Testing the Role of Chromosomal Instability in Chemotherapy Resistance in High Grade Serous Ovarian Cancer

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Chromosomal changes (gains or losses of whole, or parts of chromosomes) are almost ubiquitous in cancer, and are thought to provide tumour cells with the ability to rapidly evolve resistance to therapy. However this has never been directly tested experimentally due to difficulties in manipulating tumour chromosomal instability levels. Ovarian cancer particularly is thought to rely on chromosomal changes because other types of mutations are rarer in this cancer. Over the last years we have characterized the cellular mechanisms driving chromosome instability (CIN) in colorectal (ref 1) and ovarian (ref 2) cancer. This has allowed us to develop experimental methods to manipulate the rates of CIN placing us in a position to test the direct role of CIN in developing chemotherapy resistance for the first time.Aim 1: Track the development of chemotherapy resistance in a panel of previously characterised high grade serous ovarian cancer (HGSC) cell lines. We will use lineage tracing by 'barcoding' individual cancer cells then following the dynamics of their clonal growth over time, by deep sequencing resulting cell populations. We will compare the dynamics of chemotherapy resistance in 'naturally CIN' HGSC cell lines, and also HGSC cell lines where we have reduced CIN using methods described in Tamura et al, BioRXiv 2019.Aim 2: Discover the CIN mechanisms operating in a panel of 'ex-vivo' HGSC cultures that have been recently derived from HGSC patients (in collaboration with Prof. Taylor, University of Manchester - see Ref 4). This will involve cell biological assays to determine the rates and types of cellular dysregulation that leads to ongoing chromosome replication and segregation errors.Aim 3: Repeat lineage tracing experiments during chemotherapy resistance development, with ex-vivo cultures.This will allow us to test the importance of CIN in developing chemotherapy resistance in both established cell lines, and also ex-vivo cultures, which more accurately represent disease in patients.