March 9, 2017 /Bio Valley BIOON/ -- A few days ago, researchers from the National Institute of Science and Technology in Ulsan, South Korea, have developed a new technology through research, which can effectively identify in urine or blood. Substances that promote cancer, related research was published in the international journal ACS Nano. Here, the researchers developed an integrated centrifugal microfluidic platform (Exodisc) capable of isolating extracellular vesicles (EVs) in urine.
The researchers hope that the technique may be used in clinical devices to detect biomarkers in urine based on extracellular membrane vesicles, a type of cell-derived nanovesicle structure that can be used in cancer diagnosis. With a size of only 40-1000 nanometers, they are present in almost all types of body fluids, while extracellular membrane vesicles also play a key role in intercellular communication and can also participate in the transport of biological signals that regulate various cellular functions. Although researchers have added extracellular vesicles as potential biomarkers for the diagnosis and prognostic evaluation of various diseases, current methods for isolating and analyzing extracellular vesicles often require long and complex processes, such as a frequently used Ultracentrifugation, a method for isolating extracellular membrane vesicles, requires multiple time-consuming steps, including centrifugation, and also requires the acquisition of large sample volumes, but tends to end up with low purity and yield.
To overcome these limitations, researchers have developed a novel, fast, size-selective platform structure that can efficiently isolate and analyze nano-sized extracellular vesicle structures from raw biological samples, such as those in cell cultures. Supernatant or urine of cancer patients. According to researcher Dr. Hyun-Kyung Woo, the new platform Exodisc consists of two independent filter units (20 nanometers and 600 nanometers in size) that can process two different samples simultaneously. By spinning, the urine sample can be transferred through two integrated nanofilters, enabling the enrichment of urine extracellular vesicle structures in the size range of 20-600 nanometers.
The size of the pores in the nanoporous filter in the platform can be set arbitrarily, so that the nano-sized vesicle structure can be effectively separated from pathogenic bacteria or unnecessary proteins. The researcher Professor Cho pointed out that using the Exodisc platform, we can The extracellular membrane vesicles in the original sample can be isolated within 30 minutes, and the process of filtration by centrifugal force is completely automated, which can effectively enrich the extracellular membrane vesicle structure.
In this study, the team tested clinical samples by isolating extracellular membrane vesicles from the urine of bladder cancer patients. They did this using this desktop-sized centrifugal microsome system. It is possible to automate the enrichment of extracellular membrane vesicles with a size of 20-600 nanometers in urine within 30 minutes; researcher Vijaya Sunkara pointed out that the use of extracellular membrane vesicles isolated from bladder cancer patients for ELISA reaction can be High levels of CD9 and CD81 expression were found, suggesting that this method may be used in clinical studies to aid in the detection of extracellular membrane vesicle-based biomarkers in urine for cancer diagnosis.
Finally, the researchers said, "We are currently conducting advanced studies to determine whether a variety of diseases, including cancer, can be determined by analyzing the collected nanoparticles. We hope that the device developed in this paper will help advance current tumors. biologically relevant research and accelerate the development of individualized therapies using extracellular vesicle-based liquid biopsy techniques.
Original source:
Hyun-Kyung Woo, Vijaya Sunkara, Juhee Park, et al. Exodisc for Rapid, Size-Selective, and Efficient Isolation and Analysis of Nanoscale Extracellular Vesicles from Biological Samples. ACS Nano, 2017, DOI: 10.1021/acsnano.6b06131
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