Lymphoidal chemokine CCL19 promoted the heterogeneity of the breast tumor cell motility within a 3D microenvironment revealed by a Lévy distribution analysis.

IF 1.4 4区 生物学 Q4 CELL BIOLOGY
Beum Jun Kim, Pimkhuan Hannanta-Anan, Anders Ryd, Melody A Swartz, Mingming Wu
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引用次数: 0

Abstract

Tumor cell heterogeneity, either at the genotypic or the phenotypic level, is a hallmark of cancer. Tumor cells exhibit large variations, even among cells derived from the same origin, including cell morphology, speed and motility type. However, current work for quantifying tumor cell behavior is largely population based and does not address the question of cell heterogeneity. In this article, we utilize Lévy distribution analysis, a method known in both social and physical sciences for quantifying rare events, to characterize the heterogeneity of tumor cell motility. Specifically, we studied the breast tumor cell (MDA-MB-231 cell line) velocity statistics when the cells were subject to well-defined lymphoid chemokine (CCL19) gradients using a microfluidic platform. Experimental results showed that the tail end of the velocity distribution of breast tumor cell was well described by a Lévy function. The measured Lévy exponent revealed that cell motility was more heterogeneous when CCL19 concentration was near the dynamic kinetic binding constant to its corresponding receptor CCR7. This work highlighted the importance of tumor microenvironment in modulating tumor cell heterogeneity and invasion.

淋巴细胞趋化因子CCL19促进了乳腺肿瘤细胞在三维微环境中运动的异质性。
肿瘤细胞的异质性,无论是基因型还是表型水平,都是癌症的标志。肿瘤细胞表现出很大的差异,即使在来源相同的细胞之间也是如此,包括细胞形态、速度和运动类型。然而,目前量化肿瘤细胞行为的工作主要是基于群体的,并没有解决细胞异质性的问题。在这篇文章中,我们利用Lévy分布分析来表征肿瘤细胞运动的异质性,这是一种在社会科学和物理科学中都已知的量化罕见事件的方法。具体而言,我们使用微流体平台研究了当细胞受到明确的淋巴趋化因子(CCL19)梯度时乳腺肿瘤细胞(MDA-MB-231细胞系)的速度统计。实验结果表明,Lévy函数可以很好地描述乳腺肿瘤细胞速度分布的尾端。测量的Lévy指数显示,当CCL19浓度接近其相应受体CCR7的动态动力学结合常数时,细胞运动更加不均匀。这项工作强调了肿瘤微环境在调节肿瘤细胞异质性和侵袭方面的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Integrative Biology
Integrative Biology 生物-细胞生物学
CiteScore
4.90
自引率
0.00%
发文量
15
审稿时长
1 months
期刊介绍: Integrative Biology publishes original biological research based on innovative experimental and theoretical methodologies that answer biological questions. The journal is multi- and inter-disciplinary, calling upon expertise and technologies from the physical sciences, engineering, computation, imaging, and mathematics to address critical questions in biological systems. Research using experimental or computational quantitative technologies to characterise biological systems at the molecular, cellular, tissue and population levels is welcomed. Of particular interest are submissions contributing to quantitative understanding of how component properties at one level in the dimensional scale (nano to micro) determine system behaviour at a higher level of complexity. Studies of synthetic systems, whether used to elucidate fundamental principles of biological function or as the basis for novel applications are also of interest.
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