Nano-plasmonic technology for high-throughput single exosome analyses


Year of Award:
2019
Status:
Active
Award Type:
R21
Project Number:
CA217662
RFA Number:
RFA-CA-18-002
Technology Track:
Molecular & Cellular Analysis Technologies
PI/Project Leader:
IM, HYUNGSOON
Other PI or Project Leader:
Not Applicable
Institution:
MASSACHUSETTS GENERAL HOSPITAL
Extracellular vesicles (EVs) present new opportunities for cancer diagnoses and treatment monitoring ascirculating biomarkers. These cell-derived membrane-bound vesicles are abundantly present in biological fluidsand carry cell-specific cargos, such as lipids, proteins and genetic materials, which can be harnessed as aminimally invasive means to probe the molecular status of tumors. EV analyses, however, poses uniquetechnical challenges due to EVs' nanometer size, heterogeneity, and presence in vast biological background.We have previously developed nanoplasmonic sensing platforms that can rapidly and sensitively detect tumorEVs directly from clinical samples. Drawing upon our previous experiences with the prototypes, the goal of thisapplication is to further advance the cutting-edge nanoplasmonics technology for comprehensive molecularanalyses at single EV resolution. Specifically, we will 1) adapt gold nanorod structures that provides highersensitivity down to a single molecular level and 2) integrate plasmon-enhanced fluorescence detection formultiplexed EV protein and RNA analyses in single EVs. We hypothesize that the approach will be moresensitive and comprehensive in profiling EV protein and mRNA markers than is currently possible. Using anovarian cancer as a model system, we will evaluate 1) system implementation for high-throughput single EVdetection; 2) reliable detection of tumor-derived EVs in clinical samples; and 3) multiplexed EV markerscreening on tumor-derived EVs. If successful, the developed platform would render a more accessible tool tosignificantly accelerate the clinical adoption of EV analyses as routine screening tests for cancer care in clinicalsettings.