Background: DESMIN is a novel prognostic predictor and therapeutic target for colorectal cancer (CRC). Enzyme-linked immunosorbent assay (ELISA) and electrochemiluminescence (ELC) assays are large-scale and highcost projects; therefore, it is necessary to develop a new, fast, and simple yet highly sensitive and specific method to detect DESMIN in serum. Semiconducting quantum dots (QDs) possess high fluorescence quantum yield, stability against photobleaching, and size-controlled luminescence properties, thus being utilized in photoelectrochemical tumor marker detection, especially in ameliorating the diagnostic value in complex biological ambient ionization. However, CdTe/CdS quantum dots (QDs) have not been applied in detecting DESMIN in serum.
Methods: DESMIN in serum has been established using anti-DESMIN-conjugated CdTe/CdS quantum dots (QDs) and measurements. The assay sensitivity was determined by measurement of quenched fluorescence intensity of DESMIN at 0.1, 0.5, 1.0, 2.0, or 5.0 ng/mL in PBS or 0.25%, 0.5%, 1.0%, 2.0%, or 5% human serum diluted in PBS. The assay was optimized under different pH (7.00 - 7.40) for different reaction durations (10 - 60 minutes). The specificity of anti-DESMIN-QDs was determined by testing the interference of DESMIN activity with CEA, IgG, or AFP, each at 1 ng/mL.
Results: Under the optimized incubation time (30 minutes) at room temperature and optimal pH 7.1 - 7.2, a correlation between the decreased fluorescence intensity of anti-DESMIN-conjugated CdTe/CdS QDs and the concentration of DESMIN in the range from 0.05 to 100 ng/mL, was established. The sensitivity for the detection of DESMIN in the range from 0.05 to 100 ng/mL, with a detection limit of 0.02 ng/mL. The assay presented a high specificity because the anti-DESMIN-conjugated CdTe/CdS QDs only reacted with ABR1B10 in the sera in the presence of CEA, IgG or AFP.
Conclusions: The immunofluorescence assay to detect DESMIN in serum using anti-DEMSIN-conjugated CdTe/ CdS QDs was fast and simple yet presented high sensitivity and specificity. Our method provides a promising tool for early prediction of CRC risk.