Women have long endured probing and testing to determine their risk of breast cancer, but UC Berkeley researchers have now found a less invasive and more effective way to diagnose breast cancer — mechano-node-pore sensing, or mechano-NPS.
Mechano-NPS studies how soft or stiff a cell is by analyzing small samples of breast tissue. These samples are collected using random periareolar fine-needle aspiration, or RPFNA. Mechano-NPS analyzes the samples by putting individual cells through a very small channel, or micropore, and seeing how fast they can travel and rebound.
“The cancer cells were softer,” campus mechanical engineering professor Lydia Sohn said. “They could squeeze through these channels better than nonmalignant, normal ones.”
The study, which was done in collaboration with the City of Hope National Medical Center, introduced mechano-NPS as a technique that can help detect cancer earlier and with more accuracy than other techniques currently available.
“Because we’re so sensitive in our measurements, we hypothesize that we can use our methods to see if cells are cancerous at very early stages,” Sohn said. “We feel like we’ve hit the tip of the iceberg on what this platform could really do.”
Sohn has generally focused on biochemical testing, marking potentially cancerous cells with chemical markers in order to study them.
“It was actually the work of my grad student Junghyun Kim, who was pushing to look at mechanical properties of cells,” Sohn said. “The mechanical properties give you a different perspective and different information that’s more sensitive.”
Mechano-NPS tests these “mechanical properties” by squeezing cells and seeing how they respond and recover. Being able to distinguish between cell types allows researchers to differentiate cancerous and “normal” cells.
Sohn is the principal investigator of the Sohn Research Lab, which published a study March 12 about the discovery of mechano-NPS and its implications in studying breast cancer.
“Clinically, mechano-NPS may yield a new approach to early detection of breast and other types of cancer genesis,” the study text says.
The technology can also distinguish between subpopulations of breast cells. Two types were especially important in this study — myoepithelial, or MEP, and luminal epithelial, or LEP, cells. MEP cells are important for tumor suppression, while LEP cells are more likely to become cancerous.
Mechano-NPS also found that older breast tissue is less able to effectively recover after being squeezed than younger breast tissue. The higher ratio of LEP cells in older women, as well as the decreased elasticity of their cells, allows scientists to more accurately predict breast cancer risk.
“Pre-menopausal, you would see more MEPs over LEPs,” Sohn said. “Then post-menopausal, that ratio flips.”
Looking forward, mechano-NPS has many applications. In addition to diagnosing breast cancer, it can monitor how cells respond to treatment. The technology is already being applied to leukemia research, which, according to Sohn, has allowed scientists to analyze who will and will not respond to treatment.
“I’m surprised at how great our results are,” Sohn said. “It’s a very quick assessment of how well your cells are doing. Overall, it’s a very exciting, inexpensive technique.”