Engineering High Throughput Screening Platforms of Cervical Cancer

There is a critical need for complex multicellular three-dimensional physiomimetic models of cancer that can interface with high throughput drug screening methods to assess anti-metastatic and anti-angiogenic drug efficacy in a rapid yet high content manner. We report a multilayer multicellular platform of human cervical cancer cell lines and primary human microvascular endothelial cells that incorporates critical biophysical and extracellular matrix cues, interfaces with standard high throughput drug screening methods, and can evaluate cervical cancer invasion and endothelial microvessel formation over time. Through the use of Design of Experiments statistical optimization, we identified the specific concentrations of collagen I, fibrinogen, fibronectin, GelMA, and PEGDA in each hydrogel layer that maximized cervical cancer invasion and endothelial microvessel length simultaneously. We then validated the optimized platform and assessed the viscoelastic properties of the composite hydrogels as well as their individual constituents. Finally, using this optimized platform, we conducted a targeted drug screen of four clinically relevant drugs on two cervical cancer cell lines. From these data we identified each of the cervical cancer cell lines (SiHa and Ca Ski) as either responsive or refractive to Paclitaxel, Dasitinib, Dovitinib, or Pazopanib. Overall, we developed a phenotypic drug screening platform of cervical cancer that captures cell behavior present in the cervical cancer tumor microenvironment, captures patient to patient variability, and integrates with standard high throughput high content drug screening methods. This work provides a valuable platform that can be used to screen large compound libraries for mechanistic studies, drug discovery, and precision oncology for cervical cancer patients.