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ABSTRACT Regulatory interactions mediated by transcription factors (TFs) make up complex networks that control cellular behavior. Fully understanding these gene regulatory networks (GRNs) offers greater insight into the consequences of disease-causing perturbations than studying single TF binding events in isolation. Chromosomal translocations of the Mixed Lineage Leukemia gene ( MLL ) produce MLL fusion proteins such as MLL-AF4, causing poor prognosis acute lymphoblastic leukemias (ALLs). MLL-AF4 is thought to drive leukemogenesis by directly binding to genes and inducing aberrant overexpression of key gene targets, including anti-apoptotic factors such as BCL-2. However, this model minimizes the potential for circuit generated regulatory outputs, including gene repression. To better understand the MLL-AF4 driven regulatory landscape, we integrated ChIP-seq, patient RNA-seq and CRISPR essentiality screens to generate a model GRN. This GRN identified several key transcription factors, including RUNX1, that regulate target genes using feed-forward loop and cascade motifs. We used CRISPR screening in the presence of the BCL-2 inhibitor venetoclax to identify functional impacts on apoptosis. This identified an MLL-AF4:RUNX1 cascade that represses CASP9, perturbation of which disrupts venetoclax induced apoptosis. This illustrates how our GRN can be used to better understand potential mechanisms of drug resistance acquisition. Graphical abstract caption A network model of the MLL-AF4 regulatory landscape identifies feed-forward loop and cascade motifs. Functional screening using CRISPR and venetoclax identified an MLL-AF4:RUNX1: CASP9 repressive cascade that impairs drug-induced cell death.

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