Gold Nanopyramid Arrays for Non-Invasive Surface-Enhanced Raman Spectroscopy-Based Gastric Cancer Detection via sEVs
Zirui Liu, Tieyi Li, Zeyu Wang, Jun Liu, Shan Huang, Byoung Hoon Min, Ji Young An, Kyoung Mee Kim, Sung Hoon Kim, Yiqing Chen, Huinan Liu, Yong Kim, David T. Wong, Tony Jun Huang, Ya‐Hong Xie
Abstract
= 15 each) and analyzed. The algorithm prediction accuracies were reportedly 90, 85, and 72%. "Leave-a-pair-of-samples out" validation was further performed to test the clinical potential. The area under the curve of each receiver operating characteristic curve was 0.96, 0.91, and 0.65 in tissue, blood, and saliva, respectively. In addition, by comparing the SERS fingerprints of individual vesicles, we provided a possible way of tracing the biogenesis pathways of patient-specific sEVs from tissue to blood to saliva. The methodology involved in this study is expected to be amenable for non-invasive detection of diseases other than GC.