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

Research output: Contribution to journalJournal articleResearchpeer-review

  • Elizabeth C Randall
  • 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-Ke Lu
  • X Sunney Xie
  • Brian A Joughin
  • Raven J Reddy
  • Sen Peng
  • Walid M Abdelmoula
  • Pamela R Jackson
  • Aarti Kolluri
  • Katherine A Kellersberger
  • Jeffrey N Agar
  • Douglas A Lauffenburger
  • Kristin R Swanson
  • Nhan L Tran
  • William F Elmquist
  • Forest M White
  • Jann N Sarkaria
  • Nathalie Y R Agar

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.

Original languageEnglish
JournalNature Communications
Issue number1
Pages (from-to)4904
Publication statusPublished - 21 Nov 2018
Externally publishedYes

ID: 209323322