In essence, the mutation control process constitutes the Darwinian se-
lection pressure determining the fate of the (path dependent) output of the
mutator. Externally-imposed structured psychosocial stress then jointly in-
creases mutation rate while decreasing mutation control effectiveness through
an additional level of punctuated interpenetration. We envision this as a sin-
gle, interlinked process, and, extending Nunney’s work, find the evolutionary
anthropologist Robert Boyd’s aphorism that ‘culture is as much a part of
human biology as the enamel on our teeth’ likely true at the level of very
basic biological mechanisms.
For human populations, different forms of ‘social exposures’ can act as
carcinogens. Hormonal cancers, since they explicitly involve ‘signaling molecules’,
should be especially amenable to the information dynamics formalism we
have adapted to our analysis.
The central mystery we are addressing does not involve such detailed
questions as the relationship between metastatic spread and primary tumor
size or the like. We are, instead, focusing on the basic biology of population-
level differences in disease expression. However, the approach does provide
an explanation of the temporally staged nature of cancer, in terms of multiple
phase-change-like punctuations.
What we attempt is not without precedence. Adami et al. [1] envision
genomic complexity as the amount of information a gene sequence stores
about its environment. Something similar can be said of a reverse process:
environmental complexity is the amount of information organisms introduce
into the environment as a result of their collective actions and interactions
[33]. Extending that perspective [57], we have invoked an information theory
formalism, imposing invariance under renormalization on the mutual infor-
mation characterizing the Rate Distortion Theorem applied to Adami’s map-
ping. The result is a description of how a structured environment, through
adaptation, literally writes a (necessarily) distorted image of itself onto the
genetic structure of an organism in a punctuated manner.
We have adopted a version of Wilson’s [60] classic renormalization strat-
egy [51, 52, 54-7] to treat the dynamics of such ‘languages-on-networks’,
finding their punctuated phase-transition splittings and coagulations to rep-
resent, respectively, speciation and coevolution. Application of the Rate
Distortion and Joint Asymptotic Equipartition Theorems produced a theory
whose qualitative behavior was free of the details of the chosen renormaliza-
tion relations [56, 57]. Here we use those details to extend that theory, as it
applies to the interaction of mutating cancer cells and a set of related tumor