journal article·2023-11

The combined plasma membrane coating and cluster bombing strategy for improved tumor-targeting gene delivery of silicon nanoclusters

Yanlin Sun, Mengying Wang, Mingjie Wang, Chaobing Liu, Yong Shi, Liang Liu

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Abstract

With the promising biosafety and favorable cell imaging efficiency, silicon quantum dots (SiQDs) was broadly exploited as non-viral gene carriers in recent years. However, the low transfection efficiency and weak targeting ability hindered its further clinical applications. In this study, the combined plasma membrane coating and cluster bombing strategy was adopted to enhance the gene delivery potential of silicon quantum dots nanoclusters (SiNC). Initially, SiNC was generated via 3, 3'-Dithiodipropionic acid (DipA) crosslinking of SiQDs, then the obtained nanoclusters were coated by distinct plasma membrane. Interestingly, cell membrane coated SiNC (CM-SiNC) underwent particle size change, the typical character of "cluster bombing", when exposed to high GSH concentration, which was observed in the tumor microenvironment. Meanwhile, CM-SiNC can be efficiently uptaken by HEK 293T and HeLa cells, therefore transferring DNA into those cells. More importantly, among the particles coated by HeLa (HeLa-M), Red Blood (RBC-M) or RAW267.4 (RAW-M) cell membrane, HeLa cell membrane coating exhibited better cellular uptake and transfection efficiency in HeLa cells, which suggested the encouraging tumor targeting ability. In sum, these data suggested that cluster bombing of SiNC could be beneficial for physical stability and biodistribution, the additional plasma membrane coating further endowed SiNC the efficient gene delivery and tumor targeting ability. Therefore, CM-SiNC had the potential as a gene delivery vector and its application should be further addressed in vivo.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Graphene and Nanomaterials Applications · Advanced biosensing and bioanalysis techniques · Carbon and Quantum Dots Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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