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  • Title: Next-generation deep sequencing improves detection of BCR-ABL1 kinase domain mutations emerging under tyrosine kinase inhibitor treatment of chronic myeloid leukemia patients in chronic phase.
    Author: Machova Polakova K, Kulvait V, Benesova A, Linhartova J, Klamova H, Jaruskova M, de Benedittis C, Haferlach T, Baccarani M, Martinelli G, Stopka T, Ernst T, Hochhaus A, Kohlmann A, Soverini S.
    Journal: J Cancer Res Clin Oncol; 2015 May; 141(5):887-99. PubMed ID: 25367136.
    Abstract:
    PURPOSE: Here, we studied whether amplicon next-generation deep sequencing (NGS) could improve the detection of emerging BCR-ABL1 kinase domain mutations in chronic phase chronic myeloid leukemia (CML) patients under tyrosine kinase inhibitor (TKI) treatment and discussed the clinical relevance of such sensitive mutational detection. METHODS: For NGS data evaluation including extraction of biologically relevant low-level variants from background error noise, we established and applied a robust and versatile bioinformatics approach. RESULTS: Results from a retrospective longitudinal analysis of 135 samples of 15 CML patients showed that NGS could have revealed emerging resistant mutants 2-11 months earlier than conventional sequencing. Interestingly, in cases who later failed first-line imatinib treatment, NGS revealed that TKI-resistant mutations were already detectable at the time of major or deeper molecular response. Identification of emerging mutations by NGS was mirrored by BCR-ABL1 transcript level expressed either fluctuations around 0.1 %(IS) or by slight transcript level increase. NGS also allowed tracing mutations that emerged during second-line TKI therapy back to the time of switchover. Compound mutants could be detected in three cases, but were not found to outcompete single mutants. CONCLUSIONS: This work points out, that next-generation deep sequencing, coupled with a robust bioinformatics approach for mutation calling, may be just in place to ensure reliable detection of emerging BCR-ABL1 mutations, allowing early therapy switch and selection of the most appropriate therapy. Further, prospective assessment of how to best integrate NGS in the molecular monitoring and clinical decision algorithms is warranted.
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