Digital Profiling Subpopulations of Cancer Cell-Derived Exosomes via Aptamer-SERS Nanotags on a Wafer-Level Micropillar Array Chip
The clinical translation of exosome-based diagnostics and therapies is hindered by significant molecular heterogeneity. Current exosome phenotyping methods suffer from insufficient sensitivity, limited multiplexing capability, and poor scalability. To address these challenges, we developed a digital wafer-level micropillar array (WLM-Exo) platform. The chip features a high-surface-area micropillar array functionalized with a DSPE-PEG2000 lipid layer via Au-S bonding, enabling lipid-mediated membrane fusion for universal exosome enrichment and a uniform spatial distribution. Following capture, aptamer-based SERS nanotags bind specifically to target proteins on exosomes, generating distinct Raman signals upon laser excitation. Exosomal proteins are digitally quantified by measuring the activated area in the Raman images, exhibiting a log-log linear correlation with exosome concentration. The WLM-Exo platform demonstrates ultrasensitive detection (LOD: 2.11 particles/μL for CD63, 1.17 particles/μL for EpCAM, and 18.3 particles/μL for dual-biomarkers) and simultaneous tetra-color exosomal phenotyping capability. By enabling precise, scalable, and digital protein profiling, this technology offers significant potential for exosomes subtyping in personalized cancer diagnostics and therapeutics monitoring.
Authors
- Ruyun Jin (ORCID: https://orcid.org/0000-0001-5103-4807)
- Christopher J. Long (ORCID: https://orcid.org/0000-0002-2333-7576)
- Dongyun Zheng (ORCID: https://orcid.org/0000-0003-0124-670X)
- Chunnan Zhu (ORCID: https://orcid.org/0000-0001-7607-8523)
- Xiaofei Yang (ORCID: https://orcid.org/0000-0002-5118-7755)
- Xiaodong Lin (ORCID: https://orcid.org/0000-0002-0639-0017)
- Pan Zhang (ORCID: https://orcid.org/0000-0001-9130-5982)
- Chao Liu (ORCID: https://orcid.org/0000-0002-1251-8945)
- Chunyan Zhu (ORCID: https://orcid.org/0000-0002-2994-0376)
Institutions
- University of California, Riverside (US)
- Minzu University of China (CN)
- Peking University (CN)
- State Ethnic Affairs Commission (CN)
- University of California System (US)
Publication Details
- Journal
- ACS Sensors
- Published
- 2025-08-25
- DOI
- https://doi.org/10.1021/acssensors.5c01962
- Citations
- 1
- Primary Topic
- Extracellular vesicles in disease
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China