PURPOSE: BCR-ABL1 mutation analysis is recommended to facilitate selection of appropriate therapy for patients with chronic myeloid leukemia after treatment with imatinib has failed, since some frequently occurring mutations confer clinical resistance to nilotinib and/or dasatinib. However, mutations could be present below the detection limit of conventional direct sequencing. We developed a sensitive, multiplexed mass spectrometry assay (detection limit, 0.05% to 0.5%) to determine the impact of low-level mutations after imatinib treatment has failed. PATIENTS AND METHODS: Mutation status was assessed in 220 patients treated with nilotinib or dasatinib after they experienced resistance to imatinib. RESULTS: Mutations were detected by sequencing in 128 patients before commencing nilotinib or dasatinib therapy (switchover). In 64 patients, 132 additional low-level mutations were detected by mass spectrometry alone (50 of 132 mutations were resistant to nilotinib and/or dasatinib). When patients received the inhibitor for which the mutation confers resistance, 84% of the low-level resistant mutations rapidly became dominant clones detectable by sequencing, including 11 of 12 T315I mutations. Subsequent complete cytogenetic response rates were lower for patients with resistant mutations at switchover detected by sequencing (0%) or mass spectrometry alone (16%) compared with patients with other mutations or no mutations (41% and 49%, respectively; P < .001). Failure-free survival among the 100 patients with chronic phase chronic myeloid leukemia when resistant mutations were detected at switchover by sequencing or mass spectrometry alone was 0% and 0% compared with 51% and 45% for patients with other mutations or no mutations (P = .003). CONCLUSION: Detection of low-level mutations after imatinib resistance offers critical information to guide subsequent therapy selection. If an inappropriate kinase inhibitor is selected, there is a high risk of treatment failure with clonal expansion of the resistant mutant.
PURPOSE: BCR-ABL1 mutation analysis is recommended to facilitate selection of appropriate therapy for patients with chronic myeloid leukemia after treatment with imatinib has failed, since some frequently occurring mutations confer clinical resistance to nilotinib and/or dasatinib. However, mutations could be present below the detection limit of conventional direct sequencing. We developed a sensitive, multiplexed mass spectrometry assay (detection limit, 0.05% to 0.5%) to determine the impact of low-level mutations after imatinib treatment has failed. PATIENTS AND METHODS: Mutation status was assessed in 220 patients treated with nilotinib or dasatinib after they experienced resistance to imatinib. RESULTS: Mutations were detected by sequencing in 128 patients before commencing nilotinib or dasatinib therapy (switchover). In 64 patients, 132 additional low-level mutations were detected by mass spectrometry alone (50 of 132 mutations were resistant to nilotinib and/or dasatinib). When patients received the inhibitor for which the mutation confers resistance, 84% of the low-level resistant mutations rapidly became dominant clones detectable by sequencing, including 11 of 12 T315I mutations. Subsequent complete cytogenetic response rates were lower for patients with resistant mutations at switchover detected by sequencing (0%) or mass spectrometry alone (16%) compared with patients with other mutations or no mutations (41% and 49%, respectively; P < .001). Failure-free survival among the 100 patients with chronic phase chronic myeloid leukemia when resistant mutations were detected at switchover by sequencing or mass spectrometry alone was 0% and 0% compared with 51% and 45% for patients with other mutations or no mutations (P = .003). CONCLUSION: Detection of low-level mutations after imatinib resistance offers critical information to guide subsequent therapy selection. If an inappropriate kinase inhibitor is selected, there is a high risk of treatment failure with clonal expansion of the resistant mutant.
Authors: Katerina Machova Polakova; Vojtech Kulvait; Adela Benesova; Jana Linhartova; Hana Klamova; Monika Jaruskova; Caterina de Benedittis; Torsten Haferlach; Michele Baccarani; Giovanni Martinelli; Tomas Stopka; Thomas Ernst; Andreas Hochhaus; Alexander Kohlmann; Simona Soverini Journal: J Cancer Res Clin Oncol Date: 2014-11-04 Impact factor: 4.553
Authors: Michael W Schmitt; Justin R Pritchard; Scott M Leighow; Bella I Aminov; Lan Beppu; Daniel S Kim; J Graeme Hodgson; Victor M Rivera; Lawrence A Loeb; Jerald P Radich Journal: Clin Cancer Res Date: 2018-07-24 Impact factor: 12.531
Authors: Jamshid S Khorashad; Todd W Kelley; Philippe Szankasi; Clinton C Mason; Simona Soverini; Lauren T Adrian; Christopher A Eide; Matthew S Zabriskie; Thoralf Lange; Johanna C Estrada; Anthony D Pomicter; Anna M Eiring; Ira L Kraft; David J Anderson; Zhimin Gu; Mary Alikian; Alistair G Reid; Letizia Foroni; David Marin; Brian J Druker; Thomas O'Hare; Michael W Deininger Journal: Blood Date: 2012-12-05 Impact factor: 22.113