Synergistic interactions with PI3K inhibition that induce apoptosis

  1. Yaara Zwang
  2. Oliver Jonas
  3. Casandra Chen
  4. Mikael L Rinne
  5. John G Doench
  6. Federica Piccioni
  7. Li Tan
  8. Hai-Tsang Huang
  9. Jinhua Wang
  10. Young Jin Ham
  11. Joyce O'Connell
  12. Patrick Bhola
  13. Mihir Doshi
  14. Matthew Whitman
  15. Michael Cima
  16. Anthony Letai
  17. David E Root
  18. Robert S Langer
  19. Nathanael S Gray
  20. William C Hahn  Is a corresponding author
  1. Broad Institute of Massachusetts Institute of Technology and Harvard, United States
  2. Massachusetts Institute of Technology, United States
  3. Dana Farber Cancer Institute, United States
  4. Dana-Farber Cancer Institute, United States

Abstract

Activating mutations involving the PI3K pathway occur frequently in human cancers. However, PI3K inhibitors primarily induce cell cycle arrest, leaving a significant reservoir of tumor cells that may acquire or exhibit resistance. We searched for genes that are required for the survival of PI3K mutant cancer cells in the presence of PI3K inhibition by conducting a genome scale shRNA-based apoptosis screen in a PIK3CA mutant human breast cancer cell. We identified 5 genes (PIM2, ZAK, TACC1, ZFR, ZNF565) whose suppression induced cell death upon PI3K inhibition. We showed that small molecule inhibitors of the PIM2 and ZAK kinases synergize with PI3K inhibition. In addition, using a microscale implementable device to deliver either siRNAs or small molecule inhibitors in vivo, we showed that suppressing these 5 genes with PI3K inhibition induced tumor regression. These observations identify targets whose inhibition synergizes with PI3K inhibitors and nominate potential combination therapies involving PI3K inhibition.

Article and author information

Author details

  1. Yaara Zwang

    Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, United States
    Competing interests
    No competing interests declared.
  2. Oliver Jonas

    The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
  3. Casandra Chen

    Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, United States
    Competing interests
    No competing interests declared.
  4. Mikael L Rinne

    Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, United States
    Competing interests
    No competing interests declared.
  5. John G Doench

    Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, United States
    Competing interests
    No competing interests declared.
  6. Federica Piccioni

    Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, United States
    Competing interests
    No competing interests declared.
  7. Li Tan

    Department of Cancer Biology, Dana Farber Cancer Institute, Boston, United States
    Competing interests
    No competing interests declared.
  8. Hai-Tsang Huang

    Department of Cancer Biology, Dana Farber Cancer Institute, Boston, United States
    Competing interests
    No competing interests declared.
  9. Jinhua Wang

    Department of Cancer Biology, Dana Farber Cancer Institute, Boston, United States
    Competing interests
    No competing interests declared.
  10. Young Jin Ham

    Department of Cancer Biology, Dana Farber Cancer Institute, Boston, United States
    Competing interests
    No competing interests declared.
  11. Joyce O'Connell

    Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, United States
    Competing interests
    No competing interests declared.
  12. Patrick Bhola

    Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, United States
    Competing interests
    No competing interests declared.
  13. Mihir Doshi

    Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, United States
    Competing interests
    No competing interests declared.
  14. Matthew Whitman

    The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
  15. Michael Cima

    The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
  16. Anthony Letai

    Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, United States
    Competing interests
    No competing interests declared.
  17. David E Root

    Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, United States
    Competing interests
    No competing interests declared.
  18. Robert S Langer

    The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
  19. Nathanael S Gray

    Department of Cancer Biology, Dana Farber Cancer Institute, Boston, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5354-7403
  20. William C Hahn

    Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, United States
    For correspondence
    william_hahn@dfci.harvard.edu
    Competing interests
    William C Hahn, Consultant for Novartis.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2840-9791

Funding

Congressionally Directed Medical Research Programs (W81XWH-12-1-0115)

  • Yaara Zwang

National Institutes of Health (U01 CA176058)

  • William C Hahn

National Cancer Institute (R21-CA177391)

  • Oliver Jonas

National Institutes of Health (R01 CA130988)

  • William C Hahn

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

Ethics

Animal experimentation: Animals were maintained under conditions approved by the Institutional Animal Care and Use Committee at the Dana-Farber Cancer Institute (IACUC protocol #04-101) and at the Massachusetts Institute of Technology (IACUC protocol #0412-038-15).

Copyright

© 2017, Zwang 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

  • 2,757
    views
  • 535
    downloads
  • 22
    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. Yaara Zwang
  2. Oliver Jonas
  3. Casandra Chen
  4. Mikael L Rinne
  5. John G Doench
  6. Federica Piccioni
  7. Li Tan
  8. Hai-Tsang Huang
  9. Jinhua Wang
  10. Young Jin Ham
  11. Joyce O'Connell
  12. Patrick Bhola
  13. Mihir Doshi
  14. Matthew Whitman
  15. Michael Cima
  16. Anthony Letai
  17. David E Root
  18. Robert S Langer
  19. Nathanael S Gray
  20. William C Hahn
(2017)
Synergistic interactions with PI3K inhibition that induce apoptosis
eLife 6:e24523.
https://doi.org/10.7554/eLife.24523

Share this article

https://doi.org/10.7554/eLife.24523

Further reading

    1. Cancer Biology
    Zhenhui Chen, Lu Yu ... Yi Ding
    Research Article

    The prevalence and mortality rates of colorectal cancer (CRC) are increasing worldwide. Radiation resistance hinders radiotherapy, a standard treatment for advanced CRC, leading to local recurrence and metastasis. Elucidating the molecular mechanisms underlying radioresistance in CRC is critical to enhance therapeutic efficacy and patient outcomes. Bioinformatic analysis and tumour tissue examination were conducted to investigate the CPT1A mRNA and protein levels in CRC and their correlation with radiotherapy efficacy. Furthermore, lentiviral overexpression and CRISPR/Cas9 lentiviral vectors, along with in vitro and in vivo radiation experiments, were used to explore the effect of CPT1A on radiosensitivity. Additionally, transcriptomic sequencing, molecular biology experiments, and bioinformatic analyses were employed to elucidate the molecular mechanisms by which CPT1A regulates radiosensitivity. CPT1A was significantly downregulated in CRC and negatively correlated with responsiveness to neoadjuvant radiotherapy. Functional studies suggested that CPT1A mediates radiosensitivity, influencing reactive oxygen species (ROS) scavenging and DNA damage response. Transcriptomic and molecular analyses highlighted the involvement of the peroxisomal pathway. Mechanistic exploration revealed that CPT1A downregulates the FOXM1-SOD1/SOD2/CAT axis, moderating cellular ROS levels after irradiation and enhancing radiosensitivity. CPT1A downregulation contributes to radioresistance in CRC by augmenting the FOXM1-mediated antioxidant response. Thus, CPT1A is a potential biomarker of radiosensitivity and a novel target for overcoming radioresistance, offering a future direction to enhance CRC radiotherapy.

    1. Cancer Biology
    2. Evolutionary Biology
    Arman Angaji, Michel Owusu ... Johannes Berg
    Research Article

    In growing cell populations such as tumours, mutations can serve as markers that allow tracking the past evolution from current samples. The genomic analyses of bulk samples and samples from multiple regions have shed light on the evolutionary forces acting on tumours. However, little is known empirically on the spatio-temporal dynamics of tumour evolution. Here, we leverage published data from resected hepatocellular carcinomas, each with several hundred samples taken in two and three dimensions. Using spatial metrics of evolution, we find that tumour cells grow predominantly uniformly within the tumour volume instead of at the surface. We determine how mutations and cells are dispersed throughout the tumour and how cell death contributes to the overall tumour growth. Our methods shed light on the early evolution of tumours in vivo and can be applied to high-resolution data in the emerging field of spatial biology.