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Updated: Jul 4, 2026

Chemical Affinity-Based Isolation of Extracellular Vesicles from Biofluids for Proteomics and Phosphoproteomics Analysis
Published on: October 27, 2023
Bifunctional covalent organic framework for rapid isolation of extracellular vesicles and proteomics-based biomarker
Mengxi Chen1, Tingwei Ye1, Yu Hu1
1College of Pharmaceutical Sciences, Soochow University, Suzhou, 215123, China.
Abstract:
Extracellular vesicles (EVs), serving as crucial carriers of biomarkers for tumor diagnosis and prognostic evaluation, as well as drug delivery vehicles and therapeutic targets, making it a research hotspot. The isolation methods represent a key aspect of EV-associated research. In this work, an alkynyl-functionalized covalent organic framework (COF) was synthesized under acidic conditions at room temperature and further modified by photo-initiated thiol-yne click reaction, yielding a bifunctionalized COF material decorated with distearoyl phosphatidylethanolamine (DSPE) and Ti4+. This bifunctional COF material (COF-DSPE-Ti) can leverage the bifunctional synergistic effect between DSPE and Ti4+ sites, thereby facilitating the efficient isolation of EVs. This synergistic effect enables the efficient isolation of EVs within 3 min. Proteomic analysis reveals that this isolation method significantly outperforms ultracentrifugation, and an effective EV isolation and analysis can be completed using only 10 μL of plasma sample. For clinical liquid biopsy, the integration of the COF-DSPE-Ti method with proteomics lead to the identification of 64 upregulated proteins in plasma samples from colorectal cancer (CRC) patients, among which S100A9 emerged as a potential EV biomarker. In addition, KLK2, KLK3, and FOLH1, which have been established as diagnostic markers for prostate cancer (PCa), are successfully identified in EVs isolated from the urine of PCa patients. These findings demonstrate the reliability of this approach for screening EV-associated biomarkers and provide a novel strategy for the early diagnosis and prognostic assessment of CRC and PCa.

