Abstract / Summary
Most pediatric acute myeloid leukemia (pAML) patients achieve complete remission after chemotherapy, yet nearly 40% ultimately relapse and die from their disease. High risk cases are typically referred for stem cell transplantation (SCT) in first remission, but because SCT is associated with substantial toxicity and cures after relapse are rare, accurate risk prediction is critical. Here, we show that combining the detection of chemoresistant cell populations, inferred from single-cell transcriptomic profiles of paired diagnosis–relapse samples, and cytogenetic biomarkers at diagnosis with measurable residual disease after induction chemotherapy, substantially improves risk prediction. This approach identifies a patient subgroup comprising 20% of the patients who do not undergo SCT, with a 5-year event-free survival below 40%, and accounting for nearly half of all deaths in this population. Molecular characterization of these cell populations reveals therapeutic vulnerabilities and potential targeted treatment strategies for high-risk pAML, providing a framework for precision oncology diagnosis and intervention. Early risk prediction is essential to decide the treatment procedure for pediatric acute myeloid leukemia. Here, the authors show that rare chemoresistant cell populations, detectable at diagnosis, improve risk stratification and reveal potential targets for more effective, personalized therapies.