Computational modeling of Epithelial to Mesenchymal Transition in Breast Epithelial cells
Epithelial to mesenchymal transition (EMT) in cancer is a crucial change in cell phenotype where cells of epithelial origin lose epithelial traits such as polarity and adhesion while gaining invasive attributes of mesenchymal cells. While EMT is a central process in early embryonic morphogenesis, evidence has also shown EMT to be associated with increased aggressiveness and adverse prognosis in cancers, in particular breast cancer. In systems biology of metabolic pathways, computaional models of cellular metabolism are used to simulate functional states of the cell. In this study, we used systems biology techniques to study metabolic changes of a breast epithelial cell line (D492) during EMT (1). The human metabolic reconstruction, RECON-2, was constrained using transcriptomic data from two cellular phenotypes of D492, before and after EMT. RECON-2 is the most comprehensive representation of human metabolism that is applicable to computational modeling (2). We constructed two computational models, one epithelial cell model (Model E) and another mesenchymal cell (Model M). Simulated growth of these models revealed reduced growth of Model M. This growth retardation was largley due to the reduction in the flux through the cardiolipin synthase pathway. Alterations in amino acid and lipid metabolism were also observed between the models. These data may provide novel insights into the metabolic changes that occur in breast epithelial cells during EMT and cancer progression.
1. Sigurdsson, V., et al., Endothelial induced EMT in breast epithelial cells with stem cell properties. PLoS One, 2011. 6(9): p. e23833.
2. Thiele, I., et al., A community-driven global reconstruction of human metabolism. Nat Biotechnol, 2013. 31(5): p. 419-25.