Kinase-dead ATM protein is highly oncogenic and can be preferentially targeted by Topo-isomerase I inhibitors

  1. Kenta Yamamoto
  2. Jiguang Wang
  3. Lisa Sprinzen
  4. Jun Xu
  5. Christopher J Haddock
  6. Chen Li
  7. Brian J Lee
  8. Denis G Loredan
  9. Wenxia Jiang
  10. Alessandro Vindigni
  11. Dong Wang
  12. Raul Rabadan
  13. Shan Zha  Is a corresponding author
  1. Columbia Unviersity, United States
  2. University of California San Diego, United States
  3. Saint Louis University School of Medicine, United States
  4. Columbia University, United States

Abstract

Missense mutations in ATM kinase, a master regulator of DNA damage responses, are found in many cancers, but their impact on ATM function and implications for cancer therapy are largely unknown. Here we report that 72% of cancer-associated ATM mutations are missense mutations that are enriched around the kinase domain. Expression of kinase-dead ATM (AtmKD/-) is more oncogenic than loss of ATM (Atm-/-) in mouse models, leading to earlier and more frequent lymphomas with Pten deletions. Kinase-dead ATM protein (Atm-KD), but not loss of ATM (Atm-null), prevents replication-dependent removal of Topo-isomerase I-DNA adducts at the step of strand cleavage, leading to severe genomic instability and hypersensitivity to Topo-isomerase I inhibitors. Correspondingly, Topo-isomerase I inhibitors effectively and preferentially eliminate AtmKD/-, but not Atm-proficient or Atm-/- leukemia in animal models. These findings identify ATM kinase-domain missense mutations as a potent oncogenic event and a biomarker for Topo-isomerase I inhibitor based therapy.

Article and author information

Author details

  1. Kenta Yamamoto

    Insitute for Cancer Genetics, Columbia Unviersity, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Jiguang Wang

    Department of Biomedical Informatics and Department of Systems Biology, , College of Physicians & Surgeons, Columbia Unviersity, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Lisa Sprinzen

    Insitute for Cancer Genetics, Columbia Unviersity, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Jun Xu

    Skaggs School of Pharmacy & Pharmaceutical Sciences, University of California San Diego, San Diego, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Christopher J Haddock

    Edward A. Doisy Department of Biochemistry and Molecular Biology, Saint Louis University School of Medicine, St. Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Chen Li

    Insitute for Cancer Genetics, Columbia Unviersity, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Brian J Lee

    Insitute for Cancer Genetics, Columbia Unviersity, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Denis G Loredan

    Insitute for Cancer Genetics, Columbia Unviersity, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Wenxia Jiang

    Institute for Cancer Genetics, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Alessandro Vindigni

    Edward A. Doisy Department of Biochemistry and Molecular Biology, Saint Louis University School of Medicine, St. Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Dong Wang

    Skaggs School of Pharmacy & Pharmaceutical Sciences, University of California San Diego, La Jolla, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Raul Rabadan

    Department of Biomedical Informatics and Department of Systems Biology, College of Physicians & Surgeons, Columbia Unviersity, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  13. Shan Zha

    Institute for Cancer Genetics, Columbia University, New York, United States
    For correspondence
    sz2296@cumc.columbia.edu
    Competing interests
    The authors declare that no competing interests exist.

Ethics

Animal experimentation: All the animal work was approved by and performed according to the regulations of the Institutional Animal Care and Use Committee (IACUC) of Columbia University (protocol no AAAF7653, AAAD6250, AAAJ3651)

Copyright

© 2016, Yamamoto 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

  • 4,062
    views
  • 733
    downloads
  • 42
    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. Kenta Yamamoto
  2. Jiguang Wang
  3. Lisa Sprinzen
  4. Jun Xu
  5. Christopher J Haddock
  6. Chen Li
  7. Brian J Lee
  8. Denis G Loredan
  9. Wenxia Jiang
  10. Alessandro Vindigni
  11. Dong Wang
  12. Raul Rabadan
  13. Shan Zha
(2016)
Kinase-dead ATM protein is highly oncogenic and can be preferentially targeted by Topo-isomerase I inhibitors
eLife 5:e14709.
https://doi.org/10.7554/eLife.14709

Share this article

https://doi.org/10.7554/eLife.14709

Further reading

    1. Cancer Biology
    2. Immunology and Inflammation
    Sofia V Krasik, Ekaterina A Bryushkova ... Ekaterina O Serebrovskaya
    Research Article

    The current understanding of humoral immune response in cancer patients suggests that tumors may be infiltrated with diffuse B cells of extra-tumoral origin or may develop organized lymphoid structures, where somatic hypermutation and antigen-driven selection occur locally. These processes are believed to be significantly influenced by the tumor microenvironment through secretory factors and biased cell-cell interactions. To explore the manifestation of this influence, we used deep unbiased immunoglobulin profiling and systematically characterized the relationships between B cells in circulation, draining lymph nodes (draining LNs), and tumors in 14 patients with three human cancers. We demonstrated that draining LNs are differentially involved in the interaction with the tumor site, and that significant heterogeneity exists even between different parts of a single lymph node (LN). Next, we confirmed and elaborated upon previous observations regarding intratumoral immunoglobulin heterogeneity. We identified B cell receptor (BCR) clonotypes that were expanded in tumors relative to draining LNs and blood and observed that these tumor-expanded clonotypes were less hypermutated than non-expanded (ubiquitous) clonotypes. Furthermore, we observed a shift in the properties of complementarity-determining region 3 of the BCR heavy chain (CDR-H3) towards less mature and less specific BCR repertoire in tumor-infiltrating B-cells compared to circulating B-cells, which may indicate less stringent control for antibody-producing B cell development in tumor microenvironment (TME). In addition, we found repertoire-level evidence that B-cells may be selected according to their CDR-H3 physicochemical properties before they activate somatic hypermutation (SHM). Altogether, our work outlines a broad picture of the differences in the tumor BCR repertoire relative to non-tumor tissues and points to the unexpected features of the SHM process.

    1. Cancer Biology
    2. Computational and Systems Biology
    Rosalyn W Sayaman, Masaru Miyano ... Mark A LaBarge
    Research Article Updated

    Effects from aging in single cells are heterogenous, whereas at the organ- and tissue-levels aging phenotypes tend to appear as stereotypical changes. The mammary epithelium is a bilayer of two major phenotypically and functionally distinct cell lineages: luminal epithelial and myoepithelial cells. Mammary luminal epithelia exhibit substantial stereotypical changes with age that merit attention because these cells are the putative cells-of-origin for breast cancers. We hypothesize that effects from aging that impinge upon maintenance of lineage fidelity increase susceptibility to cancer initiation. We generated and analyzed transcriptomes from primary luminal epithelial and myoepithelial cells from younger <30 (y)ears old and older >55 y women. In addition to age-dependent directional changes in gene expression, we observed increased transcriptional variance with age that contributed to genome-wide loss of lineage fidelity. Age-dependent variant responses were common to both lineages, whereas directional changes were almost exclusively detected in luminal epithelia and involved altered regulation of chromatin and genome organizers such as SATB1. Epithelial expression variance of gap junction protein GJB6 increased with age, and modulation of GJB6 expression in heterochronous co-cultures revealed that it provided a communication conduit from myoepithelial cells that drove directional change in luminal cells. Age-dependent luminal transcriptomes comprised a prominent signal that could be detected in bulk tissue during aging and transition into cancers. A machine learning classifier based on luminal-specific aging distinguished normal from cancer tissue and was highly predictive of breast cancer subtype. We speculate that luminal epithelia are the ultimate site of integration of the variant responses to aging in their surrounding tissue, and that their emergent phenotype both endows cells with the ability to become cancer-cells-of-origin and represents a biosensor that presages cancer susceptibility.