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Integrated mapping of pharmacokinetics and pharmacodynamics in a patient-derived xenograft model of glioblastoma

Author

Listed:
  • Elizabeth C. Randall

    (Harvard Medical School)

  • Kristina B. Emdal

    (Massachusetts Institute of Technology)

  • Janice K. Laramy

    (University of Minnesota)

  • Minjee Kim

    (University of Minnesota)

  • Alison Roos

    (Mayo Clinic)

  • David Calligaris

    (Harvard Medical School)

  • Michael S. Regan

    (Harvard Medical School)

  • Shiv K. Gupta

    (Mayo Clinic)

  • Ann C. Mladek

    (Mayo Clinic)

  • Brett L. Carlson

    (Mayo Clinic)

  • Aaron J. Johnson

    (Mayo Clinic)

  • Fa-Ke Lu

    (Harvard Medical School
    Harvard University
    State University of New York)

  • X. Sunney Xie

    (Harvard University)

  • Brian A. Joughin

    (Massachusetts Institute of Technology)

  • Raven J. Reddy

    (Massachusetts Institute of Technology)

  • Sen Peng

    (Translational Genomics Research Institute)

  • Walid M. Abdelmoula

    (Harvard Medical School)

  • Pamela R. Jackson

    (Mayo Clinic)

  • Aarti Kolluri

    (Mayo Clinic)

  • Katherine A. Kellersberger

    (Bruker Daltonics)

  • Jeffrey N. Agar

    (Northeastern University)

  • Douglas A. Lauffenburger

    (Massachusetts Institute of Technology)

  • Kristin R. Swanson

    (Mayo Clinic)

  • Nhan L. Tran

    (Mayo Clinic)

  • William F. Elmquist

    (University of Minnesota)

  • Forest M. White

    (Massachusetts Institute of Technology)

  • Jann N. Sarkaria

    (Mayo Clinic)

  • Nathalie Y. R. Agar

    (Harvard Medical School
    Harvard Medical School
    Dana-Farber Cancer Institute, Harvard Medical School)

Abstract

Therapeutic options for the treatment of glioblastoma remain inadequate despite concerted research efforts in drug development. Therapeutic failure can result from poor permeability of the blood-brain barrier, heterogeneous drug distribution, and development of resistance. Elucidation of relationships among such parameters could enable the development of predictive models of drug response in patients and inform drug development. Complementary analyses were applied to a glioblastoma patient-derived xenograft model in order to quantitatively map distribution and resulting cellular response to the EGFR inhibitor erlotinib. Mass spectrometry images of erlotinib were registered to histology and magnetic resonance images in order to correlate drug distribution with tumor characteristics. Phosphoproteomics and immunohistochemistry were used to assess protein signaling in response to drug, and integrated with transcriptional response using mRNA sequencing. This comprehensive dataset provides simultaneous insight into pharmacokinetics and pharmacodynamics and indicates that erlotinib delivery to intracranial tumors is insufficient to inhibit EGFR tyrosine kinase signaling.

Suggested Citation

  • Elizabeth C. Randall & Kristina B. Emdal & Janice K. Laramy & Minjee Kim & Alison Roos & David Calligaris & Michael S. Regan & Shiv K. Gupta & Ann C. Mladek & Brett L. Carlson & Aaron J. Johnson & Fa-, 2018. "Integrated mapping of pharmacokinetics and pharmacodynamics in a patient-derived xenograft model of glioblastoma," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-07334-3
    DOI: 10.1038/s41467-018-07334-3
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