Understanding the role and regulation of a tumour suppressor's oscillatory gene expression in cancer cell plasticity

Advances in breast cancer treatment mean that more patients survive cancer than ever before. However, in estrogen positive (ER+) breast cancer, the most common type of breast cancer, some patients either develop resistance to anti-estrogen therapies during the treatment itself or relapse after the end of treatment. Developing resistance to therapies means earlier mortality due to treatment failure while relapse means cancer-related loss of life a few years after the treatment regime is over. Relapse occurs due to the re-awakening of some cancer cells, which become dormant and are not targeted by conventional cancer therapy.

Cell plasticity is cellular phenomenon whereby cells show reversible transitions between cell states may underlie the problems of cells becoming resistant to the current therapies, and also their entry into and the exit from dormancy. But how do cells acquire such plasticity? Our hypothesis, based on our work on neural stem cells, is that cancer cell plasticity is caused by an underlying fluidity in the dynamics of gene expression. This fluidity, which can manifest itself as oscillatory gene expression, is an inherent property of some gene expression networks that are based on negative feedback, biological delays and instability of molecular components. Using these criteria in a bioinformatic screen, we have identified and validated novel oscillatory genes in a breast cancer context.

In this project, we aim first, to understand how dynamic gene expression of a key oscillatory gene that we have identified, the repressor element 1 silencing transcription factor (REST). REST is already known as a tumour suppressor but the dynamic propertied of its expression have not been studied before. We will examine whether and how dynamic REST expression leads to the creation of different cellular states within a tumour. Then, we aim to manipulate the dynamics of expression of that gene with new technologies in order to lock cells in a desired state, for example preventing dormancy or preventing exit from dormancy. Intuition and biological methods are not enough to understand complex dynamic behavior therefore we will use a combination of cutting-edge experiments and mathematical theory.