Modeling somatic evolution in hierarchical tissue structures

Cancer can be viewed as an evolutionary process, where the accumulation of mutations in a cell eventually causes cancer. The cells in a tissue are not only organized spatially, but typically hierarchically. This affects the dynamics in these tissues and inhibits the accumulation of mutations. Mutations arising in primitive cells can lead to long lived or even persistent clones, but mutations arising in further differentiated cells are short lived and do not affect the organism. Both the spatial structure and the hierarchical structure can be modeled mathematically. The effect of spatial structure on evolutionary dynamics is non-trivial and depends on the precise implementation of the model. Hierarchical structure can delay or suppress the dynamics of cancer. While these models can lead to important conceptual insights, fitting these models directly to data remains challenging. However, closely related models have the remarkable property that they can make a prediction with data obtained from a single measurement.

References:
Werner et al., “Dynamics of Mutant Cells in Hierarchical Organized Tissues”, PLOS CB (2011)
Hindersin & Traulsen, “Most Undirected Random Graphs Are Amplifiers of Selection for Birth-Death Dynamics, but Suppressors of Selection for Death-Birth Dynamics “ PLOS CB (2015)
Werner, Beier et al., “Reconstructing the in vivo dynamics of hematopoietic stem cells from telomere length distributions”, eLife (2016)