ArticleBioinformatics (Oxford, England)2021
Biophysical Informatics Approach For Quantifying Phenotypic Heterogeneity In Cancer Cell Migration In Confined Microenvironments.
Article in Bioinformatics (Oxford, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Volumetric mechanoplasticity couples melanoma drug tolerance to susceptibility to CD8bioRxiv : the preprint server for biology · 2026Article
- 3D-printed plugs enhance cell usage efficiency for single-cell migration and neuron axon guidance assays.Cell reports methods · 2025Article
- Mechanical deformation and death of circulating tumor cells in the bloodstream.Cancer metastasis reviews · 2024Review
- Insights into the mechanobiology of cancer metastasis via microfluidic technologies.APL bioengineering · 2024Review
- Epithelial and mesenchymal phenotypes determine the dynamics of circulating breast tumor cells in microfluidic capillaries under chemotherapy-induced stress.Biomicrofluidics · 2024Article
- Microfluidic single-cell migration chip reveals insights into the impact of extracellular matrices on cell movement.Lab on a chip · 2023Article
- Compression drives diverse transcriptomic and phenotypic adaptations in melanoma.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Biophysical informatics reveals distinctive phenotypic signatures and functional diversity of single-cell lineages.Bioinformatics (Oxford, England) · 2023Article
- Biglycan Promotes Cancer Stem Cell Properties, NFκB Signaling and Metastatic Potential in Breast Cancer Cells.Cancers · 2022Article
- Volumetric compression develops noise-driven single-cell heterogeneity.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- A mesoscale mechanical model of cellular interactions.Biophysical journal · 2021Article
- Morphodynamic signatures of MDA-MB-231 single cells and cell doublets undergoing invasion in confined microenvironments.Scientific reports · 2021Article
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Authors and funding
2 authors.
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Abstract
motivationCancer 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.
resultsHere, 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.
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