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使用天然产物进行肺癌球体的 3D 筛选方案。

Protocol for 3D screening of lung cancer spheroids using natural products.

机构信息

Molecular Screening Center, Department of Molecular Medicine, UF Scripps Biomedical Research, Jupiter, FL, USA.

Department of Chemistry, UF Scripps Biomedical Research, Jupiter, FL, USA; Natural Products Discovery Center, UF Scripps Biomedical Research, Jupiter, FL, USA.

出版信息

SLAS Discov. 2023 Mar;28(2):20-28. doi: 10.1016/j.slasd.2023.01.005. Epub 2023 Jan 18.

Abstract

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and accounts for ∼84% of all lung cancer cases. NSCLC remains one of the leading causes of cancer-associated death, with a 5-year survival rate less than 25%. This type of cancer begins with healthy cells that change and start growing out of control, leading to the formation of lesions or tumors. Understanding the dynamics of how the tumor microenvironment promotes cancer initiation and progression that leads to cancer metastasis is crucial to help identify new molecular therapies. 3D primary cell tumor models have received renewed recognition due to their ability to better mimic the complexity of in vivo tumors and as a potential bridge between traditional 2D culture and in vivo studies. Vast improvements in 3D cell culture technologies make them much more cost effective and efficient largely because of the use of a cell-repellent surfaces and a novel angle plate adaptor technology. To exploit this technology, we accessed the Natural Products Library (NPL) at UF Scripps, which consists of crude extracts, partially purified fractions, and pure natural products (NPs). NPs generally are not very well represented in most drug discovery libraries and thus provide new insights to discover leads that could potentially emerge as novel molecular therapies. Herein we describe how we combined these technologies for 3D screening in 1536 well format using a panel of ten NSCLC cells lines (5 wild type and 5 mutant) against ∼1280 selected members of the NPL. After further evaluation, the selected active hits were prioritized to be screened against all 10 NSCLC cell lines as concentration response curves to determine the efficacy and selectivity of the compounds between wild type and mutant 3D cell models. Here, we demonstrate the methods needed for automated 3D screening using microbial NPs, exemplified by crude extracts, partially purified fractions, and pure NPs, that may lead to future use targeting human cancer.

摘要

非小细胞肺癌(NSCLC)是最常见的肺癌类型,约占所有肺癌病例的 84%。NSCLC 仍然是癌症相关死亡的主要原因之一,其 5 年生存率低于 25%。这种癌症始于健康细胞的变化并开始失控生长,导致病变或肿瘤的形成。了解肿瘤微环境如何促进癌症的发生和发展,从而导致癌症转移的动态,对于帮助识别新的分子治疗方法至关重要。3D 原代细胞肿瘤模型由于能够更好地模拟体内肿瘤的复杂性,以及作为传统 2D 培养和体内研究之间的潜在桥梁,因此受到了重新关注。3D 细胞培养技术的巨大进步使它们的成本效益和效率大大提高,这主要是因为使用了细胞排斥表面和新颖的角板适配器技术。为了利用这项技术,我们访问了 UF Scripps 的天然产物库(NPL),其中包含粗提取物、部分纯化部分和纯天然产物(NPs)。NPs 在大多数药物发现库中通常没有很好的代表性,因此为发现潜在的新型分子疗法提供了新的见解。本文描述了我们如何将这些技术结合起来,在 1536 孔板格式中进行 3D 筛选,使用一组 10 种 NSCLC 细胞系(5 种野生型和 5 种突变型)对 NPL 中的约 1280 种选定成员进行筛选。经过进一步评估,选定的活性命中优先对所有 10 种 NSCLC 细胞系进行筛选,以确定化合物在野生型和突变型 3D 细胞模型之间的疗效和选择性。在这里,我们展示了使用微生物 NPs(如粗提取物、部分纯化部分和纯 NPs)进行自动化 3D 筛选所需的方法,这可能会导致未来针对人类癌症的靶向治疗。

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