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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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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. |
format | Online Article Text |
id | pubmed-6586828 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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