Genomics of Inflammation and Cancer Immunology: inter-individual variation in response to checkpoint inhibitor therapy

We work on characterising inter-individual variation in human immune responses. Checkpoint inhibitor immunotherapy has revolutionised the management of multiple cancers, yet our understanding of how the response to these treatments diverges between patients is limited. We are investigating how factors such as patient genetics, age, sex and coexistent infections (e.g. chronic viral infections) interact with treatment and influence therapeutic outcomes. The project is of interest to a student who wishes to work with large patient derived datasets and use a combination of bioinformatic and immunological techniques.

We have purified multiple cell subsets from 120 patients across various stages of immune checkpoint immunotherapy (ICI) for cancer. We are using bulk and single-cell RNA-sequencing to characterise the main cell-types affected by treatment and determine how responses vary between individuals. We have a range of meta-data relevant to these samples, including radiological and clinical outcomes. In unpublished work we have identified genetic and patient specific factors that influence the magnitude of response. Specifically, we have defined the transcriptomic response to ICI in CD8+ cells across this cohort.

We find that ICI regulates discrete modules of genes in a non-correlated manner. Some of these modules are more activated in patients who show long-term responses to treatment. The transcriptome is under the influence of genetic and epigenetic factors – notably DNA methylation. It is unclear how ICI influences the methylation state of CD8+ T-cells and whether this occurs in similar modules.

Your project would involve exploring:

i) whether ICI modulates DNA methylation
ii) how the baseline methylation state of CD8+ T-cells influences the subsequent transcriptomic response to ICI
iii) identification of methylation signatures of prognostic significance
iv) the influence of other covariates including T-cell receptor repertoire, chronic viral infection and genetics on CD8+ T-cell methylation state

You will be given training in bioinformatics and will gain proficiency in handling large datasets in R. You will similarly be trained in core molecular biology and immunology techniques including multi-colour flow cytometry and single-cell sequencing. You will have access to courses run through the Department of Oncology and have opportunity to present within the department. You will gain experience in working with patient samples and the interface between NHS clinical activity and research.

As well as the specific training detailed above, students will have access to high-quality training in scientific and generic skills, as well as access to a wide-range of seminars and training opportunities through the many research institutes and centres based in Oxford.

All MRC WIMM graduate students are encouraged to participate in the successful mentoring scheme of the Radcliffe Department of Medicine, which is the host department of the MRC WIMM. This mentoring scheme provides an additional possible channel for personal and professional development outside the regular supervisory framework.