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Phenotypic analysis of an MLL-AF4 gene regulatory network reveals indirect CASP9 repression as a mode of inducing apoptosis resistance

Joe R. Harman, Ross Thorne, Max Jamilly, Marta Tapia, Nicholas T. Crump, Siobhan Rice, Ryan Beveridge, Edward Morrissey, Marella F.T.R de Bruijn, Irene Roberts, Anindita Roy, Tudor A. Fulga, View ORCID ProfileThomas A. Milne
doi: https://doi.org/10.1101/2020.06.30.179796
Joe R. Harman
1MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DS, UK
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Ross Thorne
1MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DS, UK
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Max Jamilly
2MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DS, UK
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Marta Tapia
1MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DS, UK
3Marta Tapia, The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, and Biotech Research and Innovation Centre (BRIC), Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
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Nicholas T. Crump
1MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DS, UK
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Siobhan Rice
1MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DS, UK
4Department of Paediatrics, University of Oxford, Oxford, UK
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Ryan Beveridge
1MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DS, UK
5Virus Screening Facility, MRC Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DS, UK
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Edward Morrissey
6Center for computational biology, Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DS, UK
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Marella F.T.R de Bruijn
1MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DS, UK
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Irene Roberts
1MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DS, UK
4Department of Paediatrics, University of Oxford, Oxford, UK
7NIHR Oxford Biomedical Research Centre Haematology Theme
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Anindita Roy
4Department of Paediatrics, University of Oxford, Oxford, UK
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Tudor A. Fulga
2MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DS, UK
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Thomas A. Milne
1MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DS, UK
7NIHR Oxford Biomedical Research Centre Haematology Theme
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  • ORCID record for Thomas A. Milne
  • For correspondence: thomas.milne@imm.ox.ac.uk
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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.

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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.

Competing Interest Statement

T.A.M. is a founding shareholder of OxStem Oncology (OSO), a subsidiary company of OxStem Ltd. All other authors have no competing interests.

Footnotes

  • ↵† The authors wish it to be known that, in their opinion, the first 2 authors should be regarded as joint First Authors

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted July 02, 2020.
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Phenotypic analysis of an MLL-AF4 gene regulatory network reveals indirect CASP9 repression as a mode of inducing apoptosis resistance
Joe R. Harman, Ross Thorne, Max Jamilly, Marta Tapia, Nicholas T. Crump, Siobhan Rice, Ryan Beveridge, Edward Morrissey, Marella F.T.R de Bruijn, Irene Roberts, Anindita Roy, Tudor A. Fulga, Thomas A. Milne
bioRxiv 2020.06.30.179796; doi: https://doi.org/10.1101/2020.06.30.179796
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Phenotypic analysis of an MLL-AF4 gene regulatory network reveals indirect CASP9 repression as a mode of inducing apoptosis resistance
Joe R. Harman, Ross Thorne, Max Jamilly, Marta Tapia, Nicholas T. Crump, Siobhan Rice, Ryan Beveridge, Edward Morrissey, Marella F.T.R de Bruijn, Irene Roberts, Anindita Roy, Tudor A. Fulga, Thomas A. Milne
bioRxiv 2020.06.30.179796; doi: https://doi.org/10.1101/2020.06.30.179796

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