Hypermutation as a driving force for cancer: Is there an error threshold for cancer cells?

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DNA polymerases epsilon (POLE) and delta (POLD1) are essential for DNA replication. In addition to their polymerase capability, these enzymes have 3’-exonuclease proofreading activity, which ensures that the correct base has been incorporated on the new, growing DNA strand. Germline and somatic POLE mutations affecting polymerase proofreading are established drivers of carcinogenesis. The POLE mutations cause increased base substitution mutations in all dividing cells and thus ought to be found in many cancer types. However, the mutations are strongly associated with cancers of the bowel and uterus, for reasons that remain largely unclear. Each tissue has distinct roles, needs, and vulnerabilities; thus, it has evolved specific mechanisms and pathways for detecting, repairing, and responding to DNA damage.

One reason for the tissue specificity of POLE mutations could be that some tissues or cells can tolerate much higher mutation burdens than others. This project will investigate several aspects of POLE-driven tumorigenesis based on underlying principles of cancer evolution. One exemplar project is to explore the notion that there is a limit to the number of mutations a cell can tolerate. In POLE mutant cancers, over 1,000,000 base substitution mutations can occur, indicating a high level of tolerance.

We will construct genetic mouse and cell models with even higher mutation rates (e.g. defects in polymerase proofreading and base excision repair) to determine the effects on cell viability and underlying mechanisms. These analyses will be supported by analysis of large-scale sequencing data from human cancers. We will thus determine whether there is a limit to mutational burden in different cells and tissues. The results will have importance for cancer treatment, since some current therapies may work in part via hypermutation at the level of the DNA base.

Training Opportunities

The DPhil candidate will receive training on a broad variety of techniques including:

Collate, manipulate and analyse genomic and clinical data from human cancers, in association with experienced post-doctoral scientists, thus gaining skills in bioinformatics, statistics and manipulation of large data sets
Develop and test conceptual models of how cancers evolve, and the therapeutic vulnerabilities that accrue as a result
Acquire skills in molecular analysis and histopathology of human and mouse tumours
Acquire skills in tissue and cell culture
bioinformatics and biostatistics related to the project.