Development of a Novel Endometrial Signature Based on Endometrial microRNA for Determining the Optimal Timing for Embryo Transfer.

Though tremendous advances have been made in the field of in vitro fertilization (IVF), a portion of patients are still affected by embryo implantation failure issues. One of the most significant factors contributing to implantation failure is a uterine condition called displaced window of implantation (WOI), which refers to an unsynchronized endometrium and embryo transfer time for IVF patients. Previous studies have shown that microRNAs (miRNAs) can be important biomarkers in the reproductive process. In this study, we aim to develop a miRNA-based classifier to identify the WOI for optimal time for embryo transfer. A reproductive-related PanelChip® was used to obtain the miRNA expression profiles from the 200 patients who underwent IVF treatment. In total, 143 out of the 167 miRNAs with amplification signals across 90% of the expression profiles were utilized to build a miRNA-based classifier. The microRNA-based classifier identified the optimal timing for embryo transfer with an accuracy of 93.9%, a sensitivity of 85.3%, and a specificity of 92.4% in the training set, and an accuracy of 88.5% in the testing set, showing high promise in accurately identifying the WOI for the optimal timing for embryo transfer.

A novel platform for discovery of differentially expressed microRNAs in patients with repeated implantation failure.

OBJECTIVE: To identify predictor microRNAs (miRNAs) from patients with repeated implantation failure (RIF). DESIGN: Systemic analysis of miRNA profiles from the endometrium of patients undergoing in vitro fertilization (IVF). SETTING: University research institute, private IVF center, and molecular testing laboratory. PATIENT(S): Twenty five infertile patients in the discovery cohort and 11 patients in the validation cohort. INTERVENTIONS(S): None. MAIN OUTCOME MEASURE(S): A signature set of miRNA associated with the risk of RIF. RESULT(S): We designed a reproductive disease-related PanelChip to access endometrium miRNA profiles in patients undergoing IVF. Three major miRNA signatures, including hsa-miR-20b-5p, hsa-miR-155-5p, and hsa-miR-718, were identified using infinite combination signature search algorithm analysis from 25 patients in the discovery cohort undergoing IVF. These miRNAs were used as biomarkers in the validation cohort of 11 patients. Finally, the 3-miRNA signature was capable of predicting patients with RIF with an accuracy >90%. CONCLUSION(S): Our findings indicated that specific endometrial miRNAs can be applied as diagnostic biomarkers to predict RIF. Such information will definitely help to increase the success rate of implantation practice.