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Biotech Math

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."
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Computer Simulation of Cancer Growth

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  • Couldnt these.... (Score:3, Interesting)

    by Creepy Crawler ( 680178 ) on Monday December 04, 2006 @03:55PM (#17104202)
    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...).

    • Re: (Score:3, Insightful)

      by Anonymous Coward
      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.
      • There is incredible sensitivity to initial conditions, we just don't know all the specific triggers yet.

        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.

        • by MadEE ( 784327 )
          I don't think this actually goes beyond the behaviour of a tumour after it has formed (starts at 1000 cells) not if cancer will form in a specific cell or which people will form tumors.
      • by Otter ( 3800 )
        Who said cancer was a chaotic system? Do very small changes in input parameters cause exponentially large deviations in output values?

        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

      • by MillionthMonkey ( 240664 ) on Monday December 04, 2006 @05:04PM (#17105178)
        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.
        • by lukesl ( 555535 )
          Sensitivity to initial conditions is one feature of a chaotic system, but that alone does not make a system chaotic. Chaotic systems are ones that are capable of generating behavior that looks random, even though the system itself is not. Even from what you're describing, it sounds like cancer cells generate random, unpredictable behavior because the patterns of mutation and aneuploidy ARE random and unpredictable, not because there are chaotic dynamics at work. A more precise definition of chaos is here [wikipedia.org]
        • Re: (Score:1, Interesting)

          by Anonymous Coward
          I guess I have to be careful because I was talking about the mathematical definition of chaos which is much more important to computer systems. Having a setpoint of initial conditions between where you have a cancer and don't doesn't necessarily make something chaotic. For a large distribution of cells this can be modeled statistically.

          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
        • 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.

          Could you please explain to us why the mechanism is poorly understood? You seem to have a good grasp of what is going on.

          • Aneuploidy (wrong chromosome copy number) is triggered during cell division and has something to do with damage to the kinetochore [nih.gov], a protein structure that sits on a centromere at the junction of the chromosome arms. This is the thing that attaches to a mitotic spindle and drags the chromosome along the spindle into its daughter cell. That mechanism can malfunction by either not transporting the chromosome, or by pulling it the wrong way, or gluing it to another chromosome, or falling apart, etc. Aneuploid
      • 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)?

    • Social network analysis has been done to death, not only by computer scientists but also by physicists and anyone else who thinks they have jurisdiction over network analysis. Large-scale models of processes spreading in social networks have already been done. The one that comes to mind is EPISIMS [lanl.gov] done at the LANL. They combined various sources of demographic, traffic and other data for the city of Portland to build a real-world simulation of an epidemiological outbreak (check the site for some nice animati
  • Bioinformatics (Score:3, Insightful)

    by HappySqurriel ( 1010623 ) on Monday December 04, 2006 @03:58PM (#17104236)
    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.
    • There are two different things you're talking about. This is different than taking a biological process and applying it to a different field (such as genetic algorithms).

      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
    • Genetic algorithms and neural networks really don't have anything to do with bioinformatics. Both are "inspired" by biological processes but the comparison really ends there. Genetic algorithms, for example, are very similar to several other informed search algorithms which have nothing to do with biology, e.g. simulated annealing ("inspired" by physics and statistical considerations) and beam search. Neural networks are also contentious in the context you mentioned in the sense that they really don't stick
      • My comment was mostly from the quote:

        "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
    • ...your comment piqued my interest. Whenever people start predicting the fall of the American Economy (offshoring, outsourcing) thoughts like yours cross my head. On a macro level industries like this replace our lost jobs overseas. I believe we are on the virge, a couple decades or so, of a BioMed Age and America and a select few other countries are on the forefront of these new technologies. The field is very young and we have just scratched the surface. If done right outsourcing, whatever, can be a
  • by User 956 ( 568564 ) on Monday December 04, 2006 @03:59PM (#17104254) Homepage
    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.
    • Re: (Score:2, Insightful)

      by The Zon ( 969911 )
      In other news, an international team of U.S. and Scottish mathemeticians and biologists has built a computer simulation of the RIAA's business model.

      I'm not that impressed. My computer can play the Goodfellas DVD, too.
  • But FFS I didn't need to see your face on a blog.
    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)

    by PingSpike ( 947548 ) on Monday December 04, 2006 @04:01PM (#17104288)
    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?
    • by fiendy ( 931228 )
      So its results are only accurate when looking about 4 hours into the future?

      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)

    by Doc Ruby ( 173196 ) on Monday December 04, 2006 @04:02PM (#17104298) Homepage Journal
    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?
    • Re:Or Not (Score:5, Informative)

      by the_humeister ( 922869 ) on Monday December 04, 2006 @04:22PM (#17104582)
      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.
      • Re:Or Not (Score:4, Interesting)

        by pimpimpim ( 811140 ) on Monday December 04, 2006 @08:20PM (#17107968)
        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.

  • Oh great! (Score:3, Funny)

    by PHAEDRU5 ( 213667 ) <instascreed@COMMAgmail.com minus punct> on Monday December 04, 2006 @04:03PM (#17104320) Homepage
    From the article:
    The researchers say their approach is similar to the one used by weather forecasters.
    I, for one, welcome our new Global Warming Tumor Overlords.
  • First bugs, then viruses, then trojans, worms and other malware - now computers can get cancer!? What's next, liver disease?

    • Yeah, but transplants are much easier on computers...
    • *sigh*---RTFA. There's nothing about computers getting cancer, and really no relation to worms/malware etc. The researchers built models of cancer growth in order to empirically study how cancer spreads. If you wanted to build worms, there are much better models for spreading influence in computer networks than cancer growth.
      • by e4g4 ( 533831 )
        *groans* the other guy who replied to my comment got the joke. I knew I should have added an emoticon for our more humor-deprived slashdot brethren.
    • by Suhas ( 232056 )
      Mine has Amnesia, which is what it gets if you buy cheap RAM.
  • by mcrbids ( 148650 ) on Monday December 04, 2006 @04:04PM (#17104342) Journal
    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.
    • Re: (Score:3, Interesting)

      by macklin01 ( 760841 )

      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.

      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

    • but it may help identify where those cells are hiding by simulating behaviour....
  • Let it be revealed!
  • by frankie ( 91710 ) on Monday December 04, 2006 @04:14PM (#17104476) Journal
    ... 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.
    • hey haven't even done IN VITRO modeling yet.

      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.
    • by lukesl ( 555535 )
      But it's not a product announcement, it's a piece of research science. From the abstract [nih.gov], the model does make useful and testable predictions, providing an unexpected mechanism by which tumor invasiveness (the most important clinical aspect of a tumor) can emerge. It doesn't bother me that people sit around and snipe at serious scientists making useful contributions to the world, but it does bother me that other people mod them up.
  • by blueZhift ( 652272 ) on Monday December 04, 2006 @04:24PM (#17104612) Homepage Journal
    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.
    • 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.

      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

    • This is actually what a large part of bio/medical-informatics is about: simulation.
      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".
  • "For a long time now, researchers and scientists have used computer simulations in the physical sciences: physics, chemistry, and engineering. But what about biology?
    What about protein folding? That's a biological problem, one computers have been attacking for a while now.
  • *yawn* (Score:4, Insightful)

    by mattjb0010 ( 724744 ) on Monday December 04, 2006 @04:31PM (#17104712) Homepage
    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 [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.
    • One of the early mathematical models of cancer dates back to 1955!
      Thomlinson R. H., Gray L. H. The histological structure of some human lung cancers and the possible implications for radiotherapy // Br. J. Cancer. -- 1955. -- Vol. 9. -- Pp. 539-549.
      But the problem is certainly becoming hot during the last ten years.
  • "For a long time now, researchers and scientists have used computer simulations in the physical sciences: physics, chemistry, and engineering. But what about biology?"

    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.
  • Too bad for them it's just been determined that the consensus about cancer implantation has been turned upside down recently.
  • Am I the only person who is tired of hearing the phrase "sea change". It's one of those journalist fads that they will cram into every article just because everyone else is using it. Seriously, isn't their any other noun that could be used as adjectives instead?
  • ,"I'm going to model how Dark Energy and Dark Matter form" when we still don't know what they even composed of. In Cell Biology nobody is even sure on how NADH is bound to lactate dehydrogenase (LDH), but I guess NIH reviewers are always too stupid enough to fall for such "computer modeling". If you really want free and accurate biological models see www.kintecus.com as it is the de facto state-of-the-art in bioinformatics and modeling...and even then, the software system with its models produce okay resul
    • You are running an ad campaign for an obscure proprietary software: "state-of-the-art in bioinformatics", "free and accurate", "de facto". What does it model? What processes does it describe? How? What methods and what data does it use? You said nothing.

      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
  • I thought I'd point out that this isn't the only group in the world doing research like this--a friend of mine here is working on tumour modelling, and has been for several years now. The research group's homepage is http://www.maths.ox.ac.uk/cmb/Research/index.html [ox.ac.uk]h ere. I suspect there are probably many more, too, given there are journals devoted to this stuff.
  • I think when talking about cancer some people overlook one basic and some would say tragic fact of the whole principle of organization of higher eukaryots. Cancer is "natural" to a cell, the absence of it is unnatural.

    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
  • I love how these press releases from universities pretend as if no one had ever even contemplated such an idea before the ground-breaking work mentioned in the press release. People have been doing mathematical modeling of tumors for years. Avner Friedman has been doing work since the late 1990's at least (see http://www.math.ohio-state.edu/node/22077 [ohio-state.edu], for example).

  • The question on everyone's mind: does it spell out the GPL license text?

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