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Abstract Recent evidence suggests that groups of cells are more likely to form clinically dangerous metastatic tumors, emphasizing the importance of understanding mechanisms underlying collective behavior. The emergent collective behavior of migrating cell sheets in vitro has been shown to be disrupted in tumorigenic cells but the connection between this behavior and in vivo tumorigenicity remains unclear. We use particle image velocimetry to measure a multidimensional migration phenotype for genetically defined human breast epithelial cell lines that range in their in vivo behavior from non-tumorigenic to aggressively metastatic. By using cells with controlled mutations, we show that PTEN deletion enhances collective migration, while Ras activation suppresses it, even when combined with PTEN deletion. These opposing effects on collective migration of two mutations that are frequently found in patient tumors could be exploited in the development of novel treatments for metastatic disease. Our methods are based on label-free phase contrast imaging, and thus could easily be applied to patient tumor cells. The short time scales of our approach do not require potentially selective growth, and thus in combination with label-free imaging would allow multidimensional collective migration phenotypes to be utilized in clinical assessments of metastatic potential.

Summary: Collective cell migration is an umbrella term for a rich variety of cell behaviors, whose distinct character is important for biological function, notably for cancer metastasis. One essential feature of collective behavior is the motion of cells relative to their immediate neighbors. We introduce an AI-based pipeline to segment and track cell nuclei from phase-contrast images. Nuclei segmentation is based on a U-Net convolutional neural network trained on images with nucleus staining. Tracking, based on the Crocker-Grier algorithm, quantifies nuclei movement and allows for robust downstream analysis of collective motion. Because the AI algorithm required no new training data, our approach promises to be applicable to and yield new insights for vast libraries of existing collective motion images. In a systematic analysis of a cell line panel with oncogenic mutations, we find that the collective rearrangement metric, D2min, which reflects non-affine motion, shows promise as an indicator of metastatic potential.

Abstract Mammosphere assays are widely used in vitro to identify prospective cancer-initiating stem cells that can propagate clonally to form spheres in free-floating conditions. However, the traditional mammosphere assay inevitably introduces cell aggregation that interferes with the measurement of true mammosphere forming efficiency. We developed a method to reduce tumor cell aggregation and increase the probability that the observed mammospheres formed are clonal in origin. Tethering individual tumor cells to lipid anchors prevents cell drift while maintaining free-floating characteristics. This enables real-time monitoring of single tumor cells as they divide to form mammospheres. Monitoring tethered breast cancer cells provided detailed size information that correlates directly to previously published single cell tracking data. We observed that 71% of the Day 7 spheres in lipid-coated wells were between 50 and 150 μm compared to only 37% in traditional low attachment plates. When an equal mixture of MCF7-GFP and MCF7-mCherry cells were seeded, 65% of the mammospheres in lipid-coated wells demonstrated single color expression whereas only 32% were single-colored in low attachment wells. These results indicate that using lipid tethering for mammosphere growth assays can reduce the confounding factor of cell aggregation and increase the formation of clonal mammospheres.

ARID1A, which is often mutated in human endometrial cancer, is a component of the SWI/SNF chromatin remodelling complex. Here, the authors show that Arid1a mutations in the mouse endometrium and primary human endometrial epithelial cells cause widespread reprogramming of gene transcription and result in a loss of response to TGFβ.

Summary: The mammosphere assay has become widely employed to quantify stem-like cells in a population. However, the problem is there is no standard protocol employed by the field. Cell seeding densities of 1,000 to 100,000 cells/mL have been reported. These high densities lead to cellular aggregation. To address this, we have individually tracked 1,127 single MCF-7 and 696 single T47D human breast tumor cells by eye over the course of 14 days. This tracking has given us detailed information for the commonly used endpoints of 5, 7, and 14 days that is unclouded by cellular aggregation. This includes mean sphere sizes, sphere-forming efficiencies, and a well-defined minimum size for both lines. Importantly, we have correlated early cell division with eventual sphere formation. At 24 hr post seeding, we can predict the total spheres on day 14 with 98% accuracy in both lines. This approach removes cell aggregation and potentially shortens a 5- to 14-day assay to a 24 hours. : Biology Experimental Methods; Cancer Subject Areas: Biology Experimental Methods, Cancer