The expression of programmed death-ligand 1 (PD-L1) on extracellular vesicles (EVs) is an emerging biomarker for cancer, and has gained particular interest for its role mediating immunotherapy. However, precise quantification of PD-L1+ EVs in clinical samples remains challenging due to their sparse concentration and the enormity of the number of background EVs in human plasma, limiting applicability of conventional approaches. In this study, we develop a high-throughput droplet-based extracellular vesicle analysis (DEVA) assay for ultrasensitive quantification of EVs in plasma that are dual positive for both PD-L1 and tetraspanin (CD81) known to be expressed on EVs. We achieve a performance that significantly surpasses conventional approaches, demonstrating 360Ã enhancement in the limit of detection (LOD) and a 750Ã improvement in the limit of quantitation (LOQ) compared to conventional plate enzyme-linked immunoassay (ELISA). Underlying this performance is DEVA's high throughput analysis of individual EVs one at a time and the high specificity to targeted EVs versus background. We achieve a 0.006% false positive rate per droplet by leveraging avidity effects that arise from EVs having multiple copies of their target ligands on their surface. We use parallelized optofluidics to rapidly process 10 million droplets per minute, â¼100Ã greater than conventional approaches. A validation study on a cohort of 14 patients with melanoma confirms DEVA's ability to match conventional ELISA measurements with reduced plasma sample volume and without the need for prior EV purification. This proof-of-concept study demonstrates DEVA's potential for clinical utility to enhance prognosis as well as guide treatment for cancer.
Ultrasensitive quantification of PD-L1+ extracellular vesicles in melanoma patient plasma using a parallelized high throughput droplet digital assay.
阅读:8
作者:Shen Hanfei, Atiyas Yasemin, Yang Zijian, Lin Andrew A, Yang Jingbo, Liu Diao, Park Juhwan, Guo Wei, Issadore David A
| 期刊: | Lab on a Chip | 影响因子: | 5.400 |
| 时间: | 2024 | 起止号: | 2024 Jul 10; 24(14):3403-3411 |
| doi: | 10.1039/d4lc00331d | ||
特别声明
1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。
2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。
3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。
4、投稿及合作请联系:info@biocloudy.com。
