Group Leader: Dr Elina Vladimirou
The most basic function of the cell cycle is to accurately duplicate DNA in the chromosomes during synthesis (S phase), and then segregate the copies precisely into two genetically identical daughter cells during mitosis (M phase). Our laboratory’s focus is understanding how these fundamental processes of the cell cycle are deregulated in cancer with a strong focus in lung cancer.
Finding mechanistic links between early driver events and chromosome instability in lung cancer
Cancer cells display a high rate of numerical and structural chromosomal alterations. This dynamic process, termed chromosomal instability (CIN), promotes tumour initiation and drives tumour heterogeneity, drug resistance and treatment failure. Defects in the mitotic machinery compromising chromosome segregation as well as replication stress and DNA repair failures lead to CIN. Mechanistic knowledge of CIN initiation, progression and tolerance enables the possibility of limiting tumour aggressiveness as well as tackling resistance to therapy. The Chromosome Instability Research Group investigates the mechanisms by which early somatic mutations and copy-number alterations deregulate cell cycle and the mitotic machinery, giving rise to CIN in non-small-cell lung cancer (NSCLC). Driver mutations found to be linked to specific errors could be used as prognostic markers and the mechanistic pathways could reveal novel molecular inhibitor targets for correcting or modulating CIN depending on therapeutic requirements.
Using high spatiotemporal resolution fluorescent live cell imaging combined with cellular and subcellular object tracking, we find mechanistic links between early driver events and CIN initiation. We use CRISPR technology to fluorescently label and follow specific chromosomes in living cells. We develop image analysis and use machine learning to implement automated software to reconstruct cell lineages and investigate the effect of specific chromosome segregation errors on cell fate at a single-cell resolution. We use data driven mathematical modelling of clonal karyotypic evolution to understand how it shapes the heterogeneous tumour genome.
- Armond, J. W., Vladimirou, E., McAinsh, A. D., & Burroughs, N. J. (2016). KiT: a MATLAB package for kinetochore tracking. Bioinformatics (Oxford, England), 32 (12), 1917-1919. doi:10.1093/bioinformatics/btw087
- Armond, J. W.*, Vladimirou, E.*, Erent, M., McAinsh, A. D., & Burroughs, N. J. (2015). Probing microtubule polymerisation state at single kinetochores during metaphase chromosome motion. Journal of cell science, 128 (10), 1991-2001. doi:10.1242/jcs.168682
- Vladimirou, E., Harry, E., Burroughs, N., & McAinsh, A. D. (2011). Springs, clutches and motors: driving forward kinetochore mechanism by modelling. Chromosome research, 19 (3), 409-421. doi:10.1007/s10577-011-9191-x
- Vladimirou, E.*, Mchedlishvili, N.*, Gasic, I.*, Armond, J. W., Samora, C. P., Meraldi, P., & McAinsh, A. D. (2013). Nonautonomous movement of chromosomes in mitosis. Developmental cell, 27 (1), 60-71. doi:10.1016/j.devcel.2013.08.004
* joint first authors