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.

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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.

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).

Edge of existance

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

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.

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.