Automated platform for cell selection and separation based on four-dimensional motility and matrix degradation.

Motility and invasion are key steps in the metastatic cascade, enabling cells to move through normal tissue borders into the surrounding stroma. Most available in vitro assays track cell motility or cell invasion but lack the ability to measure both simultaneously and then separate single cells with unique behaviors. In this work, we developed a cell-separation platform capable of tracking cell movement (chemokinesis) and invasion through an extracellular matrix in space and time. The platform utilized a collagen scaffold with embedded tumor cells overlaid onto a microraft array. Confocal microscopy enabled high resolution (0.4 × 0.4 × 3.5 µm voxel) monitoring of cell movement within the scaffolds. Two pancreatic cancer cell lines with known differing invasiveness were characterized on this platform, with median motilities of 14 ± 6 μm and 10 ± 4 μm over 48 h. Within the same cell line, cells demonstrated highly variable motility, with XYZ movement ranging from 144 μm to 2 μm over 24 h. The ten lowest and highest motility cells, with median movements of 33 ± 11 μm and 3 ± 1 μm, respectively, were separated and sub-cultured. After 6 weeks of culture, the cell populations were assayed on a Transwell invasion assay and 227 ± 56 cells were invasive in the high motility population while only 48 ± 10 cells were invasive in the low motility population, indicating that the resulting offspring possessed a motility phenotype reflective of the parental cells. This work demonstrates the feasibility of sorting single cells based on complex phenotypes along with the capability to further probe those cells and explore biological phenomena.