Literature DB >> 24727677

Silencing AML1-ETO gene expression leads to simultaneous activation of both pro-apoptotic and proliferation signaling.

P V Spirin1, T D Lebedev1, N N Orlova2, A S Gornostaeva2, M M Prokofjeva1, N A Nikitenko1, S E Dmitriev3, A A Buzdin4, N M Borisov5, A M Aliper6, A V Garazha5, P M Rubtsov1, C Stocking7, V S Prassolov2.   

Abstract

The t(8;21)(q22;q22) rearrangement represents the most common chromosomal translocation in acute myeloid leukemia (AML). It results in a transcript encoding for the fusion protein AML1-ETO (AE) with transcription factor activity. AE is considered to be an attractive target for treating t(8;21) leukemia. However, AE expression alone is insufficient to cause transformation, and thus the potential of such therapy remains unclear. Several genes are deregulated in AML cells, including KIT that encodes a tyrosine kinase receptor. Here, we show that AML cells transduced with short hairpin RNA vector targeting AE mRNAs have a dramatic decrease in growth rate that is caused by induction of apoptosis and deregulation of the cell cycle. A reduction in KIT mRNA levels was also observed in AE-silenced cells, but silencing KIT expression reduced cell growth but did not induce apoptosis. Transcription profiling of cells that escape cell death revealed activation of a number of signaling pathways involved in cell survival and proliferation. In particular, we find that the extracellular signal-regulated kinase 2 (ERK2; also known as mitogen-activated protein kinase 1 (MAPK1)) protein could mediate activation of 23 out of 29 (79%) of these upregulated pathways and thus may be regarded as the key player in establishing the t(8;21)-positive leukemic cells resistant to AE suppression.

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Year:  2014        PMID: 24727677     DOI: 10.1038/leu.2014.130

Source DB:  PubMed          Journal:  Leukemia        ISSN: 0887-6924            Impact factor:   11.528


  37 in total

Review 1.  AML1 and the AML1-ETO fusion protein in the pathogenesis of t(8;21) AML.

Authors:  J D Licht
Journal:  Oncogene       Date:  2001-09-10       Impact factor: 9.867

2.  [Downregulation of activated leukemic oncogenes AML1-ETO and RUNX1(K83N) expression with RNA-interference].

Authors:  P V Spirin; F Baskaran; N N Orlova; A V Rulina; N A Nikitenko; E L Chernolovskaia; M A Zenkova; V V Vlasov; P M Rubtsov; P M Chumakov; C Stocking; V S Prasolov
Journal:  Mol Biol (Mosk)       Date:  2010 Sep-Oct

Review 3.  AML1-ETO driven acute leukemia: insights into pathogenesis and potential therapeutic approaches.

Authors:  Megan A Hatlen; Lan Wang; Stephen D Nimer
Journal:  Front Med       Date:  2012-08-09       Impact factor: 4.592

4.  Extracellular KIT receptor mutants, commonly found in core binding factor AML, are constitutively active and respond to imatinib mesylate.

Authors:  Jörg Cammenga; Stefan Horn; Ulla Bergholz; Gunhild Sommer; Peter Besmer; Walter Fiedler; Carol Stocking
Journal:  Blood       Date:  2005-08-04       Impact factor: 22.113

5.  Inhibitors of histone deacetylase relieve ETO-mediated repression and induce differentiation of AML1-ETO leukemia cells.

Authors:  J Wang; Y Saunthararajah; R L Redner; J M Liu
Journal:  Cancer Res       Date:  1999-06-15       Impact factor: 12.701

6.  C-KIT mutation cooperates with full-length AML1-ETO to induce acute myeloid leukemia in mice.

Authors:  Yue-Ying Wang; Li-Juan Zhao; Chuan-Feng Wu; Ping Liu; Lin Shi; Yang Liang; Shu-Min Xiong; Jian-Qing Mi; Zhu Chen; Ruibao Ren; Sai-Juan Chen
Journal:  Proc Natl Acad Sci U S A       Date:  2011-01-24       Impact factor: 11.205

7.  ETO, fusion partner in t(8;21) acute myeloid leukemia, represses transcription by interaction with the human N-CoR/mSin3/HDAC1 complex.

Authors:  J Wang; T Hoshino; R L Redner; S Kajigaya; J M Liu
Journal:  Proc Natl Acad Sci U S A       Date:  1998-09-01       Impact factor: 11.205

8.  Hematopoietic stem cell expansion and distinct myeloid developmental abnormalities in a murine model of the AML1-ETO translocation.

Authors:  Cristina G de Guzman; Alan J Warren; Zheng Zhang; Larry Gartland; Paul Erickson; Harry Drabkin; Scott W Hiebert; Christopher A Klug
Journal:  Mol Cell Biol       Date:  2002-08       Impact factor: 4.272

9.  Erythroid inhibition by the leukemic fusion AML1-ETO is associated with impaired acetylation of the major erythroid transcription factor GATA-1.

Authors:  Youngjin Choi; Kamaleldin E Elagib; Lorrie L Delehanty; Adam N Goldfarb
Journal:  Cancer Res       Date:  2006-03-15       Impact factor: 12.701

10.  AML1-ETO inhibits maturation of multiple lymphohematopoietic lineages and induces myeloblast transformation in synergy with ICSBP deficiency.

Authors:  Maike Schwieger; Jürgen Löhler; Jutta Friel; Marina Scheller; Ivan Horak; Carol Stocking
Journal:  J Exp Med       Date:  2002-11-04       Impact factor: 14.307

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  32 in total

1.  Data aggregation at the level of molecular pathways improves stability of experimental transcriptomic and proteomic data.

Authors:  Nicolas Borisov; Maria Suntsova; Maxim Sorokin; Andrew Garazha; Olga Kovalchuk; Alexander Aliper; Elena Ilnitskaya; Ksenia Lezhnina; Mikhail Korzinkin; Victor Tkachev; Vyacheslav Saenko; Yury Saenko; Dmitry G Sokov; Nurshat M Gaifullin; Kirill Kashintsev; Valery Shirokorad; Irina Shabalina; Alex Zhavoronkov; Bhubaneswar Mishra; Charles R Cantor; Anton Buzdin
Journal:  Cell Cycle       Date:  2017-08-21       Impact factor: 4.534

2.  Definition of a small core transcriptional circuit regulated by AML1-ETO.

Authors:  Kristy R Stengel; Jacob D Ellis; Clare L Spielman; Monica L Bomber; Scott W Hiebert
Journal:  Mol Cell       Date:  2020-12-30       Impact factor: 17.970

3.  Early stage of cytomegalovirus infection suppresses host microRNA expression regulation in human fibroblasts.

Authors:  Anton A Buzdin; Alina V Artcibasova; Natalya F Fedorova; Maria V Suntsova; Andrew V Garazha; Maxim I Sorokin; Daria Allina; Mikhail Shalatonin; Nikolay M Borisov; Alex A Zhavoronkov; Igor Kovalchuk; Olga Kovalchuk; Alla A Kushch
Journal:  Cell Cycle       Date:  2016-12-16       Impact factor: 4.534

4.  MiRImpact, a new bioinformatic method using complete microRNA expression profiles to assess their overall influence on the activity of intracellular molecular pathways.

Authors:  Alina V Artcibasova; Mikhail B Korzinkin; Maksim I Sorokin; Peter V Shegay; Alex A Zhavoronkov; Nurshat Gaifullin; Boris Y Alekseev; Nikolay V Vorobyev; Denis V Kuzmin; Аndrey D Kaprin; Nikolay M Borisov; Anton A Buzdin
Journal:  Cell Cycle       Date:  2016       Impact factor: 4.534

5.  Screening and personalizing nootropic drugs and cognitive modulator regimens in silico.

Authors:  Leslie C Jellen; Alexander Aliper; Anton Buzdin; Alex Zhavoronkov
Journal:  Front Syst Neurosci       Date:  2015-02-06

6.  The OncoFinder algorithm for minimizing the errors introduced by the high-throughput methods of transcriptome analysis.

Authors:  Anton A Buzdin; Alex A Zhavoronkov; Mikhail B Korzinkin; Sergey A Roumiantsev; Alexander M Aliper; Larisa S Venkova; Philip Y Smirnov; Nikolay M Borisov
Journal:  Front Mol Biosci       Date:  2014-08-26

7.  Combinatorial high-throughput experimental and bioinformatic approach identifies molecular pathways linked with the sensitivity to anticancer target drugs.

Authors:  Larisa Venkova; Alexander Aliper; Maria Suntsova; Roman Kholodenko; Denis Shepelin; Nicolas Borisov; Galina Malakhova; Raif Vasilov; Sergey Roumiantsev; Alex Zhavoronkov; Anton Buzdin
Journal:  Oncotarget       Date:  2015-09-29

8.  Signaling pathways activation profiles make better markers of cancer than expression of individual genes.

Authors:  Nikolay M Borisov; Nadezhda V Terekhanova; Alexander M Aliper; Larisa S Venkova; Philip Yu Smirnov; Sergey Roumiantsev; Mikhail B Korzinkin; Alex A Zhavoronkov; Anton A Buzdin
Journal:  Oncotarget       Date:  2014-10-30

9.  Novel robust biomarkers for human bladder cancer based on activation of intracellular signaling pathways.

Authors:  Ksenia Lezhnina; Olga Kovalchuk; Alexander A Zhavoronkov; Mikhail B Korzinkin; Anastasia A Zabolotneva; Peter V Shegay; Dmitry G Sokov; Nurshat M Gaifullin; Igor G Rusakov; Alexander M Aliper; Sergey A Roumiantsev; Boris Y Alekseev; Nikolay M Borisov; Anton A Buzdin
Journal:  Oncotarget       Date:  2014-10-15

10.  Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing Using Transcriptomic Data.

Authors:  Alexander Aliper; Sergey Plis; Artem Artemov; Alvaro Ulloa; Polina Mamoshina; Alex Zhavoronkov
Journal:  Mol Pharm       Date:  2016-06-08       Impact factor: 4.939

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