Abstract
FLT3 internal tandem duplications (ITDs) are found in approximately one-third of patients with acute myeloid leukemia and have important prognostic and therapeutic implications that have supported their assessment in routine clinical practice. Conventional methods for assessing FLT3-ITD status and allele burden have been primarily limited to PCR fragment size analysis because of 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 acute myeloid leukemia.