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Related Experiment Video

Updated: May 16, 2026

Clinical Microfluidic Chip Platform for the Isolation of Versatile Circulating Tumor Cells
05:58

Clinical Microfluidic Chip Platform for the Isolation of Versatile Circulating Tumor Cells

Published on: October 13, 2023

A Bioinspired Three-Dimensional High-Curvature Nano-Interface Integrated Microfluidic Chip for Small Extracellular

Le Wang1,2, Yizhong Liang2, Manan Sulaiman3

  • 1Department of Pharmacy, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|May 14, 2026
PubMed
Summary

A novel microfluidic chip rapidly isolates small extracellular vesicles (sEVs) for prostate cancer (PCa) diagnostics. This technology enables proteomic and mRNA analysis, aiding in early PCa detection and distinguishing it from benign conditions.

Keywords:
affinity interactionmachine learningprostate cancer diagnosissize recognitionsmall extracellular vesicles

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Published on: September 19, 2019

Area of Science:

  • Biomedical Engineering
  • Nanotechnology
  • Molecular Diagnostics

Background:

  • Efficient isolation of small extracellular vesicles (sEVs) from biological fluids is crucial for clinical diagnostics but remains challenging.
  • Current methods often face limitations in speed, efficiency, and unbiased recovery of sEVs.

Purpose of the Study:

  • To develop a bioinspired microfluidic chip for rapid and efficient isolation of sEVs.
  • To enable downstream proteomic and transcriptomic analysis of sEVs for prostate cancer (PCa) diagnostics.

Main Methods:

  • Integration of a 3D high-curvature TiO2 nano-interface (3D Hic-TiO2) with biotin-modified artificial insertion peptide (BAIP) on a microfluidic chip.
  • Utilizing size-selective capture via topological nanotraps and BAIP-mediated membrane affinity with chaotic mixing for sEV enrichment.
  • Employing redox-responsive BAIP for mild release of intact sEVs.

Main Results:

  • The BAIP-TiO2-Chip achieved >90% sEV capture efficiency within 5 minutes.
  • Proteomic profiling of sEVs from PCa patients identified 110 differentially expressed proteins.
  • Simultaneous quantification of PSA and PSMA mRNAs in sEVs was achieved, contributing to an 80% diagnostic accuracy for PCa using machine learning.

Conclusions:

  • The developed microfluidic platform offers a versatile solution for sEV isolation, facilitating both proteomic and mRNA analysis.
  • This technology provides new molecular insights into PCa, supporting improved early diagnosis.
  • The BAIP-TiO2-Chip demonstrates significant potential for advancing liquid biopsy applications in cancer diagnostics.