MDA-MB-231乳腺癌细胞运动的定量研究:对表皮生长因子浓度及其梯度的依赖

IF 3.743 Q2 Biochemistry, Genetics and Molecular Biology
Tanzila Islam and Haluk Resat
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引用次数: 9

摘要

细胞运动增强是癌症的主要特征之一。越来越多的证据表明,表皮生长因子受体(EGFR)介导的途径在乳腺癌细胞的增殖和迁移中起着重要作用。我们量化了MDA-MB-231乳腺癌细胞在其配体EGF刺激下对EGFR通路的迁移,以确定MDA-MB-231细胞的细胞运动如何依赖于配体浓度和梯度。在单细胞水平上进行分析,结合数学建模和使用微流体装置局部改变配体浓度和梯度的能力,使我们能够分离配体浓度和配体梯度对细胞运动的独特贡献。在不同的EGF刺激条件下,我们使用延时成像技术分别追踪了6600个细胞的运动情况。利用非线性多元回归模型对跟踪的细胞进行轨迹分析,结果表明:(1)MDA-MB-231乳腺癌细胞的迁移依赖于配体梯度,而不依赖于配体浓度。这一观察结果对总(方向无关)和定向(沿梯度方向)细胞速度都有效。虽然定向运动对配体梯度的依赖是预期的,但总速度仅对配体梯度的依赖是一个意想不到的新观察。(ii)暴露于配体后,群体中单个细胞的运动增强是高度不均匀的,只有很小比例的细胞对外部刺激有强烈反应。利用单个细胞运动的定量分析分离出无反应细胞,使我们能够确定响应细胞的运动增强确实随着EGF梯度的增加而单调增加。(iii)种群中很大一部分细胞对配体刺激没有反应,它们的存在给观察带来了相当大的随机内在变异性。这表明,在单个细胞水平上研究细胞运动对于更好地捕捉生物学现实是必要的,应该避免群体平均方法。在单个细胞水平上研究运动对于理解可能由群体中一小部分细胞的行为驱动的生物学过程(如转移)尤为重要。我们讨论了我们的结果对肿瘤微环境中癌细胞的总和趋化运动的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Quantitative investigation of MDA-MB-231 breast cancer cell motility: dependence on epidermal growth factor concentration and its gradient†

Quantitative investigation of MDA-MB-231 breast cancer cell motility: dependence on epidermal growth factor concentration and its gradient†

Enhanced cell motility is one of the primary features of cancer. Accumulated evidence demonstrates that Epidermal Growth Factor Receptor (EGFR) mediated pathways play an important role in breast cancer cell proliferation and migration. We have quantified the MDA-MB-231 breast cancer cell migration in response to the stimulation of EGFR pathways with their ligand EGF to determine how the cell motility of MDA-MB-231 cells depends on the ligand concentration and gradient. Analysis at the single cell level combined with mathematical modeling and the ability to vary the ligand concentration and gradients locally using microfluidic devices allowed us to separate the unique contributions of ligand concentration and ligand gradient to cell motility. We tracked the motility of 6600 cells individually using time lapse imaging under varying EGF stimulation conditions. Trajectory analysis of the tracked cells using non-linear multivariate regression models showed that: (i) cell migration of MDA-MB-231 breast cancer cells depends on the ligand gradient but not on the ligand concentration. This observation was valid for both the total (direction independent) and directed (along gradient direction) cell velocities. Although the dependence of the directed motility on ligand gradient is to be expected, the dependence of the total velocity solely on ligand gradient was an unexpected novel observation. (ii) Enhancement of the motilities of individual cells in a population upon exposure to the ligand was highly heterogeneous, and only a very small percentage of cells responded strongly to the external stimuli. Separating out the non-responding cells using quantitative analysis of individual cell motilities enabled us to establish that enhanced motility of the responding cells indeed increases monotonically with increasing EGF gradient. (iii) A large proportion of cells in a population were unresponsive to ligand stimulation, and their presence introduced considerable random intrinsic variability to the observations. This indicated that studying cell motilities at the individual cell level is necessary to better capture the biological reality and that population averaging methods should be avoided. Studying motilities at the individual cell level is particularly important to understand the biological processes that are possibly driven by the action of a small portion of cells in a population, such as metastasis. We discuss the implications of our results on the total and chemotactic movement of cancer cells in the tumor microenvironment.

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来源期刊
Molecular BioSystems
Molecular BioSystems 生物-生化与分子生物学
CiteScore
2.94
自引率
0.00%
发文量
0
审稿时长
2.6 months
期刊介绍: Molecular Omics publishes molecular level experimental and bioinformatics research in the -omics sciences, including genomics, proteomics, transcriptomics and metabolomics. We will also welcome multidisciplinary papers presenting studies combining different types of omics, or the interface of omics and other fields such as systems biology or chemical biology.
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