编辑: 麒麟兔爷 | 2019-10-17 |
Ling1 , Geoffrey R. Hill1,2,3 , Steven W. Lane1,2,3
1 QIMR Berghofer Medical Research Institute, Herston, QLD, Australia;
2 School of Medicine, University of Queensland, Brisbane, QLD, Australia;
Department of Haematology,
3 Royal Brisbane and Women's Hospital, Brisbane, QLD, Australia Corresponding author: Steven W. Lane, Translational Leukaemia Research Laboratory, QIMR Berghofer Medical Research Institute, Herston Road, Herston, Queensland, 4006, Australia;
email: [email protected];
phone: +617
3845 3962;
fax: +617
3845 3032. Scientific category: Myeloid neoplasia Word count (text):
1417 words Figures:
2 Tables:
0 References:
22 Blood First Edition Paper, prepublished online November 28, 2017;
DOI 10.1182/blood-2017-09-807438 Copyright ?
2017 American Society of Hematology For personal use only. on November 28, 2017. by guest www.bloodjournal.org From
2 Acute myeloid leukemia (AML) is a heterogeneous disease, within which genetic profiles dictate clinical outcomes. Cytogenetic and molecular profiling in AML are mandatory diagnostic and prognostic requirements, yet interpretation of these results is becoming increasingly complex. Next generation sequencing (NGS) technologies have enabled comprehensive characterization of the genomic landscape of AML revealing complex patterns of clonal evolution during development and treatment.1,2 The datasets generated represent invaluable resources to interrogate the genomic information from large patient cohorts and identify clinically relevant molecular biomarkers of disease initiation, progression and response to treatment.3,4 The
2017 update of the European LeukemiaNet recommendations on genetic risk stratification (ELN 2017) provides a comprehensive genomic classification and prognostication schema, updating the
2010 recommendations (ELN 2010).5 A key change in ELN
2017 has been to re-classify Nucleophosmin
1 mutant (NPM1mut ) AML with low allelic ratio FLT3ITD (FLT3ITD -L;
AR