Researchers at Oregon State University have developed a multilayer, multicellular model of cervical cancer in a 96-well format, which they say can be used to enable the simultaneous and rapid testing of multiple drug compounds.
A key element of the model is that it uses a three-dimensional cellular platform, which differs from the historic means of testing the effectiveness of anti-cancer drugs: a single layer of cells.
“Two-dimensional monolayer models aren’t able to fully replicate the tumor microenvironment since nothing in our bodies resembles a single layer of cells on a piece of hard plastic,” explained Kaitlin Fogg, senior author of the study published in the Journal of Biomedical Materials Research. “Cancer metastasis and the creation of new blood vessels the tumors need are inherently three-dimensional processes and need to move through materials that better resemble the body.”
But many 3D testing techniques don’t match up very well with standard high-throughput screening methods, Fogg said. Three-dimensional testing so far has mainly relied on plates with 24 wells, and 96-well plates are the norm for high-throughput screening.
“Our goals were to develop and validate a tumor in a dish model that approximates the cervical cancer tumor microenvironment, interfaces with existing high-throughput methods, and can evaluate cancer invasion and blood vessel formation over time,” Fogg added. “We engineered a multilayer, multicellular model of cervical cancer in a 96-well format that is significantly better than any currently available preclinical drug screening platform.”
The model enables the evaluation of hundreds of drugs at the same time and the rapid identification of those able to thwart cancer invasion and the formation of new blood vessels, she said. That’s important because at present there are no drugs used specifically to treat cervical cancer.
“I’m excited for the platform we came up with to be used in future studies that screen large compound libraries for drug discovery and precision oncology,” Fogg said. “The platform captures cell behavior in the tumor microenvironment and accounts for patient to patient variability.”