A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

, which uniquely characterize a wide range of molecular bonds and subcellular structures), as well as morphological data from three-dimensional refractive index tomograms (providing measurements of cell volume, surface area, footprint, and sphericity at nanometer resolution, alongside dry mass and density). By systematically breaking down the rich single-cell details that RS and TPM deliver, we demonstrate, in a quantitative manner, the advantage of such a multimodal microscopy method for phenotyping tumoral breast cancer cells. Our tools also provide further insight into the subcellular information without the use of any labels. Finally, we study and discuss any unique or correlated information that RS- and TPM-derived datasets feature. We believe our tools and quantitative data analysis pipelines can revolutionize phenotyping tasks in biomedical research when in need of a rapid and non-perturbative method on living cells in culture, with the potential for future translation into clinical and diagnostic applications.