4.6 Article

Nanoplasmonic Sandwich Immunoassay for Tumor-Derived Exosome Detection and Exosomal PD-L1 Profiling

Journal

ACS SENSORS
Volume 6, Issue 9, Pages 3308-3319

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acssensors.1c01101

Keywords

exosomes; exosomal protein; programmed death ligand 1 (PD-L1); gold-silver core-shell nanobipyramids (Au@Ag NBPs); localized surface plasmon resonance (LSPR); microfluidics; immunoassay

Funding

  1. NIH MIRA [R35GM133795, R35GM133646]
  2. NSF CAREER [CBET-1943302]
  3. NSF [CBET-1701322, DMR-2005194]
  4. CPU2AL Seed Grant

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Tumor-derived exosomes are crucial in cancer development, and quantitative analysis of exosomes can provide valuable predictive biomarkers. The role of exosomal PD-L1 in immune checkpoint therapy suggests the potential clinical application of exosomes.
Tumor-derived exosomes play a vital role in the process of cancer development. Quantitative analysis of exosomes and exosome-shuttled proteins would be of immense value in understanding cancer progression and generating reliable predictive biomarkers for cancer diagnosis and treatment. Recent studies have indicated the critical role of exosomal programmed death ligand 1 (PD-L1) in immune checkpoint therapy and its application as a patient stratification biomarker in cancer immunotherapy. Here, we present a nanoplasmonic exosome immunoassay utilizing gold-silver (Au@Ag) core-shell nanobipyramids and gold nanorods, which form sandwich immune complexes with target exosomes. The immunoassay generates a distinct plasmonic signal pattern unique to exosomes with specific exosomal PD-L1 expression, allowing rapid, highly sensitive exosome detection and accurate identification of PD-L1 exosome subtypes in a single assay. The developed nanoplasmonic sandwich immunoassay provides a novel and viable approach for tumor cell-derived exosome detection and analysis with quantitative molecular details of key exosomal proteins, manifesting its great potential as a transformative diagnostic tool for early cancer detection, prognosis, and post-treatment monitoring.

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