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Menstrual Fluid-Derived Small Extracellular Vesicles: A Novel Reservoir with Distinct Molecular Signatures and Implications for Endometriosis Etiopathology

GSE310627 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2026/04/08 Platform GPL24676
Summary
STUDY QUESTION: Can the transcriptomic profile of small extracellular vesicles (sEV) derived from menstrual fluid (MF) provide insight into their potential roles as biomarkers and mediators in endometriosis (EM) development? SUMMARY ANSWER: MF-derived sEV from EM patients display altered molecular signatures reflective of EM pathophysiology and exhibit enhanced proangiogenic activity in vitro. WHAT IS KNOWN ALREADY: EM is a chronic gynecological disorder affecting approximately 10% of reproductive-age women, associated with pain, infertility, and delayed diagnosis. Small extracellular vesicles carry cargo that resembles their cellular origin, making them promising biomarkers for various diseases. While sEV have previously been isolated from MF and their protein content analyzed, their transcriptomic profile and angiogenic potential remain unexplored. STUDY DESIGN, SIZE, DURATION: The two cross-sectional study involved cohorts of nulliparous (n = 10) and multiparous (n = 12) women, EM (n = 10) and control (n = 11) patients, recruited at the Obstetrics and Gynecology Unit of Clínica Universidad de los Andes, Santiago, Chile. Peripheral blood was collected by a trained midwife and MF was self-collected using a menstrual cup on the second day of menses. PARTICIPANTS/MATERIALS, SETTING, METHODS: sEV were isolated from the plasma fraction of MF and from peripheral blood plasma. Nanoparticle tracking analysis, transmission electron microscopy, and FACS were used to assess sEV concentration, size, morphology, and tetraspanin expression. Next-generation sequencing was performed to analyze sEV transcriptomic profiles, and proangiogenic function was assessed through endothelial tubule formation assays using human umbilical vein endothelial cells (HUVECs). MAIN RESULTS AND THE ROLE OF CHANCE: MF-sEV exhibited canonical sEV characteristics and were significantly more abundant than those isolated from peripheral blood (P = 0.008). Neither parity nor disease affected MF-sEV concentration or size; however, CD63 expression was significantly reduced in sEV from nulliparous women and EM patients (P =0.02). Transcriptomic analysis revealed unique mRNAs and long noncoding RNAs (lncRNAs) signatures that reflect their contribution to disease etiopathology. Functionally, EM-derived sEV, significantly enhanced tubule formation in vitro (P < 0.05), supporting their proangiogenic role in EM. LARGE SCALE DATA: Raw sequencing data has been submitted to GEO. LIMITATIONS, REASONS FOR CAUTION: While sample size was sufficient for initial characterization and the in vitro validation, larger cohorts and in vivo studies are necessary to confirm these findings and clarify the molecular mechanisms underlying sEV proangiogenic effects. WIDER IMPLICATIONS OF THE FINDINGS: The non-invasive isolation and disease-associated transcriptomic signatures of MF-sEV highlights their potential as biomarkers for EM. The current gold-standard for EM diagnosis is invasive laparoscopic surgery, resulting in delayed identification and staging of the disease. The proangiogenic effect of MF-sEV observed in vitro suggest that their cargo may offer relevant insights into disease progression and response to treatment. These findings are in line with a recent report that explored the proteome of MF-sEV from EM patients, demonstrating their involvement in mesothelial barrier disruption, which reinforces the role of MF-sEV in EM progression.
Published in
Menstrual fluid-derived small extracellular vesicles: a novel reservoir with distinct molecular signatures and implications for endometriosis etiopathology
Peragallo-Papic V, Cerda-Castro P, Figueroa-Valdés AI et al. · Human reproduction open 2026 · PMID 41924633 · doi:10.1093/hropen/hoag020
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Also filed as BioProject PRJNA1366604 and SRA study SRP647022. Searching any of these in the dataset finder brings you back here.

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