Somatic and non somatic evolution

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).

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.

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.

Gatenby and Smallbone: Glycolysis and tumour invasion. Two papers

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.

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

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.