High-Throughput Micro-Aperture Chip System Detects Cancer Cells

The microchip system is based on a combination of immunomagnetic separation and microfluidics for high-throughput detection of whole cells and in this system target cells bound to magnetic beads flow parallel to a microchip.

Scientists at Purdue University (West Lafayette, IN, USA) combined the two techniques of immunomagnetic separation and microfluidics. In immunomagnetic separation, magnetic beads about a micron in diameter are "functionalized," or coated with antibodies that recognize and attach to antigens on the surface of target cells. The functionalized beads recognize breast cancer and lung cancer cells in laboratory cultures.

The updated design passes the fluid through a chamber that allows for faster flow; a standard 7.5 mL fluid sample can run through the system in a matter of minutes. The beads are directed by a magnetic field to a silicon mesh containing holes 8 µm in diameter. Because the target cells are so sparse, many of the beads fail to attract any and pass through the silicon mesh. The beads that have attached to cells are too large to pass through the holes in the mesh.

The cells can be analyzed clearly under a microscope and released from the chip for further analysis by removing the magnetic field. The system was characterized by detecting human breast adenocarcinoma cell line (MCF-7) and adenocarcinomic human alveolar basal epithelial cells (A549) in culture media using anti- epithelial cell adhesion molecule (EpCAM) conjugated magnetic beads.

Cagri A. Savran, PhD, an associate professor of Biomedical Engineering at Purdue, said, “We were able to detect cancer cells with up to a 90% yield. We expect this system to be useful in a wide variety of settings, including detection of rare cells for clinical applications. What's new here is that we've built a system that can perform all of these steps on one chip. It both separates cells and also places them on a chip surface so you can count them and study them with a microscope.” The study was highlighted on September 18, 2013, in the journal Lab on a Chip.

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