Jin Ying, Zhang Junjie, Wu Xinyi, Qu Cheng, Fang Xingru, Yang Yi, Yuan Yue, Liu Honglin, Han Zhenzhen
Department of Immunology, School of Basic Medical Sciences, Anhui Medical University, Hefei, 230032, PR China.
China Light Industry Key Laboratory of Meat Microbial Control and Utilization, School of Food and Biological Engineering, Engineering Research Center of Bio-process, Ministry of Education, Hefei University of Technology, Hefei, 230009, PR China.
Talanta. 2025 Nov 1;294:128276. doi: 10.1016/j.talanta.2025.128276. Epub 2025 May 5.
Osteosarcoma (OS) calls for early diagnosis to significantly improve patient survival rates. Exosomes hold significant potential as noninvasive biomarkers for the early diagnosis of cancer. Here, we design a microfluidic device to purify and analyze plasma-derived exosomes by label-free surface-enhanced Raman spectroscopy (SERS) profiling for OS diagnosis. Exosomes were isolated, purified, and enriched using a size-dependent microfluidic chip with tangential flow filtration, achieving a high recovery rate of 82 %. The isolated exosomes were then analyzed by label-free SERS using a nanoarray chip with self-assembly monolayers of gold nanoparticles (GNPs). Exosomes originating from different OS cell types were differentiated based on the intrinsic SERS signals. Our approach was further employed to analyze the plasma-derived exosomes from healthy donors and OS patients without the need for specific biomarker labeling. A machine learning-based diagnostic model for OS was constructed, achieving an accuracy of 93 %. The findings indicate that our method is valuable for noninvasive and precise diagnosis of OS and could be generalized to other diseases in the future.
骨肉瘤（OS）需要早期诊断以显著提高患者生存率。外泌体作为癌症早期诊断的非侵入性生物标志物具有巨大潜力。在此，我们设计了一种微流控装置，通过用于OS诊断的无标记表面增强拉曼光谱（SERS）分析来纯化和分析血浆来源的外泌体。使用具有切向流过滤的尺寸依赖性微流控芯片分离、纯化和富集外泌体，实现了82%的高回收率。然后使用具有金纳米颗粒（GNP）自组装单层的纳米阵列芯片通过无标记SERS分析分离的外泌体。基于内在SERS信号区分了源自不同OS细胞类型的外泌体。我们的方法进一步用于分析健康供体和OS患者的血浆来源外泌体，而无需特定生物标志物标记。构建了基于机器学习的OS诊断模型，准确率达到93%。研究结果表明，我们的方法对于OS的非侵入性和精确诊断具有重要价值，并且未来可能推广到其他疾病。
