Evolution and Cancer

Moving to Nature Networks

2007-06-19T21:59:00.000+02:00

Dear everybody.

From now on this blog is moving to Nature Networks. Find it following this link.

See you there!

Mini workshop in Oxford

2007-06-12T13:51:00.000+02:00

Today Marcus Tindall has organised a mini symposium (for lack of a better name) for me and the guys here working on mathematical models of cancer to get to know each other. I have given a very small presentation [PDF] (<30m) that covers stuff I presented before.

From the CMB I got to know the work of:

Philip Murray, who has created a CA model to study the role of the cell cycle in tumours and that is now trying to obtain a continuous model that displays the same behaviour.
Alex Fletcher who studies hypoxia in tumour development at the sub-cellular scale.
Matt Johnston who works with W. Bodmer (whose game theory models have inspired my own work) to study the dynamics of cell populations in a colon crypt in colorectal cancer. His model shows how a homeostatic population could explode by slightly altering some of the paramers.
Natasha Li who collaborates with Gatenby to study, using Cellular Automaton and continuous models, the role of glycolysis in tumour invasion and the influence of the stromal environment. This is specially relevant to me since it is one of my two main lines of work at the moment. She mention in her talk that glycolytic cells are especially sensitive to glucose deprivation.
Rebecca Carter works on multiscale models of fluid and drug transportation in tumours.
Marcus Tindall gave a brief introduction to his multiscale model of interaction between the cell cycle and cell density.

The presentations were all quite short but I hope to hear more from these people in the coming days.

Queerer than we can suppose

2007-06-05T11:37:00.000+02:00

I found this video from a Richard Dawkins's talk in which he talks about the strangeness of science.

He talks that science is about truth but that our brain is evolved to cope with every day's reality, within the scope of the reality we have to live with. He cites the example that matter is mostly composed of space but we do not perceive it like that since it is more useful for us to perceive it as solid and opaque. He argues that a living being of the size of a neutrino and capable of vision would see matter as mostly empty space only by the nature of the space it inhabits. Similarly, things that look entirely unlikely to us (the existence of life) become inevitable when considering the vast amounts of time and space the universe has been going on compared to the space and time of our human lifetimes.

More shockingly to me he claims that humans are more akin to automata than to agents seeking what they consider positive things and avoiding negative things. The reason being that evolutionarily we rather model fellow humans as people with a purpose than as systems made of components whose design and integration we ignore.

In any case this is an important issue for scientists and philosophers of science: our brains have evolved for certain purposes and with certain biases and that should impose some limitations and constraints in what things we can understand and how we chose to interpret natural phenomena.

Oxford

2007-06-03T20:15:00.000+02:00

I will be staying one month at the Centre for Mathematical Biology directed by Philip Maini at the University of Oxford. With a little of luck I will be able to meet people interested in mathematical discrete models of cancer evolution and angiogenesis.

In the Centre they have some interesting (and relevant) research lines like "individual and collective behaviour in ecology" and of course "cancer modelling". The Centre is pioneering (with Arizona's Gatenby and Oxford's Comlab Gavaghan) the idea that glycolytic acidity promotes invasion. Maybe this could be an opportunity to test my hypothesis that this invasion comes in waves.

Talk in Girona

2007-06-01T17:18:00.000+02:00

I have been invited by Josep Vehi to give a talk about my research at the institute he directs at the University of Girona.

In this talk I have introduced for the first time the game theory model in which I have worked with people in Dresden (Andreas Deutsch, Haralambos Hatzikirou) and Bonn (Matthias Simon) in which I study Gatenby's hypothesis of acid mediated tumour invasion. I have also talked about the Cellular Automata model I have developed with Benjamin Ribba (Lyon) to study the microenvironmental influence in cancer evolution which I have previously presented in Lyon, Dundee and Dresden.

The presentation can be found here in PDF format.

cancer and the cell cycle

2007-05-29T11:16:00.000+02:00

Last Friday I came to the Max Planck Instute for Cell Biology, at the other side of Dresden, to attend a series of seminars including one from a colleague and friend of mine, Babis Hatzikirou, about the cell cycle.

The classical view on the cell cycle can be seen in this picture that I took from Babis's presentation (and which I suspect he took from somewhere else :)):
This is quite interesting although not precisely research news. Most of the cell cycle is of course devoted to interphase and only a minority of the time (assuming that the cell is not in arrest mode) is devoted to create a copy of itself (through mitosis and cytokinesis). The cell cycle is controlled by a finely tuned balance of proteins cdc2-cdc13 and a number of checkpoints make sure that before changing the phase of the cell cycle everything is in order. These checkpoints and their associated proteins (such as the famous TP53) are quite critical to prevent tumour formation as they impede the growth of cells that need DNA repair.

What science is not

2007-05-18T12:32:00.000+02:00

From an extract of the book The invisible sex: Uncovering the true roles of Woman in Prehistory (review in Nature 3rd of May issue).

"science is not truth; it is, instead, a method for diminishing ignorance"

A 3D model of human breast cancer

2007-05-16T18:01:00.000+02:00

This has been covered in a few places like the BBC and ScienceDaily. It seems that some researchers at Queen Mary College in London have recently come with a non animal 3D human breast cancer model.

This is interesting at more than one level. Their research was funded by a research charity (Dr Hadwen Trust) that supports the development of methods that avoid animal experiments. Working with rats is not that satisfactory for ethical reasons and also because there are many cases in which the results of rat experiments cannot be extrapolated to humans (seems we are not so similar in some respects after all). It is also much more realistic than just taking some human cancer cells and studying them on a petri dish.

Being capable of performing experiments using realistic 3D models quickly and efficiently is one of the holy grails of theoreticians since it would make experimental validation of our models much easier (confusingly enough what theoreticians call model, eg, equations or computer rules, is not what experimentalists understand as a model, eg. rat, arabidopsis or drosophila). This validation is quite complicated as I have already mentioned in another post. Making this validation easier and more convenient will go a long way in terms of making our work more reliable and quantitative.

Somatic and non somatic evolution

2007-05-14T10:16:00.000+02:00

Many ecologists study evolution of the non somatic kind. That is, evolution that happens as a consequence of mutations in the germ line of multicellular organisms during reproduction. The evolution of cancer is of the somatic kind. This means that it affects cells of the soma, the ones that are not transmitted to the offspring.

Some time ago I got this paper from Crespi and Summers (nicely enough, publicly available). I will probably talk about this paper, entitled Evolutionary biology of cancer (and presented to a readership of ecologists) some other time but I liked a table in which they compare somatic and non somatic evolution.

Phenotypic variation. In most ecosystems of multicellular organisms variation is attained through genetic recombination (sexual reproduction) and mutation. In a tumour we also have to consider also genomic instability (a hypothesis by which some individuals have a higher probability of mutation) and epigenetic alteration (the environment also affects the behaviour of cells in ways that could make tumour progression to cancer more or less likely).
Selection. In most ecosystems it means dealing better with competitors, avoiding predators, parasites and producing many fit successors. In a tumour means being good at competing for resources with other cells (tumour or otherwise), avoiding the immune system and coping with environmental signals designed to maintain homeostasis.
Drift. That is similar in both types of evolution.
Inheritance. In many cases that involves the transmission of genes from parents to offspring through sexual recombination. In tumours there is no sexual reproduction.
Result. In most ecosystems the result is adaptation across generations. In a tumour the end results is in many cases the death of the individual and thus of all the cells in the body, including the cancer cells.

I think that this is a quite interesting and useful comparison of evolution although I am not sure I agree with all the differences suggested. In my view the evolution in a tumour does not differ much from other types of evolution. For instance, epigenetic changes do play a role in other ecosystems asides from cancer. Genetic instability is not a source of variation, genetic mutations are (genetic instability just makes genetic mutations more likely). Also the fact that tumour cells reproduce asexually is not a big difference with more conventional ecosystems. At the end of the day most of the biomass of the planet is made of bacteria that reproduces asexually. What it is true is that as far as we know, the end result of cancer evolution is either the end of the cancer itself or the end of the individual that hosts the cancer and thus the end of the cancer cells. Thus the only way tumour cells have to be successful is to evolve in such a way that the life of the host is not threatened (you can call that tumour sustainable growth).

Autophagy and cancer

2007-05-09T10:02:00.000+02:00

This is a new cellular mechanism I did not know about: autophagy. Nature's issue of April 12th (I am bit behind I know) has an interesting article in the section Q&A on autophagy and its role in cancer.

Autophagy is the process by which cells degrade faulty or redundant components. It is used by cells when they need to reuse molecules for other uses and also it plays an important role in complementing apoptosis. Both apoptosis and autophagy are connected to cell death but in the case of autophagy cell death is not always the outcome although it can be a substitute when the apoptotic mechanism is crippled. In that case the cell literally eats itself to death.

The image bellow comes from the article. Autophagy has the potential of being useful for cancer supression but also for cancer promotion. The balance is important, too little and you get cell death when the cell cannot produce things it needs by reusing parts of itself. Too much of it and you also get cell death since the cell can eat itself. Altering this balance in a tumour cell could be the source of a new therapy although as usual it is important to remember that cells might evolve mechanisms to avoid the trouble of autophagy, maybe by inactivating the atophagy mechanism all together. Even in that case the tumour cell would be less capable of surviving in situations of stress since it would not be able to recycle material.

Autophagy seems to be a mechanism whose precise role in cancer has not been fully studied yet but could be a promising extra target for a multi target therapy that could hinder cancer evolution and growth.

Evolution and medicine

2007-05-07T10:49:00.000+02:00

Catriona MacCallum, an editor at PLoS Biology has posted the following essay (being PLoS, it is available to everybody) about medicine and evolution.

According to the article, physicians do not get much of a training in evolution as a method to study the origin of diseases. That is because most of the training of physicists is not to make them good scientists but to make them good at treating patients. Quoting the article: "does a mechanic need to understand the origins, history and technological advances that have gone into the modern motor vehicle in order to fix it?".

This approach is not entirely wrong and once can treat things that are the result of an evolutionary process without having to spend too much time studying evolution. A different thing is when the disease is not a result of evolution but they are evolution itself. They never mention cancer in the article but cancer and infectious diseases are clear cases of diseases in which evolution should be dealt with if the disease is to be cured or even contained. Without an understanding of evolution a physician will be unable to understand how the bacteria or cancer cells will react and evolve when a treatment is used or what phenotypical traits are more likely to be evolved and thus cause problems to or be exploited by the medical community.

Cell article on science blogs

2007-05-04T16:54:00.000+02:00

Blogs as a way to communicate science. This is quite an unusual topic for Cell that, as opposed to Science and Nature journals, devotes less space to the non-technical side of science. For those of you that are subscribed, the article is here.

According to the article there are approximately 20000 blogs with the label 'science'. That is quite an impressive number since most of my colleagues seem to be doing lots of things but not blogging. It seems that most of these science blogs are actually about pseudo science which would be the number of more conventional science blogs to around 1200 (always according to sources cited in the article). These are generally blogs like mine (of course in many cases better written and updated more often) which deal with fairly specific issues in a specific field of science.

These science blogs can be just about anything. Many do like I do and comment (what we personally find) interesting stuff in our own field of research that we find reading, mostly, papers and journals. Some do also include bits about their own lifes and produce some sort of hybrid between the conventional blog (understood as a personal diary) and the scientific blog. Some take the idea of science blog a step further and every day record their latest results online (although in some fields, like biology, this behaviour seems to be quite rare due to the extreme levels of competition between experimental biologists).

Why would any one start a science blog? On top of the conventional reasons why people start a blog (and weighted down by the fact that most of us do not carry sizable audiences) is the thought that when you write something with the expectation (as unlikely as it might be) that someone will read it that surely helps to clarify that something in your mind.

Mini workshop on cancer and cellular automata

2007-05-02T10:08:00.000+02:00

Today we are hosting in our group at TU Dresden a mini workshop on cellular automata in biology. Three talks (one in the morning and two in the afternoon) are actually about CAs and cancer. It will be a busy but interesting day.

The booklet for the afternoon part of the workshop (the longest part of it) is here.

evolution of multicellularity

2007-04-27T12:20:00.000+02:00

A friend of mine has found this interesting essay in Nature entitled "Unity from conflict" that deals with the evolutionary mechanisms that allowed the emergence of multicellular organisms.
The problem of how multicellular organisms came about from single cells is quite intriguing. I heard from Lewis Wolpert that this is probably the most important of the seven transitions in evolution as described by Maynard Smith and Szathmáry in their book. In retrospect it is clear that such a transition is possible (since we are here) but, why did it happen?

Paul Rainey (whom I suspect might be a microbiologist) seems to be suggesting that with the right mutation rate (or right mutation bias) multi-cellularity should be possible. Organisms such as myxobacteria seem to be able to alter their mutation rate in response to stress in the environment so I guess that evolution fiddling with the right mutation rate is not unreasonable. In any case I'd rather see it from the point of view of my friend, that is, a harsh environment does enforce cooperation in a way that makes cheating very costly. In reality I would imagine that other factors such as the immune system (that in a way can be though of a police on the lookout for cheaters) or the fact that cells in a multicellular organism share the same DNA could also help explain why there is not that much cheating in our bodies.

This article is quite interesting for any one interested in cancer. At the end of the day a cancer cell is a normal cell that due to genetic or epigenetic reasons stops cooperating. Once they evolve the means to avoid the immune system and other mechanisms designed to maintain homeostasis I would imagine that the life expectancy of a tumour cell should be rather short (necrosis, running behind in the evolution game or due to a poor microenvironment) and thus crime might not pay, at least in the mid/long term (which still would leave room for a benefit in the short term that would be enough to kick-start somatic evolution).

It should be possible using a computational model to demonstrate that an aggressive microenvironment would favour cell cooperation. A mutlicellular organism in which individual cells suffer when exposed to the exterior would evolve a morphology that would minimise the interface with the outside world. it would be also quite likely that a niche of stem cells would evolve to be in charge of generating the cells in this interface that would be in need of constant repair and maintenance. That is what happens in places in which the environment is hostile to cells like the colon or the skin. If cells in the model are allowed to cheat (by means of mutations leading cells to try to avoid being part of the interface if that is their role) that would presumably affect negatively the overall fitness of the organism. However I am not sure that this would rule out other explanations for the evolution of multicellular organisms.

Acceptance of evolution around the world

2007-04-23T10:08:00.000+02:00

National Geographic has published this chart that depicts the public acceptance of Darwinian evolution in 34 countries around the world. As a Spaniard I am happy to see that evolution is widely accepted in my country, with a higher acceptance rate than even in Germany where I currently live although not as high as in Scandinavian countries or in the UK (the birthplace of Darwin). In the U.S. less than half of the population (if the results of the poll can be extrapolated) have at least some reservations towards evolution although the country (of all those polled) that seems most hostile to it seems to be Turkey.

The laws of biology

2007-04-17T11:58:00.000+02:00

The side effect of having spending so much time traveling these last months is that I have this stack of Nature and Science journals (I switched from the former to the latter a month ago to see the difference) which I am going through quite slowly.

In a Nature from the 7th of February there is an interesting essay about the clash of cultures between biologists and physicists working on biological topics written by a physicist from MIT (good to know where the bias will come from). Physicists have a long tradition of studying an (increasing) range of phenomena and producing theoretical models that characterise as many of those phenomena as possible. These are what are called the laws of physics. The question is if biology can have also models and laws that represent biological phenomena.

Although there are some (fairly generic and neat) biological laws (thing of Darwin's evolution and Mendel's genetics) most biologists seem to be more interested in fact collecting than in putting the available information in the form of theoretical models and universal laws of biology. The physicists (and mathematicians) coming to the field have not much knowledge in how the facts are collected (which it is easy to imagine as the source of many frustrations) but a deep interest in integrating those facts into models (especially when it involves using their favourite tools such as phase transitions, fractal analysis, power laws or networks). It remains to be seen if (in the view of the author) these general laws are possible at all and if (not my view but at least my question) the tools that were useful in physics will be that useful in biology (which does not mean they could at the very least, constitute a good starting point).

Back from Scotland and Gatenby's talk

2007-04-03T17:22:00.000+02:00

I am back from sunny Scotland in sunny Saxony. Of the remaining speakers in Dundee, the one whose talk I was looking for the most was the one from Robert Gatenby, Arizona University (as with Vito Quaranta, a life scientist).

I know the work of Gatenby because he is one of the few researchers involved in using evolutionary game theory (although not of the most conventional, fitness-and-payoff-table kind) to study cancer evolution. Specifically he is working on how acidity due to glycolysis (the anaerobic metabolism that constitutes and advantage for tumour cells that lack oxygen due to the distance to a blood vessel) is a necessary step in the evolution towards cancer. The so called Warburg effect is the result of a well known biochemical mechanism but, what is the evolutionary advantage?

As he has shown in other papers, the advantage for glycolytic cells is that the poison the environment of other cells so they face less competition. They also degrade the connective tissue and thus increase the motility of cells, which is a required step for a tumour to become invasive. From my point of view it is interesting that he seemed to imply that this acidification of the microenvironment is not only a facilitator for cancer but a necessary step. I guess that Hanahan and Weinberg could include this in the section for mechanisms for invasion and metastasis.

From the therapeutic point of view, his research suggests that either alkalising the microenvironment (to counteract the progressive acidification resulting from the glycolytic metabolism) or making it even more acidic by reducing the pH in the blood (and thus contributing to self poisoning of glycolytic cells) would be something worth trying.

The cost of validation

2007-03-29T16:29:00.000+02:00

Many interesting speakers in this workshop in Dundee but most of them fall in the mathematics part of biomathematics. Among the few who do not is the biologist Vito Quaranta (Vanderbilt University). Although I have been told many times that things are changing for the better in that respect, the scarcity of life scientists and medical doctors in these type of conferences tells me that there is still a lot of work to do to convince them that computational and mathematical biology is not only relevant but necessary.

The talk from Vito Quaranta was not so much about science as about doing science at the interface between theory and experiments. He is lucky to count with the resources of the Vanderbilt Integrative Cancer Biology Center. Otherwise the problem of validating the mathematical and computational models with theoreticians come with would be next to impossible. This theoretical models make a number of assumptions about the properties of tumour cells, tissues and micro environments and predict outcomes that in many cases have to be contrasted with in vivo and in vitro experimental results. This experimental work is really challenging given the level of fragmentation of knowledge and expertise in biology and medicine. Different labs with different experimental techniques, machinery, cell lines and the necessary permissions to perform animal experiments and access human clinical data are required to validate one single theoretical model. That means that unless centres like the one in Vanderbilt become much more common most theoretical models will remain experimentally untested unless they proof to come out as the result of the consensus of the theoretical biology community.

Cooperation in a tumour and workshop in Scotland

2007-03-26T18:29:00.000+02:00

I find myself in Dundee, in Scotland, attending a workshop entitled Mathematical modelling and analysis of cancer invasion of tissues. It promises to be an interesting event and some of the attendees are working on topics that are very close to mines so it is good to know what is their contribution to the state of the art.

When I arrived this morning I was expecting good stuff from people like Philip Maini (Oxford), Bob Gatenby (Arizona), Vito Quaranta (Vanderbilt) and Sandy Anderson. Still today's most relevant talk for me was given by Anna Marciniak-Czochra (Heidelberg) who presented work based on the research presented very recently by Robert Axelrod (and reviewed in this blog here). Axelrod's work is about how the collaboration between tumour cells could mean that cells do not have to acquire all the necessary capabilities (mentioned in Hanahan and Weinberg's 2000 work) in order for the tumour to become agressive. This is a word model but in Marciniak-Czochra's presentation a mathematical description was shown in which the characteristics of the growth factors (eg. diffusion strength) can determine how useful this collaboration is. It looks like an interesting model and hope a paper will come out soon so I can take a look. Still it seems that a paper that covers Axelrod's work more comprehensively is still work to be done.

The links between scientific disciplines

2007-03-21T11:52:00.000+01:00

I have just found this amusing article about how some guys took more than a million and a half scientific papers from 776 different branches of science and came with the graph included in this post. You can find a larger version (5Mb) of it at this site. It shows how often papers from different disciples are cited by the same paper so it can give a measure of what fields are more likely to inspire interdisciplinary work.

Most of the research seems to be in Medicine and biochemistry (including all the -omics stuff). Math seems to be more unconnected to many other branches of science that I thought but to be honest I am not very sure about the methodology. More about it can be found in Mapofscience.com.

World Community Grid and Cancer

2007-03-18T15:47:00.000+01:00

Since the guys at SETI came with the idea of using the CPU time of internet users when they are not using their computers, several other projects draw inspiration from this idea to obtain some sort of highly distributed high performance computing when the funding is not there.

One of these projects is called the world community grid which involves many research centres and universities and tries to tackle several problems that should be of general concern. One of the projects is about Cancer. One of the ways to go about cancer research is by using tissue microarrays in which samples of tumour cells are treated differently and the results of the different treatments can be obtained and compared in a comparatively efficient way. I am writing this from Columbus airport but when I get the chance of getting back to Dresden I should install this client on my Linux workstation. They do have versions for Linux, Mac and Windows.

Of course one thought is that if I know that I will not use the computer in a while the right thing to do (assuming one cares about the world) is to switch the computer off but I guess that those times in which the screen saver kicks in I would be happier thinking that my computer is doing something interesting instead of just displaying pointless and CPU intensive openGL pictures.

Columbus workshop and interactions with life scientists

2007-03-13T12:54:00.000+01:00

Being a workshop on mathematical biology one of the issues we all face here is how to work with life scientists and thus one of the panel session yesterdays was precisely about that.

It seems that there are different kind of problems theoreticians might find when dealing with clinicians and experimentalists depending on a number of factors:

What kind of people are they? Are they 'math-skeptic'? do they have affinity towards theory?
Do you want them to share their expertise with you or do you want to influence the experiments they perform so they can be used in your theoretical model? The latter is significantly more difficult.
Do you work with biologists or with physicians? There is a real difference between the average PhD and the average MD that does some research on the side when it comes to understand the usefulness of theory.

Some tips where also offered by some participants on how to make finding and establishing collaborations. Mainly it helps to attend seminars from the life sciences departments, get yourself familiar with their stuff and get your face known to them so you don't come as a complete stranger.

Workshop in Ohio

2007-03-09T13:12:00.000+01:00

I will not probably have much time for posts next week since I plan to attend a workshop in Columbus, Ohio. The workshop is organised by the Mathematical Biosciences Institute of the Ohio State University and is entitled Workshop for young researchers in mathematical biology (remember what the meaning of young researcher is from my previous post from my visit to Barcelona :().

At any rate there will be some interesting people both in the category of keynote speakers and "young" researchers. Some of them doing bio mathematics of cancer so expect a report on that when I come back.

cancer genes

2007-03-08T18:14:00.000+01:00

The information can be found tailored for all types of users. For those who want an easy take here is the BBC version. Nature has a nice overview and the article proper.

Here is my take: a (fairly large) group of researchers mainly at the Sanger, in UK have studied hundreds of genes that are mutated in about 200 types of cancers. The trick here is to find what genes DO drive cancer as opposed to 'just happen to be mutated' in a cancer. At the end of the day your average tumour cell in an advanced stage tumour is likely to contain several mutations and many of them will probably be hitchhikers not necessarily contributing to the overall fitness of the cell. Unfortunately the result of the research is that the number of genes mutated in many cancers is higher than expected and telling apart driving genes from others will be a challenging task. One thing of working with so many types of cancers (200) is that genes that might not play any significant role in one type of cancer might turn to be important in the next.

Telomeres, cancer and aging

2007-03-07T17:22:00.000+01:00

One quite fascinating thing in animal biology is the question of immortality or, to be more precise, the lack of it. While most unicellular organisms can divide for as long as they have the luck to find resources and space to do so, human cells can divide only a limited amount of times (approximately around 50 times, although this does not apply to stem cells that can divide an unlimited amount of times). In principle the limitation in divisions for most human cells is due to a mechanism that has been evolved and is not an intrinsic limitation. The cancer hypothesis is that the limitation makes the appearance of cancer more unlikely. If a cell is limited to just a few divisions, if it acquires a mutation that mutation is unlikely to spread to far.

The reason for this limitation are the telomeres, situated at the end of the chromosomes, that get shorter each time the cell divides. Once these telomores reach a critical size and become to small the cell will enter a state called senescence by which they will not divide again.

This is an interesting link in which they talk about this and how in the next few decades we might know enough about the effects of limited cell replication in human life expectancy, how to increase it (maybe for ever) and how to do that avoiding nasty side effects (like increased probability of dying from cancer). The website in which this is hosted is covering all sorts of news, many of them of dubious scientific interest, but the information in the link looks sound.

On the other hand in a more reliable source (PNAS) there is a nice study on how telomere dysfunction can cause genetic instability. They work on a disease known as Werner syndrome but it is quite useful stuff for cancer research. This Werner syndrome results in people aging prematurely and researchers at the Salk institute have found how extra short telomeres can be the source of the problem.

Bioinformatics and google

2007-03-05T10:16:00.000+01:00

First of all, I am not a bioinformatician. I even thought I had an idea of what is the aim of bioinformatics but after a visit to the group of Nuria Lopez Bigas at the Biomedical Research Parc in Barcelona I realised that the scope of what I thought the field is about was too narrow (they do some nice machine learning and statistical work on disease related genes).

I have seen this video on Google video (only one of these sites that allows the user to download the video for offline use) some time this weekend. It is just a talk by David Vise, the author of a book about Google, to staff at Google Inc. Google is one company that fascinates (and in a sense, worries) me tremendously. As a side note, this blog is posted in one of their servers.

The thing is that at the end of the talk, David mentions the interests of one of Google founders (I think it is Larry Page) on biology. Then I thought (and I am sure that I will be the last of a long list of people) that, wow, that is really a good match: google and bioinformatics. Biology until know was mostly a science in which practitioners collected facts. There is loads of data and little idea of how to make sense of it, asides from evolution and a few other very general ideas. One of the aims of google is precisely to find patterns in the zitabytes of information stored in their servers. I have the feeling that we will see more of Google in that field.

Old Dawkins video on cooperation

2007-03-01T10:15:00.000+01:00

I have found this video on google video. It is an old Richard Dawkins BBC TV programme in which he goes through some topics of which I am quite fond and which I personally think have some yet-to-be-explored relevance to cancer research.

The documentary was produced a few years after Dawkins wrote The selfish gene and not long after Robert Axelrod had written The evolution of cooperation. It takes from Axelrod's research on cooperation (whose own take on how this can be observed in cancer has been mentioned in this blog before) to illustrate how cooperation might evolve in an place in which agents (say humans, bacteria or buffaloes) are selfish. The topics are the usual ones in game theory such as prisoners dilemma (how playing if for an undetermined number of times changes what is the best strategy), tragedy of the commons (if everybody is overusing a resource why shouldn't you, and if few people overuse, why shouldn't you since it will make no difference whatsoever?).

The tragedy of the commons seems to me a suitable game to model global warming (why should your country cut on carbon emissions if nobody else does or why should you if everybody does? this seems to apply to most countries but the likes of U.S. and China whose weight is to big to be considered just another player) or cancer (at the end, tumour cells do kill the host and thus themselves).

In Barcelona

2007-02-23T23:11:00.000+01:00

I have finished my stay in Lyon and arrived to Barcelona to attend a round table for young researchers organised by the Universitat Autonoma de Barcelona. Interestingly enough the definition of young researcher seemed to include any researcher after the PhD but without a stable contract (that is, postdocs, non tenured group leaders and people in teaching positions).

I was a rather interesting discussion that dealt with things that I imagine are common worries for young researchers across Europe and elsewhere. Mainly the difficulty of living on short term research contracts, (for those of us postdocing somewhere else) the strain of keeping up with friends, relatives and former colleagues while living abroad, the gap between our real age (late twenties or early thirties) and how our status is perceived by the rest of the population (not like assistant professors or people with "real" jobs and more like students with a fancy "Dr." in front). Other issues that I found very relevant not only for young researchers are the link between research and teaching (in Spain, like many other countries, university lecturers are paid to teach but their progress on the career ladder depends exclusively on publications) and linked to that if the main duty of academic staff is to perform research or to teach (there seemed to be some consensus that universities should be free to chose wether to have a research profile or a teaching profile).

Lenski et al: Balancing robustness and evolvability

2007-02-13T10:20:00.000+01:00

R. Lensi, J. Barrick and C. Ofria. Balancing robustness and evolvability. PLoS Biology, Vol. 4, 12, pp 2190-2193

This paper has not much to do with cancer but I have been interested in evolvability issues for a while so I decided to take a look at it. Tumour evolution has many but not all the features of the evolution involving longer time scales but its evolvability is not a thoroughly investigated topic. That is a shame because it seems that, given enough time, one would expect that tumour cells will not evolve only towards phenotypes that can take better advantage of the environment but also to genotypes that allow evolution to adapt better to that changing environment.

This paper does not explore this but something also interesting: that robustness and evolvability might be desirable but incompatible aims. Robustness can be seen as he ability to counteract change while evolvability represents the capability to adapt. In general it is true that species must strike some sort of compromise between these two abilities since organisms need the robustness provided, for instance, by the DNA repair mechanism but species need mutations that actually allow these organisms to better adapt to the environment. This is not always true and there are cases in which robustness and evolvability can go happily hand by hand. One such case is genomic redundancy. Up to a point, genomic redundancy improves robustness since functionality is kept in more than one location making it less vulnerable but also it helps evolvability since it allows duplicated genes to evolve different functions.

The general rule though is that organisms cannot be entirely robust to change in the form of genetic mutations since such an organism would freeze from an evolutionary point of view and thus subject to become extinct when a fitter rival comes around. I guess that that is a good explanation to cancer, a perfect reproduction mechanism would have not led from simple organisms to humans.

Cancer and biofuels

2007-02-12T13:41:00.000+01:00

I have recently commented how (in my particular view, especially at the theoretical level) research in some area can be used in a different one but I guess I did not expect this: Cancer research may help biofuels.

It seems that, inspired by research done at the Fred Hutchinson Cancer Research Center in Seattle, a company called Targeted Growth is doing to corn the opposite of what oncologists do to human cancer cells taking advantage of the fact that some pathways in these two different cells are similar. The idea is to promote plant growth by overriding the genetic clock that tells the cell when to stop growing. The advantage is that plants thus modified are not transgenic (whith the load that this label carries to many consumers) and that it can lower the price of growing them as biofuels and thus promoting them as a good value alternative to oil.

Axelrod et al: Evolution of cooperation among tumor cells

2007-02-09T11:33:00.001+01:00

R. Axelrod, D. Axelrod and K. Pienta: Evolution of cooperation among tumor cells. PNAS vol 103, 36, pp. 13474-13479, 2006.

A few months ago a friend of mine from Vienna send me the link to this paper (thanks Peter!) and although I skimmed through it at the time only now did I have the chance to read it with a little bit more of care. Robert Axelrod is well known in the complex systems and game theory communities. The research he did almost a quarter of century ago (detailed in his book: The evolution of cooperation) explained how cooperation can be established between two agents (people, elephants or cells) even when the mechanisms of the cooperation have not been agreed beforehand and the agents could gain more in the short term by not cooperating.

Now Axelrod and coauthors speculate on how this approach could be used to study carcinogenesis. They present this in the framework of Hanahan and Weinberg and the six capabilities required to progress towards cancer (self sufficiency in growth signals, ignoring anti growth signals, evasion of apoptosis, angiogenesis, limitless replicative potential and invasion/metastasis).

Now, this paper is no regular paper. Most research papers I read describe a particular piece of clinical research (we have investigated this gene in this context...), mathematical or computational model (in this paper we introduce a model that explains the influence of acidity in...) or are review papers. This one does not describe new clinical research nor does propose a formal way to describe any aspect of oncology nor represents a review of carcinogenesis research from the cooperation point of view. This is not meant to be a criticism. The paper represents for me a new category of papers, one whose aim is not as much as telling finished research as to suggest to the reader new venues of research under a particular perspective.

If that was indeed the aim then this is a good paper. According to the authors, the conventional view on tumor progression using the Hanahan and Weinberg framework is that cells have to acquire all the six capabilities but under the new cooperation based view this is no longer necessary. It could be possible that, at least some of this capabilities are provided by some cells to others and thus cancer could occur when groups of cells displaying a mixed set of capabilities collaborate to create the same effect of a single cell acquiring all the capabilities and reaching fixation (taking over the tumour population) by clonal expansion. One of the things that I was not very comfortable with is that the authors state that cancers are the result of genetic (or epigenetic) instability. Readers of this site probably know that this is currently a hotly debated topic (something as fundamental such as: what starts carcinogenesis) and that in front of the Weinberg school (cancer starts from genetic instability) is the , say, Tomlison school (a bigger number of cells and selection suffices to explain the start of cancer). My view is that if tumour cells can cooperate in order to share capabilities and progress down the path of carcinogenesis then having a higher mutation rate might not be so relevant and thus a cooperation based view on cancer would favour the view that cancer does not really need genetic instability to get started. If this view of mine turns out to be a stupidity remember that you read it here first.

The paper provides a number of examples of capabilities in which cooperation can happen. In angiogenesis (where cells can produce growth factors that benefit not only the producing cell but others in the neighbourhood), self sufficiency from (certain) growth signals (there is a certain amount of growth signals which can be produced in paracrine or autocrine fashion) and in invasion/metastasis (collaboration to degrade the ExtraCellular Matrix).

The authors point out that this view of carcinogenesis arises a number of new research questions such as what are the resources that can be shared among cooperating tumour cells, what mechanisms are used to share these resources, how does this affect the order in which mutations appear (since mutations can appear in parallel)? Interesting questions but it might take some for someone to come with the answers...if it is that answers can be found using evolutionary cooperation.

Mitochondria and apoptosis

2007-02-06T17:48:00.000+01:00

A couple of posts ago I mentioned this research in which RNAi was used to restore the functionality of the mitochondria, especially its role in apoptosis. Now I read that the same results are being obtained by Dr. Michelakis and colleagues at the University of Alberta in Canada using a well known drug, dichloroacetate (DCA).

DCA is an affordable drug that has been previously used to treat metabolic disorders so it is known to be safe and has no patent. What should have been a blessing could also be a curse since there is little incentive to large pharmaceutical companies to finance the clinical trials. The news has been reported in all sorts of news outlets from Cancer Cell to Slashdot and including The Economist. In this website you will be able to find the latest results as well as information on how to donate money so Dr. Michelakis and his group can finance the clinical trials.

Incidentally, in the link pointing to these news in the online version of The New Scientist, a researchers from Dundee mentions something I did not think of at that time. It could be that the metabolism and not genetic mutations spark cancer. Of course for the metabolic switch to take place you will still need hypoxia (low oxygen due to distance to vasculature) which means, if I am not wrong, a neoplasm.

World cancer day

2007-02-05T14:42:00.000+01:00

I guess I missed it. It seems that yesterday, 4th of February, was the world day of cancer. As many other "World day of...", this WOC was one of these events designed to raise awareness of the problem of cancer in the world, although given that cancer is in the top two of the diseases that are responsible for more deaths in the developed world I guess that many people are more than aware of it.

The headlines I am reading sound actually quite optimistic. Death rates are decreasing due to early detection and improved therapies. Of course nobody is suggesting that cancer will be eradicated but that it will become a chronic disease. I am not sure of how much impact has mathematical oncology had on all these successes but I suspect that it has been limited. For one, mathematical oncology is a fairly relative newcomer in the world of oncology and oncology is a discipline in which cutting edge discoveries take many years (or decades) to reach the public. For another one, I think it is highly unlikely that there will ever be headlines of the kind "theoretician cures cancer". Theoreticians deduce rules or laws that try to describe things like, for instance, cancer growth. These can be used by experimentalists to focus on the more promising areas of research and design the therapies with more likelihood of success faster.

Another added advantage of theoreticians is that they can connect research in different areas. Things that apply to cancer evolution can also be used to study the evolutionary dynamics of other diseases. Many diseases are dangerous due to their capability of evolving and being able to tell what (phenotypes) to expect in the near future from what is there now (genome) would be crucial to deal with them. This week's issue of science carries a paper (http://www.sciencemag.org/cgi/content/abstract/315/5812/655) about how the H5N1 virus (infamous for the avian flu) suggest that only two mutations stand between the current problem and one in which the virus could affect and spread in humans causing a global pandemic. Is there anything that we know about how a tumour evolves that could be used here? I would not be surprised if the answer turns to be positive.

Mitochondria and glycolysis

2007-01-29T10:28:00.000+01:00

As mentioned in a previous post the acquisition of the glycolytic metabolism is regarded by many researchers as a necessary step on the carcinogenic path (this is known as Warburg effect). Compared to healthy cells, glycolytic cells do no need oxygen for their metabolism and although this is very inefficient it has advantages such as the capability of surviving in environments that do not have vasculature in the vicinity and the capability of acidifying the environment (which makes other cells go to programmed death and leaves glycolytic cells room to grow). The reason that healthy cells have a more efficient metabolism is due to the mitochondria, the cellular organelles that oxidises sugar molecules to produce energy. Mitochondrias are what remains of symbiotic bacteria that in the last couple of thousands of millions of years have became integral parts of the cells of many living beings. Glycolytic cells seem to revert to a premitochondrial state thus forfeiting the need of oxygen.

Researchers at the university of Harvard Medical School have created a method based on RNAi (RNA interference, the revolutionary method to knock out genes using double stranded RNA which was the work that has rewarded its authors the Nobel prize in medicine in 2006) in order to put the mitochondria back to work not with the purpose of normalising the metabolism of tumour cells but for the role they play in programmed cell death. The result of applying this therapy on animals resulted in a surge of tumour cells performing apoptosis and a significant increase in the survival rate.

Spencer et al: Modeling Somatic Evolution in Tumorigenesis

2007-01-24T12:10:00.000+01:00

S. Spencer, R. Gerety, K. Pienta and S. Forrest. Modeling Somatic Evolution in Tumourigenesis. PLoS Computational Biology, Vol 8, 2, pp 939-947.

Because the paper has been published in an open source journal it means that any reader, regardless of location or affiliation, will be able to download and print it.

I am spending the remaining of this month and most of February in Lyon working with Dr. Benjamin Ribba, from the University Hospital of the University of Lyon. The month will be busy so I am not sure of how much time will be left for posts in this blog but at least on my way here I had time to take a look at the paper mentioned at the beginning.

This paper, together with the one mentioned in a previous post from Anderson et al, tries to create a mathematical framework in which to study the phenotypical view of carcinogenesis presented by Hanahan and Weinberg in their paper. As in Anderson's case, they use a Cellular Automata in which tumour cells occupy the discretised space and can grow and produce angiogenic factors in order to provision themselves with oxygen. The CA is let to evolve the initial population of cells in which mutations might alter the phenotype and acquire any of the six capabilities (ignoring antigrowth signals, production of paracrine growth signals, limitless replicative potential, evasion of apoptosis, angiogenesis and invasion/metastasis). Additionally a tumour cell might acquire genetical instability which significantly increases the mutation rate during mitosis. Cancer is assumed to take place whenever the cells grow over the natural boundaries of the tissue and claim 90% of the total space. This definition of cancer is, at least from my not so extensive experience, quite unconventional since it seems to allow no role to the phenotypes present in the tumour or the the shape of the tumour. At any rate, tumour growth is determined by the ability of the tumour cells of proliferating AND of surviving.

With this not too complicated system, the authors use several simulations to explore different tumourigenetic paths (or as they call them, pathways to cancer). This is how early mutations determine the likelihood of other mutations to appear successfully (the mutant cell has to survive and have other successful offspring) and how some mutations lead to early or later cancer (which I translate as the speed of the tumourigenesis).

So what do they find? They find that the mutator phenotype should play an important role in the case of early onset tumours but not necessarily in others that take more time to develop. They also find that not all the 'pathways to cancer' are equally probable and that is on its own something quite interesting. If in a particular tumour it was possible to see what genes are responsible for particular capabilities in the Hanahan&Weinberg description, then a genetic analysis of representative cells in the tumour could be used to see what further mutations would be the more likely to be successful and maybe design a therapy for it or try to alter the microenvironment to favour other competing mutations.

They also study the heterogeneity of the tumours which is an important feature when designing a therapy. They use a metric based on what it is done in evolutionary biology. The diversity is measured by aligning the different mutational paths of the different cells in the tumour and counting all the ones that have a different path. This seems to me a strange approach given that they treat tumour cells at the phenotypic level. I wonder if it would be better just to count the different phenotypes (defining phenotype in this case as a particular combination of H&W capabilities, regardless of what was the path to reach them)?

To conclude this review: it is clearly a theoretical model aimed to provide qualitative, not quantitative, results. It is probably complicated enough that biomathematicians might not feel very comfortable with it. The results are mainly simulations and it is unlikely that physicians could devise experiments to compare results with the model. Still I have to say that I like it, the quantitative results are interesting enough and the implementation of the word-model is very easy to follow.

The Darwinian perspective, the mutator phenotype and response to stress

2007-01-20T17:28:00.000+01:00

Although today I will be writing about a paper recently published in the international journal of Epidemiology and authored by Paolo Vineis and Marianne Berwick, this is not going to be a review in the usual sense. This time I would like to write about the ideas and make no reference to the methodology.

The Vineis and Berwick emphasize the role of population dynamics on cancer progression. The usual view on cancer is that cancer cells grow at a faster rate than normal cells and that is the reason why they end up (if successful) killing the host. Growing populations can be due to this but they can also be the result of other factors (think of longer lifespan). The authors hint that the success of most cancers (with respect to taking over a tissue) lays on the fact that cancer cells have a greater proportion of replicating daughter cells. That makes sense to me. For instance, in a tumour whose cells that are capable of dividing near the tumour growth front (let's call them motile tumour cells) will have an advantage over other non motile but faster proliferating tumour cells in terms of how many of its daughter cells will be in position to proliferative (regardless to the speed at which they can divide).

The authors have also something to say about the highly controversial topic of the mutator phenotype. Quick reminder: the amount of time to pick up all the mutations necessary for a neoplastic cell to become a cancer cell is, according to some researchers, big enough as to be unlikely to happen in our life time. Thus cancer is the consequence of a single mutation that makes the cell more likely to produced mutated offspring. To prove their point they compare tumour cells to the behaviour of E.coli under stress. Under normal circumstances the mutation rate of the E.coli is low but when the going gets tough the mutation rates increases significantly. The speculation is that this is no accident but a feature of the bacterial DNA that in such a way can explore a genetic solution out of the problem. Could tumour cells be attempting something similar?

I find this hypothesis quite interesting and from my limited experience it seems quite novel. It should be interesting to do some experimental work (maybe more than theoretical) to see if there are any molecular mechanisms that might have an effect on the probability of mutation (say, the DNA repair mechanism) that could be held down when there are 'stress' signals in the environment. It could even be that the mechanism is similar to that of the E.coli although since bacteria are far simpler cells than human cells that could be unlikely (not having any experience with molecular biology should make any one be skeptic about statements like this).

Edge of existance

2007-01-17T17:33:00.000+01:00

Researchers of the Zoological Society of London have started a new campaign (called EDGE) to promote the protection of certain species that might not be so close to extinction as some other more famous ones (say, whales?) but whose impact on the survival of other species might be significant. The news can be found in BBC or for those of you that can read Spanish in El Pais.

Now, this is probably not something that many people might find relevant to cancer research but I think that there might be a connection. In ecological systems (and here I assume that a tumour is one of those) species depend on other species for their survival. This dependency does not need to come in terms of food webs (a species needs other to prey on) but also in the way that one species can change the environment for the benefit (or not) of the other ones. The idea then would be to identify 'agents' in a tumour whose role in principle might not look so relevant but that might provide support to other more important but less vulnerable targets. Given the current emphasis on the role of the microenvironment in cancer research I would be surprised if there was not already some work pointing in this direction.

Online introduction to computational oncology

2007-01-08T15:45:00.000+01:00

I have recently found an interesting introduction to computational oncology on the website of Paul Macklin, a graduate student at UC Irvine.

The website comes complete with the stages of cancer evolution (not the usual 6 capabilities of Hanahan & Weinberg but a version a little bit coarse grained for my taste) and therapies. He also points out some of the challenges that need to be addressed such as explicitly incorporating the tumour microenvironment (it is a well known fact that some tumour cells behave like regular healthy cells if left in a different microenvironment from the one it comes from). Useful for people who might want to understand some of the aim of the papers I mention in my reviews.

Merlo et al: Cancer as an evolutionary and ecological process.

2007-01-01T18:53:00.000+01:00

L. Merlo, J. Pepper, B. Reid and C. Maley. Cancer as an evolutionary and ecological process. Nature reviews cancer, Vol 6, pp 924-935, December 2006.

New year and (maybe not so) old traditions: the review of a paper. Nature reviews cancer is one of the world's top scientific journal in terms of impact factor for a reason: they publish very interesting and comprehensive reviews in a field of such importance and as crowded as cancer research. Review papers are comparatively more likely to be cited than the ones about one group's research, review papers in cancer research are normally highly cited since there are so many researchers working in the field. Review papers in a prestigious journal like Nature reviews cancer are thus bound to be cited once and once again and one would expect that only very good scientists would be invited to write for them (I believe that is only by invitation that you get to publish in these journals).

This review covers a topic that is very close to my interests: cancer from an evolutionary and ecological point of view. This view sees a neoplasm, a tumour, as a population of cells with a diversity of inheritable features. This means that evolution will happen and the fitter phenotypes will tend to be more abundant in the tumour population. Questions that might arise are how to alter the mutation rates, clone expansion and how does this expansion happen. Furthermore, given that in many cancers we can find mutations in vast areas of DNA, how do these cells retain enough genetic material to even function? The authors put forward the idea that this could be because most of the human genome is devoted to the development and homeostasis of a multicellular body and thus has no effect on the survival of the single cell in a tumour.

Having a diverse range of individuals whose uniqueness is inheritable is only one of the requirements of evolution. The other one is selection. In a tumour we have two sources of selection. Natural selection is the one that takes place in any tumour when there is scarcity of resources (oxygen, glucose, space). Under these circumstances some phenotypes are bound to be better at surviving and dividing than others. Additionally there is artificial selection which is the result of a therapy applied to a patient with a tumour. Artificial selection changes the fitness landscape, hopefully in such a way as to make survival impossible to every tumour cell. Unfortunately that is somewhat difficult so in many situations is worth altering the fitness landscape in ways that promote the survival of the least aggressive (that is, less likely to be able to invade and metastasise) tumour cells. In any case, altering the fitness landscape in favour of the patient is significantly easier when the tumour did not have much time to evolve.

Evolution in a tumour is not entirely the same as the one in organismal populations. That is to be expected given that tumour evolution lacks something of great importance: time. That is why during chemotherapy, surviving tumour cells are not the ones that develop mechanisms to resist but the ones that due to other reasons (genetic drift for example) already had the capability to resist before the therapy was used. Other differences include the reliance on stem cells for population diversity or that reproduction is asexual (which, incidentally, makes mathematical treatment much easier).

If a tumour resembles an ecosystem we should expect things such as cooperation, competition or parasitism. It seems that you get some of that. Like in an ecosystem individuals compete for the available resources (there is some speculation about that in the paper from Tomlinson reviewed the 10th of October of last year). There are predators if we understand as predation the behaviour of the cells from the immune system when they meet tumour cells. There should be parasitism, mutualism and commensalism (although the authors provide no evidence for that).

I found this a very nice and readable paper. I think it will make a good introduction to any cancer researcher that wants to study the evolutionary aspects of it. My only criticism of a paper that claims to deal with cancer as an evolutionary and ecological process is that the ecological part is significantly weaker than the evolutionary one.

Gatenby and Smallbone: Glycolysis and tumour invasion. Two papers

2006-12-26T18:36:00.001+01:00

Why do cancers have high aerobic glycolysis? R Gatenby, R. Gillies. Nature reviews cancer, Vol. 4, November 2004, pp 891-899.

The role of acidity in solid tumour growth and invasion. K. Smallbone, D. Gavaghan, R. Gatenby and P. Maini. Journal of Theoretical Biology 235 (2005) pp 476-484.

Gatenby and Gillies present a review paper in which they explain that the glycolytic metabolism is a requirement for a tumour to progress into a cancer. Cancer cells tend, at least by the time they become invasive, to have an altered glucose metabolism. This metabolism has drawbacks when compared with the conventional glucose metabolism in at least two senses. First of all the glycolytic metabolism is less efficient since it produces 2 ATP (the cell's energy currency) compared with 38 ATP that result from normal metabolism. Second of all, as a by product of this metabolism lactic acid is produced. Lactic acid increases the pH of the microenvironment of the cell and when it reaches a given threshold results in apoptosis or necrosis. As a consequence of this the switch from conventional to glycolytic metabolism does not happen under normal circumstances but under hypoxia, that is, when there is insufficient access to oxygen. In those circumstances the inefficient glycolytic metabolism, which does not need oxygen, represents a significant advantage. Hypoxia is a normal event in a growing tumour since there will always come a point in which the tumour cells are far from blood vessels carrying the needed oxygen. Periodic moments of hypoxia select for cells with the glycolytic metabolism that have adapted to acid environments by, for instance, resistance to apoptosis or by reducing intracellular acidity by pumping it out. The end result of this selection is that a tumour will have a group of cells that, despite having a less efficient metabolism, are capable of harming other cells and also of degrading the ECM (Extra Cellular Matrix, that hold tissue cells together) so the next thing you know is that your tumour cells are capable of invasion and metastasis.

In the second paper, Smallbone and colleagues introduce a mathematical model to study the possibility that tumour invasion and growth could be the result, not of genetic changes, but of changes in the tumour environment. This is, of course, a mathematical formalisation of the hypothesis presented in the other paper. They decided to take multicellular spheroids and produce an ODE model that describes tumour growth and progression as travelling waves: the one for the increased microenvironmental acidity and the second one with the tumour cells invading normal tissue. This is a clearly a quantitative model that, unfortunately, has not yet been validated by in vitro experiments although it looks to me that its design has been done with care so it would be feasible to do so. The model predicts among other things that avascular tumours will have higher acidity than vascular ones (which makes sense since blood vessels can be used to take part of this acidity out of the microenvironment) and that tumour necrosis could potentially be explained without the need to talk about cell starvation or overcrowding but by the acidification of the environment. They make a good case for antiangiogenic therapies since blood vessels can contribute to a decrease of microenvironment acidity that could be sufficient for tumour cells to survive but not for healthy cells that have a lower threshold of acidity resistance. They also suggest a treatment in which the membrane pumps that transport the acidity from within the cell to the outside environment, would be somehow blocked so glycolytic cells would literally poison themselves to death without changing the microenvironment for the healthy tissue cells.

Quote of the week

2006-12-20T16:19:00.000+01:00

Maybe this will start a new trend in this blog: quotes. I was recently rereading some old issues of Nature and found this article in the careers section. It is a nice article in which the authors give an alternative view to that of this other article of how long and hard should a PhD student work. According to the original view a researcher should work all the time. According to this other alternative view some scientists have many of the weaknesses commonly associated with humans and thus this approach is likely to be useless.

They cite this anecdote from Ernest Rutherford. It seems that he found a student working late on an evening and asked him if he also worked in the mornings. The student answered that that is what he usually did and Rutherford then asked "But, when do you think?". Some times I think to myself that my best ideas usually come in the most unexpected places and circumstances. Now I think that I never had any good idea while in the office in front of the computer. Since now I am off for Xmas holidays there is a chance I will have time for some good ideas.

Evolution and creationism in Europe

2006-12-13T10:21:00.000+01:00

Many people in the European academic community have a condescending view on the lack of scientific knowledge of the American population in general and also of their political class. While probably these concerns are fair, it would be useful to redirect part of it towards our own citizens and politicians here in Europe.

The Nature issue of a couple of weeks ago reports about how creationism is on the increase in Europe (at least the public awareness of what used to be a dormant line of 'thought'). They also have an interview with the leader of a European creationist group (who has a PhD in astrophysics and whose photo in the article seems to be taken by one of his enemies). Nature has also recently published the letter of Maciej Giertych, an MEP and scientist, with a PhD in population genetics, of the Polish Academy of Sciences in which he criticises evolution. The publication of this letter in a journal with the reputation of Nature has generated a considerable amount of controversy as can be seen in the letters send to the editor and published in the last issue.

Anderson et al: Tumor morphology and phenotypic evolution driven by selective pressure from the microenvironment

2006-12-11T11:12:00.000+01:00

A. Anderson, A. Weaver, P. Cummings and V. Quaranta. Tumor morphology and phenotypics evolution driven by selective pressure from the microenvironment. Cell 127, 905-915, December 2006.

This is the paper I mentioned in my previous post. It is not that usual to find a mathematical model in a journal like Cell so I hope that this is part of a growing trend.

The paper investigates how the microenvironments helps to drive cancer evolution. To do so they use a hybrid cellular automata model in which cells live in the discrete lattice and the microenvironment (oxygen concentration, extra cellular matrix macromolecule concentration and matrix degrading enzyme) is modeled using continuous variables. The cells are characterised by a number of parameters that determine their behaviour with respect to proliferation, cell-cell adhesion, oxygen consumption, haptotaxis or production of matrix degradation enzymes. Cells follow a life cycle and only proliferate when they reach a certain age. That age depends on the cell's phenotype. During mitosis a cell might alter its phenotype and change the values of proliferation, adhesion, oxygen consumption, etc.

With heterogeneous microenvironment and cell behaviour you get different patterns of tumour growth, some of them favouring agressive invading phenotypes and some of them favouring the coexistance of all sorts of phenotypes. Having the model they described it is possible to study who different microenvironmental factors determine evolution. The results show that harsh environments (little oxygen) select for aggressive phenotypes whereas in milder environments allow for the coexistance of a much bigger range of phenotypes and that these tumours are unlikely to be invasive.

The model is very interesting and the conclusions seem pretty reasonable: Tough microenvironments lead to aggressive tumours. My intuition tells me that on the other hand, heterogeneous populations are more likely to be able to cope with an external aggression which would imply that a less aggressive but more diverse tumour would not respond well to therapies that target any specific kind of behaviour. The main problem with the paper is that the model is fairly complicated for clinical validation.

We are big news!

2006-12-05T11:51:00.000+01:00

We are big news. Ok, I am personally not included but it seems that the theorical medicine community starts to be noticed.

I browse a tech-news website, called slashdot, very often. One of the entries today is the following: "Computer simulations of cancer growth". There they talk about research performed by Sandy Anderson (Dundee, part of the Marie Curie Network in which I am involved), Vito Quaranta (Vanderbilt, I talked about him in my post on the Lyon workshop in late September) and colleagues. They have just got a paper published in Cell of which I will talk about it in a later post.

At any rate, it looks impressive than sites such as Slashdot report on mathematical and computational models of cancer research. The audience of Slashdot is reputed to be very competent in matters of IT but I could see that some of them are medically competent too (I mean, enough to convince a computer scientist like myself, not necessarily more than that), even if, as in many news in Slashdot, people tend to concentrate on what they want to say regardless of the news they are supposed to comment on.

Cancer and development

2006-12-01T10:24:00.000+01:00

Reading a just outdated issue of The Economist, I find this article in the science section about how HIV treatments could be used to treat cancer.

One of the things many people interested in biology but without a background in biology believe (I hope I am not just describing myself here) is that information goes only in one direction: genes - mRNA - proteins. Actually the opposite is true. Enzymes such as reverse transcriptase can copy can include fragments of RNA into DNA. This is of course a technique used by viruses in order to alter the genetic programme of a cell to produce more copies of the virus. This system is also used to change the genetic programme of a cell during development so if the work of the enzyme is hindered so is development (at least in some crucial steps).

It seems that cancer cells have a lot of reverse transcriptase (this is, unfortunately, not explained in the article) and thus treatments used to prevent viral diseases could be used to hinder tumour growth. In vivo experiments with mice transplanted with human cancer cells show that there is a correlation between tumour growth and the use of HIV treatments that hinder the reverse transcriptase enzymes.

It is one more example of how development and cancer are connected (my take, and I don't claim to be the first one with this insight) is that we would not have cancer if we were not the result of developmental processes.

Speakers in Step conference

2006-11-28T20:18:00.000+01:00

It has been a while since I came back from the Step conference in Brussels and I guess it is time to say something about some of the speakers I had the chance of listening to. Probably the most interesting ones from my highly subjective point of view were James Bassingthwaighte (University of Washington), Brian Goodwin (former Santa Fe Institute Faculty, now at Schumacher College) and Denis Noble (Oxford).

This Step conference was not meant to be about science per se so the talks were definitely not of a technical nature. James introduced the Physiome project which, as you might know, is about putting together all the current and future knowledge about the human phisiology with
the aim of improving health care. The ideal result would be a giant simulation of the human phisiology that could behave like a real whole organism. Such system would allow physicians and other researchers to test therapies quickly and without nasty side effects
and study 'what if' scenarios.What James thinks we need are:

* Training (No use of sophisticated systems if physicians don't use them)
* Databasing
* Standards (Too many groups out there and no way to compare or integrate their work)
* Modelling archives (I got a nice model, where do I put it for other people to play with?)
* Modelling tools

All in all a nice and light introductory talk. Everything he mentioned is quite reasonable although I am not sure if it is realistic to expect any of these things happening in the short term. People so far seem to be happy happy to come with their own models and not much effort is done to see if the results of one model are consistent with the results of the model of a different group.

Next talk came from Brian Goodwin who, although use to be in the Santa Fe Institute is know a professor of 'holistic science' (which looks quite a scary name for a professorship). The theme of his talk? Computational biology: a clash of cultures. The part of the talk which I found more interesting was when he dealt with the ambiguity of languages. Human languages are ambiguous and the meaning of a sentence gets shaped as we speak. This seems to be a good analogy to understand the language of genes which is also ambiguous (which is nice if you want to evolve it). In his view both human and gene languages have the property that are the best compromise between the effort that the speaker has to make to convey a message and the
effort of the listener. This is an interesting idea although I guess that proving it might be quite complicated (note to my self, should take a look at what has been published about this).

The talk from Denis Noble was also interesting despite the fact that his major point was: I have a new book ("The music of life") go and buy it (which I might do). He made a number of points:

1. There is no gene for function (no objections to that)
2. Transmission of information is not just one way (same here)
3. DNA is not the only transmitter of inheritance (heard that before)
4. Law of relativity in biology: there is no privileged level of causality. Message to Dawkins: the gene is not that important.
5. There is no genetic programme (message to Monod this time).
6. Actually there are no programmes at any level
7. ...and that means not even at the brain level

Cancer and stem cells

2006-11-23T09:46:00.000+01:00

Canadian and Italian scientists have just came with research that adds further strength to the idea that mutations to stem cells are the main driving force driving tumour growth and ultimately cancer. Stem cells are non differentiated cells that can replicate indefinitely. When a stem cell duplicates this can lead to two stems cells or to a stem cells and a differentiated cell. These differentiated cells can perform useful things such as become muscle cells, breast cells, epithelial cells, etc. As opposed to stem cells, these differentiated cells lose the capability of limitless replication. Every time a differentiated cell divides, the telomerase needed at the ends of the chromosomes gets shorter. Eventually there is not enough for replication and the cell undergoes apoptosis. That is one reason why many tissues have a pool of stem cells that keep producing differentiated while needed.

The researchers tried to find out how relevant stem cells are for cancer growth. They show than when performing animal experiments (much more convincing than in vitro), animals with injected colon stem cancer cells are more likely to develop cancer than those in which non-stem cancer cells are used.

It all sounds reasonable to me: one of the capabilities that tumour cells have to acquire for the tumour to become a cancer is limitless replicative potential. If you inject into an animal cells that already have that capability, that should make it easier for the cancer to appear. Also, it is known that some tumour cells, as they mutate, might revert to an undifferentiated state with stem-like behaviour. Therapies that specifically target stem-cell cancer cells should be the next step since stem cells amount to a small proportion of the cells in the body but seem to have such a great potential in cancer initiation.

Evolution on a chip

2006-11-20T10:22:00.000+01:00

Via Nature research highlights I found an intersting article in PNAS about how a group of researchers in Princeton are studying evolution in silico...for real!

Normally, when theoretical biologists talk about biology in silico they are thinking of computer models of biology, but this time the in silico referes to silicon chips that have been used to create patched environments, each one representing a different microenvironment (the main difference between the patches being the availability of nutrients). In these patches they placed colonies of E. coli and let them grow. The bacteria were allowed to move from one patch to the next using narrow corridors.

Interestingly but maybe not surprisingly, the bacteria move towards more promising neighbouring patches and some times, adapt, genetically and physiologically to the environment. Asides from some interesting experiments, the guys have been kind enough to produce some mathematical model to study the evolution in silico as well as analysis of what is the evolution of bacterial density in a patch as nutrient availability gets depleted and competition gets tougher.

It is really interesting stuff but it seems that they need to complicate a little bit more the patches in order to get more adaptation to the environment and less motility to the greener grass.

The Step conference

2006-11-09T11:10:00.000+01:00

I have just returned from my trip to Brussels for the Step conference in which a Physiome project was discussed. We had talks from some very nice speakers about which I will write in another post.

The Physiome project (or at least what I understood about it after being exposed to the idea for the very first time during this conference) is a highly ambitious project (and that is probably an understatement) whose aim is to integrate all the current and future knowledge about the human physiology. The idea is thus a multiscale modular framework in which all the models about the different parts of the human physiology could be integrated. Such a model would have a tremendous impact on our understanding of physiology, let alone the potential benefits for pharmaceutical companies. For all of you who have any experience doing modeling of biological processes I guess I don't need to tell you how (let's understate it once again) challenging this could be. In any case I am fine with any (extremly) difficult project as long as the intermediate steps are worth something.

In my opinion, the guys in the Step project should aim at something quite modest such as some system by which modelers can integrate just a few models together so different groups can check the consistency of their models and their assumptions. This process will probably take a long while but eventually most modellers will be used to think of their models not in isolation but as something that has to make sense in the context of all the models being developed elsewhere. There should be some infrastructure so the models can be shared between researchers and some protocols and interfaces between models at different scales or across the same scale (say molecular, cellular or tissue) so there can be integration.

One of the speakers mentioned that the keywords in this project are multiscale and modularity. I suggest taking a look at the field of software engineering in which different groups and companies work in different modules and at different levels of abstraction. The software produced is expected to work with other software modules. Of course the complexity to manage is different in the Physiome project but I still think it would be a good starting point.

Off to Brussels

2006-11-02T16:52:00.000+01:00

I will be away for a few days. I will be attending the Euroconference organised by EuroPhysiome whose aim is to build a virtual physiological human.

The website of the conference is here.

Will report back at the end of next week

brief introduction to cancer research using game theory

2006-10-27T15:39:00.000+02:00

I gave yesterday a small and informal presentation on the research done in cancer using game theory. For whoever might be interested, the results are here.

Interview with mathematical biologist Luigi Preziosi

2006-10-25T11:18:00.000+02:00

I guess it will be irrelevant for those of you that don't speak Spanish but the Spanish news paper El Pais has interviewed the mathematical biologist Luigi Preziosi. Luigi happens to be one of the coordinators of the EU Marie Curie Network in which I am involved.

In the interview he argues that biology is geting more mathematical, explains how mathematicians and life scientists and physicians collaborate, how the mathematical models can help to explain medical phenomena and hint to innovative therapies. He also says that traditional biologists are still necessary (as if that was not obvious: theoretical physicists still need experimentalist to work with so they can validate their theories, it should not be different in the life sciences, there would not be biology without people that know how to perform experiments).

Bach et al: An evolutionary-game model of tumour-cell interactions

2006-10-24T15:05:00.000+02:00

L.A. Bach, S.M. Bentzen, J. Alsner and F.B. Christiansen. An evolutionary-game model of tumour-cell interactions: possible relevance to gene therapy. European Journal of Cancer 27 (2001) 2116-2120.

Bach et al have taken the work from Tomlinson and Bodmer (which I reviewed a few day ago) in which angiogenesis is studied with the help a Game Theory. In the previous case the game involved two players who could chose to produce angiogenic factors or to do nothing. As long as one of the players is willing to shoulder on the cost of producing the factor, both players get the benefit. As expected the result is a polymorphism in which both types of strategies coexist. I said that this polymorphism is to be expected since if there were only factor producing cells then non cooperating cells will have an advantage (since they get the benefits without paying the costs) whereas if the population is made of non cooperating cells then factor producing cells will have an advantage (as long as the benefit of producing the factor is higher than the cost).

The revision of the model proposed by Bach et al considers the implications of extending the game to three players if the benefits of angiogenesis appear only if two out of the three players cooperate to produce the factor.

The payoff table would look like this:

A+,A+ A+,A- A-, A-
A+ 1-i+j 1-i+j 1-i
A- 1+j 1+j 1

where A+ means factor producing and A- means that is not factor producing. Also i is the cost of producing the factor and j is the benefit.

Bach et al analyse how these cost and benefit parameters affect the equilibria and the existence of polymorphism. For this they use computer simulations and find that when the benefit is three times the cost something interesting happens. In that case the final composition of the tumour population would be a consequence of the composition of the original population. Most likely this finding has limited (if any) consequences in potential therapies since physicians have not got the ability to change the initial composition of phenotypes in a tumour. Still, the (qualitative) results can be used as a guide for gene therapies.

Tumour supressor gene involved in virus protection

2006-10-24T14:42:00.000+02:00

Got this from mainstream media but the paper itself has been published in the EMBO journal in September. Researchers at the Madrid based Centre for Oncological Research have found a gene (for those interested in the gene itself: ARF) that is implicated in both tumour supression and protection from viral infection.

I guess this amounts to another cellular mechanism that has been successfully evolved to adopt an extra new function. The results of evolution can be messy but I'm still impressed.

Darwin online

2006-10-19T09:55:00.000+02:00

Heard it on the radio this morning while listening to the BBC: the University of Cambridge has digitised the text and images of thousands of pages from the publications of Charles Darwin. The website can be found here: http://darwin-online.org.uk/.

Included in the collection are works on other members of the Darwin family (such as the almost-as-famous-as-his-grandson Erasmus Darwin) as well as mp3 audio books for those who would like something more intellectual to entertain their daily jog or gym workout.

Evolution and cancer news

2006-10-18T10:05:00.000+02:00

Every morning I check a couple of sites in order to get an overview of what is going on in the world. Today I found a couple of curious things:

On the more serious (and cancer related) front, A group of researchers at the University of Missouri-Columbia have found a way to find out the spread of skin cancer cells through the blood. The technique relies on the fact that the vibrations produced by a laser into a melanoma cell is different from that of other cells like red blood cells and plasma.

More information can be obtained here (for those with a subscription to the journal of optics letters).
A different kind of research has been noticed by the bigger media (BBC, Telegraph) and it seems to illustrate how not to use the theory of evolution. Researchers at the Darwin centre at the London School of Economics have seen the future and came back to tell us: Mankind will split into two separate species: the clever and beautiful and the dim-witted goblin-like. I have already heard people labelling these groups as the Macs and the PCs.

Turning on genes again

2006-10-15T16:54:00.000+02:00

I confess to read The Economist newspaper more than occasionally and I find the Science and Technology section readable but rigorous.In this week's issue there is an article about a new class of drugs that has recently gained approval in the US.

One of the things I have learned reading this article is about how mutations might occur that could lead to tumour formation. Up to now, as far as I was concerned, a mutation is a mutation is a mutation, that is, something that just happens and, ooops, one more ticket for the lottery of cancer. Well, it seems that a curious way to turn off large parts of the DNA is by increasing the packing density of the DNA so it becomes effectively unreadable. It seems that cancer cells can use this mechanism to avoid expressing genes so they can proliferate faster as well as avoid apoptosis and senescence. Given that the drug that has just been granted regulatory approval works best with leukemia it seems that the mechanisms employed by tumour cells to deactivate certain cell mechanisms varies from cancer to cancer. Still, having cancer cells with the capability of turning off significant parts of the DNA is such an evolutionary advantage that it should not be surprising if equivalent mechanisms are found in other types of cancer.

Another article on Richard Dawkins

2006-10-14T15:21:00.000+02:00

An interview of Richard Dawkins in Salon. It is possible to read the full article if you click on the sponsor link.

Salon has a series of interviews about science and religion and this time they decided to interview Prof. Dawkins who, they claim, is second to the late Stephen Jay Gould in popularising evolutionary biology (I would claim that here in Europe Dawkins is probably better known).

Usual readers of this blog (hi mum!) know that I am a fan of Prof. Dawkins and share some (if not most) of his ideas about evolution and its lack of compatibility with established religions (the interview, and his new book - The god of delusion - deal mostly with the three big monotheistic religions although touches too any faith-based religion...which I guess means any). Reading this wont give you a new insight on cancer. Moreover, if you are a religious person, it is unlikely that you will be transformed into an unapologetic atheist, but it still makes an interesting read IMHO.

For the record, the book of Richard Dawkins is The god of delusion. For an alternative view from another famous scientist (Stephen Jay Gould, probably second to Dawkins popularising evolutionary biology) take a look at Rock of Ages. His view is that science and religion belong to different realms and should not be intermixed.The links are to wikipedia.

Tomlinson and Bodmer: Modelling the consequences of interactions between tumour cells

2006-10-13T17:17:00.000+02:00

I.P.M. Tomlinson and W.F. Bodmer. British Journal of Cancer 75 (2) 157-160, 1997.

Again Tomlinson, this time working with Bodmer, taking a couple of simple but interesting examples of the use of game theory for cancer research. This time they work on two different games: angiogenesis and apoptosis. In the first game angiogenic factors might be produced by tumour cells with the result that the cell producing and its neighbours reap the benefits of increased access to nutrients. In the second game cells might produce factors to escape angiogenesis which might or might not benefit the neighbours.

As it is usual in these cases the model assumes a large population of tumour cells, asexual reproduction and a population site that does not need to be constant since the object of the study is the frequency of particular phenotypes, not their absolute number. Further assumptions: the population of tumour cells is genetically diverse and this diversity is distributed homogeneously.

In the first game: angiogenesis, there are two strategies: either to produce or not to produce angiogenic factors. There is a cost associated to producing then and also a payoff. If you are a non producing tumour cell and you interact with a producing tumour cell you get the same benefits but none of the costs of a factor producing tumour cell. The result is that there are equilibria in which both phenotypes coexist as long as the cost of producing angiogenic factors is outweighed by the benefit.

The second game is more sophisticated. In this case we have three different strategies: either we produce factors to help neighbouring cells avoid apoptosis (paracrine factors), or we produce autocrine factors that help us avoid apoptosis or, alternatively, we might save ourselves all that trouble and do nothing. As usual there is a payoff table in which the different parameters represent the costs of producing paracrine and autocrine factors and the benefits they provide to whoever is the target of the factor. Tomlinson and Bodmer use GT to study different types of equilibria.

In this case it is easy to see that the first strategy is not viable since any group of cells doing nothing and reaping the benefits of endocrine factor producing cells would drive them to extintion. On the other hand if the cost of producing autocrine factors is smaller than the benefit of avoiding apoptosis then there will be a selection for cells capable of producing those autocrine factors.

The conclusion of the paper is that a tumour cell population might not adopt a strategy that would help the whole but does not confer any advantage to the individual that brings it (which is a reasonably safe proposition to make to people studying evolution). The question is again if there could be therapies designed to exploit the fact that tumour cells can stop cooperating among each other.

Article in Nature: Driven to Market

2006-10-12T19:28:00.000+02:00

Nature has a reputation for publishing academic articles of high-impact (that is, loads of people read nature so articules in nature are widely read and are more likely to be cited by other people which means that Nature becomes better ranked which means that more people buy it which means...), but also they have some nice articles that are more accessible to non specialists and that are written by freelance writers.

Yesterday I was reading one in last week's (I am always late with my issue) entitled "Driven to Market" by Jonah Lehre. The article is about a relatively new field called neuroeconomics which combines both psychology and economics. That does not seem related to the topic of this blog but what it is interesting (to me) is that one of the assumptions that is prevalent in economics and that the practitioners of neuroeconomics bring to question is that humans act guided by reason in order to maximise their own benefit. This is also one of the main assumptions in Game Theory (which is a common tool in Economics). Ironically one of the criticisms that opponents of evolutionary game theory have is that animals are not rational but it seems that reason is an even weaker predictor of the behaviour of humans. One nice example to illustrate that is the game called ultimatum. In this game one player is given, say, 10 euros and told that it has to share it with someone else in such a way that if any of the players is unhappy with the way the money has been split then no one gets anything. If people were rational the first player will always offer 1 euro to the second one knowing that the second one would take whatever he or she is offered since the alternative is to get nothing at all. It seems though that when this game is played by people, deals that seem to be too unfair are always rejected even if that rejection means that the money is lost.

University rankings

2006-10-12T17:54:00.000+02:00

As long as you don't take them seriously it is amusing to take a look at university rankings once in a while. This one comes from the The Times Higher Education Supplement.

1 Harvard University
2 Cambridge University
3 Oxford University
4= Massachusetts Institute of Technology
4= Yale University
6 Stanford University
7 California Institute of Technology
8 University of California, Berkeley
9 Imperial College London
10 Princeton University
11 University of Chicago
12 Columbia University
13 Duke University
14 Beijing University
15 Cornell University
16 Australian National University
17 London School of Economics
18 Ecole Normale Supérieure, Paris
19= National University of Singapore
19= Tokyo University
21 McGill University
22 Melbourne University
23 Johns Hopkins University
24 ETH Zurich
25 University College London
26 Pennsylvania University
27 University of Toronto
28 Tsing Hua University
29= Kyoto University
29= University of Michigan
31 University of California, Los Angeles
32 University of Texas at Austin
33= Edinburgh University
33= University of Hong Kong
35= Carnegie Mellon University
35= Sydney University
37 Ecole Polytechnique
38 Monash University
39 Geneva University
40 Manchester University
41 University of New South Wales
42 Northwestern University
43 New York University
44 University of California, San Diego
45 Queensland University
46= Auckland University
46= King's College London
48= Rochester University
48= Washington University, St Louis
50= University of British Columbia
50= Chinese University of Hong Kong
52 Sciences Po
53 Vanderbilt University
54= Brown University
54= Copenhagen University
56 Emory University
57 Indian Institutes of Technology
58= Heidelberg University
58= Hong Kong University Sci & Technol
60 Case Western Reserve University
61= Dartmouth College
61= Nanyang Technological University
63 Seoul National University
64= Bristol University
64= Ecole Polytech Fédérale de Lausanne
66 Boston University
67 Eindhoven University of Technology
68 Indian Institutes of Management
69 Amsterdam University
70= School of Oriental and African Studies
70= Osaka University
72 Ecole Normale Supérieure, Lyon
73 Warwick University
74 National Autonomous Univ of Mexico
75 Basel University
76 Catholic University of Louvain (French)
77 University of Illinois
78 Trinity College Dublin
79= Otago University
79= University of Wisconsin
81 Glasgow University
82= Macquarie University
82= Technical University Munich
84 Washington University
85 Nottingham University
86 Delft University of Technology
87 Vienna University
88 Pittsburgh University
89 Lausanne University
90= Birmingham University
90= Leiden University
92 Erasmus University Rotterdam
93= Lomonosov Moscow State University
93= Pierre and Marie Curie University
95 Utrecht University
96 Catholic University of Leuven (Flemish)
97 Wageningen University
98 Munich University
99= Queen Mary, University of London
99= Pennsylvania State University
101 University of Southern California
102= Georgetown University
102= Rice University
102= Sheffield University
105= University of Adelaide
105= Humboldt University Berlin
105= Sussex University
108 National Taiwan University
109= St Andrews University
109= Zurich University
111= Maryland University
111= Uppsala University
111= Wake Forest University
111= University of Western Australia
115 University of Twente
116= Fudan University
116= Helsinki University
118 Tokyo Institute of Technology
119 Hebrew University of Jerusalem
120 Keio University
121 Leeds University
122 Lund University
123 University of North Carolina
124= University of Massachusetts Amherst
124= York University
126 Aarhus University
127 Purdue University
128= Kyushu University
128= Nagoya University
130= Tufts University
130= Virginia University
132 Durham University
133= University of Alberta
133= Brussels Free University (Flemish)
133= Hokkaido University
133= Newcastle upon Tyne University
137 Nijmegen University
138 Vienna Technical University
139 Liverpool University
140 Cranfield University
141= University of California, Santa Barbara
141= Cardiff University
141= Ghent University
141= Southampton University
145 Georgia Institute of Technology
146 RMIT University
147= Chalmers University of Technology
147= Tel Aviv University
148 Free University Berlin
150= Korea University
150= Texas A&M University
152 Notre Dame University
153 Bath University
154 City University of Hong Kong
155 McMaster University
156= Curtin University of Technology
156= Göttingen University
158= Technion -- Israel Inst of Technology
158= University of Ulm
158= Waseda University
161= Chulalongkorn University
161= University Louis Pasteur Strasbourg
163 Michigan State University
164 Saint Petersburg State University
165= Brussels Free University (French)
165= China University of Sci & Technol
165= State Univ of New York, Stony Brook
168= George Washington University
168= Tohoku University
170= University of California, Davis
170= University of Tubingen
172= Aachen RWT
172= Maastricht University
172= Royal Institute of Technology
172= Yeshiva University
176 Queen's University
177 Oslo University
178 University of Bern
179 Shanghai Jiao Tong University
180 Nanjing University
181= Kobe University
181= Université de Montréal
183= Jawaharlal Nehru University
183= Free University of Amsterdam
185 University of Kebangsaan Malaysia
186 Innsbruck University
187= Brandeis University
187= Frankfurt University
187= University of Minnesota
190= University of Barcelona
190= Reading University
192= Malaya University
192= Queensland University of Technology
194 Technical University of Denmark
195 Aberdeen University
196 University of Wollongong
197 La Sapienza University, Rome
198= University of California, Irvine
198= Korea Advanced Inst Science & Technol
200 University of Paris-Sorbonne (Paris IV)

I.P.M. Tomlinson: Game theory models of interactions between tumour cells

2006-10-10T10:54:00.000+02:00

Review of EJC 35-9 (1997) 1495-1500.

This is the first paper I am aware of that uses game theory to study a problem in the field of cancer research. The paper is only from 1997 so it is easy to see that the field is ripe for further development.

The advantage of being the first to use a given tool in any area is that you can chose the problem and come with an simple and elegant study. Tomlinson has used a simple system in which tumour cells can adopt a number of strategies such as producing cytotoxic substances and cytotoxic resistance. The hypothesis is that some tumour cells attempt to gain advantage by actively harming neighbouring cells. This initial hypothesis is studied considering a number of different scenarios in which different phenotypes are combined. Initially there are three types of phenotypes or strategies: cells that can produce cytotoxic substances, cells that can produce factors that protect them from cytotoxic substances and finally cells that do none of this. Tomlinson presents a payoff table in which the interactions between the different phenotypes are presented in a parametrised way so he can hypothesise different values of the cost it represents to produce the toxin or the cost of producing the resistance or the benefit conferred to harm a player by doing so. Once the game is properly defined he goes on to study the potential equilibria by running simulations on a computer and varying the different parameters of the payoff table.

He also studies alternative strategies such as phenotypes that produce both the cytotoxic substance and its resistance and flexible strategies that behave differently according to the phenotype of the player they compete against. The conclusions he obtains are that several phenotypes can coexist simultaneously in a tumour (since there are configurations of parameters of the payoff table that lead to equilibrium), that flexible strategies are better than fixed ones (unless the cost of flexibility is too high and that therapies could be designed that could exploit the fact that tumour cells can harm other tumour cells under some circumstances (maybe promoting competition and not collaboration among them).

Of course the model is very very simple and the conclusions should be taken with some care (there are no spacial considerations, no hints of what the parameters of the payoff table could be, the results are not surprising). Still, this model gives some theoretical backing to these conclusions and suggests some ideas on how to design a therapy which is quite nice.

Recap from Lyon (II)

2006-10-06T11:15:00.000+02:00

Philip Maini is one of the most entertaining speakers (entertaining in the good sense, of course) in the European biomathematical community. Prof. Maini is the director of the Centre of Mathematical Biology at Oxford University and gave in Lyon a talk entitled "Modeling aspects of cancerous tumour dynamics".

The modeling aspects he mentions are three different projects:

1) The first project, in which he collaborates with people like Gatenby (Arizona) and Gavaghan (Oxford) studies the acid mediated invasion hypothesis.
According to (my interpretation of) this hypothesis, when tumour cells lack oxygen and start to starve then a mutation might appear that would make some cancer cells switch to what is called glycolitic phenotype. This means that these cells have an alternative metabolism that works without oxygen and that is not as efficient as the regular one. The reason why this alternative phenotype has a chance of success is because the waste produced (galatic acid) can be used to degrade the extra cellular matrix and lead to invasion of other tissue. Gatenby, Gavaghan and Maini came with a model in which tumours contain cells with the glycolitic phenotype. The results is that tumours are not benign and that an possible explanation for the existence of necrotic cores (material generated when cells die disorderly because of starvation) can be the result of too much acidification of the environment, even for acid-resistant glycolitic-type tumour cells.

2) Metabolic changes during carcinogenesis. Also with Gavaghan and Gatenby and referring to research covered by a paper in Nature reviews cancer (vol 4, 891-889, 2004). They study somatic evolution in a system in which tumour cells can be of one of three different types: hyperplastic, glycolitic or acid-resistant. These cells inhabit the space of a 2D lattice in which there is oxygen, glucose and hydrogen that diffuse in a continuous manner. Altering the reach and concentration of these elements leads to different numbers of cells displaying one or the other phenotype.

For me this is a good place in which to see how game theory could be used to study the interactions of different players (cancer cells) using different strategies (the different phenotypes) to maximise their payoff from the environment (O,H,glucose).

3) Together with Benjamin Ribba (Lyon, organiser of the workshop and one guy I am working with as of lately) Maini works on a multiscale model on which to study the differences between the vasculature generated by the normal process of vasculogenesis and the ones generated by tumour cells capable of angiogenesis. One of the conclusions he mentioned: don't trust parameters.

Mansury, Diggory and Deisboeck: Evolutionary game theory in an agent based brain tumor model: exploring the 'genotype-phernotype' link

2006-10-05T11:37:00.000+02:00

Mansury et al. JTB 238 (2006) 146-156.

One of the things I had in mind when I started this blog is that I could use it to force me to write reviews about some of the most relevant papers that I often read for my own 'dirty' purposes. Usual reasons apply: it is good to write about what you read since synthesis helps understanding.

In any case, as you know, one of the topics I am interested on is cancer research using evolutionary game theory and although evolution is not what these people have studied the other important keywords are present in this paper.

Mansury et al have devised a nice spatial (2D lattice) agent based (Cellular Automata style) system in which tumour cells inhabit a space with nutrients. Tumour cells can be found in two varieties: A (proliferative) and B (migratory). Non evolutionary game theory is used to analyse the interactions between cells that have different phenotypes and how those interactions reflect on the payoffs of the individual cells and on the tumour as a whole. The payoffs in this game are slightly more complicated (and according to the authors, more realistic) than those of other games. The payoff of a cells is made of three different factors: communication payoff, proliferation payoff and migration payoff.

For the simulations (since it is quite difficult to come with a nice analytical study) they run CAs with 500x500 lattices in which nutrients are diffused from the centre and the middle. From here they study how changing the payoff table results in different velocity of tumour growth, different tumour surface roughness (useful to analyse the malignancy of a tumour) and the numbers of both tumour populations with time

From my point of view, the most significant shortcoming of an otherwise interesting piece of research (and acknowledged by the authors) is the lack of evolution in the model. With evolution out of the equation the condition under which phenotypes emerge and take over the original population cannot be studied. One of the nice features of game theory is that it can be used to study the equilibrium states of tumour cell populations when those tumours are studied as composed of individual cells (or agents in Mansury's et al model). Since the author's know this I am looking forward their next paper to see how the improved model can be used to study carcinogenesis.

Richard Dawkins interview

2006-10-03T17:42:00.000+02:00

Nice interview in BBC of Richard Dawkins. Here he talks about his latest book The god delusion. Will be buying it as soon as it comes to Dresden (which is unlikely to be any time soon :().

Find the interview here

Recap from Lyon (I)

2006-10-03T09:36:00.000+02:00

As I mentioned in a previous post one of the nice talks in Lyon came from Vito Quaranta, from Vanderbilt University in Nashville, USA.

He is and MD collaborating with researchers in the States and Europe (eg Sandy Anderson from Dundee) to develop models on tumour invasion. That is the defining feature that separates tumours from benign to malign (eg cancer).

In order to know if a cancer is invasive MDs tend to look at the way the tumour grows. A tumour with a smooth margin is unlikely to be invasive whereas one with fingering is likely to be so.

Of course I am interested to know if there are alternative studies that could be used to predict the evolution of the cancer that are not based on how the tumour shape looks like. First because in many cases physicians don't have accurate images of the contour of tumours (or sometimes haven't got enough information about what is the result of tumour growth). Second, and maybe most important, because the current shape of a tumour doesn't say much about the potential evolution of it towards malignancy. Maybe a different measure (based on the phenotypic composition of tumour cells) could help not only to tell if a tumour is malignant or benign but if the chances of becoming invasive are high or not.

In any case his presentation showed some interesting results on how the microenvironment affects the evolution of the cancer. Homogeneous microenvironments, that is, those in which space can be created with the same ease everywhere, lead to smooth contours whereas inhomogeneous ones lead to fingering. Interestingly these inhomogeneous microenvironments tend to lead to tumours with little diversity in terms of phenotype: when it is difficult for a tumour cell to create space only invasive phenotypes tend to survive.

Reporting from Lyon

2006-09-27T20:21:00.000+02:00

Still in Lyon after attending the cancer modeling workshop mentioned in my previous post.

From a couple of very brief escapades, Lyon seems to be quite a pleasant town but the workshop has been interesting enough that I didn't had a lot of time for tourism. Nice talks from the likes of Philip Maini from Oxford and Vito Quaranta from Nashville and chats with Benjamin Ribba from Lyon have kept me entertained. The word from modelers: multiscale modeling. Lots of researchers producing models studying cancer at all sorts of scales from molecular to tissue and from seconds to years and we still have not got the way to integrate them.

Tomorrow back to Dresden

off to France again

2006-09-22T13:48:00.000+02:00

It seems that September is my French month: I am off to an interesting workshop in Lyon. The topic is Cancer Modelling and Therepeutic Innovation. Although I won't be presenting I hope to meet physicians and discuss one of my models.

The Workshop URL is : http://www.spc.univ-lyon1.fr/workshop-modcan

I am off!!

2006-09-15T09:52:00.000+02:00

Only until next Wednesday. The Marie Curie Training Network that sponsors my research here in Dresden is organising a meeting of all the scientists involved in the different projects it manages. The meeting is this monday in Paris!!

It will not be my first time in Paris but I am still looking forward spending the weekend there and meeting some friends.

Review: "From artificial evolution to computational evolution: a research agenda"

2006-09-14T23:27:00.000+02:00

A group of people whose work I respect (Dr. Miller was examiner at my PhD viva and I met Prof. Banzhaf in EA conferences) have recently written a paper entitled "From artificial evolution to computational evolution: a research agenda" that was published in the latest Nature Review Genetics (vol 7, page 729): http://www.nature.com/nrg/journal/v7/n9/full/nrg1921.html

Despite the journal in which they decided to publish it, the paper is addressed mainly to computer scientists working in the field of evolutionary computing. Researchers in this field use algorithms inspired by evolution in order to solve problems of optimisation in all sorts of field of engineering. Say you have to find the parameters that optimise a set of equations. If you encode these parameters into a string of number and create a bunch of these strings initialising them with random values you can use selection and crossover to find values that optimise the equation. Since not all the strings will produce the same results in the equation, we can discard the worst performing ones and fill the space they left with variations of the best performing ones. If we iterate this algorithm a number of times, thus producing successive generations of the initial population of strings, we are likely to obtain sets of parameters that, if not optimal, will likely to be fairly close to it.

This neat idea of using evolution in engineering (or even in art! I know a few examples of people that have used evolution inspired algorithms to produce music or paintings) has produced some interesting results but several people have already found that the very simplistic interpretation of evolution that computer scientists and engineers use in their algorithms is no match for the real thing. Real natural evolution (as opposed to artificial one) is both creative and open-ended.

Banzhaf et al identifies some of the shortcomings of traditional evolution-inspired algorithms and proposes a number of improvements framed in the new context of Computational Evolution (CE). This seems to consist, mainly, on adding extra bits of reality in the abstraction of evolution used by engineers and computer scientists in order to provide evolution with some complexity to play with. By doing this, for instance embedding it into analogue electronic circuits, they hope that artificial evolution will be successful were it was not before: solving ill-defined open-ended problems.

While I entirely agree with the idea that the original evolution-inspired algorithms could be significantly improved by enriching the stuff on which evolution works more complex and life-like, I am not sure that what they suggest is so ground breaking as to call the field a different name. Besides, many of the suggestions mentioned have been in use by computer scientists (especially the authors of the article) for some time (for example: more biologically plausible genotype-phenotype mappings, on which people like Peter Bentley or Julian Miller have done very useful work).

In any case I would not like to sound as if I did not like the paper. I did and I think that despite some further objections (such as: why don't they explain why the bits of nature that they decided to pick are the really necessary ones?). Actually I would like to join my voice to theirs and suggest a further use of computational evolution - A more realistic model of evolution can be used not only to do engineering but also to study evolution per se. I would definitely be interested (and in a way that is what I do for a living) in using Computational Evolution to study evolution from a theoretical perspective.

Genes and cancer

2006-09-08T19:32:00.000+02:00

I start the week with a post about something really exciting that I read in Science. Unfortunately my institution does not have access to articles in Science published online before they have been printed on paper so I had to be satisfied for the time being with the reports pusblished by conventional media like the Washington Post.

It seems that researchers have screened for and found 189 genes that are altered in colon and breast cancers. Although we are talking about only two types of cancer, breast and colon cancer are two of the most diagnosed cancers in the western hemisphere. It is remarkable that both types of cancer share very few cancer-related genes and that most of the genes discovered to have a role in these cancers have not been known to be so before.

Tumour supressor gene and aging

2006-09-08T10:16:00.000+02:00

Read at the NYT: Researchers at the universities of North Carolina, Michigan and Harvard have found that p16 gradually inhibits the proliferation capabilities of stem cells when they reach certain age. The mechanism is useful to prevent the proliferation of cells that, due to their age, have a significantly increased probability of creating tumours.

The paper reporting the research will be published in Nature. One interesting comment by one of the authors is that in his opinion aging is not random but an anticancer mechanism. I find this observation plausible but having an interest in evolution I cannot help thinking that the reason for aging could also be that once an organism has fulfilled its replication duties, its evolutionary-shaped genetic program does not care much for the long term survival of the individual. In other words, evolution does not favour individuals who are good at surviving for ever but that are good at surviving for long enough as to have lots of equally successful offspring.

Article in high-performance computing magazine

2006-09-07T19:14:00.000+02:00

It seems that the research at our group has been noticed by a news site specialised on high performance computing. Oh well, I guess it helps that our group (BIOS) is hosted in a department of high performance computing and that TU Dresden has just hosted a major conference on parallel computing.

For those interested, here is the link: http://www.hoise.com/primeur/06/articles/live/LV-PL-06-06-21.html

Scientists find molecule that tricks cancer cells into dying

2006-09-05T12:28:00.000+02:00

Taken from The Guardian, 28th August. It's molecular biology but still interesting: Scientists at the University of Illinois at Urbana-Champaign have found the way to restore apoptotic capabilities to tumour cells. It is known that tumour cells tend to have a defective apoptotic mechanism so they do not die when they should (eg. when the DNA repair mechanism is rendered useless).

One way to give back apoptotic capabilities to tumour cells is to provide the cell with a synthetic molecule that reactivates the production of enzymes involved in apoptosis. This is what Paul Hergenrother and fellow researchers seem to have acomplished.

Nature papers and reviews

2006-08-31T09:40:00.000+02:00

For those of you interested in Cancer (and I assume that if you read this blog then that is probably the case), check out Nature's special "New horizon's in cancer". Sounds interesting and hopefully it will be as good as Science's Cancer research special back in May. It looks a little bit too centered in molecular biology but that is what most of the readership of Nature would want.

The website is here: http://www.nature.com/nature/focus/cancerhorizons/index.html

For those of you without access to Nature's subscription-only website, here is a free article in the collection: http://www.nature.com/nature/journal/vaop/ncurrent/full/nature05085.html

*additionally* you might want to take a look at some article that some guys in London and I have worked on. It is not about cancer but about evolution: how evolution can bring about robustness.

The name of the paper is "The evolution of robust homeostasis and stem cell-like behaviour in artificial multicellular organisms" and you can find it here:
http://blogs.nature.com/nature/peerreview/trial/2006/08/the_evolution_of_robust_homeos.html

Take a look if you have the time and even a mild interest in computational evolution. It is also written in a very readable style (thanks to Buzz).

cancer and evolution

2006-08-25T15:06:00.000+02:00

What does cancer have to do with evolution?

Quite a lot: evolution is one of the defining features of cancer. In multicellular organisms cells cooperate in order to achieve a common goal: to preserve the organism. In a tissue containing a tumour the situation changes: mutations bring about a diversity of genotypes in which some cells will have a higher potential to reproduce and survive than others. In effect an ecosystem is created in which different individuals compete for a limited amount of resources, often to the point of destroying the ecosystem, that is, the organism.

This evolutionary nature of cancer has consequences that affect potential treatments. Since any given tumour will contain a number of different tumour cells, a therapy that is successful at eradicating one type of tumour cell might only make it easier for a different type to spread through. For a treatment to be successful its creators should consider how the ecosystem will be altered and what kind of evolutionary dynamics will be favoured.

Understanding the driving forces of cancer evolution is likely to be a necessary step to understand (and hopefully deal with) cancer. For that reason it would be interesting to see how models of what is beginning to be called computational evolution (nice article in Nature review Genetics, vol 7, september 2006, pp729-735) can be used to study evolution in the context of cancer.

hi again

2006-08-22T11:08:00.000+02:00

This is really the second post. I thought it would be a sensible idea to rename the blog I created yesterday (the cancer game) since its name might be misunderstood. My aim is to study carcinogenesis (the process by which healthy cells are transformed into cancer cells) using a number of mathematical tools such as Cellular Automata and Game Theory, thus the name 'the cancer game'. Of course (and I repeat myself) I am not implying that cancer could be considered a game in the sense of something funny or amusing but in the sense that game theory could be used to study the dynamics of cancer progression.

More to come soon (hopefully not in the front of 'apologies').