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  • Title: Stimuli-responsive magnetic silica-poly-lactic-co-glycolic acid hybrid nanoparticles for targeted cancer chemo-immunotherapy.
    Author: Gupta A, Niveria K, Chandpa HH, Singh M, Kumar V, Panda AK, Meena J.
    Journal: Drug Deliv Transl Res; 2024 Oct; 14(10):2712-2726. PubMed ID: 38347431.
    Abstract:
    Chemotherapy and immunotherapy are two important modalities in cancer management. However, due to multiple reasons, a monotherapy is only partially effective. Hence, if used concurrently in targeted and stimuli-responsive manner, it could have been superior therapeutically. To facilitate co-delivery of chemotherapeutic and immunotherapeutic agent to the target cancer cells, engineered nanoparticles, i.e., a pH-responsive polymer PLGA-coated magnetic silica nanoparticles (Fe3O4-SiO2-PLGA-PDA-PTX-siRNA NPs) encapsulating paclitaxel (PTX) and siRNA against programmed cell death ligand-1 (PD-L1) are synthesized and characterized. Developed nanoparticles demonstrated pH-sensitive sustained drug release up to 10 days. In vitro 4T1 cell line studies showed efficient cellular uptake, PD-L1 gene downregulation, and apoptosis. Further, in vivo efficacy studies carried out in the mice model demonstrated a significant reduction of tumor growth following treatment with dual-Fe3O4-SiO2-PLGA-PDA-PTX-siRNA NPs as compared with monotherapy with Fe3O4-SiO2-PLGA-PDA-PTX NPs. The high therapeutic efficacy observed with dual-Fe3O4-SiO2-PLGA-PDA-PTX-siRNA NPs was mainly due to the cytotoxic effect of PTX combined with targeted silencing of the gene of interest, i.e., PD-L1, which in turn improve CD8+ T cell-mediated cancer cell death as evident with increased proliferation of CD8+ T cells in co-culture experiments. Thereby, dual-Fe3O4-SiO2-PLGA-PDA-PTX-siRNA NPs may have a promising anti-cancer treatment potential against breast cancer; however, the beneficial effects of dual loading of PTX + PD-L1 siRNA may be corroborated against other cancer models such as lung and colorectal cancer models as well as in clinical trials.
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