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http://hdl.handle.net/2445/124022
Title: | Reverse engineering of TLX oncogenic transcriptional networks identifies RUNX1 as tumor suppressor in T-ALL |
Author: | Della Gatta, Giusy Palomero, Teresa Pérez García, Arianne Ambesi Impiombato, Alberto Bansal, Mukesh Carpenter, Zachary W. De Keersmaecker, Kim Solé Acha, Xavier Xu, Luyao Paietta, Elisabeth Racevskis, Janis Wiernik, Peter H. Rowe, Jacob M. Meijerink, Jules P. P. Califano, Andrea Ferrando, Adolfo A. |
Keywords: | Oncogens Leucèmia Oncogenes Leukemia |
Issue Date: | 1-Mar-2012 |
Publisher: | Nature Publishing Group |
Abstract: | The TLX1 and TLX3 transcription factor oncogenes have a key role in the pathogenesis of T cell acute lymphoblastic leukemia (T-ALL)(1,2). Here we used reverse engineering of global transcriptional networks to decipher the oncogenic regulatory circuit controlled by TLX1 and TLX3. This systems biology analysis defined T cell leukemia homeobox 1 (TLX1) and TLX3 as master regulators of an oncogenic transcriptional circuit governing T-ALL. Notably, a network structure analysis of this hierarchical network identified RUNX1 as a key mediator of the T-ALL induced by TLX1 and TLX3 and predicted a tumor-suppressor role for RUNX1 in T cell transformation. Consistent with these results, we identified recurrent somatic loss-of-function mutations in RUNX1 in human T-ALL. Overall, these results place TLX1 and TLX3 at the top of an oncogenic transcriptional network controlling leukemia development, show the power of network analyses to identify key elements in the regulatory circuits governing human cancer and identify RUNX1 as a tumor-suppressor gene in T-ALL. |
Note: | Versió postprint del document publicat a: http://dx.doi.org/10.1038/nm.2610 |
It is part of: | Nature Medicine, 2012, vol. 18, num. 3, p. 436-440 |
URI: | http://hdl.handle.net/2445/124022 |
Related resource: | http://dx.doi.org/10.1038/nm.2610 |
Appears in Collections: | Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL)) |
Files in This Item:
File | Description | Size | Format | |
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Della GattaG.pdf | 1.28 MB | Adobe PDF | View/Open |
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