Diversification of cancer and healthy cells through motion analysis

Researchers from the Tokyo Metropolitan University found that the movement of unmarked cells can be used to say whether they are cancerous or healthy. They observed malignant fibrous cells and healthy fibroblasts on a plate and found that monitoring and analysis of their paths could be used to accurately differentiate them up to 94%. In addition to diagnosis, their technique can also shed light on cellular mobility functions, such as tissue healing.

While scientists and medical experts examine cells under the microscope for many centuries, most studies and diagnoses focus on their shape, on what they contain and where different parts are found. But cells are dynamic, change over time and are known to be able to move. Accurate monitoring and analysis of their movement, we may be able to differentiate cells that have functions based on cell migration. An important example is the metastasis of cancer, where the mobility of the cancer cells allows them to spread.

However, this is easier to say than to be done. For one, the study of a small subset of cells can give biased results. Any accurate diagnostic technique would be based on the automated high performance monitoring of a significant number of cells. Many methods then turn to fluorescent marking, which makes the cells much easier to see under the microscope. But this labeling process can affect their own properties. The ultimate goal is an automated method that uses conventional microscopy without labels to characterize cellular mobility and show whether the cells are healthy or not.

Now, a team of researchers from the Tokyo Metropolitan University, led by Professor Hiromi Miyoshi, come in a way of monitoring cells using phase contrast microscopy, one of the most common ways of cell observation. Phase contrast microscopy is entirely without label, allowing cells to move on a petri plate closer to their inherent state and is not affected by the visual properties of Petri plastic dishes through which cells are depicted. Through innovative image analysis, they were able to export the orbits of many individual cells. They focused on the properties of the routes taken, such as the speed of immigration and how curves were the routes, which would codify subtle differences in distortion and movement.

As a test, they compared healthy fibroblast cells, the essential ingredient of animal tissue and malignant fibrous cells, cancer cells derived from fibrous connective tissue. They were able to show that cells migrated in different ways, as characterized by the “sum of the turns of the rotation” (how curves were the paths), the frequency of shallow speeds and how quickly they move. In fact, by combining both the sum of the turns and how often they made shallow turns, they could predict whether a cell was 94%cancerous or not.

The team’s work not only promises a new way to distinguish cancer cells, but also applications for researching any biological function based on cellular mobility, such as healing of wounds and tissue growth.

This project was backed by the Kakenhi Kakenhi JP24K01998 grant number, the number of research grants by the Tokyo Metropolitan Government and the TMU Strategic Research Fund for social commitment.