- Sun, Na;
- Lee, Yi-Te;
- Zhang, Ryan Y;
- Kao, Rueihung;
- Teng, Pai-Chi;
- Yang, Yingying;
- Yang, Peng;
- Wang, Jasmine J;
- Smalley, Matthew;
- Chen, Pin-Jung;
- Kim, Minhyung;
- Chou, Shih-Jie;
- Bao, Lirong;
- Wang, Jing;
- Zhang, Xinyue;
- Qi, Dongping;
- Palomique, Juvelyn;
- Nissen, Nicolas;
- Han, Steven-Huy B;
- Sadeghi, Saeed;
- Finn, Richard S;
- Saab, Sammy;
- Busuttil, Ronald W;
- Markovic, Daniela;
- Elashoff, David;
- Yu, Hsiao-hua;
- Li, Huiying;
- Heaney, Anthony P;
- Posadas, Edwin;
- You, Sungyong;
- Yang, Ju Dong;
- Pei, Renjun;
- Agopian, Vatche G;
- Tseng, Hsian-Rong;
- Zhu, Yazhen
We report a covalent chemistry-based hepatocellular carcinoma (HCC)-specific extracellular vesicle (EV) purification system for early detection of HCC by performing digital scoring on the purified EVs. Earlier detection of HCC creates more opportunities for curative therapeutic interventions. EVs are present in circulation at relatively early stages of disease, providing potential opportunities for HCC early detection. We develop an HCC EV purification system (i.e., EV Click Chips) by synergistically integrating covalent chemistry-mediated EV capture/release, multimarker antibody cocktails, nanostructured substrates, and microfluidic chaotic mixers. We then explore the translational potential of EV Click Chips using 158 plasma samples of HCC patients and control cohorts. The purified HCC EVs are subjected to reverse-transcription droplet digital PCR for quantification of 10 HCC-specific mRNA markers and computation of digital scoring. The HCC EV-derived molecular signatures exhibit great potential for noninvasive early detection of HCC from at-risk cirrhotic patients with an area under receiver operator characteristic curve of 0.93 (95% CI, 0.86 to 1.00; sensitivity = 94.4%, specificity = 88.5%).