Profiling the size-dependent heterogeneity of membrane proteins in a mixed population of small extracellular vesicle for potential cancer diagnosis

Abstract

AbstractThe heterogeneity in small extracellular vesicles (small EVs) introduces an extra level of complexity in small EV-based liquid biopsy for cancer diagnosis. Heterogeneous membrane protein expression is correlated with sizes of small EVs, but accessing this correlative information is limited by the precise isolation of size-dependent subpopulations. Herein, we present a single EV enumeration (SEVEN) approach to profile protein heterogeneity in size-dependent subpopulations, and demonstrate its potential in improving the accuracy of cancer diagnosis. The interferometric plasmonic microscopy (iPM) capable of imaging single biological nanoparticles with the diameter down to 30 nm is employed to detect small EVs at the single-particle level. Small EVs population with mixed sizes are directly imaged, individually sized and digitally counted during their binding onto different aptamer-coated iPM sensor surfaces. The protein expression levels and binding kinetics of three size-dependent subpopulations are analyzed, forming a multidimensional data matrix for cancer diagnosis. Using small EVs derived from different cancer cell lines, highly heterogeneous protein profiles are recorded in the three subpopulations. We further demonstrate that the cancer classification accuracy could be greatly improved by including the subpopulation level heterogeneous protein profiles as compared with conventional ensemble measurement.