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
We have been funding expert research since 2016, aiming to ensure that every child and young person has a safe and effective treatment for their cancer, and that they can live long and happy lives post-treatment.
Deep learning: An integrated approach to define clinical significance to components of the tumour microenvironment of rhabdomyosarcomas
Targeting mutant NRAS in paediatric AML
The use of proton beam therapy to improve outcomes in childhood abdominal tumours
Development of a paediatric version of the Sarcoma Assessment Measure (SAM-Paeds): a specific tool for assessing quality of life in children with sarcoma
Repurposing of drugs targeting drug resistant self-renewing Ewing’s sarcoma cells to accelerate new treatments into clinical trials to improve outcomes.
RNA helicase DDX3X regulates JAK-STAT signalling in acute lymphoblastic leukaemia
Modelling prophylactic (microbial) prevention of childhood acute lymphoblastic leukaemia
Teenagers and young adults with primary CNS cancers: a systematic biological characterisation
RNA‐sequencing to characterise malignant rhabdoid tumour heterogeneity: a pilot study in archival frozen material