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

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...

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Autores principales: Nelson, Louisa, Tighe, Anthony, Golder, Anya, Littler, Samantha, Bakker, Bjorn, Moralli, Daniela, Murtuza Baker, Syed, Donaldson, Ian J., Spierings, Diana C. J., Wardenaar, René, Neale, Bethanie, Burghel, George J., Winter-Roach, Brett, Edmondson, Richard, Clamp, Andrew R., Jayson, Gordon C., Desai, Sudha, Green, Catherine M., Hayes, Andy, Foijer, Floris, Morgan, Robert D., Taylor, Stephen S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7018727/
https://www.ncbi.nlm.nih.gov/pubmed/32054838
http://dx.doi.org/10.1038/s41467-020-14551-2
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author Nelson, Louisa
Tighe, Anthony
Golder, Anya
Littler, Samantha
Bakker, Bjorn
Moralli, Daniela
Murtuza Baker, Syed
Donaldson, Ian J.
Spierings, Diana C. J.
Wardenaar, René
Neale, Bethanie
Burghel, George J.
Winter-Roach, Brett
Edmondson, Richard
Clamp, Andrew R.
Jayson, Gordon C.
Desai, Sudha
Green, Catherine M.
Hayes, Andy
Foijer, Floris
Morgan, Robert D.
Taylor, Stephen S.
author_facet Nelson, Louisa
Tighe, Anthony
Golder, Anya
Littler, Samantha
Bakker, Bjorn
Moralli, Daniela
Murtuza Baker, Syed
Donaldson, Ian J.
Spierings, Diana C. J.
Wardenaar, René
Neale, Bethanie
Burghel, George J.
Winter-Roach, Brett
Edmondson, Richard
Clamp, Andrew R.
Jayson, Gordon C.
Desai, Sudha
Green, Catherine M.
Hayes, Andy
Foijer, Floris
Morgan, Robert D.
Taylor, Stephen S.
author_sort Nelson, Louisa
collection PubMed
description 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.
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spelling pubmed-70187272020-02-21 A living biobank of ovarian cancer ex vivo models reveals profound mitotic heterogeneity Nelson, Louisa Tighe, Anthony Golder, Anya Littler, Samantha Bakker, Bjorn Moralli, Daniela Murtuza Baker, Syed Donaldson, Ian J. Spierings, Diana C. J. Wardenaar, René Neale, Bethanie Burghel, George J. Winter-Roach, Brett Edmondson, Richard Clamp, Andrew R. Jayson, Gordon C. Desai, Sudha Green, Catherine M. Hayes, Andy Foijer, Floris Morgan, Robert D. Taylor, Stephen S. Nat Commun Article 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. Nature Publishing Group UK 2020-02-13 /pmc/articles/PMC7018727/ /pubmed/32054838 http://dx.doi.org/10.1038/s41467-020-14551-2 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Nelson, Louisa
Tighe, Anthony
Golder, Anya
Littler, Samantha
Bakker, Bjorn
Moralli, Daniela
Murtuza Baker, Syed
Donaldson, Ian J.
Spierings, Diana C. J.
Wardenaar, René
Neale, Bethanie
Burghel, George J.
Winter-Roach, Brett
Edmondson, Richard
Clamp, Andrew R.
Jayson, Gordon C.
Desai, Sudha
Green, Catherine M.
Hayes, Andy
Foijer, Floris
Morgan, Robert D.
Taylor, Stephen S.
A living biobank of ovarian cancer ex vivo models reveals profound mitotic heterogeneity
title A living biobank of ovarian cancer ex vivo models reveals profound mitotic heterogeneity
title_full A living biobank of ovarian cancer ex vivo models reveals profound mitotic heterogeneity
title_fullStr A living biobank of ovarian cancer ex vivo models reveals profound mitotic heterogeneity
title_full_unstemmed A living biobank of ovarian cancer ex vivo models reveals profound mitotic heterogeneity
title_short A living biobank of ovarian cancer ex vivo models reveals profound mitotic heterogeneity
title_sort living biobank of ovarian cancer ex vivo models reveals profound mitotic heterogeneity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7018727/
https://www.ncbi.nlm.nih.gov/pubmed/32054838
http://dx.doi.org/10.1038/s41467-020-14551-2
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