Unraveling the complexity of tyrosine kinase inhibitor-resistant populations by ultra-deep sequencing of the BCR-ABL kinase domain

Abstract

In chronic myeloid leukemia and Philadelphia chromosome-positive acute lymphoblastic leukemia, tyrosine kinase inhibitor (TKI) therapy may select for drug-resistant BCR-ABL mutants. We used an ultra-deep sequencing (UDS) approach to resolve qualitatively and quantitatively the complexity of mutated populations surviving TKIs and to investigate their clonal structure and evolution over time in relation to therapeutic intervention. To this purpose, we performed a longitudinal analysis of 106 samples from 33 patients who had received sequential treatment with multiple TKIs and had experienced sequential relapses accompanied by selection of 1 or more TKI-resistant mutations. We found that conventional Sanger sequencing had misclassified or underestimated BCR-ABL mutation status in 55% of the samples, where mutations with 1% to 15% abundance were detected. A complex clonal texture was uncovered by clonal analysis of samples harboring multiple mutations and up to 13 different mutated populations were identified. The landscape of these mutated populations was found to be highly dynamic. The high degree of complexity uncovered by UDS indicates that conventional Sanger sequencing might be an inadequate tool to assess BCR-ABL kinase domain mutation status, which currently represents an important component of the therapeutic decision algorithms. Further evaluation of the clinical usefulness of UDS-based approaches is warranted.