AS1411 aptamer-functionalized chitosan-silica nanoparticles for targeted delivery of epigallocatechin gallate to the SKOV-3 ovarian cancer cell lines
Source abstract
Abstract
Chemotherapy is still one of the routine methods for cancer therapy, but due to its poor specificity to the target site and a lot of side effects, it is not considered as a harmless approach for cancer therapy. For improving cancer-targeted drug delivery, in the present experiment, we synthesized chitosan-coated silica (SiO2@CS) nanoparticles and attached them to epigallocatechin gallate (EGCG). The functional amine groups of chitosan in SiO2@CS-EGCG nanoparticles (NPs) were attached to AS1411 aptamer electrostatically. Our developed nanoparticles showed spherical core-shell morphology with a size of around 100 nm in TEM images. Also, the internalization efficiency of SiO2@CS-EGCG-aptamer nanoparticles (51%) was higher than SiO2@CS-EGCG nanoparticles (29%) in the SKOV-3 cell line, which proved the successful recognition of nucleolin by attached AS1411 aptamer. Besides, DAPI staining and Annexin V analyses showed that SiO2@CS-EGCG-aptamer nanoparticles meritoriously improved the cytotoxic effect of the EGCG (with around 93% of cells showed late apoptosis). Additionally, cell cycle results showed that SiO2@CS-EGCG-aptamer nanoparticles resulted in a decrease in S and G2/M and increase G0/G1 and arrested cells in the G1 cell cycle. Moreover, the expression level of ERK2 and hTERT downregulated in SiO2@CS-EGCG-aptamer nanoparticles was treated SKOV-3 cells in comparison with the groups that were treated with free EGCG and SiO2@CS-EGCG. These results suggested that SiO2@CS-EGCG-aptamer had great potential for targeted delivery of different therapeutic agents like EGCG to the SKOV-3 cell line.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced biosensing and bioanalysis techniques · RNA Interference and Gene Delivery · Advanced Nanomaterials in Catalysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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