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Ferrata Storti Foundation
Haematologica 2019 Volume 104(5):868-871
Next-generation sequencing in the diagnosis and minimal residual disease assessment
of acute myeloid leukemia
Ross L. Levine and Peter J.M. Valk
1Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA and 2Department of Hematology, Erasmus University Medical Center, Rotterdam, the Netherlands
Introduction
Risk-stratification of acute myeloid leukemia (AML) based on recurrent somatic abnormalities has evolved substantially in recent years, as illustrated by the cur- rent 2017 European LeukemiaNet (ELN) risk stratification.1 These 2017 ELN AML risk stratification recommendations are based on (cyto)genetic aberrations, includ- ing hotspot mutations such as those in NPM1, but also small insertions, deletions and point mutations that occur throughout TP53, RUNX1 and ASXL1, the latter being associated with adverse outcome.1 Next-generation sequencing (NGS) enables reliable detection of patient-specific mutations covering complete genes in molecularly heterogeneous diseases such as AML. NGS should, therefore, be incorporated in the routine work-up of preferably bone marrow specimens for accurate risk stratification in AML. Since risk assessment according to 2017 ELN recommendations only requires knowledge of the status of a handful of well- known driver mutations,1 targeted NGS, easily reaching a sensitivity of 1-2%, is currently the most appropriate and cost-effective approach for routine testing in AML. Targeted NGS using a variety of gene panels has been successfully intro- duced in routine clinical laboratories; however, several challenges remain.
Gene panels
A number of commercially available gene panels focusing on genes frequently mutated in myeloid malignancies have been introduced, e.g., the Illumina TruSight Myeloid panel, the Archer VariantPlex Core Myeloid panel, the Human Myeloid Neoplasms QIASeq DNA Panel and the AmpliSeq for Illumina Myeloid panel among many others. As expected, these panels contain all genes relevant for the 2017 ELN classification and show an enormous overlap in additional mutational hotspots and complete coverage of genes frequently mutated in myeloid diseases. In addition to these commercial panels, gene panels can be easily configured to meet local requirements. For instance, if AML patients are classified locally accord- ing to 2017 ELN, only NPM1, CEBPA, FLT3, RUNX1, ASXL1, and TP53 need to be included in a small and cost-effective gene panel. These types of NGS-based assays are now emerging.2 Importantly, both commercial NGS-based assays and those developed in-house as well as downstream analyses should be thoroughly validat- ed locally before implementation in daily practice can be considered.
Some genes are particularly difficult to sequence with NGS using gene panels. Bi-allelic mutations in CEBPA characteristically confer a favorable outcome in patients with AML.1 CEBPA is a GC-rich gene which is notoriously difficult to amplify by polymerase chain reaction (PCR) and sequence, and should be given special attention when incorporated in a gene panel. Although some commercial NGS gene panel protocols do now successfully include this single exon gene, other NGS approaches, such as capture-based NGS or custom panels for CEBPA mutation detection could be considered. FLT3 internal tandem duplications (ITD) can be reliably determined by fragment-length PCR following standardized pro- tocols;3 however, the size of the FLT3 ITD and the duplication itself make it chal- lenging to sequence the variably-sized amplicons appropriately by NGS and sub- sequently to analyze the FLT3 ITD by sequence alignment to reference sequences. Moreover, the 2017 ELN recommendations require assessment of the size of the FLT3 ITD clone.1 NPM1-mutant AML cases with high FLT3 ITD/FLT3 wildtype ratios (>0.5) are considered at intermediate risk, whereas NPM1 wildtype AML cases with high FLT3 ITD/FLT3 wildtype ratios are seen as adverse. Standardized NGS-based protocols need to be developed not only for the detection of FLT3 ITD, but also for the quantification of FLT3 ITD/FLT3 wildtype ratios. Examples
Correspondence:
ROSS L. LEVINE
leviner@mskcc.org
PETER J.M. VALK
p.valk@erasmusmc.nl
Received: February 1, 2019. Accepted: February 14, 2019. Pre-published: March 28, 2019.
doi:10.3324/haematol.2018.205955
Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/104/5/868
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