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Multimodal platform for assessing drug distribution and response in clinical trials.

Authors :
Lopez BGC
Kohale IN
Du Z
Korsunsky I
Abdelmoula WM
Dai Y
Stopka SA
Gaglia G
Randall EC
Regan MS
Basu SS
Clark AR
Marin BM
Mladek AC
Burgenske DM
Agar JN
Supko JG
Grossman SA
Nabors LB
Raychaudhuri S
Ligon KL
Wen PY
Alexander B
Lee EQ
Santagata S
Sarkaria J
White FM
Agar NYR
Source :
Neuro-oncology [Neuro Oncol] 2022 Jan 05; Vol. 24 (1), pp. 64-77.
Publication Year :
2022

Abstract

Background: Response to targeted therapy varies between patients for largely unknown reasons. Here, we developed and applied an integrative platform using mass spectrometry imaging (MSI), phosphoproteomics, and multiplexed tissue imaging for mapping drug distribution, target engagement, and adaptive response to gain insights into heterogeneous response to therapy.<br />Methods: Patient-derived xenograft (PDX) lines of glioblastoma were treated with adavosertib, a Wee1 inhibitor, and tissue drug distribution was measured with MALDI-MSI. Phosphoproteomics was measured in the same tumors to identify biomarkers of drug target engagement and cellular adaptive response. Multiplexed tissue imaging was performed on sister sections to evaluate spatial co-localization of drug and cellular response. The integrated platform was then applied on clinical specimens from glioblastoma patients enrolled in the phase 1 clinical trial.<br />Results: PDX tumors exposed to different doses of adavosertib revealed intra- and inter-tumoral heterogeneity of drug distribution and integration of the heterogeneous drug distribution with phosphoproteomics and multiplexed tissue imaging revealed new markers of molecular response to adavosertib. Analysis of paired clinical specimens from patients enrolled in the phase 1 clinical trial informed the translational potential of the identified biomarkers in studying patient's response to adavosertib.<br />Conclusions: The multimodal platform identified a signature of drug efficacy and patient-specific adaptive responses applicable to preclinical and clinical drug development. The information generated by the approach may inform mechanisms of success and failure in future early phase clinical trials, providing information for optimizing clinical trial design and guiding future application into clinical practice.<br /> (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Details

Language :
English
ISSN :
1523-5866
Volume :
24
Issue :
1
Database :
MEDLINE
Journal :
Neuro-oncology
Publication Type :
Academic Journal
Accession number :
34383057
Full Text :
https://doi.org/10.1093/neuonc/noab197