Literature DB >> 29235051

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

Joseph R Linzey1, Bernard L Marini2, Amy Pasternak2, Cory Smith2, Zac Miklja1, Lili Zhao3, Chandan Kumar-Sinha4, Alyssa Paul1, Nicholas Harris1, Patricia L Robertson5, Lindsey M Hoffman6, Arul Chinnaiyan7, Rajen Mody1, Carl Koschmann8.   

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.

Entities:  

Keywords:  Algorithm; Neuro-oncology; Precision medicine; Targeted therapy

Mesh:

Substances:

Year:  2017        PMID: 29235051      PMCID: PMC5823756          DOI: 10.1007/s11060-017-2708-1

Source DB:  PubMed          Journal:  J Neurooncol        ISSN: 0167-594X            Impact factor:   4.130


  29 in total

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