Dynamic analysis of the combinatorial regulation involving transcription factors and microRNAs in cell fate decisions.

P53 and E2F1 are critical transcription factors involved in the choices between different cell fates including cell differentiation, cell cycle arrest or apoptosis. Recent experiments have shown that two families of microRNAs (miRNAs), p53-responsive miR34 (miRNA-34 a, b and c) and E2F1-inducible miR449 (miRNA-449 a, b and c) are potent inducers of these different fates and might have an important role in sensitizing cancer cells to drug treatment and tumor suppression. Identifying the mechanisms responsible for the combinatorial regulatory roles of these two transcription factors and two miRNAs is an important and challenging problem. Here, based in part on the model proposed in Tongli Zhang et al. (2007), we developed a mathematical model of the decision process and explored the combinatorial regulation between these two transcription factors and two miRNAs in response to DNA damage. By analyzing nonlinear dynamic behaviors of the model, we found that p53 exhibits pulsatile behavior. Moreover, a comparison is given to reveal the subtle differences of the cell fate decision process between regulation and deregulation of miR34 on E2F1. It predicts that miR34 plays a critical role in promoting cell cycle arrest. In addition, a computer simulation result also predicts that the miR449 is necessary for apoptosis in response to sustained DNA damage. In agreement with experimental observations, our model can account for the intricate regulatory relationship between these two transcription factors and two miRNAs in the cell fate decision process after DNA damage. These theoretical results indicate that miR34 and miR449 are effective tumor suppressors and play critical roles in cell fate decisions. The work provides a dynamic mechanism that shows how cell fate decisions are coordinated by two transcription factors and two miRNAs. This article is part of a Special Issue entitled: Computational Proteomics, Systems Biology and Clinical Implications. Guest Editor: Yudong Cai.