Exosomes, known as nanometer-sized vesicles (30–200 nm), are secreted by many types of cells. Cancer-derived exosomes have great potential to be biomarkers for early clinical diagnosis and evaluation of cancer therapeutic efficacy. Conventional detection methods are limited to low sensitivity and reproducibility. There are hundreds of papers published with different detection methods in recent years to address these challenges. Fudan University researchers comprehensively summarize pioneering researches about various detection strategies and the analytical performance of these tests is evaluated. Furthermore, the exosome molecular composition (protein and nucleic acid) profiling, a single exosome profiling, and their application in clinical cancer diagnosis are reviewed. Finally, the principles and applications of machine learning method in exosomes researches are presented.
Recent Progress in Detection and Profiling of Cancer Cell-Derived Exosomes
Xiong H, Huang Z, Yang Z, Lin Q, Yang B, Fang X, Liu B, Chen H, Kong J. (2021) Recent Progress in Detection and Profiling of Cancer Cell-Derived Exosomes. Small [Epub ahead of print]. [abstract]