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

Area of Science:

• Biotechnology
• Analytical Chemistry
• Cancer Research

Background:

• Extracellular vesicles (EVs) carry surface proteins crucial for understanding cancer biology, especially in heterogeneous breast cancer.
• Assessing multiple surface proteins on EVs is challenging due to their small size and spatial hindrance.
• Identifying cancer-specific EV surface proteins can reveal therapeutic targets and diagnostic markers.

Purpose of the Study:

• To develop a novel sequential labeling-assisted electrochemical method for precise multiprotein analysis on individual EVs.
• To overcome spatial hindrance limitations in analyzing EV surface proteins.
• To demonstrate the method's utility in detecting breast cancer biomarkers and its potential for clinical application.

Main Methods:

• Sequential labeling of EV surface proteins using aptamer probes functionalized with electroactive nanoparticles.
• Utilizing an oxidative cleavage process mediated by the bleomycin-Fe2+ complex to enable sequential detection.
• Electrochemical analysis for quantifying target proteins like epidermal growth factor receptor and programmed death ligand-1 on EVs.

Main Results:

• The sequential labeling method effectively mitigates spatial hindrance, allowing accurate multiprotein detection on EVs.
• The method achieved precise quantification of target proteins on low concentrations of standard EVs from triple-negative breast cancer (TNBC) cells (as low as 341 particles/mL).
• Successful application to clinical blood samples from healthy individuals and TNBC patients, demonstrating diagnostic potential.

Conclusions:

• The developed method provides a feasible tool for precise, multiplexed analysis of surface proteins on individual EVs.
• This approach offers valuable protein-level information for accurate breast cancer diagnosis and personalized treatment strategies.
• The technique shows promise for early cancer diagnosis and disease-course monitoring.