Ukr.Biochem.J. 2025; Volume 97, Issue 6, Nov-Dec, pp. 79-92

doi: https://doi.org/10.15407/ubj97.06.079

Enzyme-linked immunosorbent assay for the determination of total prostate-specific antigen

K. M. Shevchuk1, O. B. Besarab1*, Yu. V. Gorshunov1, O. Yu. Galkin1,2

1National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv;
2Palladin Institute of Biochemistry, National Academy of Sciences of Ukraine, Kyiv;
*e-mail: besarab@lll.kpi.ua

Received: 26 August 2025; Revised: 08 October 2025;
Accepted: 28 November 2025; Available on-line:  23 December 2025

Prostate-specific antigen (PSA) remains the most widely used biomarker for prostate cancer diagnostics and monitoring. The development of highly informative, sensitive, and reproducible immunoassays for PSA determination is essential for improving diagnostic accuracy. The aim of the study was to develop and optimize a non-competitive “sandwich” ELISA for the determination of total PSA, using a panel of monoclonal antibodies (mAbs) of different specificity groups and epitopes. “Sandwich” ELISA configurations were designed using different capture and detecting antibody pairs. Antibody sorption conditions, reagents working concentrations, incubation parameters and buffer composition were optimized. Analytical performance was evaluated using PSA preparations standardized against the WHO International Standard (96/670). The most effective antibody combinations were found among mAbs targeting epitopes P2 (capture: 21B7, 11G5, 26B9) and P3 (detection: 21F4, 23B4, 27C10), with the high-affinity pair 26B9-27C10 showing the best sorption–detection properties. The use of mixed conjugates did not improve sensitivity in the range of 1-10 ng/ml PSA. Hydrophilization of polystyrene plates surface increased the ELISA signal up to 1.39-fold, depending on the antibody isotype and origin. The developed optimized “sandwich” ELISA demonstrates high specificity and sensitivity for total PSA determination, with analytical characteristics suitable for potential clinical diagnostic applications.

Keywords: , , , , , , , ,


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