In-silico modeling for the identification of regulatory microRNA targets in epithelial mesenchymal transition

Abstract

Epithelial Mesenchymal Transition (EMT) is a common process in many cases of cancer that leads to metastasis. Current understanding of this process has determined that the capability of cancer progression is dependent on this process. Thus, there is great interest on the understanding of the complex pathway regulating this process. Previous work has established a close association between the mir200 family of microRNA and the development of EMT establishing a double negative feedback loop with ZEBl. However, there are no reports studying the quantitative properties of this system to identify the more robust targets to direct an anticancer therapy. In the present work, we constructed an in silico model of EMT in order to identify the main microRNA-regulated factors that contribute to this transition. The resulting model fits the experimental data of the NCI-60 cell line panel, leading to the identification of a strong influence on EMT by mir205a, which could be used as a breakthrough target for EMT regulation.