Different Dosages of Progesterone in Luteal Phase Support Reflect Varying Endometrial microRNA Expression in Frozen Embryo Transfer Cycles.

Despite serum progesterone being a widely accepted method for luteal phase support during embryo transfer cycles, debates persist regarding the optimal strategy for guiding clinical decisions on progesterone dosages to maximize reproductive outcomes. This retrospective study explored the utility of microRNA (miRNA) biomarkers in guiding personalized progesterone dosage adjustments for frozen embryo transfer (FET) cycles in 22 in vitro fertilization (IVF) patients undergoing hormone replacement therapy. Utilizing MIRA, an miRNA-based endometrial receptivity test, we analyzed patients' miRNA expression profiles before and after progesterone dosage adjustments to determine suitable dosages and assess endometrial status. Despite patients receiving identical progesterone dosages, variations in miRNA profiles were observed in the initial cycle, and all patients presented a displaced window of implantation. Following dosage adjustments based on their miRNA profiles, 91% of patients successfully transitioned their endometrium towards the receptive stages. However, two patients continued to exhibit persistent displaced receptivity despite the adjustments. Given the evident variation in endometrial status and serum progesterone levels among individuals, analyzing miRNA expression profiles may address the challenge of inter-personal variation in serum progesterone levels, to deliver more personalized dosage adjustments and facilitate personalized luteal phase support in IVF.

Development of a Predictive Model for Optimization of Embryo Transfer Timing Using Blood-Based microRNA Expression Profile.

MicroRNAs (miRNAs) can regulate the expression of genes involved in the establishment of the window of implantation (WOI) in the endometrium. Recent studies indicated that cell-free miRNAs in uterine fluid and blood samples could act as alternative and non-invasive sample types for endometrial receptivity analysis. In this study, we attempt to systematically evaluate whether the expression levels of cell-free microRNAs in blood samples could be used as non-invasive biomarkers for assessing endometrial receptivity status. We profiled the miRNA expression levels of 111 blood samples using next-generation sequencing to establish a predictive model for the assessment of endometrial receptivity status. This model was validated with an independent dataset (n = 73). The overall accuracy is 95.9%. Specifically, we achieved accuracies of 95.9%, 95.9%, and 100.0% for the pre-receptive group, the receptive group, and the post-respective group, respectively. Additionally, we identified a set of differentially expressed miRNAs between different endometrial receptivity statuses using the following criteria: p-value < 0.05 and fold change greater than 1.5 or less than -1.5. In conclusion, the expression levels of cell-free miRNAs in blood samples can be utilized in a non-invasive manner to distinguish different endometrial receptivity statuses.

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.

A Novel Multi-Gene Detection Platform for the Analysis of miRNA Expression.

The study of miRNAs and their roles as non-invasive biomarkers has been intensely conducted in cancer diseases over the past decade. Various platforms, ranging from conventional qPCRs to Next Generation Sequencers (NGS), have been widely used to analyze miRNA expression. Here we introduced a novel platform, PanelChip™ Analysis System, which provides a sensitive solution for the analysis of miRNA levels in blood. After conducting miRQC analysis, the system's analytical performance compared favorably against similar nanoscale qPCR-based array technologies. Because PanelChip™ requires only a minimal amount of miRNA for analysis, we used it to screen for potential diagnostic biomarkers in the plasma of patients with oral cavity squamous cell carcinoma (OSCC). Combining the platform with a machine learning algorithm, we were able to discover miRNA expression patterns capable of separating healthy subjects from patients with OSCC.