Validation of Five Gene Expression Signature for Diagnosis of Endometriosis

Study Objective To validate a complex gene expression biomarker for the diagnosis of endometriosis created based on differences between molecular signatures of endometrium from women with and without endometriosis. Design Prospective observational cohort study. II-1. Evidence obtained from a well-designed, controlled trial without randomization. Setting Department of Reproductive Medicine and Surgery at the A.I. Evdokimov Moscow State Medical and Dental University. Patients or Participants 50 women with endometriosis and 35 women without endometriosis (control group). Interventions Laparoscopic excision of endometriotic foci, hysteroscopy with endometrial sampling. RNA was isolated from all samples and stored in RNA Later. Following histologic analysis of all samples, RNA sequencing was performed using Illumina HiSeq 3000 equipment for single-end sequencing. Unique bioinformatics algorithms were validated using experimental gene expression datasets. Measurements and Main Results We performed gene expression analysis of dataset containing 100 samples (50 endometrial and 50 endometriotic) of patients with endometriosis and 35 endometrial samples from patients of control group. We created several different gene expression signatures and validated them on separated groups of samples. The final gene signature was constructed with the core genes commonly shared by all preliminary signatures. This endometrial genetic signature successfully differentiated samples of endometriotic lesions from endometrial samples of healthy women (area under the ROC curve (AUC) =0.982. The comparison of our dataset of 100 samples of endometrial and endometriotic tissue with preexisting dataset containing 120 samples of other tissues (cervix, ovary, stomach, lung) revealed high sensitivity (94%) and specificity (97%) in the ability of studied molecular signature to equally identify endometrium and endometriotic tissue of patients with endometriosis. Conclusion We obtained a complex genetic biomarker that could be potentially used as a basis for early diagnosis of endometriosis via utilization of endometrial biopsy.