Profiling of single-vesicle surface proteins via droplet digital immuno-PCR for multi-subpopulation extracellular vesicles counting towards cancer diagnostics

Quantification of protein-specific extracellular vesicle (EV) subpopulations at the single-vesicle level is of great significance for cancer diagnosis. Although individual vesicle analysis has been implemented by novel emerging technologies, developing an easy-to-operate and cost-effective single EV analysis approach to promote clinical applications is still challenging. Herein, we constructed a versatile droplet digital immuno-PCR (ddiPCR) assay which integrates the high specificity of immuno-PCR and superior sensitivity of droplet digital PCR to profile the surface proteins of single EVs for multi-subpopulation EVs counting. The clinical application of the ddiPCR assay was validated by simultaneous profiling the EV proteins of CD9/CD63/CD81, HER2, EpCAM in a breast cancer cohort, and CD9/CD63/CD81, GPC-3, EpCAM in a hepatocellular carcinoma cohort (HCC). The results demonstrated that the counting of multi-subpopulation EVs could significantly distinguish patients with breast tumor or HCC from healthy controls. Furthermore, with the assistance of machine learning algorithm and under the best combination of sEV subpopulations, our method exhibited great performance in differentiating breast cancer from healthy individuals. Therefore, this study provides a promising strategy to count multi-subpopulation EVs at the single-vesicle level for cancer diagnosis.