Exploratory Biomarker Analysis from ENESTnd: Gene Expression Signature Distinguishes Deep Molecular Response (DMR) from Poor Response in Chronic Myeloid Leukemia (CML)

Context For patients with CML, achieving sustained DMR is a prerequisite for attempting treatment-free remission. However, biomarkers that predict DMR are unknown. Objective Identify biomarkers associated with DMR. Design Exploratory analysis of samples from a phase 3, randomized, open-label study (NCT00471497). Patients Whole blood samples collected prior to tyrosine kinase inhibitor (TKI) therapy from 112 patients in the nilotinib 300-mg twice-daily (n=33), nilotinib 400-mg twice-daily (n=32), or imatinib 400-mg once-daily (n=47) arms of ENESTnd were analyzed using RNA sequencing. Samples from poor responders (BCR-ABL1IS \u003e 10% by 3 months of therapy) and good responders (BCR-ABL1IS Main outcome measures Using multivariate logistic regression, the association of clinical variables (e.g., Sokal risk score, TKI, age, sex) with responder status was assessed. Additionally, we applied penalized regression to clinical variables and gene expression (13,569 genes) in independent and combined (gene and clinical) models to develop a predictive model of responder status. Results By multivariate analysis, younger age ( Conclusions Our gene expression model differentiates patients who achieved DMR from those with poor treatment response at 5 years. This work could be used to develop therapeutic targets and facilitate DMR in patients who would otherwise be poor responders. Study sponsored by Novartis Pharmaceuticals Corporation. This abstract was accepted and previously published at the 61st ASH® Annual Meeting and Exposition.