Tumor-derived extracellular
vesicles (EVs) are under intensive
study for their potential as noninvasive diagnosis biomarkers. Most
EV-based cancer diagnostic assays trace supernumerary of a single
cancer-associated marker or marker signatures. These types of biomarker
assays are either subtype-specific or vulnerable to be masked by high
background signals. In this study, we introduce using the β-sheet
richness (BR) of the tumor-derived EVs as an effective way to discriminate
EVs originating from malignant and nonmalignant cells, where EV contents
are evaluated as a collective attribute rather than single factors.
Circular dichroism, Fourier transform infrared spectroscopy, fluorescence
staining assays, and a de novo workflow combining proteomics, bioinformatics,
and protein folding simulations were employed to validate the collective
attribute at both cellular and EV levels. Based on the BR of the tumorous
EVs, we integrated immunoprecipitation and fluorescence labeling targeting
the circulating tumor-derived EVs in serum and developed the process
into a clinical assay, named EvIPThT. The assay can distinguish patients
with and without malignant disease in a pilot cohort, with weak correlations
to prognosis biomarkers, suggesting the potential for a cancer screening
panel with existing prognostic biomarkers to improve overall performance.