Development of the CNS TAP tool for the selection of precision medicine therapies in neuro-oncology

Development of the CNS TAP tool for the selection of precision medicine therapies in neuro-oncology The number of targeted therapies utilized in precision medicine are rapidly increasing. Neuro-oncology offers a unique challenge due to the varying blood brain barrier (BBB) penetration of each agent. Neuro-oncologists face a difficult task weighing the growing number of potential targeted therapies and their likelihood of BBB penetration. We developed the CNS TAP Working Group and performed an extensive literature review for the evidence-based creation of the CNS TAP tool, which was retrospectively validated by analyzing brain tumor patients who underwent therapy targeted based on genomic results from an academic sequencing study (MiOncoseq, n = 17) or private molecular profiling (Foundation One, n = 7). The CNS TAP tool scores relevant targeted agents by applying multiple variables (i.e., pre-clinical data, clinical data, BBB permeability) to patient specific genomic information and clinical trial availability. In the Michigan cohort, the CNS TAP tool predicted the selected agent 85.7% of the time. The CNS TAP tool predicted the agent independently selected by pediatric neuro-oncologists in the Colorado cohort 50% of the time. Patients with recurrent brain tumors treated with agents predicted by the CNS TAP tool demonstrated a median progression-free survival of 4 months and four patients with recurrent high-grade glioma maintained ongoing partial responses of at least 6 months. The CNS TAP tool is a formalized algorithm to assist clinicians select the optimal targeted therapy for neuro-oncology patients. The CNS TAP tool has relatively high concordance with selected therapies and clinical outcomes in patients receiving targeted therapy in this heterogeneous retrospective cohort were promising. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Neuro-Oncology Springer Journals
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Publisher
Springer US
Copyright
Copyright © 2017 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Medicine & Public Health; Oncology; Neurology
ISSN
0167-594X
eISSN
1573-7373
D.O.I.
10.1007/s11060-017-2708-1
Publisher site
See Article on Publisher Site

Abstract

The number of targeted therapies utilized in precision medicine are rapidly increasing. Neuro-oncology offers a unique challenge due to the varying blood brain barrier (BBB) penetration of each agent. Neuro-oncologists face a difficult task weighing the growing number of potential targeted therapies and their likelihood of BBB penetration. We developed the CNS TAP Working Group and performed an extensive literature review for the evidence-based creation of the CNS TAP tool, which was retrospectively validated by analyzing brain tumor patients who underwent therapy targeted based on genomic results from an academic sequencing study (MiOncoseq, n = 17) or private molecular profiling (Foundation One, n = 7). The CNS TAP tool scores relevant targeted agents by applying multiple variables (i.e., pre-clinical data, clinical data, BBB permeability) to patient specific genomic information and clinical trial availability. In the Michigan cohort, the CNS TAP tool predicted the selected agent 85.7% of the time. The CNS TAP tool predicted the agent independently selected by pediatric neuro-oncologists in the Colorado cohort 50% of the time. Patients with recurrent brain tumors treated with agents predicted by the CNS TAP tool demonstrated a median progression-free survival of 4 months and four patients with recurrent high-grade glioma maintained ongoing partial responses of at least 6 months. The CNS TAP tool is a formalized algorithm to assist clinicians select the optimal targeted therapy for neuro-oncology patients. The CNS TAP tool has relatively high concordance with selected therapies and clinical outcomes in patients receiving targeted therapy in this heterogeneous retrospective cohort were promising.

Journal

Journal of Neuro-OncologySpringer Journals

Published: Dec 12, 2017

References

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