Chromosomal instability (CIN) comprises continual gain and loss of chromosomes or parts of chromosomes and occurs in the majority of cancers, often conferring poor prognosis. Due to a scarcity of functional studies and poor understanding of how genetic or gene expression landscapes connect to specific CIN mechanisms, causes of CIN in most cancer types remain unknown. High-grade serous ovarian carcinoma (HGSC), the most common subtype of ovarian cancer, is the major cause of death due to gynaecological malignancy in the Western world, with chemotherapy resistance developing in almost all patients. HGSC exhibits high rates of chromosomal aberrations and knowledge of causative mechanisms would represent an important step towards combating this disease. Here we perform the first in-depth functional characterization of mechanisms driving CIN in HGSC in seven cell lines that accurately recapitulate HGSC genetics. Multiple mechanisms co-existed to drive CIN in HGSC, including elevated microtubule dynamics and DNA replication stress that can be partially rescued to reduce CIN by low doses of paclitaxel and nucleoside supplementation, respectively. Distinct CIN mechanisms indicated relationships with HGSC-relevant therapy including Poly (ADP-Ribose) Polymerase (PARP) inhibition and microtubule-targeting agents. Comprehensive genomic and transcriptomic profiling revealed deregulation of various genes involved in genome stability but were not directly predictive of specific CIN mechanisms, underscoring the importance of functional characterization to identify causes of CIN. Overall, we show that HGSC CIN is complex and suggest that specific CIN mechanisms could be used as functional biomarkers to indicate appropriate therapy. Statement of SignificanceFindings characterize multiple deregulated mechanisms of genome stability that lead to chromosomal instability in ovarian cancer and demonstrate the benefit of integrating analysis of said mechanisms into predictions of therapy response.

Digital PCR (dPCR) is an important tool for precise nucleic acid quantification in clinical setting, but the limited multiplexing capability restricts its applications for quantitative gene panel profiling. Here, this work describes melt‐encoded‐tags for expanded optical readout in digital PCR (METEOR‐dPCR), a simple two‐step assay that enables simultaneous quantification of a large panel of arbitrary genes in a dPCR platform. Target genes are quantitatively converted into DNA tags with unique melting temperatures through a ligation approach. These tags are then counted and distinguished by their melt‐curve profiles on a dPCR platform. A multiplexing capacity of M^N, where M is the number of resolvable melting temperature and N is the number of fluorescence channel, can be achieved. This work validates METEOR‐dPCR with simultaneous DNA copy number profiling of 60 targets using dPCR in cancer cells, and demonstrates its sensitivity for estimating tumor fraction in mixed tumor and normal DNA samples. The rapid, quantitative, and highly multiplexed METEOR‐dPCR assay will have wide appeal for many clinical applications.

Chromosomal instability (CIN), the continual gain and loss of chromosomes or parts of chromosomes, occurs in the majority of cancers and confers poor prognosis. Mechanisms driving CIN remain unknown in most cancer types due to a scarcity of functional studies.High-grade serous ovarian carcinoma (HGSC), the most common subtype of ovarian cancer, is the major cause of death due to gynaecological malignancy in the Western world with chemotherapy resistance developing in almost all patients. HGSC exhibits high rates of chromosome aberrations and knowledge of causative mechanisms is likely to represent an important step towards combating the poor prognosis of this disease. However, very little is known about the nature of chromosomal instability exhibited by this cancer type in particular due to a historical lack of appropriate cell line models. Here we perform the first in-depth functional characterisation of mechanisms driving CIN in HGSC by analysing eight cell lines that accurately recapitulate HGSC genetics as defined by recent studies. We show, using a range of established functional CIN assays combined with live cell imaging and single molecule DNA fibre analysis, that multiple mechanisms co-exist to drive CIN in HGSC.These include supernumerary centrosomes, elevated microtubule dynamics and DNA replication stress. By contrast, the spindle assembly checkpoint was intact. These findings are relevant for developing therapeutic approaches to manipulating CIN in ovarian cancer, and suggests that such approaches may need to be multimodal to combat multiple co-existing CIN drivers.

<p>RNA seq pathway analysis</p>