发展神经母细胞瘤的临床前模型:推动治疗试验。

BMC biomedical engineering Pub Date : 2019-12-20 eCollection Date: 2019-01-01 DOI:10.1186/s42490-019-0034-8
Kimberly J Ornell, Jeannine M Coburn
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引用次数: 15

摘要

尽管癌症治疗取得了进展,特别是在免疫肿瘤学领域,但神经母细胞瘤(NB)的成功治疗仍然是一个挑战。NB是1岁以下婴儿最常见的癌症,约占所有儿科癌症的10%。目前,高危NB患儿的存活率为40-50%。NB的异质性使得开发有效的治疗策略具有挑战性。许多临床前模型试图模拟肿瘤表型和肿瘤微环境。体内小鼠模型,以遗传、同基因和异种移植小鼠的形式,是有利的,因为它们复制了复杂的肿瘤-基质相互作用,代表了临床前治疗测试的金标准。传统的体外模型虽然具有高通量,但存在许多局限性。新的组织工程模型的出现有可能弥合体外和体内模型之间的差距,用于治疗试验。治疗方法继续从传统的细胞毒性化疗发展到生物靶向治疗。这些治疗方法既作用于肿瘤细胞,也作用于肿瘤微环境中的其他细胞,这使得开发准确反映肿瘤异质性的临床前模型比以往任何时候都更加重要。在这篇综述中,我们将讨论目前的体外和体内临床前测试模型,以及它们在治疗开发中的潜在应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Developing preclinical models of neuroblastoma: driving therapeutic testing.

Despite advances in cancer therapeutics, particularly in the area of immuno-oncology, successful treatment of neuroblastoma (NB) remains a challenge. NB is the most common cancer in infants under 1 year of age, and accounts for approximately 10% of all pediatric cancers. Currently, children with high-risk NB exhibit a survival rate of 40-50%. The heterogeneous nature of NB makes development of effective therapeutic strategies challenging. Many preclinical models attempt to mimic the tumor phenotype and tumor microenvironment. In vivo mouse models, in the form of genetic, syngeneic, and xenograft mice, are advantageous as they replicated the complex tumor-stroma interactions and represent the gold standard for preclinical therapeutic testing. Traditional in vitro models, while high throughput, exhibit many limitations. The emergence of new tissue engineered models has the potential to bridge the gap between in vitro and in vivo models for therapeutic testing. Therapeutics continue to evolve from traditional cytotoxic chemotherapies to biologically targeted therapies. These therapeutics act on both the tumor cells and other cells within the tumor microenvironment, making development of preclinical models that accurately reflect tumor heterogeneity more important than ever. In this review, we will discuss current in vitro and in vivo preclinical testing models, and their potential applications to therapeutic development.

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