Evolutionary dynamics of cancer

Niko Beerenwinkel
ETH Zürich

Cancer progression is driven by mutation and selection in an asexually reproducing population of tumor cells. We present mathematical models for the genetic progression of cancer. A statistical model is introduced to describe the ordered accumulation of mutations in cancer genomes and shown to improve genetics-based survival predictions for patients with renal cell carcinoma. We analyze the evolutionary dynamics of tumor progression using a population genetics approach and derive an approximate closed-form expression for the waiting time to cancer. Finally, we discuss statistical methods for inferring the genetic diversity of tumors from ultra-deep sequencing experiments and compare experimental results to model predictions.

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