A living biobank of ovarian cancer ex vivo models reveals profound mitotic heterogeneity

Abstract

High-grade serous ovarian carcinoma is characterised by TP53 mutation and extensive chromosome instability (CIN). Because our understanding of CIN mechanisms is based largely on analysing established cell lines, we developed a workflow for generating ex vivo cultures from patient biopsies to provide models that support interrogation of CIN mechanisms in cells not extensively cultured in vitro. Here, we describe a "living biobank" of ovarian cancer models with extensive replicative capacity, derived from both ascites and solid biopsies. Fifteen models are characterised by p53 profiling, exome sequencing and transcriptomics, and karyotyped using single-cell whole-genome sequencing. Time-lapse microscopy reveals catastrophic and highly heterogeneous mitoses, suggesting that analysis of established cell lines probably underestimates mitotic dysfunction in advanced human cancers. Drug profiling reveals cisplatin sensitivities consistent with patient responses, demonstrating that this workflow has potential to generate personalized avatars with advantages over current pre-clinical models and the potential to guide clinical decision making.

The Mechanics of Mitotic Cell Rounding

“…Cells with increased cortical elasticity following E-cadherin knockdown were more efficient at clustering supernumerary centrosomes, facilitating bipolar spindle formation and division (Rhys et al, 2018). The idea that enhanced mitotic rounding can minimize mitotic errors in cancer is somewhat paradoxical, as cancers are often characterized by a high degree of aneuploidy, generated through errors in chromosome segregation in mitosis (Sansregret and Swanton, 2017;Nelson et al, 2020). However, some of the mitotic errors observed when mitotic rounding is compromised such as tripolar division are unlikely to result in viable daughter cells.…”

Recycling the Purpose of Old Drugs to Treat Ovarian Cancer

“…Specifically, in epithelial OC, ex vivo models have been shown to faithfully recapitulate phenotypic and genotypic tumour features [ 236 ]. Furthermore, results of drug profiling using these OC models showed sensitivity to drugs, such as, platinum and iPARPs, which correlated with patient clinical responses [ 237 ]. Likewise, ex vivo models are also suitable for testing high-throughput drug repurposing, as demonstrated in other cancers [ 238 ].…”

Increased expression of UBE2T predicting poor survival of ovarian cancer: based on comprehensive analysis of UBE2s, clinical samples and the GEO database

“…In patients with high UBE2T expression, TP53, TTN, DST, FAT3, CSMD1, MUC16, and MUC17 exhibited a signi cant rate of alterations. TP53 mutation frequency in ovarian serous carcinomas has been reported to range from 50% and 80% [58]; ubiquitous TP53 mutations are characteristic of high-grade serous ovarian cancer (HGSOC) and related to relapse [59]. TTN encodes a large polypeptide expressed in many cancer cell types and involved in oncogenesis, and its mutation has been found in OC by using an the next-generation sequencing (NGS) library [60].…”