Regulatory circuits central to RUNX1 function in developmental haematopoiesis and leukaemia
Lead Research Organisation:
University of Oxford
Department Name: RDM Radcliffe Department of Medicine
Abstract
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 (MLL-FPs). MLL-FPs are a major cause of poor prognosis infant acute lymphoblastic leukaemias (ALLs) and 34% of total paediatric ALLs, and these leukaemias are generally incurable. The MLL-FP mutation alone is sufficient to drive leukaemogensis, but it is not known how MLL-FPs disrupt normal development and cause leukaemia. Recent work in our lab has identified RUNX1 as a key gene target regulated by MLL-FPs. RUNX1 is essential for the emergence of HSCs during normal haematopoieisis. Using cutting edge imaging techniques as well as network analysis, we want to develop a model of RUNX1 dependent HSC emergence and then determine how MLL-FPs alter this process. The eventual goal of this project will be to better understand how MLL mutations impact the stochastic nature of gene regulation and normal versus leukaemic development. This will require not only detailed molecular analysis, but also require interdisciplinary work with a lab adept at mathematical modelling. The project has an ambitious goal and if successful it will impact Information and communication technologies by developing an imaging and informatics platform to support this type of single cell analysis. In addition, although it is not a purely mathematical sciences-based project, it will require modelling of alterations in transcription patterns and thus impacts biological informatics as well as mathematical biology. Projects such as this will be instrumental in better understanding how targeted therapies can specifically impact cancers on the molecular level, and potentially aid in novel drug development.
Organisations
Publications
Title | A computational approach for integrating RNA-seq and ChIP-seq data to create a gene regulatory network, and subsequent analyses |
Description | This is a GitHub page collecting scripts we have used to generate gene regulatory network models, and their subsequent analyses |
Type Of Material | Data analysis technique |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | This analysis approach has been used to develop networks in different contexts, and has aided interpretation of existing datasets within the group. |
URL | https://github.com/JoeHarman/MLLAF4-GRN_paper_2021 |
Description | Poster presentation at RUNX-2019 conference, Seoul |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Attended the RUNX-2019 conference in Seoul. Made and presented a poster describing preliminary results to fellow scientists working on RUNX1/2/3. This generated interest in the data. |
Year(s) Of Engagement Activity | 2019 |