Obesity has emerged as a socially prominent risk factor for cancer-related death, but a clear understanding of the underlying molecular mechanisms is lacking. We and others have demonstrated that a specific type of leukemia, Acute Promyelocytic Leukemia (APL), is heavily influenced by the systemic metabolic state (Breccia et al Blood 2012 and unpublished data). APL is well modeled in the mouse, and we have devised experimental setups that very well reproduce the effect of systemic metabolic alterations (high fat diet and caloric restriction) on the natural history of APL. We are now using this experimental setting to delve more deeply into the mechanism. Two main bioinformatics-intensive projects are ongoing:
-using whole genome sequencing of cellular genomes to measure single-cell mutational history. We wish to evaluate intra-individual mutational variability to understand if diet can modulate the rate of mutation acquisition
-using ChIP-seq, RNAseq and metabolomics on mouse APL samples to identify epigenetic changes associated with metabolic adaptation to diet modification, a process that we have seen is highly susceptible to pharmacological targeting.
The candidate is expected to implement comprehensive bioinformatics analysis and to also integrate with other ongoing research projects in the group.