Preparation of glycan-oriented imprinted polymer coating Gd-doped silicon nanoparticles for targeting cancer Tn antigens and dual-modal cell imaging via boronate-affinity surface imprinting.

Talanta

College of Chemistry, Research Center for Analytical Sciences, State Key Laboratory of Medicinal Chemical Biology, Tianjin Key Laboratory of Biosensing and Molecular Recognition, Nankai University, Tianjin, 300071, China; National Chromatographic Research and Analysis Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China. Electronic address:

Published: February 2021

Early and accurate detection of breast cancer plays an important role in improving the survival rates of patients. In this work, we designed and synthesized the Gal-NAc-imprinted nanoparticles (GIPs) via boronate-affinity glycan-oriented surface imprinting strategy. Molecularly imprinted polymers (MIPs) were hybridized with fluorescent silicon nanoparticles (SiNPs) to target Tn antigens. However, the single fluorescent imaging mode is not conducive to obtaining accurate diagnosis, due to its poor tissue penetration. To resolve this obstacle, doping gadolinium (Gd) into SiNPs was adopted to emerge an extra significant magnetic resonance (MR) signal, achieving highly sensitive fluorescence imaging and magnetic resonance imaging (MRI) with high spatial resolution. GIPs had uniform particle size around 31.8 nm, and exhibited satisfactory fluorescence stability. The maximum adsorption capacity of GIPs was 1.15 μM/g with a high imprinting factor (IF) of 7.5. Confocal laser scanning microscope imaging revealed that the GIPs had excellent specific recognition ability with a low cytotoxicity. GIPs also showed an outstanding MR performance on cancer cells. Therefore, the synthesized nanoparticles had desirable performance in dual-model imaging to specifically target recognition cancer cells. It may have a tremendous potential in real biological samples.

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Source
http://dx.doi.org/10.1016/j.talanta.2020.121706DOI Listing

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