posted on 2023-10-23, 16:05authored byZheng-Chi Lee, Marco Hadisurya, Zhuojun Luo, Li Li, W. Andy Tao
Extracellular vesicles (EVs) have emerged as a promising
source
of disease biomarkers for noninvasive early stage diagnoses, but a
bottleneck in EV sample processing restricts their immense potential
in clinical applications. Existing methods are limited by a low EV
yield and integrity, slow processing speeds, low sample capacity,
and poor recovery efficiency. We aimed to address these issues with
a high-throughput automated workflow for EV isolation, EV lysis, protein
extraction, and protein denaturation. The automation can process clinical
urine samples in parallel, resulting in protein-covered beads ready
for various analytical methods, including immunoassays, protein quantitation
assays, and mass spectrometry. Compared to the standard manual lysis
method for contamination levels, efficiency, and consistency of EV
isolation, the automated protocol shows reproducible and robust proteomic
quantitation with less than a 10% median coefficient of variation.
When we applied the method to clinical samples, we identified a total
3,793 unique proteins and 40,380 unique peptides, with 992 significantly
upregulated proteins in kidney cancer patients versus healthy controls.
These upregulated proteins were found to be involved in several important
kidney cancer metabolic pathways also identified with a manual control.
This hands-free workflow represents a practical EV extraction and
profiling approach that can benefit both clinical and research applications,
streamlining biomarker discovery, tumor monitoring, and early cancer
diagnoses.