MMP-9 as a clinical marker for endometriosis: a meta-analysis and bioinformatics analysis

Abstract

Aim: This study systematically evaluated the potential efficacy of serum matrix metalloproteinase-9 (MMP-9) concentration as a diagnostic marker for endometriosis through meta-analysis. Early and accurate diagnosis of endometriosis, a common gynecological disease, is crucial for improving patient prognosis. Hence, this study aimed to comprehensively analyze the data from multiple studies to assess the diagnostic value of serum MMP-9 concentration for endometriosis. Methods: Articles investigating the association between MMP-9 and endometriosis, published from the inception of the databases until February 2024, were systematically retrieved from multiple databases, including PubMed, Embase, Cochrane, Web of Science, Scopus, and CNKI. Download and analyze the GSE7305, GSE23339, and GSE51981 datasets. Statistical analyses of all eligible studies were conducted using RevMan 5.4, Stata 11.0, and R software version 4.3.3. Results: Fifteen studies fully met the inclusion criteria for the meta-analysis. The concentration of MMP-9 in the blood of patients with endometriosis was significantly higher compared to that of the control group (p < 0.0001). Subgroup analysis based on different stages of endometriosis revealed a trend towards significantly higher serum MMP-9 concentrations in patients, whether in stages I-II or III-IV. Bioinformatics analysis revealed differences in the expression of MMP-9 in endometrial tissue between EMT patients and healthy controls in the GSE7305 and GSE23339 datasets. Additionally, in the GSE51981 dataset, we found significant differences between the normal group and both mild and severe cases of endometriosis. Conclusion: Both the current meta-analysis and bioinformatics analysis indicate differences in MMP-9 concentration levels between endometriosis patients and healthy individuals, with potentially elevated MMP-9 concentrations in serum samples from patients with endometriosis. Systematic review registration: https://www.crd.york.ac.uk/prospero, identifier CRD42024525864.