The BCR::ABL1 gene fusion initiates chronic myeloid leukemia (CML), however evidence has accumulated from studies of highly selected cohorts that variants in other cancer-related genes are associated with treatment failure.… Click to show full abstract
The BCR::ABL1 gene fusion initiates chronic myeloid leukemia (CML), however evidence has accumulated from studies of highly selected cohorts that variants in other cancer-related genes are associated with treatment failure. Nevertheless, the true incidence and impact of additional genetic abnormalities (AGAs) at diagnosis of chronic phase (CP)-CML is unknown. We sought to determine whether AGAs at diagnosis in a consecutive imatinib-treated cohort of 210 patients enrolled in the TIDEL-II trial influenced outcome despite a highly proactive treatment intervention strategy. Survival outcomes including overall survival, progression-free survival, failure-free survival and BCR::ABL1 kinase domain mutation acquisition were evaluated. Molecular outcomes were measured at a central laboratory and included major molecular response (MMR, BCR::ABL1 ≤0.1%IS), MR4 (BCR::ABL1 ≤0.01%IS) and MR4.5 (BCR::ABL1 ≤0.0032%IS). AGAs included variants in known cancer genes and novel rearrangements involving the formation of the Philadelphia chromosome. Clinical outcomes and molecular response were assessed based on the genetic profile and other baseline factors. AGAs were identified in 31% of patients. Potentially pathogenic variants in cancer-related genes were detected in 16% of patients at diagnosis (including gene fusions and deletions) and structural rearrangements involving the Philadelphia chromosome (Ph-associated rearrangements), detected in 18%. Multivariable analysis demonstrated that the combined genetic abnormalities plus the ELTS clinical risk score were independent predictors of lower molecular response rates and higher treatment failure. Despite a highly proactive treatment intervention strategy, first-line imatinib-treated patients with AGAs had poorer response rates. This data provides evidence for the incorporation of genomically-based risk assessment for CML.
               
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