in enhancing personalized treatments. Traditionally, this selection process has heavily relied on predicting the binding of peptides to human leukocyte antigens (pHLA). Nevertheless, this approach often overlooks the dynamic interaction between tumor cells and the immune system. In response to this limitation, we have developed an innovative prediction algorithm rooted in machine learning, integrating T cell receptor β chain (TCRβ) profiling data from colorectal cancer (CRC) patients for a more precise neoantigen prioritization. TCRβ sequencing was conducted to profile the TCR repertoire of tumor-infiltrating lymphocytes (TILs) from 28 CRC patients. The data unveiled both intra-tumor and inter-patient heterogeneity in the TCRβ repertoires of CRC patients, likely resulting from the stochastic utilization of V and J segments in response to neoantigens. Our novel combined model integrates pHLA binding information with pHLA-TCR binding to prioritize neoantigens, resulting in heightened specificity and sensitivity compared to models using individual features alone. The efficacy of our proposed model was corroborated through ELISpot assays on long peptides, performed on four CRC patients. These assays demonstrated that neoantigen candidates prioritized by our combined model outperformed predictions made by the established tool NetMHCpan. This comprehensive assessment underscores the significance of integrating pHLA binding with pHLA-TCR binding analysis for more effective immunotherapeutic strategies.

    1. Cancer Biology
    Honglei Zhang, Chao Liu ... Gaofeng Li
    Research Article

    Air pollution significantly impacts lung cancer progression, but there is a lack of a comprehensive molecular characterization of clinical samples associated with air pollution. Here, we performed a proteogenomic analysis of lung adenocarcinoma (LUAD) in 169 female never-smokers from the Xuanwei area (XWLC cohort), where coal smoke is the primary contributor to the high lung cancer incidence. Genomic mutation analysis revealed XWLC as a distinct subtype of LUAD separate from cases associated with smoking or endogenous factors. Mutational signature analysis suggested that Benzo[a]pyrene (BaP) is the major risk factor in XWLC. The BaP-induced mutation hotspot, EGFR-G719X, was present in 20% of XWLC which endowed XWLC with elevated MAPK pathway activations and worse outcomes compared to common EGFR mutations. Multi-omics clustering of XWLC identified four clinically relevant subtypes. These subgroups exhibited distinct features in biological processes, genetic alterations, metabolism demands, immune landscape, and radiomic features. Finally, MAD1 and TPRN were identified as novel potential therapeutic targets in XWLC. Our study provides a valuable resource for researchers and clinicians to explore prevention and treatment strategies for air-pollution-associated lung cancers.