Protein analysis of extracellular vesicles to monitor and predict therapeutic response in metastatic breast cancer

Fei Tian, Shaohua Zhang, Chao Liu (), Ziwei Han, Yuan Liu, Jinqi Deng, Yike Li, Xia Wu, Lili Cai, Lili Qin, Qinghua Chen, Yang Yuan, Yi Liu, Yulong Cong, Baoquan Ding, Zefei Jiang () and Jiashu Sun ()
Additional contact information
Fei Tian: National Center for Nanoscience and Technology
Shaohua Zhang: Chinese PLA General Hospital
Chao Liu: National Center for Nanoscience and Technology
Ziwei Han: National Center for Nanoscience and Technology
Yuan Liu: National Center for Nanoscience and Technology
Jinqi Deng: National Center for Nanoscience and Technology
Yike Li: National Center for Nanoscience and Technology
Xia Wu: Chinese PLA General Hospital
Lili Cai: Chinese PLA General Hospital
Lili Qin: Chinese PLA General Hospital
Qinghua Chen: National Center for Nanoscience and Technology
Yang Yuan: Chinese PLA General Hospital
Yi Liu: Chinese PLA General Hospital
Yulong Cong: Chinese PLA General Hospital
Baoquan Ding: National Center for Nanoscience and Technology
Zefei Jiang: Chinese PLA General Hospital
Jiashu Sun: National Center for Nanoscience and Technology

Nature Communications, 2021, vol. 12, issue 1, 1-13

Abstract: Abstract Molecular profiling of circulating extracellular vesicles (EVs) provides a promising noninvasive means to diagnose, monitor, and predict the course of metastatic breast cancer (MBC). However, the analysis of EV protein markers has been confounded by the presence of soluble protein counterparts in peripheral blood. Here we use a rapid, sensitive, and low-cost thermophoretic aptasensor (TAS) to profile cancer-associated protein profiles of plasma EVs without the interference of soluble proteins. We show that the EV signature (a weighted sum of eight EV protein markers) has a high accuracy (91.1 %) for discrimination of MBC, non-metastatic breast cancer (NMBC), and healthy donors (HD). For MBC patients undergoing therapies, the EV signature can accurately monitor the treatment response across the training, validation, and prospective cohorts, and serve as an independent prognostic factor for progression free survival in MBC patients. Together, this work highlights the potential clinical utility of EVs in management of MBC.

Date: 2021
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DOI: 10.1038/s41467-021-22913-7

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