Research in Engineering and Aviation
High-throughput stiffness assay for the study of cancer cell susceptibility to anti-cancer drugs
Author(s): Zustiak, S.P., Ferguson, D., Nossal, R., Sackett, D.
AIChE Symposia Proceedings, 2012 Annual Fall Meeting, Pittsburg, PA, October 2012.
Biomaterial-based in-vitro models are an emerging research field that promises to bridge the gap between traditional 2-dimensional cell culture and animal models. It is now well understood that the cell microenvironment, including the properties of the surrounding matrix such as matrix stiffness, profoundly affects cell fate. This is especially true for solid tumors where, for example, the matrix stiffness is believed to be an important factor in tumorogenesis. Our hypothesis is that since matrix stiffness affects cell fate, it may also be important in drug resistance mechanisms.
In order to test this hypothesis, we built a “high-throughput” polyacrylamide (PA)-based stiffness assay. The gels were coated with collagen in order to facilitate cell attachment and proliferation. Polyacrylamide was the material of choice because it spans stiffness values from 0.3 to 300 kPa. The “high-throughput” format was chosen in order to facilitate determination of dose response curves and to provide for simultaneous testing of multiple parameters. The assay improved upon currently available techniques in terms of preparation time, robustness, and cost.
The PA-based assay was further used to test the effect of stiffness on cancer cell responsiveness to anti-cancer drugs. In particular, we tested multiple cell lines and their susceptibility to microtubule-targeting agents (MTAs) on substrates of various stiffness. By assessing the cell’s viability and proliferation, and determining the drug’s IC50, we were able to establish that the stiffness affects cancer cell responsiveness to drugs in a cell dependent manner. We are currently evaluating possible mechanisms responsible for this finding. This work will ultimately unveil relationships between the stiffness of the cell microenvironment and cell drug response, and thus may lead to the development of more predictive drug screening platforms and, potentially, alternative cancer treatments.