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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."

10 of 70 comments (clear)

  1. Re:Couldnt these.... by Anonymous Coward · · Score: 3, Insightful

    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.

  2. in other news... by User+956 · · Score: 3, Funny

    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.

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    The theory of relativity doesn't work right in Arkansas.
  3. Oh boy... by PingSpike · · Score: 4, Funny

    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?

  4. Or Not by Doc+Ruby · · Score: 3, Funny
    The researchers say their approach is similar to the one used by weather forecasters.


    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

    1. Re:Or Not by the_humeister · · Score: 4, Informative

      Diagnosis is usually the easy part. Prognosis, however, is a little harder to predict. Sure there are usually the benign ones where you have to be very unlucky for it to do any harm (eg basal cell carcinoma). We already have good statistics on the most common cancers with regard to morbidity/mortality with and without treatment. If you have grade 1 endometrial carcinoma, take the uterus out and you're most likely cured. If you have grade 4 astrocytoma, it's basically a death sentence. So I don't think these computer simulations of tumor behavior will really be of much help. Although the article does touch upon microenvironment issues, which sound promising if they can be adequately controlled for those tumors in the middle of the malignancy spectrum.

    2. Re:Or Not by pimpimpim · · Score: 3, Interesting
      take the uterus out and you're most likely cured

      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.

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      molmod.com - computing tips from a molecular modeling
  5. Connections with Stem Cells? by mcrbids · · Score: 3, Interesting

    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.

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    I have no problem with your religion until you decide it's reason to deprive others of the truth.
  6. Simulating Research Protocols by blueZhift · · Score: 3, Insightful

    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.

  7. *yawn* by mattjb0010 · · Score: 3, Insightful

    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.

  8. Cancer as a chaotic system by MillionthMonkey · · Score: 4, Interesting
    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.