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Front Physiol. 2012 Nov 19;3:410. doi: 10.3389/fphys.2012.00410. eCollection 2012.

Modeling the Mechanism of GR/c-Jun/Erg Crosstalk in Apoptosis of Acute Lymphoblastic Leukemia.

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1
Faculty of Life Sciences, University of Manchester Manchester, UK ; Faculty of Life Sciences, Manchester Institute of Biotechnology, University of Manchester Manchester, UK.

Abstract

Acute lymphoblastic leukemia (ALL) is one of the most common forms of malignancy that occurs in lymphoid progenitor cells, particularly in children. Synthetic steroid hormones glucocorticoids (GCs) are widely used as part of the ALL treatment regimens due to their apoptotic function, but their use also brings about various side effects and drug resistance. The identification of the molecular differences between the GCs responsive and resistant cells therefore are essential to decipher such complexity and can be used to improve therapy. However, the emerging picture is complicated as the activities of genes and proteins involved are controlled by multiple factors. By adopting the systems biology framework to address this issue, we here integrated the available knowledge together with experimental data by building a series of mathematical models. This rationale enabled us to unravel molecular interactions involving c-Jun in GC induced apoptosis and identify Ets-related gene (Erg) as potential biomarker of GC resistance. The results revealed an alternative possible mechanism where c-Jun may be an indirect GR target that is controlled via an upstream repressor protein. The models also highlight the importance of Erg for GR function, particularly in GC sensitive C7 cells where Erg directly regulates GR in agreement with our previous experimental results. Our models describe potential GR-controlled molecular mechanisms of c-Jun/Bim and Erg regulation. We also demonstrate the importance of using a systematic approach to translate human disease processes into computational models in order to derive information-driven new hypotheses.

KEYWORDS:

dynamic model; gene expression; glucocorticoid receptor; kinetic simulation; systems biology

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