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用于胶质母细胞瘤治疗的抗血管生成因子的纳米载体和非病毒方法:迄今为止的故事。

Nanocarriers and nonviral methods for delivering antiangiogenic factors for glioblastoma therapy: the story so far.

机构信息

Department of Neurosurgery, CHU, Angers, France,

CRCINA, INSERM, University of Nantes, University of Angers, Angers, France,

出版信息

Int J Nanomedicine. 2019 Apr 9;14:2497-2513. doi: 10.2147/IJN.S194858. eCollection 2019.

Abstract

Angiogenesis, the formation of new blood vessels, is an essential component of glioblastoma (GB) progression. The development of angiogenesis inhibitor therapy, including treatments targeting vascular endothelial growth factor (VEGF) in particular, raised new hopes for the treatment of GB, but no Phase III clinical trial to date has reported survival benefits relative to standard treatment. There are several possible reasons for this limited efficacy, including VEGF-independent angiogenesis, induction of tumor invasion, and inefficient antiangiogenic factor delivery to the tumor. Efforts have been made to overcome these limitations by identifying new angiogenesis inhibitors that target angiogenesis through different mechanisms of action without inducing tumor invasion, and through the development of viral and nonviral delivery methods to improve antiangiogenic activity. Herein, we describe the nonviral methods, including convection-enhanced delivery devices, implantable polymer devices, nanocarriers, and cellular vehicles, to deliver antiangiogenic factors. We focus on those evaluated in intracranial (orthotopic) animal models of GB, the most relevant models of this disease, as they reproduce the clinical scenario of tumor progression and therapy response encountered in GB patients.

摘要

血管生成,即新血管的形成,是胶质母细胞瘤(GB)进展的一个重要组成部分。血管生成抑制剂治疗的发展,包括针对血管内皮生长因子(VEGF)的治疗,为 GB 的治疗带来了新的希望,但迄今为止,没有一项 III 期临床试验报告相对于标准治疗有生存获益。这种有限疗效可能有几个原因,包括 VEGF 非依赖性血管生成、肿瘤侵袭的诱导以及抗血管生成因子向肿瘤的传递效率低下。人们已经通过识别通过不同作用机制靶向血管生成而不诱导肿瘤侵袭的新的血管生成抑制剂,以及通过开发病毒和非病毒传递方法来改善抗血管生成活性,努力克服这些局限性。本文描述了非病毒方法,包括对流增强传递装置、可植入聚合物装置、纳米载体和细胞载体,以传递抗血管生成因子。我们重点关注那些在颅内(原位)GB 动物模型中评估的方法,因为这些模型最能模拟 GB 患者中遇到的肿瘤进展和治疗反应的临床情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6047/6461002/23f84a673cdc/ijn-14-2497Fig1.jpg

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