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High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer

Ovarian cancer is usually detected at a late stage and the overall 5-year survival is only 30–40%. Additional means for early detection and improved diagnosis are acutely needed. To search for novel biomarkers, we compared circulating plasma levels of 593 proteins in three cohorts of patients with o...

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Autores principales: Enroth, Stefan, Berggrund, Malin, Lycke, Maria, Broberg, John, Lundberg, Martin, Assarsson, Erika, Olovsson, Matts, Stålberg, Karin, Sundfeldt, Karin, Gyllensten, Ulf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586828/
https://www.ncbi.nlm.nih.gov/pubmed/31240259
http://dx.doi.org/10.1038/s42003-019-0464-9
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author Enroth, Stefan
Berggrund, Malin
Lycke, Maria
Broberg, John
Lundberg, Martin
Assarsson, Erika
Olovsson, Matts
Stålberg, Karin
Sundfeldt, Karin
Gyllensten, Ulf
author_facet Enroth, Stefan
Berggrund, Malin
Lycke, Maria
Broberg, John
Lundberg, Martin
Assarsson, Erika
Olovsson, Matts
Stålberg, Karin
Sundfeldt, Karin
Gyllensten, Ulf
author_sort Enroth, Stefan
collection PubMed
description Ovarian cancer is usually detected at a late stage and the overall 5-year survival is only 30–40%. Additional means for early detection and improved diagnosis are acutely needed. To search for novel biomarkers, we compared circulating plasma levels of 593 proteins in three cohorts of patients with ovarian cancer and benign tumors, using the proximity extension assay (PEA). A combinatorial strategy was developed for identification of different multivariate biomarker signatures. A final model consisting of 11 biomarkers plus age was developed into a multiplex PEA test reporting in absolute concentrations. The final model was evaluated in a fourth independent cohort and has an AUC = 0.94, PPV = 0.92, sensitivity = 0.85 and specificity = 0.93 for detection of ovarian cancer stages I–IV. The novel plasma protein signature could be used to improve the diagnosis of women with adnexal ovarian mass or in screening to identify women that should be referred to specialized examination.
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spelling pubmed-65868282019-06-25 High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer Enroth, Stefan Berggrund, Malin Lycke, Maria Broberg, John Lundberg, Martin Assarsson, Erika Olovsson, Matts Stålberg, Karin Sundfeldt, Karin Gyllensten, Ulf Commun Biol Article Ovarian cancer is usually detected at a late stage and the overall 5-year survival is only 30–40%. Additional means for early detection and improved diagnosis are acutely needed. To search for novel biomarkers, we compared circulating plasma levels of 593 proteins in three cohorts of patients with ovarian cancer and benign tumors, using the proximity extension assay (PEA). A combinatorial strategy was developed for identification of different multivariate biomarker signatures. A final model consisting of 11 biomarkers plus age was developed into a multiplex PEA test reporting in absolute concentrations. The final model was evaluated in a fourth independent cohort and has an AUC = 0.94, PPV = 0.92, sensitivity = 0.85 and specificity = 0.93 for detection of ovarian cancer stages I–IV. The novel plasma protein signature could be used to improve the diagnosis of women with adnexal ovarian mass or in screening to identify women that should be referred to specialized examination. Nature Publishing Group UK 2019-06-20 /pmc/articles/PMC6586828/ /pubmed/31240259 http://dx.doi.org/10.1038/s42003-019-0464-9 Text en © The Author(s) 2019 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
Enroth, Stefan
Berggrund, Malin
Lycke, Maria
Broberg, John
Lundberg, Martin
Assarsson, Erika
Olovsson, Matts
Stålberg, Karin
Sundfeldt, Karin
Gyllensten, Ulf
High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer
title High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer
title_full High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer
title_fullStr High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer
title_full_unstemmed High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer
title_short High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer
title_sort high throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586828/
https://www.ncbi.nlm.nih.gov/pubmed/31240259
http://dx.doi.org/10.1038/s42003-019-0464-9
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