Study Objective: To introduce a method for the rapid assessment of endometriotic tissues using direct mass spectrometry (MS)-based lipidomics.

Design: A prospective observational cohort study (Canadian Task Force classification II2).

Setting: Department of Operative Gynecology of the Research Centre for Obstetrics, Gynecology and Perinatology.

Patients: Fifty patients with ovarian cysts and peritoneal endometriosis who underwent laparoscopic surgery between 2014 and 2016.

Intervention: Differences in mass spectrometric profiles of ectopic endometria (endometriosis) and eutopic endometria were analyzed for each patient in combination with morphohistologic evaluation. The lipidomic approach was applied using a direct high-resolution MS method.

Measurements And Main Results: Of 148 metabolites, 15 showed significant differences between endometriotic tissue and a healthy endometrium of the same patient, considered as a control in this study. The main lipids prevalent in endometriotic tissues were phosphoethanolamine (PE O-20:0), sphingomyelin (SM 34:1), diglycerides (DG 44:9), phosphatidylcholines (PC 32:1, PC O-36:3, PC 38:7, PC 38:6, PC 40:8, PC 40:7, PC 40:6, PC 40:9, and PC O-42:1), and triglycerides (TG 41:2, TG 49:4, and TG 52:3). Using partial least squares discriminant analysis models, MS showed that the lipidomic profile of endometriotic tissue (peritoneal endometriosis and ovarian endometriomas) was clearly separated from the eutopic endometrium, indicating tissue-type differentiation.

Conclusion: Our results suggest that direct MS may play an important role for endometriotic tissue identification. Such an approach has potential usefulness for real-time tissue determination and differentiation during surgical treatment. Lipids of 3 important classes, sphingolipids, phospholipids, and the fatty acids (di- and triglycerides), were identified. Validation is required to determine whether these lipids can be used to discriminate between patients with endometriosis and those with other gynecologic diseases.

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Source
http://dx.doi.org/10.1016/j.jmig.2017.08.658DOI Listing

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