Abstract
As biophysical properties of tissues and cells play essential roles in cellular function, morphogenesis, and disease progression, numerous conventional techniques have been developed to characterize cells and differentiate benign cells from cancer cells. Recently, Transmembrane Receptor Dynamics, a single-particle tracking based biophysical phenotyping assay, was developed as a contact-free technique that can probe the topography of the plasma membrane and nanostructure of the membrane-associated cytoskeleton with sub-diffraction-limited resolution. Here, we review this state-of-the-art technology by narrating the underlying biophysical principles of single-particle tracking and discussing the interpretation of the dynamics of tyrosine kinase receptors. We further elaborate its potential for gaining insights into biology and being translated as a cancer diagnostic tool on the basis of machine learning models.
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Acknowledgments
We thank Dr. Hsin-Chih Yeh for sharing his experience of SPT/SMT techniques. Soonwoo Hong for insightful discussions and feedback on the application of deep-learning in the trajectory analysis. This work was funded by the Ministry of Science and Technology, Taiwan (MOST 108-2636-E-039-001) and China Medical University, Taiwan (CMU108-YTY-01).
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M. Kim and Y.-L. Liu wrote the manuscript.
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Kim, M., Liu, YL. (2021). Transmembrane Receptor Dynamics as Biophysical Markers for Assessing Cancer Cells. In: Santra, T.S., Tseng, FG. (eds) Handbook of Single Cell Technologies. Springer, Singapore. https://doi.org/10.1007/978-981-10-4857-9_38-1
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