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In chronic-phase chronic myeloid leukemia (CML) patients, the lack of a major cytogenetic response (< 36% Ph(+) metaphases) to imatinib within 12 months indicates failure and mandates a change of therapy. To identify biomarkers predictive of imatinib failure, we performed gene expression array profiling of CD34(+) cells from 2 independent cohorts of imatinib-naive chronic-phase CML patients. The learning set consisted of retrospectively selected patients with a complete cytogenetic response or more than 65% Ph(+) metaphases within 12 months of imatinib therapy. Based on analysis of variance P less than .1 and fold difference 1.5 or more, we identified 885 probe sets with differential expression between responders and nonresponders, from which we extracted a 75-probe set minimal signature (classifier) that separated the 2 groups. On application to a prospectively accrued validation set, the classifier correctly predicted 88% of responders and 83% of nonresponders. Bioinformatics analysis and comparison with published studies revealed overlap of classifier genes with CML progression signatures and implicated beta-catenin in their regulation, suggesting that chronic-phase CML patients destined to fail imatinib have more advanced disease than evident by morphologic criteria. Our classifier may allow directing more aggressive therapy upfront to the patients most likely to benefit while sparing good-risk patients from unnecessary toxicity.