Computer Simulation of Cancer Growth

Roland Piquepaille writes "For a long time now, researchers and scientists have used computer simulations in the physical sciences: physics, chemistry, and engineering. But what about biology? An international team of U.S. and Scottish mathematicians and biologists has built a math model to predict tumor behavior. The researchers say their approach is similar to the one used by weather forecasters. So far, this approach is entirely theoretical. But the scientists see their effort as the beginning of a new era in cancer research — 'a sea change in how biology is being done,' as the lead researcher described it. Read more for additional references and illustrations about this use of computer simulation to predict a cancer evolution."

Comments

Cancer as a chaotic system

[MillionthMonkey]

Who said cancer was a chaotic system? Do very small changes in input parameters cause exponentially large deviations in output values? I doubt it. Cancer is probably difficult to simulate due to its complexity, not its chaoticness.

Cancer is complex because it is chaotic. There is a (poorly understood) mechanism cells use to ensure that each chromosome has the right copy number (usu. 2) and that no chromosome is missing a chunk. In a tumor, or even a precancerous growth, something has happened to break this mechanism. When cells in a tumor or precancerous growth divide, they don't copy their chromosomes correctly- they make way more mistakes than normal cells during mitosis. A cell division event might give one daughter cell a single copy of chromosome 5, while the other daughter cell gets three copies. Or, one daughter cell gets a chunk of a chromosome that is missing in the other daughter cell. As a result there is enormous genetic variability within a single tumor or precancerous growth- each one is a little version of evolution in action as individual cells within the tumor population compete for fitness. (Most genes still work if you only have one copy, or 3, but it's much better to have 2.)

Eventually one cell has zero copies of at least a part of a chromosome, and that's when the fun really starts. One of the arms of chromosome 3, for example, appears to confer certain "superpowers" on any cell that loses it, since there appear to be certain tumor suppressor genes on that chromosome. As chromosome parts are gradually lost in the tumor population, the various superpowers of cancer become evident: growth in absence of any growth signals, loss of contact inhibition (you keep dividing even when you run out of room), the ability to ignore suicide signals from attacking white blood cells, the ability to promote blood vessel growth into the tumor, the ability to metastasize, etc. If a cell loses the right chunk of the right chromosome it can quickly take over the entire tumor, and you have a population of cells that are all missing that chromosome chunk and are ready to start losing more random chunks. So as you see, "very small changes in input parameters cause exponentially large deviations in output values".

I could be wrong but I think what they are modeling here is the genetic variation within the tumor, as evident in the chromosomal copy number within each cell.