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A multiplex platform for the identification of ovarian cancer biomarkers
BACKGROUND: Currently, there are no FDA approved screening tools for detecting early stage ovarian cancer in the general population. Development of a biomarker-based assay for early detection would significantly improve the survival of ovarian cancer patients. METHODS: We used a multiplex approach t...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5634875/ https://www.ncbi.nlm.nih.gov/pubmed/29051715 http://dx.doi.org/10.1186/s12014-017-9169-6 |
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author | Boylan, Kristin L. M. Geschwind, Kate Koopmeiners, Joseph S. Geller, Melissa A. Starr, Timothy K. Skubitz, Amy P. N. |
author_facet | Boylan, Kristin L. M. Geschwind, Kate Koopmeiners, Joseph S. Geller, Melissa A. Starr, Timothy K. Skubitz, Amy P. N. |
author_sort | Boylan, Kristin L. M. |
collection | PubMed |
description | BACKGROUND: Currently, there are no FDA approved screening tools for detecting early stage ovarian cancer in the general population. Development of a biomarker-based assay for early detection would significantly improve the survival of ovarian cancer patients. METHODS: We used a multiplex approach to identify protein biomarkers for detecting early stage ovarian cancer. This new technology (Proseek(®) Multiplex Oncology Plates) can simultaneously measure the expression of 92 proteins in serum based on a proximity extension assay. We analyzed serum samples from 81 women representing healthy, benign pathology, early, and advanced stage serous ovarian cancer patients. RESULTS: Principle component analysis and unsupervised hierarchical clustering separated patients into cancer versus non-cancer subgroups. Data from the Proseek(®) plate for CA125 levels exhibited a strong correlation with current clinical assays for CA125 (correlation coefficient of 0.89, 95% CI 0.83, 0.93). CA125 and HE4 were present at very low levels in healthy controls and benign cases, while higher levels were found in early stage cases, with highest levels found in the advanced stage cases. Overall, significant trends were observed for 38 of the 92 proteins (p < 0.001), many of which are novel candidate serum biomarkers for ovarian cancer. The area under the ROC curve (AUC) for CA125 was 0.98 and the AUC for HE4 was 0.85 when comparing early stage ovarian cancer versus healthy controls. In total, 23 proteins had an estimated AUC of 0.7 or greater. Using a naïve Bayes classifier that combined 12 proteins, we improved the sensitivity corresponding to 95% specificity from 93 to 95% when compared to CA125 alone. Although small, a 2% increase would have a significant effect on the number of women correctly identified when screening a large population. CONCLUSIONS: These data demonstrate that the Proseek(®) technology can replicate the results established by conventional clinical assays for known biomarkers, identify new candidate biomarkers, and improve the sensitivity and specificity of CA125 alone. Additional studies using a larger cohort of patients will allow for validation of these biomarkers and lead to the development of a screening tool for detecting early stage ovarian cancer in the general population. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12014-017-9169-6) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5634875 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-56348752017-10-19 A multiplex platform for the identification of ovarian cancer biomarkers Boylan, Kristin L. M. Geschwind, Kate Koopmeiners, Joseph S. Geller, Melissa A. Starr, Timothy K. Skubitz, Amy P. N. Clin Proteomics Research BACKGROUND: Currently, there are no FDA approved screening tools for detecting early stage ovarian cancer in the general population. Development of a biomarker-based assay for early detection would significantly improve the survival of ovarian cancer patients. METHODS: We used a multiplex approach to identify protein biomarkers for detecting early stage ovarian cancer. This new technology (Proseek(®) Multiplex Oncology Plates) can simultaneously measure the expression of 92 proteins in serum based on a proximity extension assay. We analyzed serum samples from 81 women representing healthy, benign pathology, early, and advanced stage serous ovarian cancer patients. RESULTS: Principle component analysis and unsupervised hierarchical clustering separated patients into cancer versus non-cancer subgroups. Data from the Proseek(®) plate for CA125 levels exhibited a strong correlation with current clinical assays for CA125 (correlation coefficient of 0.89, 95% CI 0.83, 0.93). CA125 and HE4 were present at very low levels in healthy controls and benign cases, while higher levels were found in early stage cases, with highest levels found in the advanced stage cases. Overall, significant trends were observed for 38 of the 92 proteins (p < 0.001), many of which are novel candidate serum biomarkers for ovarian cancer. The area under the ROC curve (AUC) for CA125 was 0.98 and the AUC for HE4 was 0.85 when comparing early stage ovarian cancer versus healthy controls. In total, 23 proteins had an estimated AUC of 0.7 or greater. Using a naïve Bayes classifier that combined 12 proteins, we improved the sensitivity corresponding to 95% specificity from 93 to 95% when compared to CA125 alone. Although small, a 2% increase would have a significant effect on the number of women correctly identified when screening a large population. CONCLUSIONS: These data demonstrate that the Proseek(®) technology can replicate the results established by conventional clinical assays for known biomarkers, identify new candidate biomarkers, and improve the sensitivity and specificity of CA125 alone. Additional studies using a larger cohort of patients will allow for validation of these biomarkers and lead to the development of a screening tool for detecting early stage ovarian cancer in the general population. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12014-017-9169-6) contains supplementary material, which is available to authorized users. BioMed Central 2017-10-10 /pmc/articles/PMC5634875/ /pubmed/29051715 http://dx.doi.org/10.1186/s12014-017-9169-6 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Boylan, Kristin L. M. Geschwind, Kate Koopmeiners, Joseph S. Geller, Melissa A. Starr, Timothy K. Skubitz, Amy P. N. A multiplex platform for the identification of ovarian cancer biomarkers |
title | A multiplex platform for the identification of ovarian cancer biomarkers |
title_full | A multiplex platform for the identification of ovarian cancer biomarkers |
title_fullStr | A multiplex platform for the identification of ovarian cancer biomarkers |
title_full_unstemmed | A multiplex platform for the identification of ovarian cancer biomarkers |
title_short | A multiplex platform for the identification of ovarian cancer biomarkers |
title_sort | multiplex platform for the identification of ovarian cancer biomarkers |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5634875/ https://www.ncbi.nlm.nih.gov/pubmed/29051715 http://dx.doi.org/10.1186/s12014-017-9169-6 |
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