Taxol reduces synergistic, mechanobiological invasiveness of metastatic cells

Abstract

Paclitaxel (Taxol) is a chemotherapy drug widely used to treat different types of solid tumors (e.g. ovarian, breast, and pancreatic). Taxol acts by hyper-stabilizing microtubules, inhibiting mitosis, and eventually causing cell apoptosis. The change in cytoskeleton dynamics likely influences the cell's ability to apply force and change shape; both are required for metastatic invasion. We have previously shown that the mechanobiological invasiveness of metastatic cells can be determined through their mechanical interactions with a synthetic polyacrylamide gel; a subset of metastatic cells indent gels in attempted invasion, while benign cells do not. In the current study, we reveal reduction due to Taxol treatment in the mechanobiological invasiveness of metastatic cancer cells, as measured by their ability to forcefully indent elastic gels. We evaluate the mechanical interaction of two human, metastatic breast cell lines, MDA-MB-231 and MDA-MB-468, with a physiological-stiffness, synthetic, non-degradable and impenetrable polyacrylamide gel. We evaluate the effects of Taxol at concentrations of 5–25 µM. Using an inverted, epifluorescence microscope we obtain images of the cells and fluorescent particles embedded at the gel surface. When cells indent the gels, the particles at the indentation location (beneath the cells) are pushed to lower focal depths. The indentation depth is then calculated by the difference in focal depths for each individual cell within a group. Treatment with Taxol rapidly (<2 h) reduces the number of indenting cells as well as their indentation depth. Specifically, the cells exhibit smaller indentations and lose their ability to synergistically and collectively apply force. In addition, the effect of Taxol increases linearly with drug concentration, and depends on the cancer cells' metastatic potential. Our synthetic gel-platform shows drug-induced reduction in the mechanobiological invasiveness capacity of metastatic cells. This approach may be extended to patient-personalized testing of drugs and optimization of drug-treatment protocols.