Abstract

BackgroundDetecting cancer biomarker levels in body fluids is essential for medical diagnosis. Enzyme-linked immunosorbent assay (ELISA) has been broadly used to detect cancer biomarkers. However, colorimetric ELISA based solely on nanoparticles (NPs) are susceptible to environmental influences, which often results in the detection inaccuracy, being limited in clinical applications. In this regard, the dual-mode approach would add signal diversity to the detection, making the results more reliable. ResultsWe present colorimetric and photothermal immunosensor that enables direct reading of the color and temperature of the solution. A core-satellite nanoprobe constructed by polydopamine (PDA) as the core and gold seeds as satellites is rationally designed as the signal reporter. When ascorbic acid is present in the solution, PDA can cooperate with ascorbic acid to reduce chloroauric acid and mediate the growth of gold seeds on the PDA surface, inducing a redshift of the localized surface plasmon resonance peak of the nanosensor and the change in photothermal conversion efficiency. The method is further combined with the sandwiched immunoassay to construct an alkaline phosphatase based colorimetric and photothermal ELISA for the highly sensitive and accurate evaluation and detection of prostate-specific antigen (PSA). The linear range was from 0.05 to 100 ng mL−1 with a detection limit of 6.71 pg mL−1 for the colorimetric detection, while the linear range was from 0.5 to 90 ng mL−1 with a detection limit of 0.13 ng mL−1 in the photothermal analysis. The accurate detection of PSA levels in serum samples was well demonstrated with the dual-mode approach. SignificanceThe presented immunoassay allows straightforward, sensitive, and selective readout by color and temperature without advanced instrumentation. Particularly, the LOD was much lower than the threshold in clinical trials for PSA. Therefore, this method has a great prospect in the early diagnosis of cancer biomarkers based on a dual-mode multifunctional platform.

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