A single cell analysis of MLL-AF4 leukaemias

Supervisor: Professor Thomas Milne

There has been much progress in treating human cancers, especially leukaemias, but most remain resistant to treatment. A potentially exciting approach is the development of small molecule inhibitors that specifically target aberrant processes in cancer cells but leave normal cells unharmed. In order to be successful, such an approach requires highly detailed information about normal and aberrant cellular processes on the molecular level, including better understanding the heterogeneity of leukaemia samples in patients.

Chromosome translocations of the Mixed Lineage Leukaemia (MLL) gene fuse the N-terminus of MLL in-frame with over 60 different partner genes producing novel MLL fusion proteins. The MLL-AF4 fusion protein is a major cause of poor prognosis infant acute lymphoblastic leukaemias (ALLs) and 34% of total paediatric ALLs. MLL-AF4 leukaemias are associated with very few cooperating mutations and this along with its relatively short latency suggests that MLL-AF4 alone is sufficient for leukaemic transformation. MLL-AF4 is thought to promote leukaemogenesis by activating key target genes, but it is not known if there exist different subsets of leukaemia clones in patients.

Recent work in our lab has identified several key gene targets regulated by the MLL-AF4 fusion protein. Using cutting edge techniques such as REAP-seq and ATAC-seq this project is designed to determine the clonal structure of human patient samples and to determine if key target genes are expressed in all MLL-AF4 leukaemia cells. The eventual goal will be to use information from this project to rationally design drug combinations that can be tested and eventually used in human patients.


Training Opportunities
Interdisciplinary by design, this project will involve interactions with multiple labs in the WIMM and will use a broad range of cutting edge technologies. This includes state of the art techniques for the analysis of gene regulation (e.g. ATAC-seq), and single cell transcriptome analysis as well as computational biology. Training will be specifically provided in the use of basic bioinformatics pipelines, with the opportunity to further expand this knowledge base depending upon interest.

For further information please contact Prof Tom Milne