One quite fascinating thing in animal biology is the question of immortality or, to be more precise, the lack of it. While most unicellular organisms can divide for as long as they have the luck to find resources and space to do so, human cells can divide only a limited amount of times (approximately around 50 times, although this does not apply to stem cells that can divide an unlimited amount of times). In principle the limitation in divisions for most human cells is due to a mechanism that has been evolved and is not an intrinsic limitation. The cancer hypothesis is that the limitation makes the appearance of cancer more unlikely. If a cell is limited to just a few divisions, if it acquires a mutation that mutation is unlikely to spread to far.
The reason for this limitation are the telomeres, situated at the end of the chromosomes, that get shorter each time the cell divides. Once these telomores reach a critical size and become to small the cell will enter a state called senescence by which they will not divide again.
This is an interesting link in which they talk about this and how in the next few decades we might know enough about the effects of limited cell replication in human life expectancy, how to increase it (maybe for ever) and how to do that avoiding nasty side effects (like increased probability of dying from cancer). The website in which this is hosted is covering all sorts of news, many of them of dubious scientific interest, but the information in the link looks sound.
On the other hand in a more reliable source (PNAS) there is a nice study on how telomere dysfunction can cause genetic instability. They work on a disease known as Werner syndrome but it is quite useful stuff for cancer research. This Werner syndrome results in people aging prematurely and researchers at the Salk institute have found how extra short telomeres can be the source of the problem.
First of all, I am not a bioinformatician. I even thought I had an idea of what is the aim of bioinformatics but after a visit to the group of Nuria Lopez Bigas at the Biomedical Research Parc in Barcelona I realised that the scope of what I thought the field is about was too narrow (they do some nice machine learning and statistical work on disease related genes).
I have seen this video on Google video (only one of these sites that allows the user to download the video for offline use) some time this weekend. It is just a talk by David Vise, the author of a book about Google, to staff at Google Inc. Google is one company that fascinates (and in a sense, worries) me tremendously. As a side note, this blog is posted in one of their servers.
The thing is that at the end of the talk, David mentions the interests of one of Google founders (I think it is Larry Page) on biology. Then I thought (and I am sure that I will be the last of a long list of people) that, wow, that is really a good match: google and bioinformatics. Biology until know was mostly a science in which practitioners collected facts. There is loads of data and little idea of how to make sense of it, asides from evolution and a few other very general ideas. One of the aims of google is precisely to find patterns in the zitabytes of information stored in their servers. I have the feeling that we will see more of Google in that field.
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).