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Cited by 179Acute Myeloid Leukemia ResearchGenomics and Chromatin DynamicsChromatin Remodeling and Cancer

Subtype-specific regulatory network rewiring in acute myeloid leukemia

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Assi, Salam A., Imperato, Maria Rosaria, Coleman, Daniel J. L., Pickin, Anna, Potluri, Sandeep, Ptasinska, Anetta, Chin, Paulynn Suyin, Blair, Helen +16 more·2019·Nature Genetics
DOI 10.1038/s41588-018-0270-1PMC PMC6330064
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Abstract

Acute myeloid leukemia (AML) is a heterogeneous disease caused by a variety of alterations in transcription factors, epigenetic regulators and signaling molecules. To determine how different mutant regulators establish AML subtype-specific transcriptional networks, we performed a comprehensive global analysis of cis-regulatory element activity and interaction, transcription factor occupancy and gene expression patterns in purified leukemic blast cells. Here, we focused on specific subgroups of subjects carrying mutations in genes encoding transcription factors (RUNX1, CEBPα), signaling molecules (FTL3-ITD, RAS) and the nuclear protein NPM1). Integrated analysis of these data demonstrates that each mutant regulator establishes a specific transcriptional and signaling network unrelated to that seen in normal cells, sustaining the expression of unique sets of genes required for AML growth and maintenance.

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  • Leukemia is frequently driven by mutations in epigenetic modifiers or signaling master regulators that lead to gross alterations of the epigenetic landscape and an epigenetic environment widely permissive of activation.

    “Leukemia is frequently driven by mutations in epigenetic modifiers or signaling master regulators58 that lead to gross alterations of the epigenetic landscape59 and an epigenetic environment widely permissive of activation.”

    From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [59]

    The Abstract and Results (‘AML subtypes adopt unique chromatin landscapes’; page unavailable) link AML mutations to altered, mutation-specific chromatin accessibility and gene expression. They do not establish an epigenetic environment widely permissive of activation; the paper instead emphasizes distinct subtype-specific patterns. It also reports that the presence or absence of DNMT3A mutations did not influence chromatin accessibility levels in its analysis. (LLM, conf=0.84)

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Research works printed but not linked: 61

  1. [1]Cancer Genome Atlas Research N Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia N Engl J Med 2013 368 2059 74 23634996 PMC3767041
  2. [3]Bonifer C Cockerill PN Chromatin Structure Profiling Identifies Crucial Regulators of Tumor Maintenance Trends Cancer 2015 1 157 160 28741472
  3. [5]Cockerill PN Receptor Signaling Directs Global Recruitment of Pre-existing Transcription Factors to Inducible Elements Yale J Biol Med 2016 89 591 596 28018147 PMC5168834
  4. [6]Ward AF Braun BS Shannon KM Targeting oncogenic Ras signaling in hematologic malignancies Blood 2012 120 3397 406 22898602 PMC3482854
  5. [7]Parikh C Subrahmanyam R Ren R Oncogenic NRAS rapidly and efficiently induces CMML- and AML-like diseases in mice Blood 2006 108 2349 57 16763213 PMC1895567
  6. [8]Masson K Ronnstrand L Oncogenic signaling from the hematopoietic growth factor receptors c-Kit and Flt3 Cell Signal 2009 21 1717 26 19540337
  7. [9]Gerloff D NF-kappaB/STAT5/miR-155 network targets PU.1 in FLT3-ITD-driven acute myeloid leukemia Leukemia 2015 29 535 47 25092144 PMC4490787
  8. [10]Corces-Zimmerman MR Hong WJ Weissman IL Medeiros BC Majeti R Preleukemic mutations in human acute myeloid leukemia affect epigenetic regulators and persist in remission Proc Natl Acad Sci U S A 2014 111 2548 53 24550281 PMC3932921
  9. [12]Di Croce L Helin K Transcriptional regulation by Polycomb group proteins Nature structural & molecular biology 2013 20 1147 55 24096405
  10. [13]Broske AM DNA methylation protects hematopoietic stem cell multipotency from myeloerythroid restriction Nature genetics 2009 41 1207 15 19801979
  11. [14]Bonifer C Bowen DT Epigenetic mechanisms regulating normal and malignant haematopoiesis: new therapeutic targets for clinical medicine Expert reviews in molecular medicine 2010 12 e6 20152067
  12. [15]Challen GA Dnmt3a is essential for hematopoietic stem cell differentiation Nature genetics 2012 44 23 31 PMC3637952 22138693
  13. [16]Ko M Impaired hydroxylation of 5-methylcytosine in myeloid cancers with mutant TET2 Nature 2010 468 839 43 21057493 PMC3003755
  14. [17]Shih AH Abdel-Wahab O Patel JP Levine RL The role of mutations in epigenetic regulators in myeloid malignancies Nature reviews. Cancer 2012 12 599 612 22898539
  15. [18]Goode DK Dynamic Gene Regulatory Networks Drive Hematopoietic Specification and Differentiation Dev Cell 2016 36 572 87 26923725 PMC4780867
  16. [19]Obier N Bonifer C Chromatin programming by developmentally regulated transcription factors: lessons from the study of haematopoietic stem cell specification and differentiation FEBS Lett 2016 590 4105 4115 27497427
  17. [20]Wilson NK Combinatorial transcriptional control in blood stem/progenitor cells: genome-wide analysis of ten major transcriptional regulators Cell Stem Cell 2010 7 532 44 20887958
  18. [22]Ptasinska A Identification of a Dynamic Core Transcriptional Network in t(8;21) AML that Regulates Differentiation Block and Self-Renewal Cell Reports 2014 8 1974 1988 25242324 PMC4487811
  19. [23]Loke J RUNX1-ETO and RUNX1-EVI1 Differentially Reprogram the Chromatin Landscape in t(8;21) and t(3;21) AML Cell Rep 2017 19 1654 1668 28538183 PMC5457485
  20. [24]Cauchy P Chronic FLT3-ITD Signaling in Acute Myeloid Leukemia Is Connected to a Specific Chromatin Signature Cell Rep 2015 12 821 36 26212328 PMC4726916
  21. [25]Corces MR Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution Nat Genet 2016 48 1193 203 27526324 PMC5042844
  22. [26]McKeown MR Superenhancer Analysis Defines Novel Epigenomic Subtypes of Non-APL AML, Including an RARalpha Dependency Targetable by SY-1425, a Potent and Selective RARalpha Agonist Cancer Discov 2017 7 1136 1153 28729405 PMC5962349
  23. [27]Martens JH ERG and FLI1 binding sites demarcate targets for aberrant epigenetic regulation by AML1-ETO in acute myeloid leukemia Blood 2012 120 4038 48 22983443 PMC3496958
  24. [28]Pulikkan JA Tenen DG Behre G C/EBPalpha deregulation as a paradigm for leukemogenesis Leukemia 2017 31 2279 2285 28720765 PMC8197657
  25. [29]Piper J Wellington: a novel method for the accurate identification of digital genomic footprints from DNase-seq data Nucleic Acids Res 2013 41 e201 24071585 PMC3834841
  26. [30]Ptasinska A Depletion of RUNX1/ETO in t(8;21) AML cells leads to genome-wide changes in chromatin structure and transcription factor binding Leukemia 2012 26 1829 1841 22343733 PMC3419980
  27. [31]Mandoli A CBFB-MYH11/RUNX1 together with a compendium of hematopoietic regulators, chromatin modifiers and basal transcription factors occupies self-renewal genes in inv(16) acute myeloid leukemia Leukemia 2014 28 770 8 24002588
  28. [32]Dunne J AML1/ETO proteins control POU4F1/BRN3A expression and function in t(8;21) acute myeloid leukemia Cancer Res 2010 70 3985 95 20460523 PMC2883733
  29. [33]Dekker J Rippe K Dekker M Kleckner N Capturing chromosome conformation Science 2002 295 1306 11 11847345
  30. [34]Mifsud B Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C Nat Genet 2015 47 598 606 25938943
  31. [35]Chasman D Roy S Inference of cell type specific regulatory networks on mammalian lineages Curr Opin Syst Biol 2017 2 130 139 29082337 PMC5656272
  32. [36]Neph S Circuitry and dynamics of human transcription factor regulatory networks Cell 2012 150 1274 86 22959076 PMC3679407
  33. [37]Lin S A FOXO1-induced oncogenic network defines the AML1-ETO preleukemic program Blood 2017 130 1213 1222 28710059 PMC5606002
  34. [38]O'Connor C Nfix expression critically modulates early B lymphopoiesis and myelopoiesis PLoS One 2015 10 e0120102 25780920 PMC4363787
  35. [39]Somerville TD Frequent Derepression of the Mesenchymal Transcription Factor Gene FOXC1 in Acute Myeloid Leukemia Cancer Cell 2015 28 329 42 26373280
  36. [40]Olive M A dominant negative to activation protein-1 (AP1) that abolishes DNA binding and inhibits oncogenesis J Biol Chem 1997 272 18586 94 9228025
  37. [41]Obier N Cooperative binding of AP-1 and TEAD4 modulates the balance between vascular smooth muscle and hemogenic cell fate Development 2016 143 4324 4340 27802171 PMC5201045
  38. [42]Verhaak RGW Prediction of molecular subtypes in acute myeloid leukemia based on gene expression profiling Haematologica 2009 94 131 134 18838472 PMC2625407
  39. [43]Figueroa ME DNA Methylation Signatures Identify Biologically Distinct Subtypes in Acute Myeloid Leukemia Cancer cell 2010 17 13 27 20060365 PMC3008568
  40. [44]Lin S Mulloy JC Goyama S RUNX1-ETO Leukemia Adv Exp Med Biol 2017 962 151 173 28299657
  41. [45]Goyama S UBASH3B/Sts-1-CBL axis regulates myeloid proliferation in human preleukemia induced by AML1-ETO Leukemia 2016 30 728 39 26449661 PMC4775400
  42. [46]Sun XJ A stable transcription factor complex nucleated by oligomeric AML1-ETO controls leukaemogenesis Nature 2013 500 93 7 23812588 PMC3732535
  43. [47]Essig A Duque-Afonso J Schwemmers S Pahl HL Lubbert M The AML1/ETO target gene LAT2 interferes with differentiation of normal hematopoietic precursor cells Leuk Res 2014 38 340 5 24456692 PMC4135084
  44. [48]Trop-Steinberg S Azar Y AP-1 Expression and its Clinical Relevance in Immune Disorders and Cancer Am J Med Sci 2017 353 474 483 28502334
  45. [49]Kesarwani M Targeting c-FOS and DUSP1 abrogates intrinsic resistance to tyrosine-kinase inhibitor therapy in BCR-ABL-induced leukemia Nat Med 2017 23 472 482 28319094 PMC5424814
  46. [50]Faber ZJ The genomic landscape of core-binding factor acute myeloid leukemias Nat Genet 2016 48 1551 1556 27798625 PMC5508996
  47. [51]Levis M Results from a randomized trial of salvage chemotherapy followed by lestaurtinib for patients with FLT3 mutant AML in first relapse Blood 2011 117 3294 301 21270442 PMC3069671
  48. [52]DePristo MA A framework for variation discovery and genotyping using next-generation DNA sequencing data Nat Genet 2011 43 491 8 21478889 PMC3083463
  49. [53]van Gosliga D Establishing long-term cultures with self-renewing acute myeloid leukemia stem/progenitor cells Exp Hematol 2007 35 1538 49 17889721
  50. [54]Weber K Bartsch U Stocking C Fehse B A multicolor panel of novel lentiviral "gene ontology" (LeGO) vectors for functional gene analysis Mol Ther 2008 16 698 706 18362927
  51. [55]Mostoslavsky G Efficiency of transduction of highly purified murine hematopoietic stem cells by lentiviral and oncoretroviral vectors under conditions of minimal in vitro manipulation Mol Ther 2005 11 932 40 15922964
  52. [56]Bert AG Johnson BV Baxter EW Cockerill PN A modular enhancer is differentially regulated by GATA and NFAT elements that direct different tissue-specific patterns of nucleosome positioning and inducible chromatin remodeling Mol Cell Biol 2007 27 2870 85 17283044 PMC1899937
  53. [57]Langmead B Salzberg SL Fast gapped-read alignment with Bowtie 2 Nat Methods 2012 9 357 9 22388286 PMC3322381
  54. [58]Zhang Y Model-based analysis of ChIP-Seq (MACS) Genome Biol 2008 9 R137 18798982 PMC2592715
  55. [59]Love MI Huber W Anders S Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 Genome Biol 2014 15 550 25516281 PMC4302049
  56. [60]Dobin A STAR: ultrafast universal RNA-seq aligner Bioinformatics 2013 29 15 21 23104886 PMC3530905
  57. [61]Trapnell C Differential analysis of gene regulation at transcript resolution with RNA-seq Nat Biotechnol 2013 31 46 53 23222703 PMC3869392
  58. [62]Wingett S HiCUP: pipeline for mapping and processing Hi-C data F1000Res 2015 4 1310 26835000 PMC4706059
  59. [63]Mifsud B GOTHiC, a probabilistic model to resolve complex biases and to identify real interactions in Hi-C data PLoS One 2017 12 e0174744 28379994 PMC5381888
  60. [64]Heinz S Simple Combinations of Lineage-Determining Transcription Factors Prime cis-Regulatory Elements Required for Macrophage and B Cell Identities Molecular Cell 2010 38 576 589 20513432 PMC2898526
  61. [65]Zhang HM AnimalTFDB: a comprehensive animal transcription factor database Nucleic Acids Res 2012 40 D144 9 22080564 PMC3245155

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Authors
Assi, S. A., Imperato, M. R., Coleman, D. J. L., Pickin, A., Potluri, S., Ptasinska, A., Chin, P. S., Blair, H., Cauchy, P., James, S. R., Zacarias-Cabeza, J., Gilding, L. N., Beggs, A., Clokie, S., Loke, J. C., Jenkin, P., Uddin, A., Delwel, R., Richards, S. J., Raghavan, M., Griffiths, M. J., Heidenreich, O., Cockerill, P. N., & Bonifer, C.
Affiliations
  • University of Birmingham (GB)
  • Newcastle University (GB)
  • University of Leeds (GB)
  • Erasmus MC (NL)
  • St James's University Hospital (GB)
  • Queen Elizabeth Hospital Birmingham (GB)
  • Princess Máxima Center (NL)
Corresponding author
  • Cockerill, Peter N.
  • Bonifer, Constanze
ORCID
Venue
Nature Genetics
Publisher
Springer Science and Business Media LLC
Published
2018-11-12
Volume
51
Issue
1
Pages
151-162
ISSN
  • 1061-4036 (ISSN-L)
  • 1546-1718
DOI
10.1038/s41588-018-0270-1
PMC
PMC6330064
OpenAlex
W2900205062
Cited by
179
References
4
Citations by year
2026: 15 · 2025: 20 · 2024: 27 · 2023: 21 · 2022: 24 · 2021: 27 · 2020: 23 · 2019: 19 · 2018: 1
FWCI
12.35
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Genetics (publishedVersion)
  • PubMed (publishedVersion)
  • University of Birmingham Research Portal (University of Birmingham) (publishedVersion, other-oa)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
  • White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (submittedVersion)
  • MPG.PuRe (Max Planck Society) (submittedVersion)
  • Newcastle University ePrints (Newcastle Univesity)
Funders
  • Leuka
  • Cancer Research UK (23389, 15001)
  • CHILDREN with CANCER UK (17-245)
  • Blood Cancer UK (15001)
  • Medical Research Council (MR/P019609/1, MR/M009157/1)
Topics
  • Health Sciences › Medicine › Hematology › Acute Myeloid Leukemia Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
Keywords
acute myeloid leukemia, AML subtypes, transcriptional regulatory networks, cis-regulatory elements, transcription factor occupancy, RUNX1, C/EBPα, RAS mutations, NPM1 mutation, open chromatin, chromatin conformation, leukemic blasts, gene expression
MeSH terms
Nucleophosmin, Adult, Aged, Aged, 80 and over, Female, Humans, Male, Middle Aged, Transcription Factors, Signal Transduction, Leukemia, Myeloid, Acute, Gene Expression Regulation, Leukemic, Gene Regulatory Networks, Young Adult

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