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Quantitative fragment analysis of FLT3-ITD efficiently identifying poor prognostic group with high mutant allele burden or long ITD length

  • Y. Kim
  • , G. D. Lee
  • , J. Park
  • , J. H. Yoon
  • , H. J. Kim
  • , W. S. Min
  • , M. Kim*
  • *Corresponding author for this work
  • The Catholic University of Korea

Research output: Contribution to journalJournal articlepeer-review

Abstract

Mutation of the fms-like tyrosine kinase 3-internal tandem duplication (FLT3-ITD), which is one of the most frequent genetic alterations, strongly contributes to an increased risk of treatment failure and to poor prognosis. In this study, we established quantitative fragment analysis of FLT3-ITD simultaneously measuring mutant allele burden and length, verified the analytical performance and evaluated the clinical significance in adult acute myeloid leukemia (AML) patients. FLT3-ITD was detected in 73 of 363 adult AML patients (20.1%) and high mutant allelic burden ((≥50%, n = 13) and long ITD length (≥70 base pairs, n = 15) were significantly associated with inferior overall survival (OS; P = 0.002 and 0.005, respectively) and event-free survival (EFS; P = 0.004 and 0.007, respectively). FLT3-ITD poor prognostic group was identified as patients with high allele burden or long ITD length (n = 24), which revealed significant adverse clinical outcome for both OS (P < 0.001) and EFS (P < 0.001). In cytogenetically normal AML, even FLT3-ITD low allele burden and short length was associated with poorer OS (P = 0.037) and EFS (P = 0.044) than wild type, whose influence was overcome when hematopoietic stem cell transplantation was performed. In minimal residual disease monitoring, FLT3-ITD negativity after consolidation therapy was a valuable predictor of better OS (P < 0.001) and EFS (P < 0.001). FLT3-ITD poor prognostic group with high mutant allele burden or long ITD length is efficiently identified by quantitative fragment analysis.

Original languageEnglish
Article numbere336
JournalBlood Cancer Journal
Volume5
Issue number8
DOIs
StatePublished - 2015.08.14

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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