Label-free Optical Phenotyping for Identifying Metastatic Potential of Cancer Cells
Our recent study utilized both the morphological and molecular information provided by 3D optical diffraction tomography and Raman spectroscopy, respectively, to show a label-free route for optical phenotyping of cancer cells at single-cell resolution. We used an isogenic panel of cell lines derived from MDA-MB-231 breast cancer cells that vary in their metastatic potential and demonstrated that 3D refractive index tomograms can capture subtle morphological differences among the parental, circulating tumor cells, and lung metastatic cells. By leveraging its molecular specificity, we demonstrated that coarse Raman microscopy is capable of rapidly mapping a sufficient number of cells for training a random forest classifier that can accurately predict the metastatic potential of cells at a single- cell level. Overall, we showed that coarse Raman mapping can substantially reduce measurement time and enable the acquisition of reasonably large training datasets for label-free single-cell analysis.
Paidi SK et al., Biosensors and Bioelectronics, 2020