ASU Mathematician: Cancer Cells May Move More Like Flocks Of Birds

By Andrew Bernier
Published: Tuesday, December 22, 2015 - 10:16am
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Cell growth, including cancer growth, has long been thought of physically connected cells growing together. Now, new cell modeling from ASU mathematicians suggests cells move and grow independently, like a flock of birds.

Biologists have long thought cells in the body were attached to each other when growing or moving. But the new research shows cells both repel and attract to independently move together, much like a school of fish.

After developing computer simulations of cell movement and development, ASU mathematician Sebastien Motsch studied geometric shapes that cells and tumors formed. By making more of an elliptical shape instead of a circular one, he said cells were more prone to move.

“The shape will actually enhance the migration of the cell," said Motsch. "In the model you observe that when you have this elliptic shape, then it’s much more likely that you’re going to have flocking. So, they’re all aligning, going one direction. And therefore, they’re able to migrate in a larger distance.”

Motsch said other cells tended to follow elongated cells, forming tumor shapes like streams and swirls. The researchers hope by discerning stationary cancer cells from mobile ones, it may help predict how aggressive a tumor may become.

(Photo by Pedro Lowenstein - University of Michigan)
This figure shows the correlation between the mathematical agent based model (right and left images) and the structures formed within glioma tumors (inset in middle image). The elongated morphology of glioma cells within the streams is predicted by the mathematical model (indicated by blue arrows), and the more circular morphology of glioma cells outside the streams is also predicted by the mathematical model (red arrow). Furthermore, the mathematical model proves that only elongated cells can form streams. The quantification of cell eccentricity (middle image), an indication of cellular elongated morphology, correlated very well with the data predicted by the mathematical model to form streams.

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