Research
Computational identification of the normal and perturbed genetic networks involved in myeloid differentiation and acute promyelocytic leukemia
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* Corresponding author: Gary D Stormo stormo@genetics.wustl.edu
1 Department of Biomedical Engineering, Washington University, St Louis, MO 63130, USA
2 Department of Pathology and Immunology, Division of Laboratory Medicine, Washington University School of Medicine, St Louis, MO 63110, USA
3 Division of Oncology, Department of Medicine, Washington University School of Medicine, St Louis, MO 63110, USA
4 Department of Genetics, Washington University School of Medicine, St Louis, MO 63110, USA
Genome Biology 2008, 9:R38 doi:10.1186/gb-2008-9-2-r38
Published: 21 February 2008Abstract
Background
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.
Results
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-RARĪ± activates the dysregulation in APL through six mediator TFs.
Conclusion
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.