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Clinical diagnosis of ovarian cancer lacks high accuracy due to the weak selection of specific biomarkers along with the circumstance biomarkers localization. Clustering analysis of proteins transported on exosomes enables a more precise screening of effective biomarkers. Herein, through bioinformatics analysis of ovarian cancer and exosome proteomes, two coexpressed proteins, EpCAM and CD24, specifically enriched, were identified, together with the development of an as-derived dual-aptamer targeted exosome-based strategy for ovarian cancer screening. In brief, a DNA ternary polymer with aptamers targeting EpCAM and CD24 was designed to present a logic gate reaction upon recognizing ovarian cancer exosomes, triggering a rolling circle amplification chemiluminescent signal. A dynamic detection range of 6 orders of magnitude was achieved by quantifying exosomes. Moreover, for clinical samples, this strategy could accurately differentiate exosomes from healthy persons, other cancer patients, and ovarian cancer patients, enabling promising
Zhao et al. (Thu,) studied this question.