Accurate Cancer Diagnosis and Stage Monitoring Enabled by Comprehensive Profiling of Different Types of Exosomal Biomarkers: Surface Proteins and miRNAs. Issue 48 (10th November 2020) - Zhou, Sisi; Hu, Tao; Han, Gaohua; Wu, Yafeng; Hua, Xin; Su, Juan; Jin, Weiwei; Mou, Yiping; Mou, Xiaozhou; Li, Quan; Liu, Songqin
Abstract: Exosomes are recognized as promising biomarkers for early cancer diagnosis and prognosis owing to a large amount of biological information they carried. But the key is that single type of exosomal biomarker analysis is not sufficient enough for accurate cancer diagnosis and stage monitoring due to the insufficient information and high false positive signal. To address the challenge, here simultaneous in situ detection of different types of exosomal biomarkers (surface proteins: CD81, ephrin type‐A receptor 2, and carbohydrate antigen 19‐9; miRNAs: miR‐451a, miR‐21, and miR‐10b) is conducted with a 3D microfluidic chip, which works in conjunction with quantum dot (QD) labeling and vesicle fusion technology. After exosomes are efficiently captured by the microfluidic chip, the quantification of multiple exosomal proteins is achieved by using three kinds of QDs with the same excitation and different emission wavelengths, and virus‐mimicking fusogenic vesicles encapsulating three exquisitely engineered molecular beacons are introduced for ultrasensitive detection of multiple exosomal miRNAs without requiring RNA extraction. Through comprehensive profiling different types of exosomal biomarkers, the false positive rate is substantially avoided and the accuracy of cancer diagnosis and stage monitoring is improved to ≈100%, which are critical to cancer effective treatment and favorable prognosis. Abstract : An accurate cancer diagnosis platform is established through comprehensive profiling of different types of exosomal biomarkers (surface proteins and miRNAs) with 3D microfluidic chip, which works in conjunction with quantum dot labeling and vesicle fusion technology. The chip can not only accurately distinguish cancer cells and normal cells, but also successfully discriminate cancer cell subtypes and monitor cancer stage.