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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2019
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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. |
format | Online Article Text |
id | pubmed-6589488 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
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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