Quantitative genetic and epigenetic lineage tracing of blood in the decades preceding leukaemia diagnosis
Audience: Member of University - ALL Format: HybridTuesday, 23 June 2026, 9.30am to 10.30am
For our next talk, in the BDI/CHG (gen)omics Seminar series, we will be hearing from Prof. Jamie Blundell, Ursula Zoellner Professor of Cancer Research at the Early Cancer Institute at the University of Cambridge and a UKRI future leaders fellow. We’re delighted to host Jamie in what promises to be a great talk!
Date: Tuesday 23 June
Time: 9:30 am – 10:30 am
Talk title: Quantitative genetic and epigenetic lineage tracing of blood in the decades preceding leukaemia diagnosis
Location: Big Data Institute, Seminar Room 0
Abstract
Many human tissues are maintained by large numbers of long-lived stem cells. Positive and negative selection on somatic mutations that occur in these stem cells can drive rapid evolution in human tissues over timescales of years to decades with important implications for future cancer risk. Blood is an ideal system for gaining a quantitative understanding of these dynamics because it is easily sampled, less spatially structured relative to other tissues and genomically well characterised. Here I will describe work that exploits unique collections of serial blood samples from people destined to develop future blood cancers to reveal quantitative insights into this evolutionary process. By performing high resolution lineage tracing of genetic and epigenetic marks we can time the key driving events in the evolution of Acute Myeloid Leukaemia, estimate fitness effects of clones throughout the full disease trajectory, and characterise competition between clones. These data shed light on the evolutionary dynamics occurring in pre-cancerous stem cells and suggest that many aspects of the observed dynamics can be understood within a surprisingly simple framework of clonal evolution with competition
Bio
Jamie is the Ursula Zoellner Professor of Cancer Research at the Early Cancer Institute at the University of Cambridge and a UKRI future leaders fellow. He obtained his PhD in theoretical physics at Cambridge before moving to Stanford to undertake postdoctoral research in quantitative biology with Daniel Fisher and Dmitri Petrov in which he developed new ways of measuring and clonal evolution. He established his lab in Cambridge in 2017 with a focus on the somatic evolution that occurs in healthy tissues as we age and how this evolution is altered at the earliest stages of cancer. The lab also has an active interest in quantitative immunology particularly in T-cell antigen recognition.
Speaker(s): Professor Jamie Blundell (University of Cambridge)
Series: BDI/CHG Genomics seminar
Venue:
Big Data Institute - Lower Ground Seminar Room 0
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Lower Ground Seminar Room 0 Big Data Institute Old Road Campus Oxford Oxfordshire OX3 7LF United Kingdom
Department: Big Data Institute - NDPH (Unit)
Organiser: Sumeeta Maheshwari
Host: Prof Thomas Nichols
More info:
All members of the University are welcome to join, please let reception at BDI know you’re here for the seminar and sign-in. We hope you can join us!
We also now have a mailing list –
To be added, ping genomics_bdi_whg-subscribe@maillist.ox.ac.uk (with any message), you should get a bounce-back with three options to confirm your subscription. Follow any of those options, and with a bit of luck you should be signed up!
As a reminder, the (gen)omics seminar series runs every other Tuesday morning and is intended to increase interaction between individuals working in genomics across Oxford. We encourage in-person attendance where possible. There is time for discussion over, tea, coffee and pastries after the talks.
Hybrid Option: Please note that these meetings are closed meetings and only open to members of the University of Oxford to encourage sharing of new and unpublished data. Please respect our speakers and do not share the link with anyone outside of the university.
Microsoft Teams meeting
Join: https://teams.microsoft.com/meet/367401229776497?p=TdvkO5YozJFAsvkBt5
Meeting ID: 367 401 229 776 497
Passcode: Sn2pH3vT
