NanoVelcro-Embedded MicroChips for Detection and Isolation of Circulating Tumor Cells

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November 18, 2013

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  • This presentation will introduce a new type of cell-affinity assay that is capable of detecting circulating tumor cells (CTCs) in blood samples collected from metastatic cancer patients. Similar to most of the existing approaches, anti-EpCAM was grafted onto the surfaces to distinguish CTCs from the surrounding hematologic cells. The uniqueness of our technology is the use of nanostructured surfaces, which facilitates local topographical interactions between CTCs and substrates at the very first cell/substrate contacting time point. We demonstrated the ability of these nanostructured substrates to capture CTCs in whole blood samples with significantly improved efficiency and selectivity. Abstract. Our team at UCLA has demonstrated a highly efficient, inexpensive CTC assay capable of detecting and isolating CTCs in blood samples collected from metastatic cancer patients. First, we pioneered a unique concept of “NanoVelcro” cell-affinity substrates, by which capture agent (antibodies or aptamers)-coated nanostructured surfaces were utilized to immobilize CTCs in a stationary device setting. Second, by integrating the NanoVelcro substrate with an overlaid microfluidic component that can generate vertical flows, further improved CTC capture efficiency (>85%) has been achieved as a result of the enhanced collisions between CTCs and the substrate. Side-by-side analytical validation using both artificial and patient CTC samples suggested that the sensitivity of our CTC Assay outperforms that of CellSearch. In order to further exploit CTC’s diagnostic value, we combine the use of NanoVelcro Chip with the Laser MicroDissection (LMD) technique to enable highly efficient and specific isolation of viable/preservative-free CTCs from patient blood samples. Ultimately, our goal is to carry out sequential molecular and functional analyses of the single CTCs harvested by our NanoVelcro-embedded microchips.

    Drug DiscoveryGenomicsInformatics

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