Computer simulation of cancer growth
For a long time now, researchers and scientists have used computer simulations in physical sciences, such as physics, chemistry or engineering. But what about biology? An international team of U.S. and Scottish mathematicians and biologists has decided to use a math model to predict tumor behavior. As say the researchers, their approach is similar to the one used by weather forecasters. So far, and even if it was successful, this approach is entirely theoretical. But the scientists see their effort as the beginning of a new era in cancer research. And it might be the beginning of customized cancer treatments.
This research has been led by Vito Quaranta, professor of cancer biology at Vanderbilt University, and Dr Alexander (Sandy) Anderson, who developed the mathematical model at the University of Dundee in Scotland. And the math model is similar to the ones used to predict the weather.
"Today we can know pretty well that for the next few days we're going to expect good weather or that there's a storm on the way," Quaranta said. "That's the kind of predictive power we want to generate with our model for cancer invasion." The model -- a series of mathematical equations that drive computer simulations of tumor growth -- suggests that the microenvironment around tumor cells determines the tumor's ultimate cellular makeup and invasive potential.
Below is an illustration showing various simulation results (Credit: Vanderbilt University, University of Dundee). And here is a link to a larger version.
Here is the full caption: "Each row shows the simulation results from three different stages of the hybrid discrete-continuum (HDC) model development. In these simulations, the spatiotemporal evolution of cells growing is driven by the following models: row 1: purely continuous partial differential equations model where cells and other variables are considered as densities or concentrations (colors represent cell density, as defined by the heat map on the right); row 2: hybrid model where cells are considered as discrete (although without a phenotype) and the other variables as continuous concentrations; row 3: hybrid model in which cells have a phenotype and can mutate to different phenotypes (red = dead cells; blue = the most aggressive type IV phenotype, which comes to dominate the population over time)."
But does this model work -- and evolve?
"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."
Still, this mathematical modeling of a cancer evolution is only in its initial stage. And with the computers used by the researchers today, it takes eight hours to simulate four months of tumor growth.
The initial results suggest that some current therapies used to cure cancer may not target the most aggressive and invasive tumor cells. But remember that this is theoretical research.
The findings suggest that current chemotherapy approaches which create a harsh microenvironment in the tumor may leave behind the most aggressive and invasive tumor cells. "In the immediate term we may be diminishing tumor burden, but the long term effect is to have a much nastier tumor than there was to begin with," Quaranta said.
For more information about this computer simulation of tumor behavior, the scientific journal Cell has published the research work in its latest issue. It is named "Microenvironment controls cancer invasion" in the table of contents but the name of the scientific paper is "Tumor Morphology and Phenotypic Evolution Driven by Selective Pressure from the Microenvironment," which is certainly more impressive (Cell, Volume 127, Issue 5, Pages 905-915, November 30, 2006). Here are the links to the abstract and to the full text of this paper from which the above figure has been extracted.
Sources: Leigh MacMillan, Vanderbilt University, December 1, 2006; and various websites
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