Determining the rise in BCR-ABL RNA that optimally predicts a kinase domain mutation in patients with chronic myeloid leukemia on imatinib

Richard Press, Stephanie G. Willis, Jennifer Laudadio, Michael J. Mauro, Michael W N Deininger

Research output: Contribution to journalArticle

60 Scopus citations

Abstract

In imatinib-treated chronic myeloid leukemia (CML), secondary drug resistance is often caused by mutations in the BCR-ABL kinase domain (KD). As alternative therapies are available for imatinib resistance, early identification of mutations may prevent disease progression. Because most patients are routinely monitored by BCR-ABL quantitative polymerase chain reaction (PCR), it is important to define the optimal increase in BCR-ABL that should trigger mutation testing. Expert panels have provisionally recommended a 10-fold BCR-ABL increase as the trigger for mutation screening, acknowledging the lack of consensus. To address this question, we monitored 150 CML patients by quantitative PCR and DNA sequencing. Thirty-five different mutations were identified in 53 patients, and, during 22.5 months (median) of follow-up after sequencing, mutations were significantly predictive of shorter progression-free survival. An unbiased receiver operating characteristic analysis identified a 2.6-fold increase in BCR-ABL RNA as the optimal cutoff for predicting a concomitant KD mutation, with a sensitivity of 77% (94% if including subsequent samples). The 2.6-fold threshold approximated the analytic precision limit of our PCR assay. In contrast, transcript rise cutoffs of 5-fold or greater had poor diagnostic sensitivity and no significant association with mutations. We conclude that the currently recommended 10-fold threshold to trigger mutation screening is insensitive and not universally applicable.

Original languageEnglish (US)
Pages (from-to)2598-2605
Number of pages8
JournalBlood
Volume114
Issue number13
DOIs
Publication statusPublished - 2009

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ASJC Scopus subject areas

  • Hematology
  • Biochemistry
  • Cell Biology
  • Immunology

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