A Universal Platform for Identification of Novel Lung Cancer Biomarkers Based on Exosomes
Abstract
Circulating tumor-derived extracellular vesicles (EVs) have emerged as a promising source for identifying cancer biomarkers for early cancer detection. However, the clinical utility of EVs has thus far been limited by the fact that most EV isolation methods are tedious, nonstandardized, and require bulky instrumentation such as ultracentrifugation (UC). Here, we report a size-based EV isolation tool called ExoTIC (exosome total isolation chip), which is simple, easy-to-use, modular, and facilitates high-yield and high-purity EV isolation from biofluids. ExoTIC achieves an EV yield ~41000-fold higher than that with UC, and EV-derived protein and microRNA levels are well-correlated between the two methods. Moreover, we demonstrate that ExoTIC is a modular platform that can sort a heterogeneous population of cancer cell line EVs based on size. Further, we utilize ExoTIC to isolate EVs from cancer patient clinical samples, including plasma, urine, and lavage, demonstrating the devices broad applicability to cancers and other diseases. Finally, the ability of ExoTIC to efficiently isolate EVs from small sample volumes opens up avenues for preclinical studies in small animal tumor models and for point-of-care EV-based clinical testing from fingerprick quantities (10-100 muL) of blood.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2017
- Accession Number
- AD1048377
Entities
People
- Demirci Utkan
Organizations
- Stanford University