Traces of selection: cellular heterogeneity in the tumor microenvironment

Our quest to develop comprehensive mathematical and experimental models of somatic and tumor evolution hinges on the necessity for advanced tissue and tumor ecology models.

The accumulation of genetic or epigenetic changes over a lifetime is called somatic evolution. This process inevitably occurs in multicellular organisms and can lead to disease development. The conventional dogma of tumor evolution postulates that the observed genomic changes are due to the acquisition of driver mutations that improve cell-intrinsic fitness independent of context. In contrast, increasing evidence suggests that cell-phenotypic diversity and spontaneous changes in the environment lead to context-dependent fitness differences.

The resulting selection is driven by inflammation in the tumor microenvironment or the exchange of growth factors that act as public goods. This environment includes stroma cells, immune cells, and signaling molecules. An important question is how selection in this complex environment leads to disease progression. The tumor (micro)environment provides a powerful adaptive force that codetermines the fate of the disease and could inform treatment options. We integrate biological and clinical data with mathematical modeling to ask how stochastic effects and nonlinear selection dynamics operate in concert to drive disease onset and progression and shape observed cellular diversity. The resulting models can improve our understanding of the roles of selection, temporal variation, and spatial variation during cancer evolution.