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Device And Method Of Identifying Exosomes Label-Free

Technology Benefits
Fast  Economical  High resolution  Label-free
Technology Application
Early stage cancer detection Diagnosis of disease from bodily fluids Identification of exosomes
Detailed Technology Description
UCLA researchers have developed a new method for identifying exosomes based on their biological composition as well as their size using surface enhanced Raman spectroscopy (SERS) with 2D mapping of SERS plus multivariate analysis/machine learning. Comparing to other methods reported in the literature, our method affords higher level of certainty, and offers more information about the content of captured exosomes.The method consists of establishing a database of the Raman spectra of exosomes of known type and origin that are known as training samples. The Raman spectra of test samples will then be compared to the database in a way much like the use of fingerprints for identifying people.
Others

Background

Exosomes contain proteins, messenger RNAs (mRNA), microRNAs (miRNA), and lipids. Cancer cells have been shown to secret exosomes excessively compared to normal cells. There are also ample evidence implicating the process of exosome secretion, transport, and uptake by distant cells as one of the pathways of cancer metastasis. The vesicle membrane protects the content from the environment allowing exosomes to travel long distances in the body and still keep the content intact. Exosomes hold a wealth of information about their parent cells. As a result, exosomes can be used as biomarkers for remote sensing of the state of these cells as exosomes are present in all bodily fluids including blood, saliva, urine, etc. They hold the promise of screening for and early detection of cancer. Current methods for exosomes isolation and identification such as mass spectrometry, flow cytometry and western blot are insufficient for clinical applications.


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Tech ID/UC Case

29393/2017-696-0


Related Cases

2017-696-0

*Abstract
UCLA researchers in the Department of Materials Science and Engineering have developed a new method of using surface enhanced Raman spectroscopy (SERS) with 2D mapping of SERS plus multivariate analysis/machine learning to identify exosomes based on composition and size.
*Principal Investigator

Name: Ya-Hong Xie

Department:

Country/Region
USA

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