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High‐Sensitivity Detection of Urinary Extracellular Vesicles With Upconverting Nanoparticle‐Based Lateral Flow Immunoassay

Islam, Md. Khirul; Mahmud, Imran; Ali, Klinton; Salminen, Teppo; Taimen, Pekka; Boström, Peter J.; Leivo, Janne; Lamminmäki, Urpo; Martiskainen, Iida

High‐Sensitivity Detection of Urinary Extracellular Vesicles With Upconverting Nanoparticle‐Based Lateral Flow Immunoassay

Islam, Md. Khirul
Mahmud, Imran
Ali, Klinton
Salminen, Teppo
Taimen, Pekka
Boström, Peter J.
Leivo, Janne
Lamminmäki, Urpo
Martiskainen, Iida
Katso/Avaa
J of Extracellular Bio - 2025 - Islam - High‐Sensitivity Detection of Urinary Extracellular Vesicles With Upconverting.pdf (746.2Kb)
Lataukset: 

Wiley
doi:10.1002/jex2.70053
URI
https://doi.org/10.1002/jex2.70053
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Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2025082790012
Tiivistelmä
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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