INTEGRATED MICROFLUIDIC EXOSOME PROFILING FOR EARLY DETECTION OF CANCER


Year of Award:
2014
Award Type:
R21
Project Number:
CA186846
RFA Number:
RFA-CA-13-001
Technology Track:
Molecular & Cellular Analysis Technologies
PI/Project Leader:
ZENG, YONG
Other PI or Project Leader:
N/A
Institution:
UNIVERSITY OF KANSAS LAWRENCE
Detection of asymptomatic early-stage disease is critical for effective treatment of most cancer types. For instance, when detected at Stage I, the 5-year survival rate for ovarian cancer patients is greater than 90%, versus 20% for advanced-stage disease. However, currently most cancers are diagnosed at late stages, which underscore the pressing need of novel biomarkers, strategies and technologies. Probing circulating exosomes is emerging as a new paradigm for non-invasive cancer diagnosis and monitoring of treatment response, because of growing evidences of their biological functions and clinical implications in tumorigenesis and progression. Tumor-derived exosomes accumulate in human blood and are enriched in a selective repertoire of biomolecules, including signaling proteins, enzymes, tumor antigens, miRNAs, and mRNAs. The constitutive release and exosome enrichment of certain tumor markers present distinctive opportunities for early cancer diagnosis. Despite the potential for cancer diagnosis, biology and clinical value of exosomes remain largely unknown, due to the challenges in efficient isolation, molecular classification and comprehensive characterization of exosomes. Here we propose to tackle this major roadblock by developing an innovative microfluidic technology that enables selective isolation, subpopulation classification by surface protein topography, and in situ multiplexed barcode protein profiling of exosomes, all streamlined in a 'sample-in-answer-out' system. The project consists of two specific aims: 1) Develop an integrated Microfluidic Exosome Profiling Assay (MEPA) for molecular analysis of circulating exosomes in microliter volumes of plasma; and 2) Characterize and validate MEPA for potential use in early detection of cancer using ovarian cancer as the disease model. This research, if successful, will yield a transformative technology that can substantially improve the analytical performance for molecular characterization of tumor-derived exosomes while overcoming the constraints of exosome loss/damage during isolation, analysis throughput, and sample consumption in conventional protocols. Thus the technology should offer an unprecedented ability to accelerate the exosome research, opening new opportunities to probing the biology of a tumor noninvasively and to developing novel reliable biomarkers for screening and early detection of cancer.