Integrative Analysis of Drug Response and Clinical Outcome in Acute Myeloid Leukemia

Abstract

Acute myeloid leukemia (AML) is a cancer of myeloid-lineage cells with limited therapeutic options. We previously combined ex vivo drug sensitivity with genomic, transcriptomic, and clinical annotations for a large cohort of AML patients, which facilitated discovery of functional genomic correlates. Here, we present a new dataset, which has been harmonized with our initial report to yield a cumulative cohort of 805 patients (942 specimens). We show strong cross-cohort validation and identify new features of drug response. Further, deconvoluting transcriptomic data shows that drug sensitivity is governed broadly by AML cell differentiation state, sometimes conditionally impacting other correlates of response. Finally, modeling of clinical outcome reveals a single gene, PEAR1, to be among the strongest predictors of patient survival, especially for young patients. Collectively, this report expands a large functional genomic resource, offers new avenues for mechanistic exploration and drug development, and reveals new tools for predicting outcome in AML.

Keywords: hematologic malignancy, targeted therapy, LSC17, cell state, leukemia stem cell, monocyte, eigengene, JEDI, MEGF12