WE Combine evolution, mathematics and genomics to understand how cancers evolve
Cancer develops through an evolutionary process in which genetic and epigenetic changes accumulate in our tissues. The first steps of this evolutionary path to cancer occur in healthy tissue decades before cancer onset. This raises the possibility of using these early events as a bellwether for predicting who is most at risk of developing cancer and possibly intercepting it. However, at present, we are unable to reliably identify which mutant clones will progress to lethal cancers.
Serial blood samples collected annually from hundreds of thousands of initially healthy people give us a unique ability to study evolutionary dynamics of tissues in vivo. By “zooming in” on the people who develop cancer, we can “rewind” time by analysing blood samples collected years before the cancer was diagnosed. By analysing these data using mathematical techniques from evolutionary theory and population genetics, we aim to identify the clones that are most likely to progress to lethal cancers in order to intervene before cancer develops.
clonal haematopoiesis and LeukAemia risk from longitudinal samples
We make ~5,000,000 new blood cells each second. To achieve this, haematopoietic stem- and progenitor-cells (HSPCs) must constantly divide. Throughout our lifetimes, therefore, our populations of HSPCs evolve: accumulating genetic alterations, some of which cause clonal expansions. Certain expansing clones are known to increase your risk of developing a subsequent blood cancer, and hence are thought to be the earliest events in this process. We are studying this by performing ultra-deep sequencing on longitudinal blood samples collected over decade-long timescales from the UKCTOCS study to quantitatively understand the earliest stages of cancer evolution.
People: Caroline Watson, Gladys Poon, Hamish MacGregor
Papers & preprints: Mutation rates and fitness consequences of mosaic chromosomal alterations in blood Watson et al. Science 2020; Watson et al. Nature 2023; MacGregor et.al. bioRxiv 2023; Poon et. al. bioRxiv 2023
Collaborators: Usha Menon (UCL), Daniel Fisher (Stanford), Todd Druley (Wash U)
Methylation DYNAMICS IN ageing and early cancer
Epigenetic changes play a key role in the development of many cancers. We are studing how changes in DNA methylation arise during the development of cancers and how this differs from methylation changes that are known to occur during ageing. To study this we use serial blood samples collected annually from healthy people and from people who go into develop a known cancer diagnosis. Most of our work here has focussed on the blood cancer AML where many of the known early driver mutations are in epigenetic regulators such as DNMT3A, TET2 and IDH1/2. Using these unique collections of clinical blood samples we perform state of the art targeted methylation sequencing techniques (deep EM-seq) to look into how methylation profiles are dysregulated in the earliest stages of disease. We are also interested in using phased long-read methylation sequencing to build phylogenies from tissue samples.
People: Adriana Fonseca, Amanda Tan, Yuexuan Zhang
Papers & Preprints: coming soon!
Collaborators: Usha Menon (UCL), Hisham Mohammed (OHSU), Paul Spellman (OHSU)
Mathematical Modelling of clonal dynamics in “Healthy” tissues
The fate of a new mutation depends on the evolutionary forces of mutation, genetic drift and selection. In both normal and cancerous tissue evolution, the relative roles of each of these forces remains controversial. How much of the somatic evolution we observe is due to chance or effect? This project aims to address these questions by making quantitative predictions of mutation frequencies under different evolutionary scenarios and comparing these predictions to available data. These models will provide a rational basis for detecting abnormal clones. One particular focus at the moment is on what can be learned from the spectrum of silent mutations (e.g. synonymous variants) in healthy tissues and the phenomenon of genetic hitchhiking: whereby silent mutations are dragged to high variant allele frequencies by virtue of a linked “beneficial” mutation.
People: Gladys Poon, Matthew Bradley
Papers & Preprints: Poon et al. Nature Genetics 2021
Collaborators: Diana Fusco, Daniel Fisher
TCR repertoire DYnamics in cancer
Adaptive immune cells (including T- and B-cells) do not share the same DNA sequence as the rest of our cells. They shuffle a specific part of their genome to generate a diverse set of sequences that code for surface receptors that are used to recognise foreign antigens. An individual’s T-cell receptor (TCR) repertoire (i.e. the set of all their TCR sequences) therefore records information about what antigens an individual has been exposed to through infectious diseases and cancers. As tumours develop, neo-antigens on the surface of the tumour cells are recognised by T-cells, causing changes in the TCR repertoire. This cancer-specific signal may be detectable years before traditional diagnosis. We are analysing TCR repertoires in cancer-cases and controls to determine whether statistical differences exist and how early these differences arise. This research is kindly supported by a multi-centre ACED Immunology Programme grant.
People: Iñigo Ayesteran, Jinqi Fu, Sam Hackett
Papers & Preprints: Ayestaran et al. bioRxiv 2022
Collaborators: Elizabeth Soilleux, Doug Easton, Richard Mair