Cancer is typically a disease of old age. As our cells grow and divide throughout our lifetime, errors are introduced to their DNA, some of which can be harmful. Over time, these harmful errors (termed “mutations”) can build up, leading to the development of cancer. By comparing the DNA from a cancer to DNA from healthy cells of the same patient, it is possible to identify the mutations that accumulated in the cancer cells.
Applying computational tools to these mutations, we can establish the order in which mutations were acquired, and approximately when they were acquired during a patient’s lifetime. Furthermore, we can infer what caused the mutations (for example, smoking, UV light, etc.), and estimate when the cell was exposed to these damaging processes. Across many cancer samples, this approach lets us build a picture of how different cancers evolve over time.
Previously, we have used these computational methods to study the evolution of primary tumours (i.e. the tumour at the original site, observed at diagnosis) over time. In this project, we seek to understand the development of cancer as it spreads from the initial site to another site (known as metastasis). This is particularly important, as metastasis is responsible for 90% of cancer deaths.
We will compare mutations, and their causes, across metastatic cancers from different sites in the body to learn about how cancers adapt to new locations. We will also reconstruct timelines of cancer evolution for the metastatic samples, and compare these to timelines for primary tumours. This will show whether tumours that metastasise evolve in the same way as non-metastatic cancers, and may give insight that helps to predict the metastatic step in cancer evolution.
Peter van Loo, The Francis Crick Institute, United Kingdom