Identification of proteins involved in a Novel Mitotic DNA Damage Checkpoint

Cancer and healthy cells rely on conserved Deoxyribonucleic Acid (DNA) damage response (DDR) checkpoints to maintain genomic stability and reduce the chance of mutation. Cancer treatments predominantly function by inducing huge amounts of DNA damage to kill rapidly dividing cells. However, our DNA damage response can potentially lead to resistance to DNA damaging agents due to the total repair of damage induced. For this reason, it is vital that we have a full understanding of how our DNA damage response functions to exploit this for better cancer therapy. While interphase DDR checkpoints are well understood and categorised, mitotic-specific DDR checkpoints are poorly studied. Emerging evidence suggests crosstalk between the spindle assembly checkpoint (SAC) and DDR during mitosis. Despite global DDR downregulation in mitosis, local waves of key DDR component activation highlight the lack of complete DDR deactivation.

A delay in mitotic transit times following DNA damage induction from various agents, such as irradiation (IR), was detected during this project. This indicates the existence of a mitotic DNA damage checkpoint (MDDC), which could be a source of treatment resistance. This thesis aims to identify if X-ray repair cross-complementing 4 (XRCC4) plays a novel role in the MDDC. XRCC4 was highlighted in a preliminary Small interfering Ribonucleic acid (siRNA) DNA damage screen of potential proteins involved in the checkpoint. I observed a significant impact on cell fate, mitotic transit, and mitotic population upon XRCC4 depletion, indicating XRCC4 could play a role outside of Non-Homologous End-Joining (NHEJ). At the end of this project, the specific role of XRCC4 concerning the MDDC remained inconclusive but warrants further investigation.

The aims of this thesis shifted focus towards the analysis of the mitotic-specific transcriptome response to DNA damage, derived from genomic expression data analysed via RNA sequencing (RNAseq). We observed that whilst tools exist for cell-cycle analysis from RNAseq data, there was no reliable tool for the isolation of mitotic cells from the G2 population. Here I developed and validated Modified Seurat Mitotic Sort (MoSMiS), a tool to identify mitotic cells from single-cell RNA sequencing datasets based in the Spatial Reconstruction Of Single-Cell Gene Expression Data (Seurat) toolset. MoSMiS was then used to investigate the mitotic transcription responses to DNA damage and highlight MDDC-related genes of interest. MoSMiS was utilised to analyse published data sets to generate novel gene lists to guide future MDDC investigations.