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Suppression of insulin feedback enhances the efficacy of PI3K inhibitors

Nature (2018) | Download Citation


Mutations in PIK3CA, encoding the insulin-activated phosphoinositide-3-kinase (PI3K), and loss of function mutations in PTEN, a phosphatase that degrades the phosphoinositide lipids generated by PI3K, are among the most frequent events in human cancers1,2. However, pharmacological inhibition of PI3K has resulted in variable clinical responses, raising the possibility of an inherent mechanism of resistance. Since the PIK3CA-encoded enzyme, p110α, mediates virtually all cellular responses to insulin, targeted inhibition of this enzyme disrupts glucose metabolism in multiple tissue types. For example, blocking insulin signalling promotes glycogen breakdown in the liver and prevents glucose uptake in the skeletal muscle and adipose tissue, resulting in transient hyperglycemia that occurs within a few hours of PI3K inhibition. The effect is usually transient because compensatory insulin release from the pancreas (i.e. insulin feedback) restores normal glucose homeostasis3. However, the hyperglycemia may be exacerbated or prolonged in patients with any degree of insulin resistance and, in these cases, requires discontinuation of therapy3–6. We hypothesized that insulin feedback induced by PI3K inhibitors may be reactivating the PI3K-mTOR signalling axis in tumours, compromising their effectiveness7,8. Here, we show in several model tumours, that systemic glucose-insulin feedback caused by targeted inhibition of this pathway is sufficient to activate PI3K signalling, even in the presence of PI3K inhibitors. We demonstrate that this insulin feedback can be prevented using dietary or pharmaceutical approaches, which greatly enhance the efficacy/toxicity ratios of these compounds. These findings have direct clinical implications for the multiple p110α inhibitors that are in clinical trials and provide a means to significantly increase treatment efficacy for patients with a myriad of tumour types.

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Author information


  1. Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA

    • Benjamin D. Hopkins
    • , Diana G. Wang
    • , David Wu
    • , Solomon C. Amadiume
    • , Marcus D. Goncalves
    • , Cindy Hodakoski
    • , Mark R. Lundquist
    • , Rohan Bareja
    • , Andrea Sboner
    • , Himisha Beltran
    •  & Lewis C. Cantley
  2. Institute of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland

    • Chantal Pauli
  3. Englander Institute for Precision Medicine, Weill Cornell Medicine-New York Presbyterian Hospital, New York, NY, USA

    • Chantal Pauli
    • , Rohan Bareja
    • , Andrea Sboner
    • , Himisha Beltran
    •  & Mark A. Rubin
  4. Department of Medicine, Division of Hematology and Oncology, Columbia University Medical Center and New York Presbyterian Hospital, New York, NY, USA

    • Xing Du
    • , Yan Ma
    • , Emily M. Harris
    •  & Siddhartha Mukherjee
  5. Weill Cornell Medicine/Rockefeller University/Sloan Kettering Tri-Institutional MD-PhD Program, New York, NY, USA

    • Diana G. Wang
  6. Weill Cornell Graduate School of Medical Sciences, New York, NY, USA

    • Xiang Li
  7. Division of Endocrinology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA

    • Marcus D. Goncalves
  8. Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, NY, USA

    • Himisha Beltran
  9. Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA

    • Rohan Bareja
    •  & Andrea Sboner
  10. Department of Pathology, Weill Cornell Medicine, New York, NY, USA

    • Andrea Sboner
  11. Department of Biomedical Research and the Center for Precision Medicine, University of Bern, and the Inselspital, Bern, Switzerland

    • Mark A. Rubin


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Corresponding authors

Correspondence to Siddhartha Mukherjee or Lewis C. Cantley.

Supplementary information

  1. Supplementary Figures

    This file contains Supplementary Figures 1-2, the uncropped blots.

  2. Reporting Summary

  3. Supplementary Tables

    This file contains Supplementary Tables 1-3. Supplementary Table 1 contains the nutritional content of normal and ketogenic diets used in these studies, Supplementary Table 2 contains the cell lines used and Supplementary Table 3 contains the targeted inhibitors used.

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