Aggregation-Induced Emission Fluorophore-Based Molecular Beacon for Differentiating Tumor and Normal Cells by Detecting the Specific and False-Positive Signals.

Accurate and nondestructive detection of tumor-related mRNA in living cells is of great significance for tumor diagnosis. The universal technique for imaging mRNA in living cells is nucleic-acid-based fluorescent probes. However, the majority of developed nucleic-acid-based fluorescent probes were only designed to detect the targeted mRNA but could not avoid the interference arising from nuclease or other biological matrices, which results in inevitable false-positive signals. To overcome this dilemma, a new aggregation-induced emission (AIE) fluorophore and the fluorescence resonance energy transfer (FRET) principle were used to establish a novel AIE fluorophore-based molecular beacon (AIE-MB). The AIE fluorophore tetraphenylethylene-quinoxaline (TPEQ) was designed by incorporating quinoxalinone with one typical AIE active luminogen tetraphenylethene (TPE), which could acquire a wide range of excitation wavelength. On this basis, the AIE-MB was designed by labeling two fluorophores: the TPEQ acceptor and an aggregation-caused quenching (ACQ) fluorophore 7-amino-4-methylcoumarin acid (AMCA) donor. On the basis of these two fluorophores, the AIE-MB could exhibit three states: weak fluorescence at primary stage, blue fluorescence (specific signal) generated by pairing with target mRNA in tumor cells, and both blue and green fluorescence (false-positive signal) due to the endogenous degradation in normal cells. Obviously, the specific imaging for target mRNA in tumor cells and the false-positive signal resulting from endogenous degradation in normal cells could be accurately distinguished through the different fluorescence emission. As a result, in contrast to traditional nucleic-acid-based fluorescent probes, the AIE-MB could improve the accuracy of the tumor detection by efficiently differentiating both specific and false-positive signals, which showed potential application value in tumor diagnosis and biomedical research.