Cell-type-specific role of CHK2 in mediating DNA damage-induced G2 cell cycle arrest

Cancer is a life-threatening disease that affects one in three people. Although most cases are sporadic, cancer risk can be increased by genetic factors. It remains unknown why certain genes predispose for specific forms of cancer only, such as checkpoint protein 2 (CHK2), in which gene mutations convey up to twofold higher risk for breast cancer but do not increase lung cancer risk. We have investigated the role of CHK2 and the related kinase checkpoint protein 1 (CHK1) in cell cycle regulation in primary breast and lung primary epithelial cells. At the molecular level, CHK1 activity was higher in lung cells, whereas CHK2 was more active in breast cells. Inhibition of CHK1 profoundly disrupted the cell cycle profile in both lung and breast cells, whereas breast cells were more sensitive toward inhibition of CHK2. Finally, we provide evidence that breast cells require CHK2 to induce a G2–M cell cycle arrest in response of DNA damage, whereas lung cells can partially compensate for the loss of CHK2. Our results provide an explanation as to why CHK2 germline mutations predispose for breast cancer but not for lung cancer

Constraint-Based Modeling and Kinetic Analysis of the Smad Dependent TGF-β Signaling Pathway

Background Investigation of dynamics and regulation of the TGF-β signaling pathway is central to the understanding of complex cellular processes such as growth, apoptosis, and differentiation. In this study, we aim at using systems biology approach to provide dynamic analysis on this pathway. Methodology/Principal Findings We proposed a constraint-based modeling method to build a comprehensive mathematical model for the Smad dependent TGF-β signaling pathway by fitting the experimental data and incorporating the qualitative constraints from the experimental analysis. The performance of the model generated by constraint-based modeling method is significantly improved compared to the model obtained by only fitting the quantitative data. The model agrees well with the experimental analysis of TGF-β pathway, such as the time course of nuclear phosphorylated Smad, the subcellular location of Smad and signal response of Smad phosphorylation to different doses of TGF-β. Conclusions/Significance The simulation results indicate that the signal response to TGF-β is regulated by the balance between clathrin dependent endocytosis and non-clathrin mediated endocytosis. This model is useful to be built upon as new precise experimental data are emerging. The constraint-based modeling method can also be applied to quantitative modeling of other signaling pathways