This Technicolor 3D Cancer Model Lets Researchers Glimpse a Tumor’s Evolution

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This Technicolor 3D Cancer Model Lets Researchers Glimpse a Tumor’s Evolution

Each color represents the out-of-control behavior of different cell types.

How does cancer progress? New research provides insight into just how a tumor can grow via a new modeling technique. The simulation above reveals a mosaic of mutations, with each color representing a bunch of malignant cells.

"As cancerous tumors grow, cells accumulate more, and more of these mutations become aggressive," Bartek Waclaw, a researcher at the school of physics and astronomy at University of Edinburgh, told me. "Our model shows that cells in different regions of the tumor will have different mutations, hence the colors are different in different parts of the image."

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In a paper published today in the journal Nature, Waclaw and an international team of researchers from the University of Edinburgh, Harvard University, and John Hopkins University describe using mathematical algorithms to create their 3D simulation showing the development of cancer cells over space and time.

The aim of the study is to visualise, chart, and understand some of the complexities of the disease.

"Our principal question is how is it possible that tumors are so genetically homogenous. By this I mean that cells in different parts of the tumor are very similar to each other despite being separated by large distances," said Waclaw.

Waclaw said their project comprised modelling the death of cells and their replication, how they moved about, what happened when cancer cells grow faster than regular ones—all within a 3D spatial setting. "Previously, these processes have been studied in isolation, and in much more idealised models," Waclaw said.

This simulation helps the researchers understand the tumor's evolution. However, Waclaw said that it still didn't match up exactly to reality. "Our model (as any model) is a necessary idealisation. It neglects certain processes and simplifies others," he said. "We cannot use our model to fully predict the behavior of a real tumor."