Computational identification of the normal and perturbed genetic networks involved in myeloid differentiation and acute promyelocytic leukemia.

Computational identification of the normal and perturbed genetic networks involved in myeloid differentiation and acute promyelocytic leukemia.
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DOI:
10.1186/gb-2008-9-2-r38
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发表时间:
2008
期刊:
影响因子:
12.3
通讯作者:
Stormo GD
Stormo GD
中科院分区:
生物学1区
文献类型:
--
作者:
Chang LW;Payton JE;Yuan W;Ley TJ;Nagarajan R;Stormo GD

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A dissection of the genetic networks and circuitries is described for two form of leukaemia. Integrating transcription factor binding and gene expression profiling, networks are revealed that underly this important human disease. Acute myeloid leukemia (AML) comprises a group of diseases characterized by the abnormal development of malignant myeloid cells. Recent studies have demonstrated an important role for aberrant transcriptional regulation in AML pathophysiology. Although several transcription factors (TFs) involved in myeloid development and leukemia have been studied extensively and independently, how these TFs coordinate with others and how their dysregulation perturbs the genetic circuitry underlying myeloid differentiation is not yet known. We propose an integrated approach for mammalian genetic network construction by combining the analysis of gene expression profiling data and the identification of TF binding sites. We utilized our approach to construct the genetic circuitries operating in normal myeloid differentiation versus acute promyelocytic leukemia (APL), a subtype of AML. In the normal and disease networks, we found that multiple transcriptional regulatory cascades converge on the TFs Rora and Rxra, respectively. Furthermore, the TFs dysregulated in APL participate in a common regulatory pathway and may perturb the normal network through Fos. Finally, a model of APL pathogenesis is proposed in which the chimeric TF PML-RARα activates the dysregulation in APL through six mediator TFs. This report demonstrates the utility of our approach to construct mammalian genetic networks, and to obtain new insights regarding regulatory circuitries operating in complex diseases in humans.
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