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Detection of kinase domain mutations in BCR::ABL1 leukemia by ultra-deep sequencing of genomic DNA

Authors :
Ricardo Sánchez
Sara Dorado
Yanira Ruíz-Heredia
Alejandro Martín-Muñoz
Juan Manuel Rosa-Rosa
Jordi Ribera
Olga García
Ana Jimenez-Ubieto
Gonzalo Carreño-Tarragona
María Linares
Laura Rufián
Alexandra Juárez
Jaime Carrillo
María José Espino
Mercedes Cáceres
Sara Expósito
Beatriz Cuevas
Raúl Vanegas
Luis Felipe Casado
Anna Torrent
Lurdes Zamora
Santiago Mercadal
Rosa Coll
Marta Cervera
Mireia Morgades
José Ángel Hernández-Rivas
Pilar Bravo
Cristina Serí
Eduardo Anguita
Eva Barragán
Claudia Sargas
Francisca Ferrer-Marín
Jorge Sánchez-Calero
Julián Sevilla
Elena Ruíz
Lucía Villalón
María del Mar Herráez
Rosalía Riaza
Elena Magro
Juan Luis Steegman
Chongwu Wang
Paula de Toledo
Valentín García-Gutiérrez
Rosa Ayala
Josep-Maria Ribera
Santiago Barrio
Joaquín Martínez-López
Source :
Scientific Reports, Vol 12, Iss 1, Pp 1-11 (2022)
Publication Year :
2022
Publisher :
Nature Portfolio, 2022.

Abstract

Abstract The screening of the BCR::ABL1 kinase domain (KD) mutation has become a routine analysis in case of warning/failure for chronic myeloid leukemia (CML) and B-cell precursor acute lymphoblastic leukemia (ALL) Philadelphia (Ph)-positive patients. In this study, we present a novel DNA-based next-generation sequencing (NGS) methodology for KD ABL1 mutation detection and monitoring with a 1.0E−4 sensitivity. This approach was validated with a well-stablished RNA-based nested NGS method. The correlation of both techniques for the quantification of ABL1 mutations was high (Pearson r = 0.858, p

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
20452322
Volume :
12
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.900f483793a442ea9469078a704f59fa
Document Type :
article
Full Text :
https://doi.org/10.1038/s41598-022-17271-3