PDF(Pubmed)
Abstract：
OBJECTIVE: Pseudo-vascular network formation in vitro is considered a key characteristic of vasculogenic mimicry. While many cancer cell lines form pseudo-vascular networks, little is known about the spatiotemporal dynamics of these formations.
METHODS: Here, we present a framework for monitoring and characterising the dynamic formation and dissolution of pseudo-vascular networks in vitro. The framework combines time-resolved optical microscopy with open-source image analysis for network feature extraction and statistical modelling. The framework is demonstrated by comparing diverse cancer cell lines associated with vasculogenic mimicry, then in detecting response to drug compounds proposed to affect formation of vasculogenic mimics. Dynamic datasets collected were analysed morphometrically and a descriptive statistical analysis model was developed in order to measure stability and dissimilarity characteristics of the pseudo-vascular networks formed.
RESULTS: Melanoma cells formed the most stable pseudo-vascular networks and were selected to evaluate the response of their pseudo-vascular networks to treatment with axitinib, brucine and tivantinib. Tivantinib has been found to inhibit the formation of the pseudo-vascular networks more effectively, even in dose an order of magnitude less than the two other agents.
CONCLUSIONS: Our framework is shown to enable quantitative analysis of both the capacity for network formation, linked vasculogenic mimicry, as well as dynamic responses to treatment.
METHODS: Here, we present a framework for monitoring and characterising the dynamic formation and dissolution of pseudo-vascular networks in vitro. The framework combines time-resolved optical microscopy with open-source image analysis for network feature extraction and statistical modelling. The framework is demonstrated by comparing diverse cancer cell lines associated with vasculogenic mimicry, then in detecting response to drug compounds proposed to affect formation of vasculogenic mimics. Dynamic datasets collected were analysed morphometrically and a descriptive statistical analysis model was developed in order to measure stability and dissimilarity characteristics of the pseudo-vascular networks formed.
RESULTS: Melanoma cells formed the most stable pseudo-vascular networks and were selected to evaluate the response of their pseudo-vascular networks to treatment with axitinib, brucine and tivantinib. Tivantinib has been found to inhibit the formation of the pseudo-vascular networks more effectively, even in dose an order of magnitude less than the two other agents.
CONCLUSIONS: Our framework is shown to enable quantitative analysis of both the capacity for network formation, linked vasculogenic mimicry, as well as dynamic responses to treatment.
摘要：
目的：体外假血管网络形成被认为是血管生成拟态的关键特征。虽然许多癌细胞系形成假血管网络，对这些地层的时空动力学知之甚少。
方法：这里，我们提出了一个监测和表征体外假血管网络动态形成和溶解的框架。该框架将时间分辨光学显微镜与开源图像分析相结合，用于网络特征提取和统计建模。通过比较与血管生成拟态相关的多种癌细胞系来证明该框架，然后在检测对药物的反应中提出了影响血管生成模拟物形成的化合物。对收集的动态数据集进行形态计量学分析，并建立了描述性统计分析模型，以测量所形成的伪血管网络的稳定性和相异性。
结果：黑色素瘤细胞形成了最稳定的假血管网络，并被选择用于评估其假血管网络对阿西替尼治疗的反应，马钱子碱和tivantinib.已发现替万替尼更有效地抑制假性血管网络的形成，即使剂量比其他两种药物小一个数量级。
结论：我们的框架可以定量分析网络形成的能力，相关的血管生成拟态,以及对治疗的动态反应。
方法：这里，我们提出了一个监测和表征体外假血管网络动态形成和溶解的框架。该框架将时间分辨光学显微镜与开源图像分析相结合，用于网络特征提取和统计建模。通过比较与血管生成拟态相关的多种癌细胞系来证明该框架，然后在检测对药物的反应中提出了影响血管生成模拟物形成的化合物。对收集的动态数据集进行形态计量学分析，并建立了描述性统计分析模型，以测量所形成的伪血管网络的稳定性和相异性。
结果：黑色素瘤细胞形成了最稳定的假血管网络，并被选择用于评估其假血管网络对阿西替尼治疗的反应，马钱子碱和tivantinib.已发现替万替尼更有效地抑制假性血管网络的形成，即使剂量比其他两种药物小一个数量级。
结论：我们的框架可以定量分析网络形成的能力，相关的血管生成拟态,以及对治疗的动态反应。
