Research

Quantitating Somatic Evolution in Cancer

Tumours at diagnosis present with a tremendous amount of intra-tumour genetic heterogeneity. We do now understand that a stochastic somatic evolutionary process of mutation accumulation and selection can explain these patterns. However, it remains difficult to quantify these evolutionary forces within tumours of single patients. One of our main goals is the development of methods that can explain and quantitate these processes. To do so we combine mathematical descriptions of somatic evolutionary processes and cancer genomic data. 


Theoretical Population Genetics

An important aspect of our work is to develop new theoretical tools rooted in population genetics. We often combine stochastic branching processes and individual based computer simulations to explain and quantitate somatic evolutionary processes.  


Resistance Evolution and Treatment Strategies

Exciting new cancer treatments are developed continuously  e.g. novel targeted therapies or Immunotherapy. Unfortunately, emerging treatment resistance remains a major challenge. New strategies, e.g. adaptive therapie, are in early clinical stages. Our aim is to quantitate the process of resistance evolution within single patients. We use ctDNA (cell free tumour DNA) to be able to follow resistance evolution over time, which allows us to quantify forecast relapse times, providing a treatment window of oppertunity. 


Stochastic Dynamics of Extra Chromosomal DNA Elements

Recent studies have identified extra chromosomal DNA elements (ecDNA) to contribute to tumour evolution and resistance emergence. These elements have a random pattern of inheritance and thus the stochastic dynamics of these elements differs greatly from standard somatic evolutionary dynamics. We develop a theoretical understanding of these dynamics and test these predictions in patient data. 


Predator-prey coevolution

We also have an interest in non-somatic evolutionary processes. In particular, coevolutionary processes of interacting species and the resulting stochastic dynamics are fascinating. Our lab has been involved and continuous to work on coevolutionary experiments in a number of predator-prey systems. Questions involve the understanding of the emergence and maintenance of diversity as well as the interpretation of complicated population genetics data under coevolutionary processes. 


© Benjamin Werner 2019