Using 3-D printing technologies, a team of University of Wisconsin–Madison researchers are developing new tools for understanding how ovarian cancer develops in women.
Paul Campagnola, a professor of biomedical engineering and medical physics at UW–Madison, leads a group aiming to understand how ovarian cancer cells interact with nearby body tissue, and by developing new tools for imaging and detecting the disease.
With a $2 million grant from the National Institutes of Health, they will use technology they’ve developed on the UW–Madison campus to develop images of tissues from surgical patients. The first target is collagen, a common protein that gives much of the body structure by holding bones, ligaments and muscles together.
“In most cancers, including ovarian, there are large changes in the collagen structure that goes along with the disease,” Campagnola said. “It might happen first. It might be later. It’s actually not known.”
Campagnola and his colleagues, including Kevin Eliceiri, director of UW-Madison’s Laboratory for Optical and Computational Instrumentation, and Manish Patankar, associate professor of obstetrics and gynecology, hope to eliminate that unknown by printing tiny, 3-D models of the collagen samples.
The models will be biomimetic — synthetic, but mimicking biological materials, as Velcro mimics the burs of a plant — and extremely small. Because, after seeding the models with ovarian cancer cells, the researchers will implant them into mice.
By implanting a 3-D tissue model seeded with ovarian cancer into mice, Campagnola hopes to mimic more closely the conditions of metastatic ovarian cancer in humans.
“What’s different is our tissues will already be 3-D structured,” Campagnola said. “One problem when people study cancer sometimes is that they put cells in a dish. Cells in a dish don’t act like cells in tissue. So we’re trying to give them the tissue structure that cancer cells would have in a native environment.”
From there, they’ll study how the implanted tumors grow inside the mice, and hopefully begin to learn more about the cues and processes involved in the disease’s progression and spread.
“It’s an integrated approach to improving our imaging capabilities, but then also using our imaging capabilities to make these models so we can study the biology,” Campagnola said.
Ultimately, the team’s long-term goal is to improve screening, diagnosis and treatment of ovarian cancer.