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Chapter 3 : Cancer mutation processes

A major area of cancer research involves identifying these mutations and the associated genes/pathways, discriminating them from the larger number of background mutations (passenger/neutral mutations). The data that is widely available to do this is sequence data, samples from a range of tumour types, e.g. the Cancer Genome Atlas (TCGA) and the Cancer Genome Project. A common approach is to identify genes that are mutated at higher frequency — the logic is that mutations in these genes (at appropriate sites) are under positive selection and so will be mutated at a higher frequency in the samples, i.e. significantly above the background rate. However, the difficulty in identifying these driver mutations is the fact that cancers have different mutation signatures, and different mutation rates. In the following, in section 2, we examine how mutation signatures are determined for different cancers. Secondly, in section 4 we examine how driver mutations are detected, illustrated by a basic Binomial model and discuss more advanced algorithms that take into account more varaibles. Thirdly, we present an analysis of mutation accumulation, agreeing with a predominantly neutral evolution model. Finally, in section 6 we examine pathways, and the fact that multiple mutations within the same pathway in a given patient are rare.