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. (Fertil Steril Ò 2021;116:181-8. Ó2021 by American Society for Reproductive Medicine.) El resumen está disponible en Español al final del artículo.

Though tremendous advances have been made in the field of in vitro fertilization (IVF), a portion of patients are still troubled by embryo implantation failure issues. One of the significant factors contributing to implantation failure is a uterine condition called the displaced window of implantation (WOI), which results in an unsynchronized endometrium and embryo transfer time for IVF patients during treatment. Previous studies have shown that microRNAs (miRNAs) can be important indicators in the reproductive process, regulating important functions such as embryo development, organ development, and cytokinesis. In this study, we have built and validated a microRNA-based prediction model for analyzing endometrial receptivity to identify the WOI of patients undergoing frozen embryo transfer cycles. Based on miRNA biomarkers’ expression profiles, a miRNA-based classifier was built with an accuracy of 94% in the training set and 89% in the testing set, showing high promise in accurately identifying the ideal time for embryo transfer (WOI).