One in two adults will be diagnosed with cancer in their lifetime.

This dismal statistic means that preventative measures are desperately needed to reduce cancer risk and incidence. Our research has recently shown that the lifelong risk of cancer in young mice is significantly lower compared to adult mice, an observation that suggests that during a time of rapid growth, there are biological mechanisms that actively protect against cancer formation, and this is lost in adulthood. If we can understand this protective mechanism, we could reactivate them in adults as a way of reducing cancer risk.

To get to the heart of the protective mechanism we have built an epigenetic, transcriptomic and proteomic atlas of mouse stem cell ageing. Using natural language processing and other machine learning approaches, we are understanding the process of ageing in a completely holistic and agnostic way. This approach is unlocking the biological mechanisms that are unique to the process of development and therefore the processes that protect against cancer.

By perturbing this biology in our adult animal models of cancer through our target discovery approach, we aim to reduce cancer risk in adults and therefore identify mechanisms that will be taken into the clinic as an approach to reduce the risk of cancer in adults.