适体
卵巢癌
外体
微泡
计算生物学
蛋白质组学
癌症
癌症研究
生物
小RNA
生物信息学
分子生物学
生物化学
遗传学
基因
作者
Ming Zhao,Li Q,Yan Zhao,Hanlin Zhou,Yuntian Yan,Rongmei Kong,Qian Tan,Weiheng Kong,Fengli Qu
出处
期刊:ACS Sensors
[American Chemical Society]
日期:2024-04-18
标识
DOI:10.1021/acssensors.4c00270
摘要
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 in situ detection. By accurately selecting biomarkers and constructing a dual-targeted exosomal protein detection strategy, the limitation of insufficient specificity of traditional protein markers was circumvented. This work contributed to the development of exosome-based prognosis monitoring in ovarian cancer through the identification of disease-specific exosome protein markers.
科研通智能强力驱动
Strongly Powered by AbleSci AI