Infection-related cancers make up 25% of all cancers world-wide. In particular, Epstein Barr Virus (EBV) causes nasopharyngeal cancer frequently encountered in China and various different types of lymphomas. EBV-driven endemic Burkitt’s lymphoma (eBL) is the most common type of solid childhood tumour in Sub-Saharan East Africa.
Together with our NIH collaborators, (CI: Sam Mbulaiteye), we are leading two major research programmes in epidemiology (EMBLEM) and early diagnosis of EBV-driven lymphomas (AI-REAL) in three countries bordering Lake Victoria.
The aim of this thesis will be to better understand the viral factors that predict the risk for lymphomagenesis by comprehensively analysing EBV DNA sequences taken from EBV positive children with and without lymphoma. Our data from targeted sequencing of eBL tissue biopsies supports the hypothesis that EBV LMP-1 Pattern A may be associated with eBL, but it is not the sole associated variant (Lei H et al, Sci Rep 2015; Liao HM et al, Cancers 2018). Here, we would like to extend this analysis to circulating plasma EBV DNA using whole genome sequencing.
The objectives will be to:
1. Apply recently-described analytical methodologies for EBV whole genome analysis from tissue and plasma including but not limited to EBV strains, sequence variation across the genome, epitope prediction for future vaccination, quantification of viral load, size distribution and sticky end analysis of circulating tumour and viral DNA (fragmentomics). This will be done in collaboration with Prof Dennis Lo, whose group has established the bio-informatics for EBV analysis in nasopharyngeal carcinoma.
2. Explore an alternative analysis approach using oxford Nanopore to perform global methylation analyses of the EBV genome.
3. Compare results with those obtained from 115 cases with EBV-positive PBMC DNA of children living in endemic regions but without lymphoma.
4. Establish a risk score derived from plasma DNA to predict the risk of either getting (or already having) early-stage Burkitt's lymphoma.
The student will be jointly co-supervised by Prof Sam Mbulaiteye (NIH), Dr Kate Ridout (Oxford) and Prof Anna Schuh (Oxford). Day-to-day supervision will be primarily by senior post-doctoral fellows in Oxford in the Schuh group.
Year 1: Introduction into R and at least one computer programming language (3 months). Depending on the COVID19 situation, the candidate will spend at least 3 months at MUHAS in Dar es Salaam where the Schuh group has established a satellite lab that is currently performing EBV whole genome sequencing on relevant samples. The final 3 months of year one will be to learn EBV WGS analysis extracting the different modalities of fragmented EBV DNA described above
Year 2: The different bioinformatics tools will be applied to data sets from two different cohorts living in endemic regions: (1) EBV positive children without lymphoma; (2) EBV positive children with lymphoma. These data sets are already available in Sam Mbulaiteye’s and the Schuh group (NIHR Global Health Programme grant).
Year 3: Summary of analyses (6 months) and writing thesis and first author publication.
Training Opportunities: The student will gain extensive experience in bio-informatics analysis of circulating cell free plasma DNA and of analysis of viral genomes. These are transferrable skills that can be used in a wide range of applications in biology and cancer research, in particular in the field of early cancer detection and cancer vaccine development.
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