Model of tumor growth dynamics helps predict cancer progression

By analyzing the distribution of tumor cells and vasculature, a research team has created a model that predicts how a cancer will grow and respond to intervention.

As Neil Johnson, PhD, and colleagues explained in Scientific Reports (, a direct mapping of all tumor cells is unfeasible, but they took advantage of “invaluable” data gathered from patient images to form the basis of a model for ascertaining future cancer growth or metastasis. The model is based on the distribution of feeding vessels in a tumor section: Because the vessels both feed and are fed by the tumor, growth characteristics can be estimated.

The method outlines paths of future tumor expansion and identifies specific points in the vessels that can be targeted to control such growth. This information can potentially be used to design more effective treatment intervals and dosage schedules for patients.

“Cancer is a disease of many scales,” affirmed Johnson—the director of the Complexity Research Group at University of Miami (Florida) College of Arts and Sciences—in a separate statement. “By including information about how the tumor grows in response to its nutrients, and how the growth of the tumor feeds back the nutrient supply itself, our model moves us one step closer to predicting the future evolution of a patient's tumor. It opens up a path toward personalized treatment and intervention.”

According to the researchers, their work can be used to eventually build a model that will be able to describe a likely corridor of cancer progression based on real-time information drawn from images and other data from a specific patient.

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