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Updated: May 13, 2026

In Vivo Immunogenicity Screening of Tumor-Derived Extracellular Vesicles by Flow Cytometry of Splenic T Cells
Published on: September 23, 2021
Selective Recognition of Tumor-Derived EVs by EpCAM-Imprinted Polymers for Proteomic Biomarker Discovery
Wenjing Yu1, Fengxiang Lou2, Luxi Chen1
1School of Life Sciences, Jilin University, Changchun 130012, China.
Abstract:
EpCAM, a key biomarker for epithelial tumors, is overexpressed in multiple cancers and enriched on tumor-derived extracellular vesicles (EVs), positioning it as a promising liquid biopsy target. However, conventional isolation methods such as ultracentrifugation suffer from nonspecific adsorption and interference from normal EVs, obscuring critical biological information. In this study, we developed a highly selective artificial antibody material based on molecular imprinting technology, using the N-terminal sequence of EpCAM as a template for targeted capture of EpCAM-positive (EpCAM+) EVs. The resulting molecularly imprinted polymer (MIP) exhibited an adsorption capacity of 11.76 × 103 μg/g and an imprinting factor of 6.02, demonstrating excellent template recognition. At the cellular level, MIP selectively bound to EpCAM-high tumor cells (e.g., PANC-1, HeLa) while showing negligible adsorption to normal cells (293T), confirming its targeting specificity. Proteomic analysis of preoperative versus postoperative urine samples and matched tumor versus peritumor tissues revealed that MIP-captured EVs reliably reflect tumor status, with tumor-associated proteins such as GPC1 and TIMP1 exhibiting consistent expression changes across both sample types. In summary, this study establishes a method for specific capture of EpCAM+ EVs in complex biological environments. The low cost and high stability of the MIP material offer a novel tool for liquid biopsy. With further validation using large-scale clinical samples, this approach may have potential for advancing EpCAM+ EV-based early diagnosis of malignant tumors such as pancreatic cancer (PC) and for enabling new strategies in tumor microenvironment research and personalized therapy.

