Size-selective Circulating Tumor Cell Isolation on a Centrifugal Microfluidic Device
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- Size-selective Circulating Tumor Cell Isolation on a Centrifugal Microfluidic Device
- Lee, Ada Younglim
- Cho, Yoon-Kyoung
- Issue Date
- Graduate School of UNIST
- Detection of circulating tumor cells (CTCs) has gained increasing attention as scientists and physicians learn more about the roles these malignant cells play in metastatic cancer and disease progression. Quantification and molecular analysis of CTCs are considered very important because they can function as potential indicators of early diagnosis and prognosis of cancer metastasis. Therefore, many efforts have been made to develop a reliable method to detect the CTCs. However, one major drawback of CTC detection using a conventional microfluidic approach is that it generally requires a long and complicated processing time due to its small scale and slow fluid velocity. In addition, commonly used immunoaffinity-based positive selection method has a limitation that its recovery rate heavily relies on EpCAM expression of target CTCs, which is known to be heterogeneous among different cell types. In this thesis, a size-selective lab-on-a-disc platform is introduced for a rapid and label-free isolation of CTCs from whole blood. The polycarbonate track-etch (PCTE) membrane was utilized to isolate CTCs based on the size difference between the target cell and other blood cells. Validation of the device was performed using the MCF7 breast cancer cell line spiked into PBS buffer solution as well as healthy donor blood. The capture efficiency of approximately 50~65 % was achieved with the devised CTC isolation system. The purity of the captured cells varied, ranging from 15 % to 30 %. For the clinical studies, patient blood samples from gastric cancer and breast cancer patients were tested and analyzed. The number of CTCs ranging from 5 to 29 CTCs was captured. Overall, the CTC detection rate for the lung cancer patient was 50 %, and the detection rate for the gastric cancer patients was 38.4 %.
- Biomedical Engineering
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