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  2. Sequential Labeling-Assisted Precise and Multitarget Analysis of Surface Proteins on Extracellular Vesicles

Sequential Labeling-Assisted Precise and Multitarget Analysis of Surface Proteins on Extracellular Vesicles

  • Anal Chem. 2025 Jun 3;97(21):11073-11081. doi: 10.1021/acs.analchem.5c00326.
Xiaomeng Yu 1 Ya Cao 1 Jianan Xia 2 Kai Zhang 3 Zihan Zou 2 Jie Yang 1 Zhaoyin Wang 4 5 Jing Zhao 2
Affiliations

Affiliations

  • 1 State Key Laboratory of Analytical Chemistry for Life Science, School of Life Sciences, Nanjing University, Nanjing 210023, PR China.
  • 2 Center for Molecular Recognition and Biosensing, Shanghai Engineering Research Center of Organ Repair, Joint International Research Laboratory of Biomaterials and Biotechnology in Organ Repair (Ministry of Education), School of Life Sciences, Shanghai University, Shanghai 200444, China.
  • 3 Department of Gastroenterology, Dongying People's Hospital, Dongying 257091, China.
  • 4 Jiangsu Collaborative Innovation Center of Biomedical Functional Materials and Jiangsu Key Laboratory of Biofunctional Materials, School of Chemistry and Materials Science, Nanjing Normal University, Nanjing 210023, China.
  • 5 State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210093, China.
Abstract

Analysis of multiple surface proteins on extracellular vesicles (EVs) can reveal biological characteristics and potential therapeutic targets of Cancer, particularly in highly heterogeneous breast Cancer. However, due to the limited surface area of EVs, spatial hindrance remains a challenge for multiprotein assessment. Here, we present a sequential labeling-assisted electrochemical method for the precise and multitarget analysis of surface proteins on EVs, using breast cancer-related epidermal growth factor receptor and programmed death ligand-1 as examples. This sequential labeling is achieved through the use of a pair of aptamer probes functionalized with electroactive nanoparticles and an oxidative cleavage process facilitated by the bleomycin-Fe2+ complex. The results demonstrate that sequential labeling efficiently avoids the adverse effects of spatial hindrance, enabling accurate analysis of target surface proteins on as low as 341 particles/mL of standard EVs derived from triple-negative breast Cancer (TNBC) cells. Moreover, this sequential labeling-assisted method is successfully applied to clinical blood samples from healthy individuals and TNBC patients, highlighting its potential utility in early diagnosis and disease-course monitoring of breast Cancer. Therefore, this work offers a feasible tool for the precise identification and analysis of multiple surface proteins on individual EVs, providing valuable information at the protein level for the accurate diagnosis and personalized treatment of breast Cancer.

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