Progress in improving survival from childhood leukaemias has been remarkable. However, in one subtype called Acute Myeloid Leukaemia (AML) outcomes remain poor and about 40% of children still die. Mechanisms of therapy resistance and relapse in childhood AML are poorly understood and investigation has been complicated by molecular heterogeneity, which means large patient cohorts are required to robustly identify cellular and molecular mechanisms of therapy resistance, which may differ within molecularly-defined disease subclasses.
MyeChild was the first international clinical trial for children with AML and enrolled 709 patients across 6 countries. All children had baseline genomic and transcriptomic sequencing performed and sequential cryopreserved samples are available in our laboratory.
Using this baseline information, the PhD candidate will select 3 genomic subgroups of interest. In each group, markers of therapy resistance will be identified by comparison of patients with durable remission against those with relapsed or refractory disease. The overall aim is to define new markers of resistance to use as biomarkers and potential future therapy targets.
In year 1, the student will learn bioinformatic analysis using already generated whole genome and whole transcriptome sequencing data sets, and will begin to generate their own epigenetic profiling data sets using techniques including ATACseq, Cut&Run.
In year 2, the student will generate single-cell data sets (single-cell DNA and RNA sequencing) and learn further bioinformatic methods to analyse these. The student will be focusing on resolving the cellular hierarchies of the malignant myeloid compartment and also the perturbed non-malignant cell populations (e.g. innate / adaptive immune or stromal components) to understand the role of these populations in therapy resistance.
In years 3 and 4 the student will have identified candidate markers of therapy resistance and will validate these in model systems such as cell lines and patient-derived xenografts.