Detection of reliable biomarkers that represent treatment response and drug resistance remains a major
clinical challenge for ovarian cancer. Extracellular vesicles (EVs) represent new opportunities as emerging
circulating cancer biomarkers. These cell-derived membrane-bound vesicles contain protein and nucleic acid
cargos, which could represent a molecular `snapshot' of tumors. Namely, molecular analyses of tumor-derived
EVs have shown promise to enable non-invasive, real-time cancer monitoring. A major technical challenge in
further exploiting EVs' potential and accelerating their clinical translation is developing a sensitive, robust, and
standardized assay that can determine EVs' composition, cellular origins, and molecular profiles in clinical
samples. Most EVs are small vesicles with limited numbers of epitopes and surface areas for immunolabeling
(i.e., weak detectable signals), which often require sophisticated multi-step signal amplification strategies. A
key aspect of new EV assays is thus a robust signal amplification strategy; otherwise, a significant fraction of
EVs remain undetected. The overall goal of this application is to address these technical challenges by
developing an integrated nanoplasmonic sensing platform. Termed nano-CRISPR, the new system will
incorporate single EV capture and analysis using plasmonic nanodisk arrays, CRISPR/Cas13a sensors for
lysis-free, amplification-free RNA detection in captured single EVs, and plasmon enhancement for simple,
robust signal amplification. Using the integrated system, we will perform rigorous validation experiments using
cell lines and patient-derived 3D organoid models with different drug responses, establish a standard operating
protocol, and evaluate the assay reproducibility in research and clinical settings. Finally, we will apply the nano-
CRISPR technology to comprehensively profile EVs in serially collected human plasma samples of ovarian
cancer patients undergoing treatment. Success here will produce an advanced EV detection platform with high
sensitivity and multiplexed biomarker sensing capability. This will help the field understand how well EVs'
molecular profiles offer additional insight into cancer progress or treatment response and could significantly
accelerate the clinical translation of EV analyses as routine procedures for cancer patient care in clinical
settings.