Understanding and manipulating epigenetics in cancer

Abstract

The appropriate regulation of gene expression programs is essential for normal cellular function. In cancer, mutations derail normal developmental gene expression programs resulting in a malignant epigenetic state. Traditionally, therapies have attempted to kill cancer cells by targeting rapid proliferation or by directly disrupting the mutated protein. More recent therapies, such as BET inhibitors, attempt to directly target the oncogenic epigenetic state. All of these therapeutic approaches are frequently hampered by the emergence of drug resistance. In many cases, resistance is acquired through genetic changes. However, there is increasing evidence that drug resistance can also arise through non-genetic/epigenetic mechanisms. This has major implications for cancer treatment, as the processes that drive genetic and non-genetic resistance are completely different and epigenetic changes, unlike genetic changes, are potentially reversible.

Our laboratory previously generated a model of non-genetic resistance to BET inhibitors in acute myeloid leukaemia (AML). Resistance coincided with the acquisition of a less differentiated stem cell like phenotype and was stable upon drug withdrawal. To discover targets that can overcome the resistant epigenetic state, I performed a focused CRISPR-Cas9 screen, which identified the enhancer regulator, LSD1, as key to maintaining the resistance phenotype. Treatment with an LSD1 inhibitor overcame resistance through time-dependent reprogramming of the resistant cells. This epigenetic reprogramming resulted in both differentiation and the formation of new enhancers around critical BET inhibitor target genes. Through functional genomics experiments, I demonstrated that re-sensitization of the resistant cells was driven by the new enhancer formation, rather than differentiation. Mechanistically, the enhancer remodeling is caused by upregulation of Irf8, which together with the pioneer factor, Pu.1, initiates the formation of new enhancers around BET inhibitor target genes, leading to a restored BET inhibitor transcriptional response.

Motivated by the poor clinical responses and rapid acquisition of resistance to BET inhibitors in AML, I also sought to develop an assay that could identify new therapeutic targets that may be more effective. Transcription factors (TFs) are ideal targets, however they are difficult to disrupt directly. To circumvent this, I developed an assay that can identify what cofactors (which are often druggable) are required to drive the transcriptional activity of a given TF. This assay works by combining the Gal4 transactivation system with CRISPR-Cas9 screening. Preliminary screens using the transcription factors, VP64 and MYB, were able to identify previously validated cofactors for each TF. VP64 was dependent on MED25 and MYB was dependent on P300. A number of other potential specific cofactors were identified and will be validated in future work. This assay not only provides the potential to identify novel therapeutic targets, but will also provide insight into the poorly characterized interface between TFs and cofactors.