A checkpoint-oriented cell cycle simulation model

Modeling and <i>in silico</i> simulations are of major conceptual and applicative interest in studying the cell cycle and proliferation in eukaryotic cells. In this paper, we present a cell cycle checkpoint-oriented simulator that uses agent-based simulation modeling to reproduce the dynamics of a cancer cell population in exponential growth. Our <i>in silico</i> simulations were successfully validated by experimental <i>in vitro</i> supporting data obtained with HCT116 colon cancer cells. We demonstrated that this model can simulate cell confluence and the associated elongation of the G1 phase. Using nocodazole to synchronize cancer cells at mitosis, we confirmed the model predictivity and provided evidence of an additional and unexpected effect of nocodazole on the overall cell cycle progression. We anticipate that this cell cycle simulator will be a potential source of new insights and research perspectives. This figure describes the input biological data (doubling time and cell cycle distribution) and the two main outputs of the simulator. The simulator offers several tools to analyze cell cycle progression/distribution and provides a virtual dynamic view of the cell cycle parameters. Moreover, the simulator allows testing hypotheses, such as challenging the cell cycle checkpoints.