Computer Simulation of Cancer Growth 70
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."
Couldnt these.... (Score:3, Interesting)
It would be rather interesting to watch social networks in the similar style (Im not thinking of myspace gunk...).
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Introduce one random variation in the cells of a human and they can die of cancer.
Whereas other people can live and work in highly toxic environments all their lives and seemingly be immune.
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My understanding of chaos theory comes from Jurassic Park, so I can't speak to the larger question, but tumor development has enormous positive feedback because of the runaway growth of cancer cells. So I can imagine that small changes in, say, DNA repair efficiency, could lead to large changes in outcome.
(By the way, as with most Roland stories, this one is not uninterestin
Cancer as a chaotic system (Score:5, Interesting)
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.
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An example of what people generally mean when they say something is chaotic is that say for example you have an ideal population of antelope. If the temperature profiles f
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Could you please explain to us why the mechanism is poorly understood? You seem to have a good grasp of what is going on.
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Okay, so you should have no trouble predicting the exact pattern of capillary formation inside a tumor, right? Your assumption that there is no sensitivity to initial conditions is way off.
Sure, most tumors look similar macroscopically. So do most humans. Should I assume that the brain of Albert Einstein is pretty much identical to that of Jeffrey Dahmer because they happen to look identical (both men's brains have been studied by science)?
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Cancer, for the troll (Score:3, Interesting)
Bioinformatics (Score:3, Insightful)
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.
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Quantitative biology (such as bioinformatics) is still relatively new, and although computer science people understand it, there's a significant old guard in biology which still thinks of the science as a qualitative, observation based field. This modeling is just one example of biology moving from a "look what I found" field to a "look w
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"For a long time now, researchers and scientists have used computer simulations in the physical sciences: physics, chemistry, and engineering. But what about biology?"
When I read that it seemed to me that there was an implication that simulations involving Biology were a new thing; my point was to say "hey look, Biology has been looked at for awhile!" I realize that the early work in Biology was mostly pretty limited in use or understanding, but I still believe that the
Slightly OT but... (Score:1)
in other news... (Score:4, Funny)
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.
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I'm not that impressed. My computer can play the Goodfellas DVD, too.
I've supported your articles Roland (Score:1)
WTF are those glasses all about?
*off topic rant over* (someones gotta start it, might as well have a different angle to usual)
Back ontopic - if they are considering it like a weather model, just how many predictions end up in a whiteworld scenario?
Oh boy... (Score:4, Funny)
So its results are only accurate when looking about 4 hours into the future?
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Or that the most accurate prediction is to use the previous day's weather. So in this case, I guess in this case that means that you'd be safe to predict that tumour is still there.
Or Not (Score:4, Funny)
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?
Re:Or Not (Score:5, Informative)
Re:Or Not (Score:4, Interesting)
Your comment is really insightful, but it also reminds me how some doctors treat their patients as an engineer would treat a car. It must be really an unbelievable sad thing to happen. Then again, doctors can't cry over every patient, it would probably kill their spirit.
Ontopic: I quickly read the article, it seems that they especially focus on what happens if cells at certain positions in the tumor are being attacked by treatment. Depending on the type, the more actively replicating cells may be localized at the outside or something (didn't really get that). As they can go over many different schemes in a short time, their research might help optimizing treatment (if lower doses of drugs can be used that will always be better). So it might look straightforward, but this is actually a nice bit of research, done with simple means, that makes it rather elegant I think.
Oh great! (Score:3, Funny)
I, for one, welcome our new Global Warming Tumor Overlords.
Geez... (Score:2)
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Connections with Stem Cells? (Score:4, Interesting)
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.
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There's still plenty of value to be found in higher-scale models. (e.g., how the tumor as a whole interacts with the microenvironment, how proliferation-induced pressure turns off the vasculature and prevents drug delivery, how oxygen and glucose delivery throughout the tumor and the microenvironment affects the patterning of hy
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Obscure (Score:1)
a sea change in how biology is being done... (Score:3, Informative)
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It's easy to pin models down with in vitro modelling in simple systems [arxiv.org], harder to do with cancer, except in a largely qualitative way.
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Simulating Research Protocols (Score:4, Insightful)
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In fact, that's one of the main goals that we have in mathematical modeling of cancer: to make the term computational oncology a meaningful one.
Right now, there are some pretty decent models of angiogenesis, tumor growth, cell population dynamics with and without stem cells, tissue stress, and tumor microenvironment, and they're both produc
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Lab experiments are extremely expensive and by using "in-silico"-experiments one can dramatically cut down, for example, drug development costs.
Of course this is not the only area where Bioinformatics is being used, a good starting point for reading about this is the wikipedia on "Bioinformatics".
What ABOUT biology? (Score:2)
*yawn* (Score:4, Insightful)
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 [berrymanconsulting.com]). 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.
1955. Thomlinson & Gray. (Score:1)
Ignorant (Score:2)
Yes, scientists have used computer simulations heavily in biology too. Anything that can be mathematically modelled can make use of a computer. For years scientists have been using calculus and probability theory to model the way disease spreads, evolution, population growth etc.
New tact (Score:2)
Sea change? (Score:1)
Modeling CANCER is like stating (Score:1)
Modelling cancer is not an obvious problem. (Score:1)
TA is speaking about tissue-scale modelling of neoplasm growth. And these models are an interesting research tool. Yet theoretical for today. You are speaking about nothing.
Modelling cancer is difficult, because any model is a simplification. And it is not c
Not the only team... (Score:1)
How had this crap got published in Cell??? (Score:2)
Some basics (Score:2)
Let me explain. Cancer involves at least two fundamental phenomena accompaniyng affected tissues: (1) uncontrollable growth (2) detachment from the base (other cells, other tissues, bones, other structural elements).
Both things are more basic to the commonality of cells than the mechanisms exi
mathematical tumor modeling is not new! (Score:2)
So... (Score:2)