Chemotaxis model for human breast cancer cells based on signal-to-noise ratio

ABSTRACT Chemotaxis, a biased migration of cells under a chemical gradient, plays a significant role in diverse biological phenomena including cancer metastasis. Stromal cells release signaling proteins to induce chemotaxis, which further causes organ-specific metastasis. Epidermal growth factor (EGF) is an example of the chemical attractants, and its gradient stimulates metastasis of breast cancer cells. Hence, the interactions between EGF and breast cancer cells have long been a subject of interest for oncologists and clinicians. However, most current approaches do not systematically separate the effects of gradient and absolute concentration of EGF on chemotaxis of breast cancer cells. In this work, we develop a theoretical model based on signal-to-noise ratio to represent stochastic properties and report our microfluidic experiments to verify the analytical predictions from the model. The results demonstrate that even under the same EGF concentration gradients, breast cancer cells can reveal distinct chemotaxis patterns at different absolute concentrations. Moreover, we found that addition of EGF receptor antibody can promote chemotaxis at a low EGF level. This apparently counterintuitive finding suggests that EGF receptor-targeted therapy may stimulate metastasis of breast cancer at a particular condition, which should be considered in anticancer drug design.