(Credit: Purdue University)
The device consists of a small plastic case with several thin layers and an opening where a portion of tissue can be inserted. Risk factors for cancer are simulated within the micro environment, mimicking what happens in a living organism.
“We want to be able to understand how cancer starts so that we can prevent it,” said Sophie Lelièvre, a professor of cancer pharmacology at Purdue.
To develop the device, Lelièvre teamed up with Babak Ziaie, a professor of electrical and computer engineering at Purdue. Their work so far has focused on two particular risk factors for cancer: oxidative stress and tissue stiffness. The former is a chemical reaction brought on by lifestyle (diet, alcohol, smoking etc) that can alter the genome of the breast and increase the risk of cancer. Risk-on-a-chip mimics oxidative stress by producing those molecules in a cell culture system that simulates the breast ducts.
Stiffness of breast tissue has also been found to contribute to the onset and progression of breast cancer. According to the research team, the device will measure stiffness within a tunable fibre matrix, whose density is relative to stiffness.
“Unlike conventional 2D monolayer cell culture platforms, ours provides a 3D cell culture environment with engineered gradient generators that promote the biological relevance of the environment to real tissue in the body,” said Rahim Rahimi, a graduate student in Ziaie’s lab.
As cancer is a disease of gene expression - which is particular to species and organs - this type of research is not suitable for rats or mice. Indeed, different groups of women even have different risk factors, and the device will be tailorable to accommodate that, according to the team.
“We need to see if there’s a difference in primary cells from black women or Asian women or white women, because that matters,” said Lelièvre.
“The way our genome is organised depends on an individual’s ancestry and lifestyle; it’s very complex. That’s why cancer is so difficult to treat.”
As well as oxidative stress and tissue stiffness, the team says the risk-on-a-chip could be modified for other factors, with optimisation for each new condition taking between six months and a year.