Stopping ‘cut-and-run’ DNA errors to help treat leukaemia and predict relapse
Towards inhibiting cut-and-run: An aberrant V(D)J recombination reaction that leads to lymphoid cancers
Next generation molecular profiling of malignant rhabdoid tumours
Identifying which are the cellular molecules that drive growth and spread of rhabdoid tumours, and to use this information to nominate new treatment strategies and develop real-time diagnostic tests for personalising treatment
Improving the outlook for children with Philadelphia positive ALL
Unravelling clinical heterogeneity in Philadelphia positive ALL
Mapping drug targets in aggressive non-Hodgkin lymphoma
Investigation of potential therapeutic targets in paediatric aggressive B-cell non-Hodgkin lymphoma - towards kinder, more effective treatments
"Getting it right first time" for children with renal tumours
Improving prediction of relapse, treatment delivery and outcomes for children with renal tumours in the UK
Can we prevent leukaemia in children?
Modelling prophylactic (microbial) prevention of childhood acute lymphoblastic leukaemia
Investigating the genetic pathways that control leukaemia growth
RNA helicase DDX3X regulates JAK-STAT signalling in acute lymphoblastic leukaemia
Using digital technology to improve our understanding of rhabdomyosarcoma
Deep learning: An integrated approach to define clinical significance to components of the tumour microenvironment of rhabdomyosarcomas
Can we identify an 'ultra-high-risk' type of neuroblastoma?
A pilot study of expression profiling using RNAseq from formalin fixed neuroblastoma and paired diagnostic and relapsed frozen neuroblastomas.