Literature DB >> 33956058

SETBP1 overexpression acts in the place of class-defining mutations to drive FLT3-ITD-mutant AML.

Suruchi Pacharne1,2, Oliver M Dovey1, Jonathan L Cooper1, Muxin Gu1,2, Mathias J Friedrich1,3, Sandeep S Rajan1,4, Maxim Barenboim5, Grace Collord1,2, M S Vijayabaskar1,2, Hannes Ponstingl1, Etienne De Braekeleer1,2, Ruben Bautista1, Milena Mazan1,6, Roland Rad3,7, Konstantinos Tzelepis1,8,9, Penny Wright9, Malgorzata Gozdecka1,2, George S Vassiliou1,2,10.   

Abstract

Advances in cancer genomics have revealed genomic classes of acute myeloid leukemia (AML) characterized by class-defining mutations, such as chimeric fusion genes or in genes such as NPM1, MLL, and CEBPA. These class-defining mutations frequently synergize with internal tandem duplications in FLT3 (FLT3-ITDs) to drive leukemogenesis. However, ∼20% of FLT3-ITD-positive AMLs bare no class-defining mutations, and mechanisms of leukemic transformation in these cases are unknown. To identify pathways that drive FLT3-ITD mutant AML in the absence of class-defining mutations, we performed an insertional mutagenesis (IM) screening in Flt3-ITD mice, using Sleeping Beauty transposons. All mice developed acute leukemia (predominantly AML) after a median of 73 days. Analysis of transposon insertions in 38 samples from Flt3-ITD/IM leukemic mice identified recurrent integrations at 22 loci, including Setbp1 (20/38), Ets1 (11/38), Ash1l (8/38), Notch1 (8/38), Erg (7/38), and Runx1 (5/38). Insertions at Setbp1 led exclusively to AML and activated a transcriptional program similar, but not identical, to those of NPM1-mutant and MLL-rearranged AMLs. Guide RNA targeting of Setbp1 was highly detrimental to Flt3ITD/+/Setbp1IM+, but not to Flt3ITD/+/Npm1cA/+, AMLs. Also, analysis of RNA-sequencing data from hundreds of human AMLs revealed that SETBP1 expression is significantly higher in FLT3-ITD AMLs lacking class-defining mutations. These findings propose that SETBP1 overexpression collaborates with FLT3-ITD to drive a subtype of human AML. To identify genetic vulnerabilities of these AMLs, we performed genome-wide CRISPR-Cas9 screening in Flt3ITD/+/Setbp1IM+ AMLs and identified potential therapeutic targets, including Kdm1a, Brd3, Ezh2, and Hmgcr. Our study gives new insights into epigenetic pathways that can drive AMLs lacking class-defining mutations and proposes therapeutic approaches against such cases.
© 2021 by The American Society of Hematology.

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Year:  2021        PMID: 33956058      PMCID: PMC8114559          DOI: 10.1182/bloodadvances.2020003443

Source DB:  PubMed          Journal:  Blood Adv        ISSN: 2473-9529


  65 in total

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3.  RUNX1 mutations are frequent in de novo AML with noncomplex karyotype and confer an unfavorable prognosis.

Authors:  Susanne Schnittger; Frank Dicker; Wolfgang Kern; Nicole Wendland; Jana Sundermann; Tamara Alpermann; Claudia Haferlach; Torsten Haferlach
Journal:  Blood       Date:  2010-12-09       Impact factor: 22.113

4.  Mll partial tandem duplication and Flt3 internal tandem duplication in a double knock-in mouse recapitulates features of counterpart human acute myeloid leukemias.

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Journal:  Blood       Date:  2012-06-06       Impact factor: 22.113

5.  Setbp1 promotes the self-renewal of murine myeloid progenitors via activation of Hoxa9 and Hoxa10.

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7.  Promoter-bound METTL3 maintains myeloid leukaemia by m6A-dependent translation control.

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Journal:  Nature       Date:  2017-11-27       Impact factor: 49.962

8.  Detecting statistically significant common insertion sites in retroviral insertional mutagenesis screens.

Authors:  Jeroen de Ridder; Anthony Uren; Jaap Kool; Marcel Reinders; Lodewyk Wessels
Journal:  PLoS Comput Biol       Date:  2006-10-24       Impact factor: 4.475

9.  A novel mouse model identifies cooperating mutations and therapeutic targets critical for chronic myeloid leukemia progression.

Authors:  George Giotopoulos; Louise van der Weyden; Hikari Osaki; Alistair G Rust; Paolo Gallipoli; Eshwar Meduri; Sarah J Horton; Wai-In Chan; Donna Foster; Rab K Prinjha; John E Pimanda; Daniel G Tenen; George S Vassiliou; Steffen Koschmieder; David J Adams; Brian J P Huntly
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10.  The TraDIS toolkit: sequencing and analysis for dense transposon mutant libraries.

Authors:  Lars Barquist; Matthew Mayho; Carla Cummins; Amy K Cain; Christine J Boinett; Andrew J Page; Gemma C Langridge; Michael A Quail; Jacqueline A Keane; Julian Parkhill
Journal:  Bioinformatics       Date:  2016-01-21       Impact factor: 6.937

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  2 in total

Review 1.  High-Throughput CRISPR Screening in Hematological Neoplasms.

Authors:  Raquel Ancos-Pintado; Irene Bragado-García; María Luz Morales; Roberto García-Vicente; Andrés Arroyo-Barea; Alba Rodríguez-García; Joaquín Martínez-López; María Linares; María Hernández-Sánchez
Journal:  Cancers (Basel)       Date:  2022-07-25       Impact factor: 6.575

Review 2.  Mouse Models of Frequently Mutated Genes in Acute Myeloid Leukemia.

Authors:  Sagarajit Mohanty; Michael Heuser
Journal:  Cancers (Basel)       Date:  2021-12-08       Impact factor: 6.639

  2 in total

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