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

Author

Listed:
  • Fei Tian

    (National Center for Nanoscience and Technology
    University of Chinese Academy of Sciences)

  • Shaohua Zhang

    (Chinese PLA General Hospital)

  • Chao Liu

    (National Center for Nanoscience and Technology
    University of Chinese Academy of Sciences)

  • Ziwei Han

    (National Center for Nanoscience and Technology
    University of Chinese Academy of Sciences)

  • Yuan Liu

    (National Center for Nanoscience and Technology)

  • Jinqi Deng

    (National Center for Nanoscience and Technology)

  • Yike Li

    (National Center for Nanoscience and Technology
    University of Chinese Academy of Sciences)

  • 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
    University of Chinese Academy of Sciences)

  • 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
    University of Chinese Academy of Sciences)

  • Zefei Jiang

    (Chinese PLA General Hospital)

  • Jiashu Sun

    (National Center for Nanoscience and Technology
    University of Chinese Academy of Sciences)

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.

Suggested Citation

  • 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 & Jiashu, 2021. "Protein analysis of extracellular vesicles to monitor and predict therapeutic response in metastatic breast cancer," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-22913-7
    DOI: 10.1038/s41467-021-22913-7
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    Cited by:

    1. Yike Li & Shaohua Zhang & Chao Liu & Jinqi Deng & Fei Tian & Qiang Feng & Lili Qin & Lixiao Bai & Ting Fu & Liqin Zhang & Yuguang Wang & Jiashu Sun, 2024. "Thermophoretic glycan profiling of extracellular vesicles for triple-negative breast cancer management," Nature Communications, Nature, vol. 15(1), pages 1-15, December.

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