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).
Thursday, March 01, 2007
Friday, February 23, 2007
In Barcelona
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).
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).
Tuesday, February 13, 2007
Lenski et al: Balancing robustness and evolvability
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.
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.
Monday, February 12, 2007
Cancer and biofuels
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.
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.
Friday, February 09, 2007
Axelrod et al: Evolution of cooperation among tumor cells
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.
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.
Tuesday, February 06, 2007
Mitochondria and apoptosis
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.
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.
Monday, February 05, 2007
World cancer day
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.
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.
Monday, January 29, 2007
Mitochondria and glycolysis
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.
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.
Wednesday, January 24, 2007
Spencer et al: Modeling Somatic Evolution in Tumorigenesis
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.
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.
Saturday, January 20, 2007
The Darwinian perspective, the mutator phenotype and response to stress
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).
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).
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