A Bayesian active learning platform for scalable combination drug screens.

Large-scale combination drug screens are generally considered intractable due to the immense number of possible combinations. Existing approaches use ad hoc fixed experimental designs then train machine learning models to impute unobserved combinations. Here we propose BATCHIE, an orthogonal approach that conducts experiments dynamically in batches.

ETV6-FLT3-positive myeloid/lymphoid neoplasm with eosinophilia presenting in an infant: an entity distinct from JMML.

Myeloid/lymphoid neoplasm with eosinophilia (MLN-Eo) is a World Health Organization (WHO) established category of hematologic malignancies primarily arising in adults. We discuss an 8-month-old infant who presented with clinical features similar to those of juvenile myelomonocytic leukemia (JMML) but who was diagnosed with MLN-Eo driven by an ETV6-FLT3 fusion. Results of patient-derived leukemia ex vivo studies demonstrated increased sensitivity to type I FLT3 inhibitors as compared with type II inhibitors.

Patient-Driven Discovery, Therapeutic Targeting, and Post-Clinical Validation of a Novel Fusion-Driven Cancer.

Despite the important role of the PI3K/AKT/mTOR axis in the pathogenesis of cancer, to date there have been few functional oncogenic fusions identified involving the genes. A 12-year-old female with a histopathologically indeterminate epithelioid neoplasm was found to harbor a novel fusion between the and genes. Through expanded use access, she became the first pediatric patient to be treated with the oral ATP-competitive pan-AKT inhibitor ipatasertib.