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Supervisor: Thomas Jacques, Darren Hargrave
Project Description:
Background:
Tumours are the most common cause of death in children, and amongst survivors, there is a high risk of disability later in life. These long-term outcomes arise, in part, from the aggressive treatments required. Tissue-based diagnosis is essential because it predicts outcomes, determines treatment, and guides germline testing. If it can be done accurately, it maximises the chance of survival while minimising the late effects. High throughput genomics is used routinely within the NHS, including Whole Genome Sequencing (WGS). This means that for every tumour there is a wealth of genomic data. Previous work from our lab has focussed on methylation profiling in childhood brain tumours using real-world data and found that routine methylation profiling refined diagnosis above standard techniques in approximately a third of all children and modified treatment in 4 to 10%. More recently, we have analysed the genomic data held within the Genomes England Research Environment from the 100,000 Genomes project. This has allowed us to analyse in-depth, WGS from both the germline and tumour from nearly 400 children and young people with solid tumours. This data has, not only allowed us to start to understand the diagnostic impact of this technique, but we have also started to delineate genetic predispositions to childhood tumours. This data is now being supplemented by the many patients being offered WGS as part of the NHS Genomics Medicine Service.
Aims/Objectives:
This project aims to determine the impact of genomic testing on childhood tumour diagnosis and to use the extensive data in the WGS programme to identify novel drivers, germline predispositions and modifiers of childhood tumours.
Methods:
The student will analyse WGS data with the research environment Genomics England building on our existing data (from the 100,000 Genomes project) and extending it to include the large additional data available through the Genomics Medicine Service. They will build on the pipelines that our laboratory has developed to analyse the somatic and germline small variant and structure findings within these cases.
Timeline
- Year 1: Training in the use of the research environment and annotation, and analysis of the GMS data.
- Year 2: Analysis of the broad landscape of the GMS and 100,000 genomes data, focussing on germline predisposition, provisionally in brain tumours.
- Year 3: Validation of findings and writing up.
References:
1. Stone T.J., …, Hargrave, D., Jacques, T.S. (2023) DNA methylation‐based classification of glioneuronal tumours synergises with histology and radiology to refine accurate molecular stratification Neuropathology and Applied Neurobiology 49(2):e12894. doi: 10.1111/nan.12894.
2. Stefan M … Alaggio, R. (2022) A Summary of the Inaugural WHO Classification of Pediatric Tumors: Transitioning from the Optical into the Molecular Era Cancer Discovery 2(2):331-355 doi: 10.1158/2159-8290.CD-21-1094.
3. Pickles, J.C., …, Jacques, T.S. (2020) The impact of molecular profiling on CNS tumour diagnosis and treatment: A paediatric population-based study The Lancet Child and Adolescent Health 4(2):121-130
4. Trotman, J., .. Tarpey, P. (2022) The NHS England 100,000 Genomes Project: feasibility and utility of centralised genome sequencing for children with cancer British Journal of Cancer 127(1):137-144. doi: 10.1038/s41416-022-01788-5
Contact Information:
Tom Jacques