Early Cancer\nDetection via Multi-microRNA Profiling\nof Urinary Exosomes Captured by Nanowires

Multiple microRNAs encapsulated in extracellular vesicles\n(EVs)\nincluding exosomes, unique subtypes of EVs, differ in healthy and\ncancer groups of people, and they represent a warning sign for various\ncancer scenarios. Since all EVs in blood cannot be transferred from\ndonor to recipient cells during a single blood circulation, kidney\nfiltration could pass some untransferred EVs from blood to urine.\nPreviously, we reported on the ability of zinc oxide nanowires to\ncapture EVs based on surface charge and hydrogen bonding; these nanowires\nextracted massive numbers of microRNAs in urine, seeking cancer-related\nmicroRNAs through statistical analysis. Here, we report on the scalability\nof the nanowire performance capability to comprehensively capture\nEVs, including exosomes, in urine, extract microRNAs from the captured\nEVs <i>in situ</i>, and identify multiple microRNAs in the\nextracted microRNAs differing in noncancer and lung cancer subjects\nthrough machine learning-based analysis. The nanowire-based extraction\nallowed the presence of about 2500 species of urinary microRNAs to\nbe confirmed, meaning that urine includes almost all human microRNA\nspecies. The machine learning-based analysis identified multiple microRNAs\nfrom the extracted microRNA species. The ensembles could classify\ncancer and noncancer subjects with the area under the receiver operating\ncharacteristic curve of 0.99, even though the former were staged early.