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Efficient profiling of circulating extracellular vesicles (EVs) benefits noninvasive cancer diagnosis and therapeutic monitoring, but is technically hampered by tedious isolation, multistep washing, and poor sensitivity. Here, we report multifunctional bubbles that enable self-separation, wash-free, single-step, and ultrasensitive profiling of EV surface markers in plasma samples for early diagnosis and treatment monitoring of lung cancer. In this assay, the buoyancy-dominated bubble is electric field-resistant, allowing EV-responsive release of electroactive probes for electrohydrodynamic nanoshearing force-enhanced hybridization, self-separation from the electrode interface for minimizing noise in electrochemical measurements, and one-step wash-free EV profiling. This assay achieves sensitivity near a single-EV level, shows high specificity against nontarget EVs, and tracks EV phenotypic changes induced by drugs. We further show that this technology can classify plasma samples ( n = 111) between cancer patients and noncancer controls with accuracies >95%, enable accurate early diagnosis via machine learning, and monitor pre/post-surgery efficacy with higher accuracy over routine clinical serum markers. This bubble-driven one-step EV assay provides a promising wash-free quantitative tool to enable clinical precision liquid biopsies.
Zhang et al. (2025) studied this question.