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Microfluidic Devices Help Diagnose Cancer

Microfluidic Devices Help Diagnose Cancer

Orange County, CA - October 31st, 2018 - When diagnosing cancer in the early stages, it has a better chance of it being curable. Most cases of cancer are detected and diagnosed after the patient feels a tumor, or when other symptoms develop. If a patient is feeling symptoms before diagnosis, it is a possibility the cancer might have already metastasized (spread to other parts of the body). The primary and secondary sites are diagnosed through imaging tests, and the tumor tissue is removed from the patient, and sent for a biopsy, to determine the type of cancer.

However, research into microfluidic devices to help diagnose cancer promises a faster and easier diagnosis. Professor Fatih Sarioglu of Georgia Tech focused on chips that can trap circulating tumor cells (CTCs), which are found in blood samples. Presently, if doctors need to find CTC’s in blood samples, they need to manually search for them using a microscope; which is similar to finding a needle in a haystack.

Professor Sarioglu designed these microfluidic chips in hopes to replace the manual techniques, giving health care physicians the ability to minimally-invasively diagnose cancer, and provide researchers with a window on cancer metastasis and progression. His device targets CTC clusters, which are known to have increased metastatic inclination, and then single CTC’s; using the multicellularity of the CTC-clusters to separate them from the blood cells.

“Inside the device, these highly metastatic CTC-clusters are held at what we call the bifurcating trap, while all other cells run unimpeded. The bifurcating trap divides the sample flow at a junction so that different cells in a cluster balance each other similar to a fulcrum. We placed tens of thousands of these bifurcating traps running in parallel over the chip so that it can process clinically relevant volumes of blood samples” said Prof. Fatih Sarioglu.

The chip has been in clinical studies on blood samples from patients with breast, prostate cancers, and melanoma. Researchers are currently working to apply the technology to other cancer types, as well as investigating the clinical efficiency of CTC-clusters.

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