State Key Laboratory of High-Performance Ceramics and Superfine Microstructures, Shanghai Institute of Ceramics, Chinese Academy of Sciences, 1295 Dingxi Road, Shanghai, 200050, China; Graduate School of the Chinese Academy of Sciences, No.19(A) Yuquan Road, Beijing, 100049, China; Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China.
State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, 200032, Shanghai, China.
Biosens Bioelectron. 2022 Sep 1;211:114372. doi: 10.1016/j.bios.2022.114372. Epub 2022 May 15.
The tissue inhibitor of metalloproteinases-1 (TIMP-1) protein can regulate the expression of certain proteases and microRNAs in cancer cells, and it is highly possible to diagnose cancers through analyzing the expression of TIMP-1 on exosomes. However, it is still a great challenge to obtain reliable physiological information on TIMP-1 by label-free method from exosomes in plasma. Here, we designed a porous-plasmonic SERS chip functionalized with synthesized CP05 polypeptide, which can specifically capture and distinguish exosomes from diverse origins. The SERS chip can accurately locate the plasmon in TIMP-1 protein to analyze the discrepancy of related fingerprint peaks of different exosomes. Based on the designed SERS chip, we successfully distinguished the lung and colon cancer cell-derived exosomes from normal exosomes at the single vesicle level by unique Raman spectroscopy and machine learning methods. This work not only provides a practical SERS chip for the application of Raman technology in human tumor monitoring and prognosis, but also provides a new idea for analyzing the feature of exosomes at the spectral level.
组织金属蛋白酶抑制剂-1（TIMP-1）蛋白可以调节癌细胞中某些蛋白酶和 microRNAs 的表达，通过分析外泌体中 TIMP-1 的表达，很有可能诊断癌症。然而，通过无标记方法从血浆中外泌体中获得关于 TIMP-1 的可靠生理信息仍然是一个巨大的挑战。在这里，我们设计了一种多孔等离子体 SERS 芯片，该芯片用合成的 CP05 多肽功能化，能够特异性地捕获和区分来自不同来源的外泌体。SERS 芯片可以准确地定位 TIMP-1 蛋白中的等离子体，分析不同外泌体相关指纹峰的差异。基于设计的 SERS 芯片，我们成功地通过独特的拉曼光谱和机器学习方法，在外泌体的单囊泡水平上区分了肺癌和结肠癌来源的外泌体与正常外泌体。这项工作不仅为拉曼技术在人类肿瘤监测和预后中的应用提供了一种实用的 SERS 芯片，也为在光谱水平上分析外泌体的特征提供了一个新的思路。
