isolating cancer cells
Written by Brian M. Mullen
CLEMSON — Clemson University and the University of Georgia may compete on the football field, but researchers from the two institutions continue working together to develop low-cost technology that can detect and isolate cancer cells.
Researchers Jian He and Leidong Mao discovered a new method to separate mixtures of particles with different magnetic properties. They recently published their findings in journal Microfluidics and Nanofluidics.
The researchers can use their newly discovered technology to isolate cancer cells with magnetic particles from a sample.
Under external magnetic field gradients, particles with a larger magnetization within the ferrofluids — liquids that become strongly magnetized in the presence of a magnetic field — are attracted to a magnet while the ones with a smaller magnetization are pushed away from it.
Based on this principle, the researchers developed a device that can isolate magnetic and non-magnetic particles as well as particles with different magnetizations.
“Conventional equipment for measuring magnetic properties of materials is large and expensive,” said He, assistant professor of physics and astronomy at Clemson. “Our device allows for measuring magnetic properties of materials using a small device that works quickly and leaves a small footprint.”
This method is simple, cost-effective and label-free compared to other existing techniques, according to the researchers.
“Being able to measure magnetic properties in a low-cost and fast fashion is of great importance in the area of biomedical research,” said Mao, associate professor in the College of Engineering at the University of Georgia. “We aim to use our technique not only to measure magnetic properties, but also as a diagnostic tool to distinguish between normal cells and cancer cells in the long run.”
This research collaboration will continue to build on current results of their technology and apply to other types of applications including materials research and cancer diagnostics.
This material is based upon work supported by the National Science Foundation under grant number DMR 1008073 and National Institutes of Health under grant number 5R21GM104528. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding agencies.