- Main
Bio-Inspired NanoVilli Chips for Enhanced Capture of Tumor-Derived Extracellular Vesicles: Toward Non-Invasive Detection of Gene Alterations in Non-Small Cell Lung Cancer
- Dong, Jiantong;
- Zhang, Ryan Y;
- Sun, Na;
- Smalley, Matthew;
- Wu, Zipeng;
- Zhou, Anqi;
- Chou, Shih-Jie;
- Jan, Yu Jen;
- Yang, Peng;
- Bao, Lirong;
- Qi, Dongping;
- Tang, Xinghong;
- Tseng, Patrick;
- Hua, Yue;
- Xu, Dianwen;
- Kao, Rueihung;
- Meng, Meng;
- Zheng, Xirun;
- Liu, Ying;
- Vagner, Tatyana;
- Chai, Xiaoshu;
- Zhou, Dongjing;
- Li, Mengyuan;
- Chiou, Shih-Hwa;
- Zheng, Guangjuan;
- Di Vizio, Dolores;
- Agopian, Vatche G;
- Posadas, Edwin;
- Jonas, Steven J;
- Ju, Shin-Pon;
- Weiss, Paul S;
- Zhao, Meiping;
- Tseng, Hsian-Rong;
- Zhu, Yazhen
- et al.
Published Web Location
https://doi.org/10.1021/acsami.9b01406Abstract
Tumor-derived extracellular vesicles (EVs) present in bodily fluids are emerging liquid biopsy markers for non-invasive cancer diagnosis and treatment monitoring. Because the majority of EVs in circulation are not of tumor origin, it is critical to develop new platforms capable of enriching tumor-derived EVs from the blood. Herein, we introduce a biostructure-inspired NanoVilli Chip, capable of highly efficient and reproducible immunoaffinity capture of tumor-derived EVs from blood plasma samples. Anti-EpCAM-grafted silicon nanowire arrays were engineered to mimic the distinctive structures of intestinal microvilli, dramatically increasing surface area and enhancing tumor-derived EV capture. RNA in the captured EVs can be recovered for downstream molecular analyses by reverse transcription Droplet Digital PCR. We demonstrate that this assay can be applied to monitor the dynamic changes of ROS1 rearrangements and epidermal growth factor receptor T790M mutations that predict treatment responses and disease progression in non-small cell lung cancer patients.
Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.
Main Content
Enter the password to open this PDF file:
-
-
-
-
-
-
-
-
-
-
-
-
-
-