Today, a tumor's size and shape are evaluated, but they can be poor indicators of invasive potential: a very small tumor can be highly invasive. Even "molecular signatures" ?profiles of molecules that suggest how tumor cells will behave ?are not entirely predictive, he added.
Quaranta and colleagues opted for a new approach ?using the tools of mathematics to tackle the complex problem of cancer behavior.
"We have mathematics driving experimentation," Quaranta said. The team will tailor its biological experiments to test and validate the model. If the experimental data don't fit the predictions from the model, either the experiments or the model need to be corrected, he said.
"You go back and forth, and every time you get a new result, you correct the model, and you're a little bit closer to reality," Quaranta said. "This is a paradigm that is new to experimental biology."
"What is happening in biology is similar to trends seen in recent decades in the physical sciences," Cummings said. "Computational models like this, in which complex behavior emerges from computer simulations grounded in understanding phenomena at a smaller scale, have been a staple of chemistry, physics, and related engineering disciplines for a long time."
Quaranta and Cummings expect to see this new way of thinking sweep through biology.
"Particularly in cancer biology, we know so much about tumors, but we can do so little: why is that"" Quaranta said. "I think the reason is that we need additional tools, and those are the tools of mathematics."
The team's model is an initial effort. It is sophisticated enough to begin capturing tumor behavior, without being so complicated that computing power and running time for simulations become limiting. The current model simulates about four months of tumor growth in about eight hours, he said.
Source:Vanderbilt University Medical Center