Using State Space Exploration to Determine How Gene Regulatory Networks Constrain Mutation Order in Cancer Evolution

Cancer develops via the progressive accumulation of somatic mutations, which subvert the normal operation of the gene regulatory network of the cell. However, little is known about the order in which mutations are acquired in successful clones. A particular sequence of mutations may confer an early selective advantage to a clone by increasing survival or proliferation, or lead to negative selection by triggering cell death. The space of allowed sequences of mutations is therefore constrained by the gene regulatory network. Here, we introduce a methodology for the systematic exploration of the effect of every possible sequence of oncogenic mutations in a cancer cell modelled as a qualitative network. Our method uses attractor identification using binary decision diagrams and can be applied to both synchronous and asynchronous systems. We demonstrate our method using a recently developed model of ER-negative breast cancer. We show that there are differing levels of constraint in the order of mutations for different combinations of oncogenes, and that the effects of ErbB2/HER2 over-expression depend on the preceding mutations

The ecology of cancer

Neoplasia, the disease of multicellular organisms, is not only a major cause of human death worldwide but also affects numerous invertebrate and vertebrate species. Similar to other diseases, cancer is a significant physiological burden on the host and hence not only impacts the individual but also influences interindividual interactions, populations and consequently global ecosystems. Despite this, oncology and other biological sciences such as ecology and evolution have until very recently developed in relative isolation. To overcome this caveat, we draw parallel between invasive species and the metastatic cascade and provide an overview of the ecology of cancer at the scale of the organisms and the ecosystems of malignant cells (both at the micro- and macro-scales). We discuss the drivers of metastatic formations in the tissue environment and investigate how individuals respond to malignant growth and the impact of this response on populations. Finally, we provide potential avenues for applying evolutionary ecology principles to cancer prevention and to the development of novel treatment strategies