ASXL1 and BIM germ line variants predict response and identify CML patients with the greatest risk of imatinib failure

Abstract

Scoring systems used at diagnosis of chronic myeloid leukemia (CML), such as Sokal risk, provide important response prediction for patients treated with imatinib. However, the sensitivity and specificity of scoring systems could be enhanced for improved identification of patients with the highest risk. We aimed to identify genomic predictive biomarkers of imatinib response at diagnosis to aid selection of first-line therapy. Targeted amplicon sequencing was performed to determine the germ line variant profile in 517 and 79 patients treated with first-line imatinib and nilotinib, respectively. The Sokal score and <i>ASXL1</i> rs4911231 and <i>BIM</i> rs686952 variants were independent predictors of early molecular response (MR), major MR, deep MRs (MR⁴ and MR^4.5), and failure-free survival (FFS) with imatinib treatment. In contrast, the <i>ASXL1</i> and <i>BIM</i> variants did not consistently predict MR or FFS with nilotinib treatment. In the imatinib-treated cohort, neither Sokal or the <i>ASXL1</i> and <i>BIM</i> variants predicted overall survival (OS) or progression to accelerated phase or blast crisis (AP/BC). The Sokal risk score was combined with the <i>ASXL1</i> and <i>BIM</i> variants in a classification tree model to predict imatinib response. The model distinguished an ultra-high-risk group, representing 10% of patients, that predicted inferior OS (88% vs 97%; <i>P</i> = .041), progression to AP/BC (12% vs 1%; <i>P</i> = .034), FFS (<i>P</i> < .001), and MRs (<i>P</i> < .001). The ultra-high-risk patients may be candidates for more potent or combination first-line therapy. These data suggest that germ line genetic variation contributes to the heterogeneity of response to imatinib and may contribute to a prognostic risk score that allows early optimization of therapy.