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2.
Cancer Genet ; 264-265: 50-59, 2022 06.
Artigo em Inglês | MEDLINE | ID: mdl-35366592

RESUMO

Gene fusions involving the neurotrophic receptor tyrosine kinase genes NTRK1, NTRK2, and NTRK3, are well established oncogenic drivers in a broad range of pediatric and adult tumors. These fusions are also important actionable markers, predicting often dramatic response to FDA approved kinase inhibitors. Accurate interpretation of the clinical significance of NTRK fusions is a high priority for diagnostic laboratories, but remains challenging and time consuming given the rapid pace of new data accumulation, the diversity of fusion partners and tumor types, and heterogeneous and incomplete information in variant databases and knowledgebases. The ClinGen NTRK Fusions Somatic Cancer Variant Curation Expert Panel (SC-VCEP) was formed to systematically address these challenges and create an expert-curated resource to support clinicians, researchers, patients and their families in making accurate interpretations and informed treatment decisions for NTRK fusion-driven tumors. We describe a system for NTRK fusion interpretation (including compilation of key elements and annotations) developed by the NTRK fusions SC-VCEP. We illustrate this stepwise process on examples of LMNA::NTRK1 and KANK1::NTRK2 fusions. Finally, we provide detailed analysis of current representation of NTRK fusions in public fusion databases and the CIViC knowledgebase, performed by the NTRK fusions SC-VCEP to determine existing gaps and prioritize future curation activities.


Assuntos
Neoplasias , Receptor trkA , Proteínas Adaptadoras de Transdução de Sinal/genética , Proteínas Adaptadoras de Transdução de Sinal/uso terapêutico , Adulto , Biomarcadores Tumorais/genética , Carcinogênese , Criança , Proteínas do Citoesqueleto/genética , Proteínas do Citoesqueleto/uso terapêutico , Fusão Gênica , Humanos , Neoplasias/diagnóstico , Proteínas de Fusão Oncogênica/genética , Receptor trkA/genética , Receptor trkA/uso terapêutico
3.
J Am Med Inform Assoc ; 28(4): 677-684, 2021 03 18.
Artigo em Inglês | MEDLINE | ID: mdl-33447854

RESUMO

The development and implementation of clinical decision support (CDS) that trains itself and adapts its algorithms based on new data-here referred to as Adaptive CDS-present unique challenges and considerations. Although Adaptive CDS represents an expected progression from earlier work, the activities needed to appropriately manage and support the establishment and evolution of Adaptive CDS require new, coordinated initiatives and oversight that do not currently exist. In this AMIA position paper, the authors describe current and emerging challenges to the safe use of Adaptive CDS and lay out recommendations for the effective management and monitoring of Adaptive CDS.


Assuntos
Sistemas de Apoio a Decisões Clínicas/normas , Aprendizado de Máquina/normas , Informática Médica , Política Organizacional , Sociedades Médicas , Algoritmos , Inteligência Artificial , Atenção à Saúde , Política de Saúde , Humanos , Informática Médica/educação , Estados Unidos
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