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Significance of KIT exon 17 mutation depends on mutant level rather than positivity in core-binding factor acute myeloid leukemia

  • W. Jang
  • , J. H. Yoon
  • , J. Park
  • , G. D. Lee
  • , J. Kim
  • , A. Kwon
  • , H. Choi
  • , K. Han
  • , C. H. Nahm
  • , H. J. Kim
  • , W. S. Min
  • , M. Kim*
  • , Y. Kim
  • *Corresponding author for this work
  • The Catholic University of Korea
  • Inha University

Research output: Contribution to journalJournal articlepeer-review

Abstract

KIT exon 17 mutation is a poor prognostic factor in core-binding factor acute myeloid leukemia. However, the mutation detection method used for risk assessment is not assigned. It is necessary to verify the analytical and clinical performance before applying new methods. Herein, we firstly applied a highly sensitive allele-specific, real-time quantitative PCR (AS-qPCR) assay to analyze KIT mutations, which demonstrated excellent sensitivity and specificity. Much higher incidence of KIT mutations (62.2%, 69/111) and prevalence of multiple mutations (43.5%, 30/69) were observed using AS-qPCR, which meant the existence of multiple KIT mutant subclones. The relative KIT mutant level was variable (median, 0.3 per control allele 100 copies, 0.002-532.7) and was divided into two groups: high (≤10, n=26) and low (<10) mutant level. Interestingly, rather than mutation positivity, mutant level was found to be associated with clinical outcome. High mutant level showed significantly inferior overall survival (P = 0.005) and event-free survival (P=0.03), whereas low level did not influence the prognosis. The follow-up data showed that the mutant level were along with fusion transcripts in the majority (n=29), but moved separately in some cases, including the loss of mutations (n=5) and selective proliferation of minor clones (n = 2) at relapse. This study highlighted that the KIT mutation should be analyzed using sensitive and quantitative techniques and set a cutoff level for identifying the risk group.

Original languageEnglish
Article numbere387
JournalBlood Cancer Journal
Volume6
Issue number1
DOIs
StatePublished - 2016

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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