Epigenomic Stochasticity in Development and Disease (I)

Andrew Feinberg
Johns Hopkins University

I have been pursuing an idea that natural selection will favor the emergence of genetic loci for epigenetic variation that can occur randomly or in response to environmental signals and affect phenotypes in which the environment changes unpredictably but often enough. In particular, we have suggested a unifying model of cancer in which increased epigenetic stochasticity allows rapid selection for tumor cell survival at the expense of the host. With my colleagues Garrett Jenkinson and John Goutsias, we are developing a novel stochastic mathematical approach to understanding the nature of epigenetic information and its relationship to environmental exposure and biological function. This has led to several new measures, including normalized methylation entropy, which turns out to be surprisingly relevant to understanding some fundamental principles of physical biology. My colleagues will present statistical modeling and information-theoretic approaches to this question. I will then discuss their application to cancer, aging, and chromatin structure in normal development and cancer.

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