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Discovery of non-invasive biomarkers for the diagnosis of endometriosis

BACKGROUND: Endometriosis is a common gynaecological disorder affecting 5–10% of women of reproductive age who often experience chronic pelvic pain and infertility. Definitive diagnosis is through laparoscopy, exposing patients to potentially serious complications, and is often delayed. Non-invasive...

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Autores principales: Irungu, Stella, Mavrelos, Dimitrios, Worthington, Jenny, Blyuss, Oleg, Saridogan, Ertan, Timms, John F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6451201/
https://www.ncbi.nlm.nih.gov/pubmed/30992697
http://dx.doi.org/10.1186/s12014-019-9235-3
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author Irungu, Stella
Mavrelos, Dimitrios
Worthington, Jenny
Blyuss, Oleg
Saridogan, Ertan
Timms, John F.
author_facet Irungu, Stella
Mavrelos, Dimitrios
Worthington, Jenny
Blyuss, Oleg
Saridogan, Ertan
Timms, John F.
author_sort Irungu, Stella
collection PubMed
description BACKGROUND: Endometriosis is a common gynaecological disorder affecting 5–10% of women of reproductive age who often experience chronic pelvic pain and infertility. Definitive diagnosis is through laparoscopy, exposing patients to potentially serious complications, and is often delayed. Non-invasive biomarkers are urgently required to accelerate diagnosis and for triaging potential patients for surgery. METHODS: This retrospective case control biomarker discovery and validation study used quantitative 2D-difference gel electrophoresis and tandem mass tagging–liquid chromatography–tandem mass spectrometry for protein expression profiling of eutopic and ectopic endometrial tissue samples collected from 28 cases of endometriosis and 18 control patients undergoing surgery for investigation of chronic pelvic pain without endometriosis or prophylactic surgery. Samples were further sub-grouped by menstrual cycle phase. Selected differentially expressed candidate markers (LUM, CPM, TNC, TPM2 and PAEP) were verified by ELISA in a set of 87 serum samples collected from the same and additional women. Previously reported biomarkers (CA125, sICAM1, FST, VEGF, MCP1, MIF and IL1R2) were also validated and diagnostic performance of markers and combinations established. RESULTS: Cycle phase and endometriosis-associated proteomic changes were identified in eutopic tissue from over 1400 identified gene products, yielding potential biomarker candidates. Bioinformatics analysis revealed enrichment of adhesion/extracellular matrix proteins and progesterone signalling. The best single marker for discriminating endometriosis from controls remained CA125 (AUC = 0.63), with the best cross-validated multimarker models improving the AUC to 0.71–0.81, depending upon menstrual cycle phase and control group. CONCLUSIONS: We have identified menstrual cycle- and endometriosis-associated protein changes linked to various cellular processes that are potential biomarkers and that provide insight into the biology of endometriosis. Our data indicate that the markers tested, whilst not useful alone, have improved diagnostic accuracy when used in combination and demonstrate menstrual cycle specificity. Tissue heterogeneity and blood contamination is likely to have hindered biomarker discovery, whilst a small sample size precludes accurate determination of performance by cycle phase. Independent validation of these biomarker panels in a larger cohort is however warranted, and if successful, they may have clinical utility in triaging patients for surgery. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12014-019-9235-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-64512012019-04-16 Discovery of non-invasive biomarkers for the diagnosis of endometriosis Irungu, Stella Mavrelos, Dimitrios Worthington, Jenny Blyuss, Oleg Saridogan, Ertan Timms, John F. Clin Proteomics Research BACKGROUND: Endometriosis is a common gynaecological disorder affecting 5–10% of women of reproductive age who often experience chronic pelvic pain and infertility. Definitive diagnosis is through laparoscopy, exposing patients to potentially serious complications, and is often delayed. Non-invasive biomarkers are urgently required to accelerate diagnosis and for triaging potential patients for surgery. METHODS: This retrospective case control biomarker discovery and validation study used quantitative 2D-difference gel electrophoresis and tandem mass tagging–liquid chromatography–tandem mass spectrometry for protein expression profiling of eutopic and ectopic endometrial tissue samples collected from 28 cases of endometriosis and 18 control patients undergoing surgery for investigation of chronic pelvic pain without endometriosis or prophylactic surgery. Samples were further sub-grouped by menstrual cycle phase. Selected differentially expressed candidate markers (LUM, CPM, TNC, TPM2 and PAEP) were verified by ELISA in a set of 87 serum samples collected from the same and additional women. Previously reported biomarkers (CA125, sICAM1, FST, VEGF, MCP1, MIF and IL1R2) were also validated and diagnostic performance of markers and combinations established. RESULTS: Cycle phase and endometriosis-associated proteomic changes were identified in eutopic tissue from over 1400 identified gene products, yielding potential biomarker candidates. Bioinformatics analysis revealed enrichment of adhesion/extracellular matrix proteins and progesterone signalling. The best single marker for discriminating endometriosis from controls remained CA125 (AUC = 0.63), with the best cross-validated multimarker models improving the AUC to 0.71–0.81, depending upon menstrual cycle phase and control group. CONCLUSIONS: We have identified menstrual cycle- and endometriosis-associated protein changes linked to various cellular processes that are potential biomarkers and that provide insight into the biology of endometriosis. Our data indicate that the markers tested, whilst not useful alone, have improved diagnostic accuracy when used in combination and demonstrate menstrual cycle specificity. Tissue heterogeneity and blood contamination is likely to have hindered biomarker discovery, whilst a small sample size precludes accurate determination of performance by cycle phase. Independent validation of these biomarker panels in a larger cohort is however warranted, and if successful, they may have clinical utility in triaging patients for surgery. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12014-019-9235-3) contains supplementary material, which is available to authorized users. BioMed Central 2019-04-06 /pmc/articles/PMC6451201/ /pubmed/30992697 http://dx.doi.org/10.1186/s12014-019-9235-3 Text en © The Author(s) 2019 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
Irungu, Stella
Mavrelos, Dimitrios
Worthington, Jenny
Blyuss, Oleg
Saridogan, Ertan
Timms, John F.
Discovery of non-invasive biomarkers for the diagnosis of endometriosis
title Discovery of non-invasive biomarkers for the diagnosis of endometriosis
title_full Discovery of non-invasive biomarkers for the diagnosis of endometriosis
title_fullStr Discovery of non-invasive biomarkers for the diagnosis of endometriosis
title_full_unstemmed Discovery of non-invasive biomarkers for the diagnosis of endometriosis
title_short Discovery of non-invasive biomarkers for the diagnosis of endometriosis
title_sort discovery of non-invasive biomarkers for the diagnosis of endometriosis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6451201/
https://www.ncbi.nlm.nih.gov/pubmed/30992697
http://dx.doi.org/10.1186/s12014-019-9235-3
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