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Testing algorithm for identification of patients with TRK fusion cancer

The neurotrophic tyrosine receptor kinase (NTRK) gene family encodes three tropomyosin receptor kinases (TRKA, TRKB, TRKC) that contribute to central and peripheral nervous system development and function. NTRK gene fusions are oncogenic drivers of various adult and paediatric tumours. Several metho...

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Autores principales: Penault-Llorca, Frédérique, Rudzinski, Erin R, Sepulveda, Antonia R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6589488/
https://www.ncbi.nlm.nih.gov/pubmed/31072837
http://dx.doi.org/10.1136/jclinpath-2018-205679
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author Penault-Llorca, Frédérique
Rudzinski, Erin R
Sepulveda, Antonia R
author_facet Penault-Llorca, Frédérique
Rudzinski, Erin R
Sepulveda, Antonia R
author_sort Penault-Llorca, Frédérique
collection PubMed
description The neurotrophic tyrosine receptor kinase (NTRK) gene family encodes three tropomyosin receptor kinases (TRKA, TRKB, TRKC) that contribute to central and peripheral nervous system development and function. NTRK gene fusions are oncogenic drivers of various adult and paediatric tumours. Several methods have been used to detect NTRK gene fusions including immunohistochemistry, fluorescence in situ hybridisation, reverse transcriptase polymerase chain reaction, and DNA- or RNA-based next-generation sequencing. For patients with TRK fusion cancer, TRK inhibition is an important therapeutic target. Following the FDA approval of the selective TRK inhibitor, larotrectinib, as well as the ongoing development of multi-kinase inhibitors with activity in TRK fusion cancer, testing for NTRK gene fusions should become part of the standard diagnostic process. In this review we discuss the biology of NTRK gene fusions, and we present a testing algorithm to aid detection of these gene fusions in clinical practice and guide treatment decisions.
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spelling pubmed-65894882019-07-11 Testing algorithm for identification of patients with TRK fusion cancer Penault-Llorca, Frédérique Rudzinski, Erin R Sepulveda, Antonia R J Clin Pathol Best Practice The neurotrophic tyrosine receptor kinase (NTRK) gene family encodes three tropomyosin receptor kinases (TRKA, TRKB, TRKC) that contribute to central and peripheral nervous system development and function. NTRK gene fusions are oncogenic drivers of various adult and paediatric tumours. Several methods have been used to detect NTRK gene fusions including immunohistochemistry, fluorescence in situ hybridisation, reverse transcriptase polymerase chain reaction, and DNA- or RNA-based next-generation sequencing. For patients with TRK fusion cancer, TRK inhibition is an important therapeutic target. Following the FDA approval of the selective TRK inhibitor, larotrectinib, as well as the ongoing development of multi-kinase inhibitors with activity in TRK fusion cancer, testing for NTRK gene fusions should become part of the standard diagnostic process. In this review we discuss the biology of NTRK gene fusions, and we present a testing algorithm to aid detection of these gene fusions in clinical practice and guide treatment decisions. BMJ Publishing Group 2019-07 2019-05-09 /pmc/articles/PMC6589488/ /pubmed/31072837 http://dx.doi.org/10.1136/jclinpath-2018-205679 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Best Practice
Penault-Llorca, Frédérique
Rudzinski, Erin R
Sepulveda, Antonia R
Testing algorithm for identification of patients with TRK fusion cancer
title Testing algorithm for identification of patients with TRK fusion cancer
title_full Testing algorithm for identification of patients with TRK fusion cancer
title_fullStr Testing algorithm for identification of patients with TRK fusion cancer
title_full_unstemmed Testing algorithm for identification of patients with TRK fusion cancer
title_short Testing algorithm for identification of patients with TRK fusion cancer
title_sort testing algorithm for identification of patients with trk fusion cancer
topic Best Practice
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6589488/
https://www.ncbi.nlm.nih.gov/pubmed/31072837
http://dx.doi.org/10.1136/jclinpath-2018-205679
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