We study the genetics of cancer initiation and development from healthy tissue, as well as using computational and experimental approaches to analyse therapeutic responses.
Our research builds upon the idea that cancer results from cellular and genetic disruptions and, although the faulty genes that lead to cancer differ functionally, they share properties that are not detectable when studying each gene individually. We use computational biology to characterise these distinctive properties in the context of genome evolution and tumour progression. Understanding the properties of genes that drive cancer, especially in individual patients, or even single tumours, allows us to predict new genes that underlie cancer development for improved treatment and early tumour detection.
We also aim to understand how genetic alterations within tumours affect their function using high-resolution tissue imaging and single-cell data. We look at changes in the DNA blueprint itself (genomic data) as well as the parts of the DNA that provide instructions for turning that blueprint into proteins (transcriptomic data).
Our work is revealing a deeper understanding of how alterations occurring in individual cancer cells fuel the evolution of the whole tumour and its surrounding tissue microenvironment, pointing us toward potential targets for the development of new, more effective cancer therapies.