What we do
Research
We measure and model how cells in our tissues accumulate mutations, compete and are selected in a Darwinian evolutionary process critical to cancer — turning sequencing data into a quantitative picture of cancer evolution, from normal tissues to the earliest lesions to metastasis and drug resistance. Our projects span three central themes in the lab.
Non-invasive tracking of evolutionary dynamics
Most of what is known about cancer evolution comes from single snapshots of disease. We track evolution longitudinally through time, over many years, using non-invasive samples that can be collected readily and repeatedly from patients or healthy participants. For example, we have used circulating tumour DNA (ctDNA) from the blood plasma of lung cancer patients to track clones as they rise and fall in response to treatment, in the TRACERx and DARWIN II studies with Prof Charles Swanton and Dr Crispin Hiley. This reveals the tempo of evolution that a single biopsy cannot. Alongside plasma, we are applying our approaches to several other non-invasive sample types, leveraging methods we have recently developed to make these measurements with ever more accuracy and across a wider range of clinical contexts.
Somatic selection: tissue ecology & spatial genomics
Understanding what drives cellular evolutionary dynamics is critical to designing appropriate clinical interventions, such as preventive therapies. Both intrinsic and extrinsic influences on the cell play a critical role in shaping somatic evolution, as they do for individuals in an ecological habitat. We are developing spatial co-DNA and RNA sequencing approaches to define somatic clones within tissues alongside their microenvironment and architecture, to better understand the drivers of both positive and negative selection throughout cancer initiation, development and drug resistance.
Evolutionary biomarkers for the clinic
We focus on understanding human disease by extracting novel insights from samples collected in the clinic, which naturally leads to insights ripe for clinical translation. In particular, non-invasive, low-morbidity sampling is ideally suited to screening healthy or at-risk populations to predict future cancer development or detect undiagnosed disease. However, these sample types are typically highly impure and so require novel technologies to extract clinically meaningful disease signal. We drive these biomarkers forward in partnership with our clinical collaborators and industry, for example in the BEST4 study of oesophageal premalignancy using the capsule sponge device, with Prof Rebecca Fitzgerald and Cyted.
