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Molecular stratification of endometrioid ovarian carcinoma predicts clinical outcome

Endometrioid ovarian carcinoma (EnOC) demonstrates substantial clinical and molecular heterogeneity. Here, we report whole exome sequencing of 112 EnOC cases following rigorous pathological assessment. We detect a high frequency of mutation in CTNNB1 (43%), PIK3CA (43%), ARID1A (36%), PTEN (29%), KR...

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Autores principales: Hollis, Robert L., Thomson, John P., Stanley, Barbara, Churchman, Michael, Meynert, Alison M., Rye, Tzyvia, Bartos, Clare, Iida, Yasushi, Croy, Ian, Mackean, Melanie, Nussey, Fiona, Okamoto, Aikou, Semple, Colin A., Gourley, Charlie, Herrington, C. Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7536188/
https://www.ncbi.nlm.nih.gov/pubmed/33020491
http://dx.doi.org/10.1038/s41467-020-18819-5
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author Hollis, Robert L.
Thomson, John P.
Stanley, Barbara
Churchman, Michael
Meynert, Alison M.
Rye, Tzyvia
Bartos, Clare
Iida, Yasushi
Croy, Ian
Mackean, Melanie
Nussey, Fiona
Okamoto, Aikou
Semple, Colin A.
Gourley, Charlie
Herrington, C. Simon
author_facet Hollis, Robert L.
Thomson, John P.
Stanley, Barbara
Churchman, Michael
Meynert, Alison M.
Rye, Tzyvia
Bartos, Clare
Iida, Yasushi
Croy, Ian
Mackean, Melanie
Nussey, Fiona
Okamoto, Aikou
Semple, Colin A.
Gourley, Charlie
Herrington, C. Simon
author_sort Hollis, Robert L.
collection PubMed
description Endometrioid ovarian carcinoma (EnOC) demonstrates substantial clinical and molecular heterogeneity. Here, we report whole exome sequencing of 112 EnOC cases following rigorous pathological assessment. We detect a high frequency of mutation in CTNNB1 (43%), PIK3CA (43%), ARID1A (36%), PTEN (29%), KRAS (26%), TP53 (26%) and SOX8 (19%), a recurrently-mutated gene previously unreported in EnOC. POLE and mismatch repair protein-encoding genes were mutated at lower frequency (6%, 18%) with significant co-occurrence. A molecular taxonomy is constructed, identifying clinically distinct EnOC subtypes: cases with TP53 mutation demonstrate greater genomic complexity, are commonly FIGO stage III/IV at diagnosis (48%), are frequently incompletely debulked (44%) and demonstrate inferior survival; conversely, cases with CTNNB1 mutation, which is mutually exclusive with TP53 mutation, demonstrate low genomic complexity and excellent clinical outcome, and are predominantly stage I/II at diagnosis (89%) and completely resected (87%). Moreover, we identify the WNT, MAPK/RAS and PI3K pathways as good candidate targets for molecular therapeutics in EnOC.
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spelling pubmed-75361882020-10-19 Molecular stratification of endometrioid ovarian carcinoma predicts clinical outcome Hollis, Robert L. Thomson, John P. Stanley, Barbara Churchman, Michael Meynert, Alison M. Rye, Tzyvia Bartos, Clare Iida, Yasushi Croy, Ian Mackean, Melanie Nussey, Fiona Okamoto, Aikou Semple, Colin A. Gourley, Charlie Herrington, C. Simon Nat Commun Article Endometrioid ovarian carcinoma (EnOC) demonstrates substantial clinical and molecular heterogeneity. Here, we report whole exome sequencing of 112 EnOC cases following rigorous pathological assessment. We detect a high frequency of mutation in CTNNB1 (43%), PIK3CA (43%), ARID1A (36%), PTEN (29%), KRAS (26%), TP53 (26%) and SOX8 (19%), a recurrently-mutated gene previously unreported in EnOC. POLE and mismatch repair protein-encoding genes were mutated at lower frequency (6%, 18%) with significant co-occurrence. A molecular taxonomy is constructed, identifying clinically distinct EnOC subtypes: cases with TP53 mutation demonstrate greater genomic complexity, are commonly FIGO stage III/IV at diagnosis (48%), are frequently incompletely debulked (44%) and demonstrate inferior survival; conversely, cases with CTNNB1 mutation, which is mutually exclusive with TP53 mutation, demonstrate low genomic complexity and excellent clinical outcome, and are predominantly stage I/II at diagnosis (89%) and completely resected (87%). Moreover, we identify the WNT, MAPK/RAS and PI3K pathways as good candidate targets for molecular therapeutics in EnOC. Nature Publishing Group UK 2020-10-05 /pmc/articles/PMC7536188/ /pubmed/33020491 http://dx.doi.org/10.1038/s41467-020-18819-5 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
Hollis, Robert L.
Thomson, John P.
Stanley, Barbara
Churchman, Michael
Meynert, Alison M.
Rye, Tzyvia
Bartos, Clare
Iida, Yasushi
Croy, Ian
Mackean, Melanie
Nussey, Fiona
Okamoto, Aikou
Semple, Colin A.
Gourley, Charlie
Herrington, C. Simon
Molecular stratification of endometrioid ovarian carcinoma predicts clinical outcome
title Molecular stratification of endometrioid ovarian carcinoma predicts clinical outcome
title_full Molecular stratification of endometrioid ovarian carcinoma predicts clinical outcome
title_fullStr Molecular stratification of endometrioid ovarian carcinoma predicts clinical outcome
title_full_unstemmed Molecular stratification of endometrioid ovarian carcinoma predicts clinical outcome
title_short Molecular stratification of endometrioid ovarian carcinoma predicts clinical outcome
title_sort molecular stratification of endometrioid ovarian carcinoma predicts clinical outcome
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7536188/
https://www.ncbi.nlm.nih.gov/pubmed/33020491
http://dx.doi.org/10.1038/s41467-020-18819-5
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