A1 Refereed original research article in a scientific journal
High‐Sensitivity Detection of Urinary Extracellular Vesicles With Upconverting Nanoparticle‐Based Lateral Flow Immunoassay
Authors: Islam, Md. Khirul; Mahmud, Imran; Ali, Klinton; Salminen, Teppo; Taimen, Pekka; Boström, Peter J.; Leivo, Janne; Lamminmäki, Urpo; Martiskainen, Iida
Publisher: Wiley
Publishing place: HOBOKEN
Publication year: 2025
Journal: Journal of Extracellular Biology
Journal name in source: Journal of Extracellular Biology
Journal acronym: J EXTRACELL BIOL
Article number: e70053
Volume: 4
Issue: 7
Number of pages: 7
ISSN: 2768-2811
eISSN: 2768-2811
DOI: https://doi.org/10.1002/jex2.70053
Web address : https://doi.org/10.1002/jex2.70053
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/499206650
Urinary extracellular vesicles (uEVs) are well-known to express tetraspanin family membrane proteins abundantly on their surface. In this study, we aimed to develop an upconverting nanoparticle (UCNP)-based lateral flow immunoassay (UCNP-LFIA) designed for the rapid and high-sensitivity detection of CD63-positive uEVs for direct urinalysis. The assay utilizes UCNPs reporter to detect low concentrations of EVs. Minimally processed uEV samples from bladder cancer (BlCa) (n = 62), benign prostatic hyperplasia (BPH) (n = 50) and healthy (n = 30) individuals were tested in sandwich UCNP-LFIA format, capturing uEVs with the same anti-CD63 antibody conjugated to UCNP and immobilized on the test zone. After 80 min, the strips were read with an upconversion luminescence reader device. This UCNP-LFIA measured CD63-positive EVs with high sensitivity, exhibiting a limit of detection (LoD) of 4 x 107 EVs/mL. The concentration of CD63-positive EVs in BlCa patients showed a 2.3-fold increase compared to benign conditions (p = 0.007), and a 16-fold increase compared to healthy controls (p = 0.00001). The results demonstrate the potential of UCNP-LFIA platform for sensitive and quantitative detection of uEVs, highlighting its promise as a tool for EV detection at point-of-care diagnostics.
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Funding information in the publication:
Research Council of Finland. Open access publishing facilitated by Turun yliopisto, as part of the Wiley - FinELib agreement. This research was supported by the PoDoCo project funded by The Paulo Foundation and Uniogen Oy, Ella and Georg Ehrnrooth Foundation, Päivikki and Sakari Sohlberg Foundation and by the Research Council of Finland's Flagship InFLAMES (337530/357910).
