FLT3 internal tandem duplications (ITDs) are found in approximately one third of patients with acute myeloid leukemia (AML) and have important prognostic and therapeutic implications that have supported its assessment in routine clinical practice. Conventional methods for assessing FLT3-ITD status and allele burden have been primarily limited to PCR fragment size analysis due to the inherent difficulty in detecting large ITD variants by next-generation sequencing (NGS). In this study, we assess the performance of publicly available bioinformatic tools for the detection and quantification of FLT3-ITDs in clinical hybridization-capture NGS data. We found that FLT3_ITD_ext had the highest overall accuracy for detecting FLT3-ITDs and was able to accurately quantify allele burden. Although all other tools evaluated were able to detect FLT3-ITDs reasonably well, allele burden was consistently underestimated. We were able to significantly improve quantification of FLT3-ITD allelic burden independent of the detection method by utilizing soft-clipped reads and/or ITD junctional sequences. In addition, we show that identifying mutant reads by previously identified junctional sequences further improves the sensitivity of detecting FLT3-ITDs in post-treatment samples. Our results demonstrate that FLT3-ITDs can be reliably detected in clinical NGS data using available bioinformatic tools. We further describe how accurate quantification of FLT3-ITD allele burden can be added on to existing clinical NGS pipelines for routine assessment of FLT3-ITD status in patients with AML.
Copyright © 2021. Published by Elsevier Inc.