ASH 2023 | Epigenetic profiling and machine learning for risk stratification in pediatric ALL

Adrian Mosquera Orgueira, MD, PhD, University Hospital of Santiago de Compostela, A Coruña, Spain, discusses the use of novel machine-learning applications for assessing DNA methylation profiles in children with refractory acute lymphoblastic leukemia (ALL). Since these patients are ineligible for traditional chemotherapies and stem cell transplants, it is useful to identify the patients who are unlikely to respond to treatment. The application successfully predicted overall survival (OS), progression-free survival (PFS) and relapse risk, and the output was correlated with the traditional cytogenetic classification of ALL. The signature’s prognostic capabilities were validated in external cohorts, and now researchers are eager to see how this approach correlates with other predictors of disease outcomes, such as measurable residual disease (MRD). This interview took place at the 65th ASH Annual Meeting and Exposition, held in San Diego, CA.

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