An exosome-based one-step high-throughput microfluidic platform for epithelial ovarian cancer diagnosis

Exosomes, reflecting the live cellular state, hold promise for non-invasive disease detection. However, the significance of exosome cargos has been underestimated, particularly in the clinic, mainly due to the scarcity of exosome. Here, we present a "one-step" high-throughput microfluidic platform integrating exosome capture, in situ lysis, and protein biomarker detection, which was further designed for epithelial ovarian cancer (EOC) detection in a prospective cohort with 2–8 μL of serum samples. Through proteomic analysis of exosomes from patients' serum, combined with cell lines, we identified total 1818 differential expressed protein (DEP) and determined DEPs to develop the EOC detection microfluidic platform via multi-step screening. Based on the results of the platform's examination of the prospective cohort, an EOC detection model (P9) was developed and validated, whose specificities reached 98.8% (95% CI, 93.6%–99.8%) in the training set and 100.0% (95% CI, 91.6%–100.0%) in the validation set. The combination of P9 and CA125 exhibited 100.0% specificity in both training and validation sets, indicating a promising non-invasive modality for EOC detection that could reduce the risks associated with false-positive results. Our study also suggests that this high-throughput microfluidic platform can be customized to target a variety of exosome cargos for diverse clinical applications.