(143b) Label-Free Interference-Based Quantitative Study of Filopodia-like Structures in Cancer-Cells of Different Metastatic Potential

Identification of cells with high metastatic potential is critical for patient prognosis and treatment when performing single cell analysis, for instance, from a population of rare cells isolated from blood in a liquid-biopsy. However, methods for cancer cell identification can be time-consuming and costly because they typically involve the use of specific antibodies and biomarkers. Filopodia, “finger-like” plasma membrane protrusions used by cells to probe their environment, play a central role in cell adhesion and migration, and have emerged as important contributors to cancer metastasis; for instance, breast carcinomas with poor prognosis exhibit upregulated filopodia-associated genes. Although filopodia lengths could reach several micrometers, filopodia characterization is hampered by their small diameters, ~200-400 nm, typically requiring the use of fluorescence microscopy and even super-resolution techniques. Here, we study filopodia-like structures in cancer cells of different metastatic potential, such as PC3 and LNCaP, to identify characteristic behaviors that can be used for cancer cell identification. Cells are analyzed using a label-free interference-based technique, reflection interference contrast microscopy (RICM), where interferograms embed detailed topographical information of the cell-substrate interaction, down to the nanometer-scale. RICM’s unique non-invasive “view from below” perspective directly reveals the presence filopodia-like structures in single cells as they settle and interact with a plasma-treated glass surface. The computational analysis of RICM interferograms, using fast custom-developed algorithms, facilitates label-free quantification of cell adhesion and filopodia dynamics. Results indicate that RICM-based analysis of the dynamics of cancer cells’ filopodia-like structures enables discrimination between cell lines of high and low metastatic potential. These results illustrate RICM’s potential for identification of highly metastatic cancer cells using the dynamics of filopodia-like structures as a label-free biomarker.