Can chemokines be used as biomarkers for endometriosis? A systematic review
Abstract
STUDY QUESTION: Can we use chemokines as biomarkers to diagnose patients with endometriosis in clinical practice? SUMMARY ANSWER: Some chemokines, especially CXCL8 (IL-8), CCL-2 (MCP-1) and CCL5 (RANTES), have the potential to work as biomarkers to identify patients with endometriosis but their accuracy could be improved by combination with other non-inflammatory markers in a panel of biomarkers. WHAT IS ALREADY KNOWN: The need for a good marker to diagnose endometriosis has increased in recent years and research in this field has intensified. Chemokines have been reported to be associated with endometriosis in several studies over the last 20 years. Many of these studies measured one or more chemokines in peritoneal fluid (PF) and peripheral blood (PB) or through endometrial biopsies in patients with and without endometriosis. STUDY DESIGN, SIZE, DURATION: A systematic review was done on all published studies that compared chemokine concentrations in patients with and without endometriosis to evaluate their potential as biomarkers for the disease. PARTICIPANTS/MATERIALS, SETTING, METHODS: Using MEDLINE database from December 1993 to August 2013 and the MeSH terms 'Endometriosis' and 'Chemokines', we identified relevant studies to include in the present review, which was based on the PRISMA statement. Studies that measured at least one chemokine in patients with endometriosis and matching controls in PB, PF or endometrial samples were included. We did not include samples from ectopic lesions. All review articles as well as studies with animals and those not written in English were excluded from this systematic review. The studies were assessed using a modified version of the Quality Assessment of Diagnostic Accuracy Studies criteria. Two authors independently assessed studies for inclusion and risk of bias, and extracted data. MAIN RESULTS AND THE ROLE OF CHANCE: After inclusion and exclusion criteria, 62 studies were selected to be included in this systematic review. A total of 27 different chemokines or their receptors were evaluated in the reviewed studies. The most studied chemokines (including their receptors) were CXCL8 (51.6%), CCL2 (38.7%) and CCL5 (19.3%) (% of studies). CXCL8 (IL-8) appears to have the best results among all the other chemokines as a marker for endometriosis. LIMITATIONS, REASONS FOR CAUTION: Some studies included have low power due to small sample size and study designs vary in the assessment criteria for the markers, the state of the patients (e.g. phase of the cycle and stage of disease) and the nature of the controls. WIDER IMPLICATIONS OF THE FINDINGS: Our findings could guide future research in this field to select the chemokines with the best potential, and to stimulate better-designed studies to determine whether they can become a useful diagnostic tool in clinical practice. STUDY FUNDING/COMPETING INTEREST(S): There was no funding to support this systematic review. The authors have no competing interest to declare.
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In peripheral blood, IL-8, MCP-1, and RANTES showed potential as biomarkers, being significantly increased in endometriosis cases versus controls in 46.1%, 50%, and 75% of assessed studies, respectively.
“In peripheral blood, IL-8, MCP-1, and RANTES showed potential as a biomarker, being significantly increased in endometriosis cases versus controls in, respectively, 46.1%, 50%, and 75% of the assessed studies [54].”
From Update on biomarkers for the detection of endometriosis (2015) · cites this paper as [54]
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The link between immunity, autoimmunity and endometriosis: a literature update
Zhang, T., De Carolis, C., Man, G. C. W., & Wang, C. C. (2018) · Autoimmunity Reviews · doi:10.1016/j.autrev.2018.03.017 · Cited by 196 · see citing works
Update on biomarkers for the detection of endometriosis
Fassbender, A., Burney, R. O., F. O, D., D’Hooghe, T., & Giudice, L. (2015) · BioMed Research International · doi:10.1155/2015/130854 · Cited by 195 · see citing works
“1%, 50%, and 75% of the assessed studies [54].”
New biomarkers in endometriosis
(2019) · Advances in clinical chemistry · doi:10.1016/bs.acc.2018.12.002 · Cited by 72 · see citing works
Overall Adiposity, Adipose Tissue Distribution, and Endometriosis: A Systematic Review
Backonja, U., Buck Louis, G. M., & Lauver, D. R. (2016) · Nursing Research · doi:10.1097/nnr.0000000000000146 · Cited by 39 · see citing works
- Authors
- Borrelli, G. M., Abrao, M. S., & Mechsner, S.
- Affiliations
- Universidade de São Paulo (BR)
- Charité – Universitätsmedizin Berlin (DE)
- Corresponding author
- Borrelli, G. M.
- ORCID
- Mechsner, S.
- Venue
- Human Reproduction
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-11-27
- Volume
- 29
- Issue
- 2
- Pages
- 253-266
- ISSN
- 0268-1161 (ISSN-L)
- 1460-2350
- OpenAlex
- W2169573141
- Cited by
- 102
- References
- 90
- Citations by year
- 2026: 9 · 2025: 7 · 2024: 7 · 2023: 7 · 2022: 9 · 2021: 5 · 2020: 12 · 2019: 7 · 2018: 5 · 2017: 12 · 2016: 8 · 2015: 10 · 2014: 4
- FWCI
- 1.18
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Human Reproduction (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Reproductive Medicine › Endometriosis Research and Treatment
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ectopic Pregnancy Diagnosis and Management
- Health Sciences › Medicine › Obstetrics and Gynecology › Endometrial and Cervical Cancer Treatments
- Keywords
- endometriosis, chemokines, biomarkers, diagnostic accuracy, interleukin-8, CCL2/MCP-1, CCL5/RANTES, peritoneal fluid, peripheral blood, endometrial biopsy, chemokine receptors, biomarker panel, inflammation, risk of bias, risk of bias assessment
- MeSH terms
- Ascitic Fluid, Endometriosis, Endometrium, Female, Humans, Inflammation, Biomarkers, Interleukin-8, Chemokines, Chemokine CCL2, Chemokine CCL5
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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