CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Optimized Fabrication of Dendritic Mesoporous Silica Nanoparticles as Efficient Delivery System for Cancer Immunotherapy.
Optimized Fabrication of Dendritic Mesoporous Silica Nanoparticles as Efficient Delivery System for Cancer Immunotherapy.
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在过去十年中,癌症免疫疗法彻底改变了肿瘤学领域。免疫检查点抑制剂、癌症疫苗、过继细胞疗法、细胞因子和免疫调节剂等主要免疫治疗方法在临床前和临床环境中显示出巨大前景。其中,包括癌症疫苗在内的免疫调节剂尤其引人关注;然而,它们面临局限性,特别是缺乏高效且精准地将免疫调节剂靶向递送至特定免疫细胞,以及潜在的脱靶毒性。纳米材料可以在解决癌症免疫治疗中的靶向及其他挑战方面发挥关键作用。树枝状介孔二氧化硅纳米颗粒(DMSNs)由于其可调孔径,能够增强免疫调节剂的有效负载,从而提高癌症疫苗的疗效。在这项工作中,优化了一种基于乳液的方法,以定制 DMSNs 的孔径,并将 DMSNs 负载卵清蛋白(OVA)和胞嘧啶-磷酸-鸟嘌呤(CpG)寡脱氧核苷酸(CpG-OVA-DMSNs)。DMSNs 的免疫治疗效果通过在抗原呈递细胞(APCs)中受控化学释放 OVA 和 CpG 来实现。
结果表明,CpG-OVA-DMSNs 有效激活了 APCs 中的免疫反应,并在小鼠 B16-OVA 肿瘤模型中减少了肿瘤生长。
In the past decade, cancer immunotherapy has revolutionized the field of oncology. Major immunotherapy approaches such as immune checkpoint inhibitors, cancer vaccines, adoptive cell therapy, cytokines, and immunomodulators have shown great promise in preclinical and clinical settings. Among them, immunomodulatory agents including cancer vaccines are particularly appealing; however, they face limitations, notably the absence of efficient and precise targeted delivery of immune-modulatory agents to specific immune cells and the potential for off-target toxicity. Nanomaterials can play a pivotal role in addressing targeting and other challenges in cancer immunotherapy.
Dendritic mesoporous silica nanoparticles (DMSNs) can enhance the efficacy of cancer vaccines by enhancing the effective loading of immune modulatory agents owing to their tunable pore sizes. In this work, an emulsion-based method is optimized to customize the pore size of DMSNs and loaded DMSNs with ovalbumin (OVA) and cytosine-phosphate-guanine (CpG) oligodeoxynucleotides (CpG-OVA-DMSNs).
The immunotherapeutic effect of DMSNs is achieved through controlled chemical release of OVA and CpG in antigen-presenting cells (APCs). The results demonstrated that CpG-OVA-DMSNs efficiently activated the immune response in APCs and reduced tumor growth in the murine B16-OVA tumor model.
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