There are many researchers in Cambridge and beyond working in all aspects of early detection research and we are proud to say that our highly multidisciplinary Programme is engaged with many of them. The groups highlighted below are those that have been established by our Programme, fully devoted to early detection and based in the Hutchison Research Centre.
Jamie Blundell’s lab works on understanding how mutant clones arise, expand and compete in our tissues as we age. Focusing predominantly on blood, we use novel genetic lineage tracking tools and deep sequencing of longitudinal samples to identify mutant clones which are under strong positive selection. Such clones are implicated in early cancer and thus are candidates for improved cancer detection.
Harveer Dev’s lab explores mechanisms of genome instability in early stage prostate cancer, in order to improve the detection and treatment of patients with lethal disease. We use high-throughput genetic screening approaches and surgically-derived early disease models to explore DNA damage response pathways in prostate cancer. This allows us to identify critical genetic drivers, and hence biomarkers, of disease progression and therapeutic responsiveness, providing opportunities to deliver personalised therapies to patients.
Using genetic and epigenetic alterations found in early prostate cancer Charlie Massie's uro-oncology early detection lab will create assays for sensitive detection and quantification of cell-free tumour DNA and develop molecular prognostic scores to help stratify early stage prostate tumours. More accurate risk stratification will spare men with indolent disease from the risks of unnecessary over treatment, and allow more targeted interventions in men with high-risk disease. Click here for the latest updates on ctDNA and liquid biopsy.
Serena Nik-Zainal's lab studies the physiology of mutagenesis, combining computational approaches with experimental and cancer data. The insights gained through Big Data analysis and experiments in cell-based systems has led to the development of clinical algorithmic tools that should translate into clinical utility in the near future.
The Shehata group focuses on understanding the dynamics of normal breast stem and progenitor cells and how errors in these cells lead to breast cancer. We use patient derived organoid models to make ‘mini-breasts’, which recapitulate many aspects of normal breast tissue. This allows us to study how pre-cancerous mutations in luminal progenitor cells from either genome edited or germline patient organoids changes cell fate leading to cancer. Our organoid models enable identifying the mechanisms influencing breast cancer initiation and providing biomarker development for the early detection of breast cancer.