Connecting Myc to transcriptional regulation through cyclin-dependent kinases

Myc proteins are transcription factors that markedly alter gene expression through both activation and repression of transcription. There are three Myc protein family members in humans (c-Myc, N-Myc, L-Myc). These are among the most frequently dysregulated proteins in human cancer, and understanding their functions at a molecular level is critical for the development of new treatments. Elegant studies in mouse models of cancer have validated the inhibition of Myc as a therapeutic strategy, but efforts to develop clinical compounds that target Myc proteins directly have failed. This is because Myc proteins have intrinsically disordered structures and are therefore lacking in stable surface features to target with small molecules. Instead, we believe that Myc is best targeted through blocking the protein-protein interactions between Myc and other factors that drive oncogenic gene expression.

This project aims to characterize the interaction between Myc and P-TEFb at a molecular and cellular level. P-TEFb is a complex of CDK9 with Cyclin T1 that drives transcriptional activation through release of the elongation pause state of RNA polymerase II. Inhibitors of CDK9 are under investigation as potential cancer therapeutics in Myc-driven cancers. However, clinical development of these inhibitors is hampered by our lack of understanding of the molecular mechanisms of CDK9 function in transcription, and the challenge of developing highly selective CDK9 inhibitors.

The project will investigate the effect of Myc binding on P-TEFb catalytic activity and inhibition by CDK9 inhibitors, and elucidate the structure of the complex between Myc and P-TEFb. Cell-based assay will also be established to determine the localisation and cell-cycle regulation of the interaction, use this to validate their biochemical and structural studies, and explore factors that regulate the interaction. Finally, the consequences of disrupting the Myc/P-TEFb interaction on transcription will be assessed using Omics approaches.