Department of Mathematics, UCI

I'll begin by describing our recent attempts to model the evolution of crypts in the colon, using methylation patterns as markers [see Yatabe et al.]. Mutations in colon crypts are thought to play an important role in pre-tumor progression, and therefore in understanding the time to cancer. One common complaint about such multistage and multihit models is that they require unrealistically high mutation rates to explain the observed incidence of cancer. I'll use our model, together with classical extreme value theory, to show that we can explain the SEER incidence data for colon cancer using typical mutation rates [Calabrese et al.]. A number of corroborative datasets and open problems will be discussed.