Integrated Microfluidic Chip for Neutrophil Extracellular Vesicle Analysis and Gastric Cancer Diagnosis

作者：Dan Yu, Jianmei Gu, Jiahui Zhang, Maoye Wang, Runbi Ji, Chunlai Feng, Hélder A. Santos, Hongbo Zhang, Xu Zhang · 发表于：ACS Nano · 年份：2025 · DOI：10.1021/acsnano.4c16894 · 被引用次数：30 · 研究领域：Extracellular vesicles in disease、Cell Adhesion Molecules Research、Immune cells in cancer

High Resolution Image Download MS PowerPoint Slide Neutrophil-derived extracellular vesicles (NEVs) are critically involved in disease progression and are considered potential biomarkers. However, the tedious processes of NEV separation and detection restrain their use. Herein, we presented an integrated microfluidic chip for NEV (IMCN) analysis, which achieved immune-separation of CD66b + NEVs and multiplexed detection of their contained miRNAs (termed NEV signatures) by using 10 μL serum samples. The optimized microchannel and flow rate of the IMCN chip enabled efficient capture of NEVs (>90%). After recognition of the captured NEVs by a specific CD63 aptamer, on-chip rolling circle amplification (RCA) reaction was triggered by the released aptamers and miRNAs from heat-lysed NEVs. Then, the RCA products bound to molecular beacons (MBs), initiating allosteric hairpin structures and amplified “turn on” fluorescence signals (RCA-MB assay). Clinical sample analysis showed that NEV signatures had a high area under curve (AUC) in distinguishing between healthy control (HC) and gastric cancer (GC) (0.891), benign gastric diseases (BGD) and GC (0.857). Notably, the AUC reached 0.912 with a combination of five biomarkers (NEV signatures, CEA, and CA199) to differentiate GC from HC, and the diagnostic accuracy was further increased by using a machine learning (ML)-based ensemble classification system. Therefore, the developed IMCN chip is a valuable platform for NEV analysis and may...