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

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

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

2020
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Overview
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. High-grade serous ovarian carcinoma is often associated with TP53 mutation and chromosomal instability (CIN). Here, the authors generate ex vivo cultures from biopsies and ascites of patients and perform characterization to evaluate CIN mechanisms and compare drug sensitivity with patient responses.

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