Biophysical Informatics Approach For Quantifying Phenotypic Heterogeneity In Cancer Cell Migration In Confined Microenvironments.
Biophysical Informatics Approach For Quantifying Phenotypic Heterogeneity In Cancer Cell Migration In Confined Microenvironments.
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DOI：
10.1093/bioinformatics/btab053
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发表时间：
2021-02
期刊：
影响因子：
5.8
通讯作者：
Xingjian Zhang;M. Mak
中科院分区：
文献类型：
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作者：
Xingjian Zhang;M. Mak
动机
癌细胞的异质性可在基因和表型上体现。生物信息学方法已被用于分析复杂的基因组学和转录组学数据，但在分析表型异质性肿瘤细胞的生物物理数据方面尚未完善建立。在此，我们采用一种信息学方法来分析MDA - MB - 231细胞（一种广泛使用的乳腺癌细胞系）在受限环境中自发迁移时的生物物理数据。在实验中，我们改变收缩微通道的几何形状（宽通道、短收缩段和长收缩段）并进行药物处理。我们发现短收缩段中的细胞在形态上与宽通道中的细胞相似。然而，它们的荧光图谱与长收缩段中的细胞相当。我们证明细胞迁移表型在非受限环境中与线粒体的相关性更强，在受限环境中与肌动蛋白的相关性更强。我们证明在受限和非受限环境中，动力蛋白抑制剂纤毛阻断素D都会改变细胞的迁移表型。总体而言，我们的方法以单细胞分辨率阐明了受限微环境下癌细胞的表型异质性。
结果
在此，我们将一种生物信息学方法应用于单细胞侵袭实验。我们证明该方法能够确定在各种几何约束下以及不同速度的细胞在形态、细胞骨架活动和线粒体活动方面的差异。我们的方法可轻易适用于不同类型输入生物物理数据的各种异质性研究。此外，该方法可应用于以单细胞分辨率研究因外部刺激差异（例如对细胞和亚细胞活动的治疗效果）导致的生物物理变化。最后，由于类似的生物信息学方法已广泛应用于基因异质性研究，使用该方法提取的生物物理信息可与基因数据一起分析，以关联基因和表型异质性。
可用性
支持本研究结果的数据可在合理请求下从通讯作者处获得。
补充信息
补充数据可在《生物信息学》在线获取。
MOTIVATION Cancer cell heterogeneity can manifest genetically and phenotypically. Bioinformatics methods have been used to analyze complex genomics and transcriptomics data, but have not been well-established for analyzing biophysical data of phenotypically heterogeneous tumor cells. Here, we take an informatics approach to analyze the biophysical data of MDA-MB-231 cells, a widely used breast cancer cell line, during their spontaneous migration through confined environments. Experimentally, we vary the constriction microchannel geometries (wide channel, short constriction, and long constriction) and apply drug treatments. We find that cells in the short constriction are similar in morphology to the cells in the wide channel. However, their fluorescence profiles are comparable to those in the long constriction. We demonstrate that the cell migratory phenotype is correlated more to mitochondria in a non-confined environment and more to actin in a confined environment. We demonstrate that the cells' migratory phenotypes are altered by ciliobrevin D, a dynein inhibitor, in both confined and non-confined environments. Overall, our approach elucidates phenotypic heterogeneity in cancer cells under confined microenvironments at single-cell resolution. RESULTS Here, we apply a bioinformatics approach to a single cell invasion assay. We demonstrate that this method can determine distinctions in morphology, cytoskeletal activities, and mitochondrial activities under various geometric constraints and for cells of different speeds. Our approach can be readily adapted to various heterogeneity studies for different types of input biophysical data. In addition, this approach can be applied to studies related to biophysical changes due to differences in external stimuli, such as treatment effects on cellular and subcellular activities, at single-cell resolution. Finally, as similar bioinformatics methods have been widely applied in studies of genetic heterogeneity, biophysical information extracted using this approach can be analyzed together with the genetic data to relate genetic and phenotypic heterogeneity. AVAILABILITY The data that support the findings of this study are available from the corresponding author upon reasonable request. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.