These days I am trying to familiarise myself with prostate cancer and the effect of TGF-Beta on tumour progression. Some relevant information:

The prostate is a gland of the mammalian reproductive system that stores and produces an alkaline fluid (that makes 10-30% of the seminal fluid). Due to this acidity there is a lot of self renewal in the prostate. The following figure from wikipedia illustrates the different parts of a human prostate:

The most important parts of prostate are the peripheral zone (biggest and responsible for 70% of the prostate cancers), the central zone (25% of tumours), the transition zone and the anterior fibro-muscular zone that contains stroma and is responsible for about 5% of the cancers.

Prostate cancer normally starts in the peripheral zone and might be confined to the gland or spread to the surrounding tissue (stroma).

Probably the most relevant cells to study tumour initation and progression are the epithelial cells and the stromal cells. Epithelial cells are normally found in the surfaces of the structures of the body. Based on the results of the biopsy it is possible to estimate the Gleason score with grades 1 to 5. A GS of grade 1 meaning a less aggressive tumour and 5 being a very aggressive tumour. The two most common patterns in the sample are graded this way and the two values combined into 1 in the range 2 to 10. This GS is a powerful predictor of a patient prognosis. A patient whose biopsy has a GS of value 6 or less has a 90% of chances of surviving more than 5 years whereas another one with a GS of 7 would have 50% or less.

Now…tumour cells are not the whole story here, the microenvironment, or a bit more specifically, the stroma, does play a role. The stroma is made of connective cells in a tissue such as fibroblasts, smooth muscle cells and from extracellular matrix (produced by the fibroblasts) and several types of growth factors such as TGF-Beta.

1. Epithelial inhibition.
2. Recruiting mobile stroma.
3. Myofibroblast induction (cells in between a fibroblast and a smooth muscle cell in differentiation).

TGF-Beta also seems to play a role in tumour progression and increased TGF-Beta expression is found in prostate cancers. Some questions still not answered and that could be addressed with a theoretical model are

1. how would loss of TGF-Beta sensitivity affect tumour progression
2. how would an increase in TGF-Beta expression affect tumour progression?
3. what is the influence of this reactive stroma?

What caught my interest were the comments of some of the subscribers who emailed him. These comments, all very positive, were about how inspiring they found the lectures and what a positive opinion they have acquired on MIT as a consequence of it. This programme is no longer limited to MIT and recently Yale started offering something similar.

With a few years delay over the rest of the world I managed to find myself thrilled at the opportunities this represents for university teaching. Most of us who live to do research but once in a while (or way to often, depending on the situation) have to teach find very little motivation to do so. It is not very valuable from the career point of view and in many cases we don’t get many or motivated students. But if your lecture is in OpenCourseware (or a similar system) there is a good chance that we might be just a bit more careful when preparing the lectures. Not only that, but knowing that many people from around the world (some of them experts in the field, some of them potential collaborators, some of them future students) could be watching and that these people will tend to be highly motivated people then things start to change. Add to that the fact Universities like MIT are likely to find out that this system is not only a moral duty but also a very effective way to promote the University and its reputation (see all these I love MIT in the article_). This should encourage universities to pay more attention (and money) to people that can be popular lecturers and thus able to raise the visibility of the university and bring in more students (since these eStudents might become fee paying students later on). I think we might be seeing the reinvention of teaching in Niversities.

The authors take a very well known game rock-paper-scissors, widely known in game theory. Now, imagine that you place the players in a space that is divided in a way similar to a chess board. Imagine that the players play with their immediate neighbours and that the collected points can be used to determine which players are removed from the board and which ones are allowed to stay and even colonise recently emptied places. In this situation and given that no strategy dominates the other two you should expect a constant shuffle of strategies. If you give each strategy a colour then you could imagine patterns of colours moving in different directions, never settling in a permanent position.

Things seem to change if you allow an addition to a game. Once in a while we could allow two players to switch positions or a player to take an unoccupied slot and giving his old place up. According to these research, the more you allow this to happen (about a certain threshold the effects are more dramatic) the more that this coexistence of three different strategies becomes impossible. Thus motility could have a huge impact in the conservation of biodiversity. This is an interesting result and one is left just wishing that the had explained not only what happened but also (if even tentatively and with due care) why does it happen that way.

Although the work is, for the time being, computational, the authors describe how research done with E.coli in petri dishes could be used to validate experimentally their conclusions.

1) Human population started to grow in Africa and then elsewhere. Larger population size lead to more room for evolution to experiment with mutations

2) As a result of population expansion, some of this early humans migrated to different parts of the world where they had to confront different environments (climates, diseases…) to which they had to adapt differently.

This is interesting, plausible (which does not make it necessarily right) and also applicable to tumours. As tumours grow, the swell in the number of tumour cells make it very likely for mutations to increase the diversity of the population. Furthermore, the raise in population numbers and the space they take makes it also likely that subpopulations of the tumour will be subject to different microenvironments which should lead to different selection pressures. This would mean more diversity and and increased selection of phenotypic capabilities present at a given time in the tumour.

Jung-Kyoo Choi and Samuel Bowles. The coevolution of parochial altruism and war. Science, Vol. 318, Oct. 2007

The evolution of cooperation is a topic that has been discussed before in this blog but the authors of these paper consider an additional twist which is not only altruism but parochial altruism. Altruism means that we help other people and parochial altruism would stand for altruism towards our own group and agressivity towards other groups.

Both traits on their own are difficult to explain in the sense that both are detrimental to the fitness of an individual displaying them. In order to study how it could evolve the authors designed and implemented a relatively sophisticated simulation environment in which individuals can be either parochial, altruistic, both or none. The results seem to imply that group evolution would explain that groups that favour the emergence of parochial altruists would have a selective advantage. These parochial altruists are willing to sacrifice themselves for the good of the community and in the simulations that sacrifice would come in terms of fighting with other groups. The groups with more fighters tend to decimate their competitors. Also, parochial altruists that are successful in these combats have a higher chance of producing offspring than the non parochial altruists of their community.

A public good game is used to determine how the spoils of war are distributed. You could understand parochial altruists as cooperators that pool in the general good even when they know. Whereas in a normal game cooperators would have a difficult time, in this game, when the presence of hostile is important, cooperators can prosper.

I am discussing with some people in Dundee and Vanderbilt about how to study cancer progression in terms of evolution of cooperation (as hinted by Axelrod et al.). One of the leading researchers in the field of biomathematics and game theory is Harvard’s Martin Nowak, In this paper he discusses five potential mechanisms of cooperation that could appear through Darwinian evolution.

Kin selection refers to the cooperation between individuals that are genetically related. It is easy to see how an individual will sacrifice something in order to help another individual as long as the relationship between what is sacrificed and the level of relatedness crosses a given threshold.

Direct reciprocity is also quite clear: if from our mutual cooperation we both get something more than what we put then it is viable. To explain its emergence Axelrod performed an study a couple of decades ago in which he found that of all competing strategies, the most successful one was Tit for tat. A player following this strategy will cooperate unless the other player does not. If the non cooperating player starts cooperating at some point then tit for tat will resume cooperation. In circumstances in which a level of noise might affect the perception of cooperation (if, for instance, one player thinks that the other one is not willing to cooperate when in fact he or she is) then a better strategy would be win-stay, lose-shift in which the player will keep a strategy for as long as it reports a benefit and will switch to the alternative one (be it cooperate or not) otherwise.

Indirect reciprocity on the other hand is less clear and is based on the idea of reputation. If individuals with a reputation for cooperation can be perceived by other participants and these participants are more likely to cooperative with individuals with a good reputation then cooperation could evolve even when the individuals in the population do not interact repeatedly. Problem with indirect reciprocity is that, depending on reputation requires skills normally not found in animals outside our own species.

Network reciprocity falls in the easily understandable category. Most game theoretical studies assume a well mixed population. That is not realistic and spatial models (like those based on Cellular Automata) and graph models (known as network models among physicists) make it easier to study cooperation when the individuals are more likely to interact with a subset of the population. It is known that in many cases, cooperation is more likely to emerge in spatial than in non spatial models. From the mathematical point of view though, these systems are easy to simulate in a computer than to analyse formally.

Group selection is a controversial type of selection in which selection does work not only at the level of the individuals but also at the level of the species to which these individuals belong. According to this line of thought although cooperation might not benefit cooperative individuals (whose efforts could be misused by freeriders), species in which cooperation emerges are more likely to stick around that species with exclusively selfish behaviour.

I am always playing catch up with my issues of Nature and Science and this is no exception. One of the main frustrations of game theoreticians in sociology is that humans do not behave like rational players. Ironically enough that does not seem to be a problem for those of us that use game theory in biology. In nature individuals of a species seek to maximise their benefit (otherwise they become extinct).

In their paper Jensen and coauthors show how chimpanzees,our closest relatives, do play like rational players in the ultimatum game. In the Ultimatum game one of the players offers how to split a particular item and then the other players decides whether to accept or reject the offer. If the offer is rejected then none of the players gets anything. Humans tend to reject what they perceive as unfair deals (like 20-80 or more skewed) and seldom offer deals more skewed than 60-40. Chimpanzees on the other hand where likely to offer unfair deals and when offered, they were likely to accept them.

The article takes advantage of the recent (Nobel) successes of German science to comment on the new governmental approach to science funding in which the universities are not treated equally. Winners of the second round of the excellence initiative: the technical university of Aachen, the universities of Freiburg, Heidelberg, Göttingen and Kostanz and the Free University of Berlin join the winners of the first round: the technical universities of Munich and Karlsruhe and the Ludwig Maximiliam University of Munich. Then the writer goes on to focus on all the positive things that will come from this new approach (like a perceived increase in the capability to compete with American universities) but also mentions the things that are not likely to change: that the majority of the PhD students and postdocs in Germany are unlikely to ever get a non-temporal position.

It is also worth noting that asides to some mention to an advertisement of Dresden there is no much mention to the fact that no former GDR university has managed to achieve the status of elite university despite hopes of Humboldt University of Berlin, Leipzig or Dresden.

It is something of The rise, fall and rise of group selection. It basically goes through the many reasons by which group selection was dismissed in the 60s and how, nowadays, people start to accept that it might be more relevant than previously thought. It is interesting that the article draws from so many theoretical models (many of them based on game theory) to show how they anticipated the experimental results that were found later. According to some (quite popular) interpretation of Dawkins selfish gene, only the most strictly selfish behaviour has a chance of spreading through a population. The experiment described in the article in which prudent virus strains could outcompete the nastier ones proves that this does not necessarily have to be the case. In general it is clear the pro ‘multiple levels of selection’ bias in the article.

My take is that Dawkins is right that anything that is detrimental to the goal of a gene to perpetuate will have slim chances of surviving in an evolutionary process. Still cooperation is known to exist and species capable of cooperation are, in many cases, more likely to thrive than those that are not. The twist lays on the fact that cooperation does not need to be detrimental for a gene (although not necessarily for the individual that carries it). First, species in which selfishness precludes collaboration and promotes explotation, selfish genes might die due to their own success. There is one typical game in game theory called the tragedy of the commons which explains how a common good can be overexploited by uncollaborative individuals with the result of everyone in the population paying a steep price for it (potentially extintion). It is also known that collaborative behaviour can emerge in a population if it benefits other individuals with related genes (kin selection), the participating individuals (the Hawk-Dove game could be used to explain that one) or if collaborative individuals manage to establish a punishment mechanism (there was a talk in Dresden by Karl Sigmund just about a month ago in which he explained this).

So for the sake of light-hearted fun I will post here a ranking of research in British universities that the Guardian has compiled on occasion of the impeding deadline for submissions to the Research Assessment Exercise that will determine how a lot of the government research money will be distributed.

On top, the usual ones: Oxford, Cambridge, Imperial, UCL, Edinburgh, King’s, Birmingham, Manchester, Glasgow and Bristol. It looks likely that, as usual Oxford, Cambridge and London will get the bulk of the money. Scottish Universities do not to bad either with Edinburgh in the 5th position, Glasgow on the 9th and Dundee still in the top 20.

Now, in order to compile this statistics, the Guardian measures the usual which, of course, includes publication numbers and impact. Another blogger in Nature Networks and a fellow Dresdner, Joseph Zhou, has posted this about how Andrew Wiles found the time to proof Fermat’s last theorem : He just wrote 20 papers, kept them on this desk and submitted them at a rate of two a year in order to keep his academic career going while using his time in the very risky task of finding a solution to a problem that had been unsolved for hundreds of years.

UPDATE: Ranking from the THES. Still same story.

Unfortunately, the review itself does not say that much about the book so I might have to wait until I get hold of a copy before I can tell if it would be a good idea to buy it or not. It is clear thought that Weinberg sees it as a revival of the mathematical biology school that started in the University of Chicago in the 60s. If he thinks that mathematical biology is of any use in cancer research or not does not come very clear in his review and one suspects that he is quite skeptical about its future role.

Still, game theory has been making headlines the last couple of weeks and since this is one of my favourite mathematical tools I could not help coming with a post.

Fist, The Economist had an article in which the especulate on how game theory could be used to save the world. One of the problems enforcing the measures needed to prevent climate change is that although most players (countries in this game) recognise to some extend that doing something about it is in everybody’s interest. But also, like in the tragedy of the commons game, players know that what is really in their interest is to let everybody else take the burden of protecting the environment while they keep carrying on as usual. The Economist cites research from an institute called New Energy Finance, but anyone working on game theory knows that one approach to the dilemma of the tragedy of the commons is to punish the free riders. Another complementary solution is to set targets that are less ambitious but that can be achieved quickly in order to have frequent and accurate feedback on what players are cooperating and which ones are not.

It has been proven that game theory can help you be awarded a nobel prize, it would be nice if it could also be a tool to coerce countries into taking the measures needed to prevent climate change (or maybe other tasks that also benefit mankind but require the collaboration of many countries).

This does not mean that German science should rest on their laurels, there are some issues that are holding back German universities and research institutes from reaching their full potential. Some of them are discussed here.
One feature of the German academic system is that there seems to be a two-layer system with the Max Planck Society carrying out most of the world-class research and the Universities taking responsability for the teaching. The other feature, shared by most continental European countries, is that there is a flat field in which universities are provided with funds according to the size of the student population (and the specific policies of the local state). This dependency from the Federal and state administration makes change more difficult. That coupled with a lack of incentives for Universities to produce outstanding research (since the state will finance them the same regardless) means that some good researchers move to the Max Plancks (or abroad) leaving the university system without some good researchers that could also teach.

One issue not mentioned in the article though is the difficulty for young (or not so young) researchers to obtain more than temporal contracts. Whereas this seems to be a problem in most countries, in Germany this is better and worse. It is worse because there are not that many positions for a postdoc asides from becoming a full professor, leaving many of us without hope to have an academic career. It is also better because in Germany, people with a PhD are less likely to be discriminated for the fact of having a doctorate. In fact many companies are happy to hire PhDs for more than their R&D departments.

UPDATE: Just one interesting fact that I read today in the paper about the procedence of the nobel laureates from 1951 to 2006: 56% american, 13.2% British, 8.7% German, 3.38% Russian and 2.8% French

This ranking is slightly different than the one provided by the World Health Organization which includes non EU countries although most of the top positions are in Europe. In this ranking the top 10 countries are France, Italy, San Marino, Andorra, Malta, Singapore, Spain, Oman, Austria and Japan. UK comes at position 18th, Germany at position 25th and the US in position 37. The WHO ranking seems to be less biased towards Scandinavian countries and more biased to Mediterranean ones.

The workshop was organised by J. Claussen (Kiel), C. Hauert (Harvard) and G. Szabo (Budapest) and allowed me to to have an overview of recent research in game theory. Of course this view will be biased, first by the fact that not every game theoretician is interested in complex systems (and thus won’t attend a conference like this) and also because the organisers probably have their own preferences too. Thus, although my view until now is the GT is more popular among economists and evolutionary biologists, a good proportion of the speakers today were physicists.

That may (or may not) have influenced much their topic of research. In general the talks focused on the classical games used to study the evolution of co-operation: prisoners dilemma and public goods game (I mentioned an introduction to these games in an old post). With this games in mind people try all kinds of variations: spatial models, games with stochastic payoffs, stochastic strategies, games with more than two players interacting, games in which players interact via graphs (or networks). Although not much was shown in terms of applications it was quite helpful to listen about things I could use to improve my glycolysis game.

The workshop also allowed me to introduce my model to some people like Jacek Miękisz (Warsaw) so I got a few hints of what I could use in the next version.

It seems that MSCs that interact with weakly metastatic cells release a paracrine substance (CCL5) that promotes metastasis. The effect works for as long as the tumour cells have access to CCL5 so these cells revert to their normal state once the factor is out of reach.

Interestingly, Weinberg reckons that this mechanism is unlikely to be breast-specific and that it could be used to explain metastasis in many kinds of cancers. This work seems to give strength to the idea that dealing with stem cells is necessary when treating a cancer.

I was particularly interested in the keynote of Karl Sigmund at the University of Vienna, about the evolution of cooperation. As some of you know, the evolution of cooperation is something that is normally studied using game theory. GT can be used to explain the situations in which genetically related and (sometimes unrelated) individuals cooperate. Evolution of cooperation could potentially be used to explain how is it that tumour cells acquire all the capabilities required to progress to malignancy overcoming the anti cancer mechanisms of our bodies (already discussed here).

Since tumour cells are not necessarily so genetically related (at least compared to non tumour cells), the cooperation has meaning only when both cooperating cells receive a benefit. Without referring to cancer, Prof. Sigmund talked about the ways in which cooperation can emerge in populations in which individuals may chose to cooperate or not. Of those that chose to cooperate some of them might actually do so or alternatively can cheat, playing to be cooperators and receiving the benefits without actually contributing to the common good. In order to enforce cooperation, cooperating individuals might chose to punish defectors (thus making cheat more costly than cooperation) or non punishers. It is assumed that punishers do have to pay a bit (although not as much as the punished).This solution is not entirely satisfactory: in this way punishing enforces cooperation that benefits all cooperators, be it punishers or not, but with costs that are shouldered only by punishers. Thus punishing is a second level of cooperating that should need the same kind of reinforcement to work.

Prof. Sigmund showed some simulations (that can be found in this site) in which the
dynamics change depending on how many types of players we put in the game. In games with only cooperators, punishers (also cooperators) and cheaters, the cheaters tend to take over the population. Interestingly enough when non cheating non cooperators (they just never benefit from other people’s work but they do not contribute either) are allowed then it is punishers who thrive.

Interesting fact about this conference is that the keynotes and talks are being videorecorded and will be put online at Videolectures.net site.

Of course he notes that evolution is really happening in our organism and at least in one case (the immune system) evolution happens to our advantage. The point is nonetheless, that our organism has been evolved to avoid evolving itself (with the mentioned exception), or at least, to make this somatic evolution as unlikely as possible. The way to do this is by means of stem cells and transient amplifying cells.

This hypothesis was tested computationally by John Pepper and colleagues when working at the Santa Fe Institute. If every cell in the organism is in charge of making sure that there are enough cells of their own type then you don’t need many alterations to have cancer. The route is a bit more complicated. Stem cells are in charge of making sure that there are enough cells of a given type. They divide very slowly and have been evolved to be especially immune to mutations. They divide creating a copy of themselves and a transient amplifying cell. These TACs divide in a way that the offspring is different from the mother so even if they mutate, given that the offspring is different, it is unlikely that their faulty behaviour will be inherited and spread in a tissue.

Based on these assumptions the computer models show that even though energetically wasteful, this system minimises significantly the possibility of cancer.

Also this week I found this piece of news reported at the BBC’s website about research by scientists at Wake Forest show how white blood cells (granulocytes) from one person can help treat a cancer in a different one. Interestingly the article mentions that granulocytes (which according to wikipedia that refers in many cases to neutrophils) are not normally thought to be relevant in cancer research. That should support the research of people (Antonio Bru at UCM comes to mind here) studying how the non adaptive part of the immune system (neutrophils) could be leveraged as a cancer therapy.

A second interesting finding is that the granulocyte count in patients with cancer is lower than in healthy people and that even in that case this number changes in the year with higer counts in the spring/summer and lower in the autumn/winter. Could it be that (and I not claiming it is my idea, I heard it before) a tumour is more likely to start when the immune system is depressed?

It is also interesting that this researchers found how (at least in mice) to transplant cancer-fighting granulocytes from one individual to another. Since different people have different immune systems that could imply that we could use our own diversity as a species to fight tumours, whose growth could be explained as cells taking advantage of somatic evolution

My trip tomorrow will allow me to meet Dr. Benjamin Ribba (Universite Claude Bernard) with whom I am investigating the role of the microenvironment in driving cancer evolution. We start from the hypothesis put forward by Hanahan and Weinberg 7 years ago that tumour cells have to acquire a number of capabilities if a group of rapidly and unorderly dividing cells is to become a cancer. The capabilities mentioned in their paper (Cell, 2000, Vol 100, 57-70) are: unlimited replicative potential, self sufficiency of growth signals, ignoring anti growth signals, angiogenesis,evasion of apoptosis and invasiveness. Now, from the evolutionary view point, what makes a cell with a particular phenotype (resulting from acquiring one or more of these capabilities) more or less successful is its capability to produce offspring and this capability will depend on how this phenotype adapts and modifies the microenvironment it inhabits. Different microenvironments are likely to lead to cancers that become aggressive using different different paths (of capability acquisition). It might even be the case that we could find out which microenvironments are more likely to lead to cancers in which this path takes longer or does not occur in a relevant amount of time (that is, the normal life span of a human being).

As was the case last year, these summer schools consist of a mixture of lectures given by senior researchers about general topics of cancer modelling and short contributed talks given by the younger (and not so younger) researchers about our specific research.

This year mean topic seemed to be radiotherapy. Radiotherapy works on the principle that tumour cells have a faulty DNA repair mechanism compared with healthy cells. Using radiation it is possible to produce breaks on the DNA which might incapacitate the cell. The trick is in how much and how often. Even if the right amount of radiation is used, too many doses might not allow healthy cells to repair the damage and thus destroy the tissue. Too few doses and then the therapy would be useless.

Now, there are mathematical models (starting with the Linear Quadratic Model) that can predict, given some information about the tissue, what is the best radiation and dosage for a patient. Apart from mathematics we had the luck to have some physicians in the audience. Is always refreshing, coming from the theoretical side, to listen to their point of view. Is also shocking (but necessary if we theoreticians want to understand what is at stake) to see images of patients with breast cancer. Some times, watching our colourful simulations on the screen, it is too easy to forget that Cancer is a disease that kills many people, and not in a particularly painless way.

The release from the WHO produced headlines in most of the media around the world (for instance, the Spanish press). There was also this TV debate that counted with the presence of Paul Nurse, the Nobel laureate.

Up to now nothing new but it is reasonable that as human population grows the chances of one of us getting in contact with the wrong virus at the wrong time increase. Also, as we travel more often to more places the chance of transmitting the virus or disease increase significantly.

So what is the best defence (short of stopping people from travelling)? My guess is that involves having, as accurate as possible, models of diseases spreading if we know where the focus of the disease is and the spreading characteristics of the disease. Another thing is that it probably helps to have populations that are genetically diverse. Since a disease is unlikely to affect everybody in a genetically diverse population, that information could be useful to find out how to better fight the disease.

One of the milestones of the last GECCO was the public debate on complexity and evolution organised by GECCO in one of London’s most impressive locations, the Natural History Museum. The debate was chaired by Peter Bentley, my former PhD advisor and included some of the biggest names in evolutionary biology and development: Richard Dawkins, Steve Jones and Lewis Wolpert. This debate alone would have been a reason good enough to make GECCO an event woth attending. For those of us that could not make it, Peter has created this site in which is possible to download the videocast of the event.

They show information from the World Health Organisation that shows that the biggest killer in the world (not just the developed world) are heart diseases. Cancer is responsible for a mere 15.7% of the world deaths.

This is interesting because, traditionally, heart diseases as a significant health problem, were thought to be the preserve of rich countries but nowadays affects most countries. It seems that as poorer countries improve their living standards (or at least that is what the article claims) more and more people are discovering the diseases that characterise the old age in the developed world. Unfortunately it seems that poor countries are less able to cope with people suffereing from these diseases than richer ones. These diseases also impose a great economic (as well as emotional) burden on the families of the affected.

Science has published a couple of weeks ago a study that, according to the authors, shows that (at least in their experiments with xenotransplantation in mice) most cells are capable of seeding a tumour in the new host. About 10% of the transplanted cells could seed a tumour and less than 5% of those were stem cells.

That is all quite interesting although in my opinion they fail to ask themselves if the cells they xenotransplanted (that are already cancer cells) were or were not initiated by a stem cell.

It seems to be an exciting time to be doing oncological research in Dresden and hopefully there will be opportunities for some collaboration with biologists to test a model I have in mind about the role of stem cells in cancer initiation.

The group in which I worked had a fair balance of biologists and mathematicians and, apparently, a keen interest in studying the role of the protein known as TGF-Beta in prostate tumours. The project focused (and still does, since some of the people in the group will keep working on that) on producing an indivudual-cell based model that could answer questions such as :

• How does the loss of TGF-Beta responsiveness in epithelial cells (cells in the outer layer of organisms including the colon and the prostate) affect tumour initiation?
• Does the increased production of TGF-Beta affect tumour progression? and if so, how?
• What is the role of monocytes (immune cells that can be recruited by TGF-Beta and, when matured, become macrophages) in tumour progression?
• Given that TGF-Beta produces different and some times, mutually opposed effects in each cell type, is it possible to study this interplay of TGF-Beta responses in the most relevant cell types?

The results where pretty spectacular given that we had approximately a couple of days to come with the project, the model, the questions we wanted to approach with the model and some initial simulations. An example of one of these simulations can be seen in movies cell, bm, tgf and mde. Each of the movies shows a different aspect of the simulations. The cell movie shows tumour progression in a domain containing a double layer of basal and lumen cells, separated from the rest by a membrane. In the outside, as shown in the figure there are stromal cells, receptive to TGF-Beta, and monocytes, that move towards the source of TGF-Beta once the concentration reaches a certain level. After a few seconds, a mutation transforms one of the epithelial tumour cells into a tumour cell that does not consume