Advanced computational methods exploit gene expression and epigenetic datasets to predict gene regulatory networks controlled by transcription factors (TFs). These methods have identified cell fate determining TFs but require large amounts of reference data and experimental expertise. Here, we present an easy to use network-based computational framework that exploits enhancers defined by bidirectional transcription, using as sole input CAGE sequencing data to correctly predict TFs key to various human cell types. Next, we applied this Analysis Algorithm for Networks Specified by Enhancers based on CAGE (ANANSE-CAGE) to predict TFs driving red and white blood cell development, and THP-1 leukemia cell immortalization. Further, we predicted TFs that are differentially important to either cell line- or primary- associated MLL-AF9-driven gene programs, and in primary MLL-AF9 acute leukemia. Our approach identified experimentally validated as well as thus far unexplored TFs in these processes. ANANSE-CAGE will be useful to identify transcription factors that are key to any cell fate change using only CAGE-seq data as input.

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A t(9;11)(p22;q23) translocation produces the MLL-AF9 fusion protein, which is found in up to 25% of de novo AML cases in children. Despite major advances, obtaining a comprehensive understanding of context-dependent MLL-AF9-mediated gene programs during early hematopoiesis is challenging. Here, we generated a human inducible pluripotent stem cell (hiPSC) model with a doxycycline dose-dependent MLL-AF9 expression. We exploited MLL-AF9 expression as an oncogenic hit to uncover epigenetic and transcriptomic effects on iPSC-derived hematopoietic development and the transformation into (pre-)leukemic states. In doing so, we observed a disruption in early myelomonocytic development. Accordingly, we identified gene profiles that were consistent with primary MLL-AF9 AML and uncovered high-confidence MLL-AF9-associated core genes that are faithfully represented in primary MLL-AF9 AML, including known and presently unknown factors. Using single-cell RNA-sequencing, we identified an increase of CD34 expressing early hematopoietic progenitor-like cell states as well as granulocyte-monocyte progenitor-like cells upon MLL-AF9 activation. Our system allows for careful chemically controlled and stepwise in vitro hiPSC-derived differentiation under serum-free and feeder-free conditions. For a disease that currently lacks effective precision medicine, our system provides a novel entry-point into exploring potential novel targets for personalized therapeutic strategies.

A t(9;11)(p22;q23) translocation produces the MLL-AF9 fusion protein, which is found in up to 25% of de novo AML cases in children. Despite major advances, obtaining a comprehensive understanding of context-dependent MLL-AF9-mediated gene programs during early hematopoiesis is challenging. Here, we generated a human inducible pluripotent stem cell (hiPSC) model with doxycycline dose-dependent MLL-AF9 expression. We exploit MLL-AF9 expression as an oncogenic hit to uncover epigenetic and transcriptomic effects on iPSC-derived hematopoietic development and the transformation into (pre-)leukemic states. In doing so, we observed disruption of early myelomonocytic development and expansion of a CD34+ early hematopoietic progenitor compartment upon MLL-AF9 activation. In agreement, we identified gene profiles consistent with primary MLL-AF9 AML and uncovered highly confident MLL-AF9-associated core genes that faithfully represent primary MLL-AF9 AML, including known and thus far unknown factors. Our system allows for careful chemically controlled and stepwise in vitro hiPSC-derived differentiation under serum-free and feeder-free conditions. For a disease that currently lacks effective precision medicine, our system provides a novel entry-point into exploring potential novel biomarkers and targets for personalized therapeutic strategies.