Title: Inference for stochastic processes in cancer evolution


Speaker: Simon Tavaré

Date: August 14
Time: 11:10 - 12:10
Room: Ballroom C

Chair: Ziheng Yang


Abstract: Each tumour evolves as a population of cells within its host. At a simplistic level, it is mutations in the DNA of the tumour cells that govern the way the tumour evolves. As a result, ideas from molecular population genetics may be used to study the properties of this evolution, particularly with respect to origination, growth, metastasis and relapse. In this talk I will describe some stochastic models that have been developed to study tumour evolution, including cellular Potts models and their relatives. With the advent of cheap DNA sequencing it is now possible to identify mutations in tumour cells, thus begging the question about how inference about tumour evolution might be performed.

After outlining the basic biology and aspects of ancestral inference, I will describe how Approximate Bayesian Computation methods can be used to estimate relevant biological parameters, and I will illustrate the methods with examples from glioblastoma and colorectal cancer.

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