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Kinome rewiring reveals AURKA limits PI3K-pathway inhibitor efficacy in breast cancer

Nature Chemical Biology volume 14, pages 768–777 (2018)Cite this article

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Abstract

Dysregulation of the PI3K-AKT-mTOR signaling network is a prominent feature of breast cancers. However, clinical responses to drugs targeting this pathway have been modest, possibly because of dynamic changes in cellular signaling that drive resistance and limit drug efficacy. Using a quantitative chemoproteomics approach, we mapped kinome dynamics in response to inhibitors of this pathway and identified signaling changes that correlate with drug sensitivity. Maintenance of AURKA after drug treatment was associated with resistance in breast cancer models. Incomplete inhibition of AURKA was a common source of therapy failure, and combinations of PI3K, AKT or mTOR inhibitors with the AURKA inhibitor MLN8237 were highly synergistic and durably suppressed mTOR signaling, resulting in apoptosis and tumor regression in vivo. This signaling map identifies survival factors whose presence limits the efficacy of targeted therapies and reveals new drug combinations that may unlock the full potential of PI3K–AKT–mTOR pathway inhibitors in breast cancer.

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Fig. 1: Measurement of kinome dynamics to identify correlates of drug sensitivity.
Fig. 2: Maintenance of AURKA is associated with resistance to PI3K inhibition.
Fig. 3: AURKA suppression enhances sensitivity and drives cell death in response to PI3K-pathway inhibitors in breast cancer cell lines.
Fig. 4: The Aurora kinase inhibitor MLN8237 enhances sensitivity to everolimus (RAD001) and induces cell death in vivo.
Fig. 5: Aurora kinase co-inhibition durably suppresses mTORC1 signaling and alters the BAX/BCL2 ratio.
Fig. 6: AURKA transcription is regulated by MYC downstream of the PI3K pathway.

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Acknowledgements

The authors would like to thank members of the Bandyopadhyay laboratory for helpful discussions and technical assistance. We also thank A. Beardsley, E. Markegard, D. Ruggero and W. Weiss for helpful discussions and reagents. This work was supported in part by NCI U01CA168370 (S.B.), NIGMS R01GM107671 (S.B.), NCI R01CA170447 (A.G.), Prospect Creek Foundation (S.B., A.G.), OHSU Pilot Project Funding (S.B., J.K.), American Cancer Society Postdoctoral Fellowship (J.D.G.), the Gazarian Foundation (A.G.), DOD W81XWH-12-1-0272 and DOD W81XWH-16-1-0603 (A.G.).

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Authors and Affiliations

  1. Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA

    Hayley J. Donnella, James T. Webber, Khyati N. Shah & Sourav Bandyopadhyay

  2. Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA

    Rebecca S. Levin & Kevan M. Shokat

  3. Department of Medicine, University of California San Francisco, San Francisco, CA, USA

    Roman Camarda, Olga Momcilovic, Andrei Goga & John D. Gordan

  4. Center for Spatial Systems Biology, Oregon Health and Sciences University, Portland, OR, USA

    Nora Bayani & James E. Korkola

  5. Howard Hughes Medical Institute, University of California San Francisco, San Francisco, CA, USA

    Kevan M. Shokat

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Contributions

H.J.D., J.T.W., K.M.S, J.K., J.D.G., and S.B. contributed toward study conceptualization. H.J.D., J.T.W., and J.D.G. performed data analyses supporting the study. H.J.D. designed and performed the majority of experiments. N.B. assisted with samples for initial MIBs/MS profiling. R.S.L. J.T.W., and J.D.G. provided technical advice and guided the interpretation of mass spectrometry data from MIB/MS profiling. R.C. and O.M. assisted with animal studies, and K.N.S. helped with additional experiments. H.J.D. and S.B. composed the original draft, and all authors contributed to manuscript finalization. S.B. and A.G. supervised the study.

Corresponding authors

Correspondence to John D. Gordan or Sourav Bandyopadhyay.

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Supplementary Text and Figures

Supplementary Figures 1–19

Reporting Summary

Supplementary Dataset 1

Kinase activity scores and P values from MIBs/MS profiling.

Supplementary Dataset 2

Gene set enrichment analysis (GSEA) of BYL719-treated cells.

Supplementary Dataset 3

Receptor status, synergy scores (Loewe and Bliss) and assessment of increase in apoptosis over single-agent or combinations tested in this study.

Supplementary Dataset 4

MYC signature derived from isogenic MCF10A cell lines.

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Donnella, H.J., Webber, J.T., Levin, R.S. et al. Kinome rewiring reveals AURKA limits PI3K-pathway inhibitor efficacy in breast cancer. Nat Chem Biol 14, 768–777 (2018). https://doi.org/10.1038/s41589-018-0081-9

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