Cancer is influenced by its microenvironment

Recently, there has been an increasing discussion about the role of genes in cancer. The gene-centric view of cancer was reinforced by molecular studies, but this popular conception of the gene as a simple causal agent of cancer is loosing place on the platform of genetic discourse. In fact, cancer is influenced by its microenvironment, yet broader, environmental effects also play a role. Cao et al (Cell 142, 52–64, July 9, 2010) reported that mice living in an enriched housing environment show reduced tumor growth and increased remission. They found this effect in melanoma and colon cancer models, and that it was not caused by physical activity alone. Serum from animals held in an enriched environment (with social and physical activities, joys, etc) inhibited cancer proliferation in vitro. This suggests that the stretch of DNA code for a gene is like a word without a grammar. The environment provides the semantic frame (or grammar) of the organism language.

See here:

Mutational robustness can facilitate adaptation

The relationship between robustness and evolvability is complex because robust populations harbour a large diversity of neutral genotypes that may be important in adaptation. Although neutral mutations do not change an organism’s phenotype, they may nevertheless have epistatic consequences for the phenotypic effects of subsequent mutations. In particular, a neutral mutation can alter an individual’s ‘phenotypic neighbourhood’, that is, the set of distinct phenotypes that the individual can access through a further mutation. Pioneering studies based on RNA folding and network dynamics suggest that genotypes expressing a particular phenotype are often linked by neutral mutations into a large neutral network, and that members of a neutral network differ widely in their phenotypic neighbourhoods. Numerous studies have documented the importance of neutral variation in allowing a
population to access adaptive phenotypes, and neutral networks have consequently been proposed to facilitate adaptation. (Draghi et al. Nature Vol. 463, 21 January 2010).

Architecture of complex systems

How is a complex system architectured? To start to answer this though question is necessary firstly to consider that it has large number of relatively simple elements working parallely, which provides robustness and efficiency. Secondly, the system works by simultaneous exploration of many possibilities or pathways, in which the resources are made available according to the probability of success. Many different possibilities are explored simultaneously, but with different depth and speeds. In this process, information is used to evaluate the probability of success and to invest important resources in what is worth exploring.
A good example is provided by Melanie Mitchell in "Complexity: a guided tour". The immune system must determine which regions of the exploratory universe of pathogen shapes will be screened. There are trillions of lymphocytes in the body at any given time, most of them can uniquely identify a specific pathogen shape (or antigen). The shape ranges that are most successful are given more exploration resources: the immunological system increases the number of lymphocytes specifically compromised to that shape range. Thus, the system is able to focus on the most promising pathogens, while never neglecting to explore new possibilities.

Cellular automaton

One the most interesting topics in the field of complex systems are the cellular automata, which were invented by John von Newman in the 1940s. The cellular automata (plural of automaton) are grids of cells, where a cell is a simple unit that turns on or off in response to the status of local neighbor cells. There is a rule to update the status of each cell, and this rule is identical to all cells. This rule establishes the status of the cells in the next time step as a function of the current state in its local neighborhood.

At any point in the timeframe, the cellulr automaton processes information by applying its rule to its current configuration. Stephen Wolfram believes that natural systems work much the same way - that they contain information and process that information according to simple rules.

Why this idealized model of a complex system is so interesting?

This model simulates complex systems in nature, with no central controller and it can exhibit very complex behavior that is difficult or impossible to predict from the cell update rule.

See here a practical example of cellular automata:

A bioinformatics revolution?

A good question to be answered by those working in bioinformatics is whether there has been a revolution in "techne" ( in the sense of technology) or in "episteme" (scientific knowledge). Or was it in both? I'm affraid Thomas Kuhn could not help us to answer this though question, because maybe the anwer is beyond the limits of epistemology, and the central point is the relationship between science and technology. For those who think about technology as a mere tool for science, it must be said that much of the scientific advancement is due to technology, while technology does not necessarily depend on science to advance. The technology depends on science to discover new phenomena, which will permit the building of new technological tools, but that's not always the case. Technology can advance by combining existing technologies, as usually it does.

In this sense, I like the W. Brian Arthur's definition in his "The nature of technology":

"From all this it follows that science not only uses technology, it builds itself from technology. (...) Science builds itself from the instruments, methods, experiments, and conceptual constructions it uses. Science, after all, is a method: a method for understanding, for probing, for explaining. A method composed of many submethods. Stripped to its core structure, science is a form of technology."

Ad hoc committee

According to Lenny Moss: "The critical decisions made at the nodal points of organismic development and organismic life are not made by a prewritten script program, or master plan but rather are made on the spot by an ad hoc committee".

Molecular biology would be different if its practitioners took this phrase seriously.

Putting order in chaos

From "Complexity, a guided tour" by Melanie Mitchell:

"The discovery and understanding of chaos produced a rethinking of many core tenets of science:

1) Seemingly random behavior can emerge from deterministic systems, with no external source of randomness.

2) The behavior of some simple, deterministic systems can be impossible, even in principle, to predict in the long term, due to sensitive dependence on initial conditions."

I think Melanie Mitchell made an useful guide for cancer researchers. Hopefully, they will read her book.

What genes can't do

My second post comes from an article by Richard Levontin, with his broad humanistic perspective of science. It's about the dream of the human genome, and its promises. He wrote:

"Daniel Koshland, the editor of Science, when asked why the Human Genome Project funds should not be given to the homeless, answered, "What these people don't realize is that the homeless are impaired... Indeed, no group will benefit more from the application of human genetics""

Unfortunately, this deterministic ideology is the basis of most genomics research made nowadays. This ontological claim, of the dominance of DNA over all aspects of life, has key social and political consequences.

Hi people!!

This is my first post... nothing to say for a while, but don't worry, there will be a busload of posts pretty soon.