Digital Drug Screening and Computational Modeling Identifies Treatment Opportunities Despite Lack of Directly Actionable Mutations in Acute Myeloid Leukemia (AML) and Myelodysplastic Syndromes (MDS)

Background: Although virtually all patients (pts) with AML or MDS harbor at least one somatic mutation, a minority of pts possess genetic mutations considered directly targetable by a drug. Moreover, in pts with multiple gene mutations, single-gene/single-drug matching often produces conflicting drug recommendations. This lack of clinically relevant mutation-targeted therapy represents an unmet need in treating AML and MDS, and is a major limitation in personalized medicine. We hypothesized that genomic mutations from pts with AML or MDS could be used to generate pt-specific protein network maps for use in digital drug screening (DDS) even in cases when the gene mutations per se are not directly actionable. This would dramatically increase the percent of pts with actionable findings. Our primary goal was to establish a genomics and computational biology workflow that identified disease-relevant treatment options for every pt.