Chemotaxis model for 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 leads to 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 (0 – 50 ng/ml or 0 – 150 ng/ml), breast cancer cells reveal more evident chemotaxis pattern when the absolute EGF concentrations are low. Moreover, we found that reducing the number of EGF receptors (EGFRs) with addition of EGFR antibody (1 ng/ml) can promote chemotaxis at an EGF gradient of 0 – 1 ng/ml as shown by chemotaxis index (0.121 ± 0.037, reduced EGFRs vs. 0.003 ± 0.041, control). This counterintuitive finding suggests that EGFR-targeted therapy may stimulate metastasis of breast cancer as the partial suppression of the receptors makes the number of receptors close to the optimal one for chemotaxis. This analysis should be considered in anticancer drug design.