A Study of Ex Vivo Drug Screen Survival Predictions in AML Patients for Clinical Application

Abstract

Acute Myeloid Leukemia (AML) is a heterogeneous malignancy involving the clonal expansion of myeloid progenitor cells (blasts) in the bone marrow and peripheral blood. Most AML patients are treated with intensive chemotherapy, but despite initially high complete response rates, many patients relapse and die from their disease. New methods are required to better stratify patients in different treatment groups. A model system that can potentially identify personalized treatments from both novel and approved drugs is Ex vivo drug screens. However, little is known about the level of the predictivity of drug screen outcomes for clinical efficacy, and the preservation of cancer dependencies to ex vivo cultures. In this study, we used L2 regularized Cox regression to analyze ex vivo drug profiling data of 349 drugs form an ex vivo drug screen covering 55 AML patients who were subjected to standard 7+3 chemotherapy to predict patient survival.