Despite advances in chemotherapy-based protocols, the outcomes of pediatric acute myeloid leukemia (AML) remain suboptimal. Implementation of targeted therapy based on genomics is challenging due to the complex mutational patterns and scarcity of pharmacologic agents for most lesions. This study aims to adopt a functional approach that directly measure the response of patient-derived leukemic cells to targeted agents, and to establish the drug sensitivity pattern and identify candidates of immediate clinical relevance for precision usage in high-risk cases.
A high-throughput drug screen, comprising 39 targeted agents and 6 conventional chemotherapeutics, was performed on 25 pediatric AML samples using a serum-free, cytokine-supported culture system. The robustness of the drug testing platform for predicting in vivo activities was validated in animal models. Patients with refractory AML were treated with targeted agents based on drug profiling results, and assessed for clinical responses.
Unsupervised clustering revealed 5 distinct clusters of drug response: highly active compounds (IC50<20nM, 6 drugs); generally active compounds (IC50<500nM, 11 drugs); compounds with bimodal activities (wide IC50 ranges, 4 drugs); generally inactive compounds (14 drugs); and inactive compounds (10 drugs). Targeted agents, including Bcl-2, HDAC, proteasome, HSP and survivin inhibitors, had substantially higher potency than standard chemotherapeutic agents. New agents approved for adult AML were essentially inactive in pediatric AML. Drug sensitivity ex vivo accurately predicted in vivo single-agent and combinatorial activities with cytarabine in cell line- and patient-derived xenografts. Administration of venetoclax and dasatinib to two patients with refractory AML resulted in rapid blast clearance and achieved long-term remission.
Our study establishes a pediatric-specific drug response profile of AML, which enables an evidence-based selection of targeted agents for patients without treatment options and endows therapies increasingly precise and personalized. It will ultimately impact the future design of clinical trials and protocols for managing high-risk pediatric AML.