Slashdot Mirror
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."
Programs and techniques be used wherever chaotic systems take place? I guess it's in the domain of the weather, disease rates and population growth.
It would be rather interesting to watch social networks in the similar style (Im not thinking of myspace gunk...).
Bioinformatics has been a growing area of research in Computer Science for over a decade now ...
Everything from developing algorithms to produce leafs/trees (for graphics) and to model pond-slime growth (for optimization problems) has been studied for awhile; hell, genetic algorithms and neural networks have been around for awhile.
But what about biology? An international team of U.S. and Scottish mathematicians and biologists has built a math model to predict tumor behavior.
In other news, an international team of U.S. and Scottish mathematicians and biologists has built a computer simulation of the RIAA's business model.
The theory of relativity doesn't work right in Arkansas.
The researchers say their approach is similar to the one used by weather forecasters.
So its results are only accurate when looking about 4 hours into the future?
If I could sue my weather reporter for malpractice, I'd be rich enough to live somewhere there's no weather, only climate.
I should trust my cancer diagnosis to become as reliable as the rain forecast for the weekend?
--
make install -not war
I, for one, welcome our new Global Warming Tumor Overlords.
668: Neighbour of the Beast
Increasingly, researches seem to be finding a clear connection between stem cells, aging, and cancer. It looks like cancer depends on errant stem cells for its rejuvination - and years of cancer study supports this theory.
So, by all appearances, if we could destroy just the right cells, a small percentage (0.10%) of the tumor, the tumor goes away!
So, while the mathematical model of growth might represent some predictive value, it certainly will not effectively model new developments, such as the above, when they are found.
I have no problem with your religion until you decide it's reason to deprive others of the truth.
... IF their proposed technique (which has not actually been tested against live cells) comes anywhere near a useful prediction. They haven't even done IN VITRO modeling yet. If this were a product announcement, I'd call it VAPORWARE of the highest order.
I've been hoping that eventually it will be possible to run a complete simulation of clinical research protocols long before any research participants are recruited. So this is very good news and a step in the right direction. Simulation cannot replace actual experimentation, but it can give you a very good idea of what to expect based on your theory which in the clinical sphere could have life saving potential.
To the making of books there is no end, so let's get started
Basically an oncologist should be able to get a rough guess of how a series of treatments will work, and if a set of treatments is just going to make a more resilient cancer, then they can consider more viable options. Cancer is tricky, and some treatments arent effective at the same stages.
Storm
For a long time now, researchers and scientists have used computer simulations in the physical sciences: physics, chemistry, and engineering. But what about biology?
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.
I've read papers on maths models of tumours that are decades old. Even more sophisticated models like the one the scientists have done, have been done to death in recent years, on everything from angiogenesis to metastasis (I should know, I wrote one). There's also a wealth of work done tying down theory and experiments with gene circuits in phages. So what is new about this work? Their results that Roland (who wouldn't know how to do a literature review if it bit him on the proverbial) lists:
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.
certainly aren't new. A model of invasiveness with different levels of agressiveness isn't new either. There model does give nice results on the phenotypes of cells that are selected for, and the ways it allows them to control the microenvironment are certainly cute.
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.