Immunomagnetic Assay Using Upconversion Nanoparticles for the Detection of Prostate-Specific Antigen
| Autoři | |
|---|---|
| Rok publikování | 2022 |
| Druh | Konferenční abstrakty |
| Fakulta / Pracoviště MU | |
| Citace | |
| Popis | Prostate-specific antigen (PSA) is one of the most important biomarkers of prostate cancer, the leading cause of death in the male population caused by oncologic diseases. Sensitive biomarker detection is essential for early-stage disease diagnosis, enabling more effective treatment. Immunochemical methods, such as enzyme-linked immunosorbent assay (ELISA), are considered the gold standard for PSA detection. However, there are several limitations that render ELISA insufficient regarding the sensitivity required for early-stage diagnosis. Photon-upconversion nanoparticles (UCNPs) are nanocrystals that exhibit anti-Stokes luminescence, thus avoiding optical background interference. When conjugated with biorecognition molecules (antibodies or streptavidin), UCNPs can be used as a sensitive label in various immunoassay formats, including microtiter plate-based upconversion-linked immunosorbent assay (ULISA). However, as many biomarkers are present in extremely low levels, even ULISA may still not be sensitive enough, making it necessary to search for new, even more sensitive approaches. Magnetic microparticles represent a promising alternative for microtiter plates used in immunoassays, mainly for their superparamagnetic properties that allow for analyte preconcentration and thus higher assay sensitivity. We have developed a sandwich immunoassay for PSA based on magnetic microparticles and UCNP-based labels. The assay reached an LOD of 93 pg/mL, comparable to an ELISA using identical immunoreagents. Consequently, magnetic preconcentration was utilized, resulting in an LOD of 0,46 pg/mL, which represents a 31-fold improvement compared to the ELISA. The achieved results demonstrate the potential of using magnetic microparticles combined with UCNPs for the sensitive detection of cancer biomarkers. |
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