Evaluation of endometrial receptivity using the level of small non-coding RNAs in uterine aspirate from women undergoing cyclic hormone therapy

Modern methods of diagnosing endometrial receptivity which have been introduced into clinical practice (ERA, Igenomix; ER-Map, iGLS; ERPeak, CooperGenomics), are based on transcriptome analysis of invasively obtained endometrial tissue; therefore, embryo cannot be transferred in the same cycle when endometrial biopsy is performed.

Objective: To evaluate endometrial receptivity by determining the number of small non-coding RNAs (ncRNAs) in uterine fluid (UF) on the day of cryopreserved embryo (CE) transfer in women receiving cyclic hormone therapy (CHT) and to develop a logistic regression model for calculating the optimal endometrial receptivity for embryo implantation by comparing the UF transcriptome from patients with positive and negative outcomes of the ART program.

Materials and methods: The study included 54 women whose UF was aspirated in a volume of 5–50 µl depending on the level of its secretion immediately before the CE transfer with the help of a catheter (COOK, Australia). Small ncRNAs isolated from UF with the miRNeasy Serum/Plasma Kit (Qiagen) were analyzed using deep sequencing on the NextSeq 500/550 platform (Illumina, USA); the obtained data were subsequently validated with real-time quantitative PCR using the miScript II RT Kit and miScript SYBR Green PCR Kit (Qiagen, Hilden, Germany).

Results: The UF samples were classified into two groups: receptive endometrium and non–receptive endometrium depending on the results of the ART program (the presence and absence of implantation, respectively). Seven logistic regression models were developed on the basis of the small ncRNAs profile in the UF samples and endometrial thickness at the time of embryo transfer into the uterine cavity. The most accurate model appears to be the combination of content of miR-1180-3p in UF and endometrial thickness (71% sensitivity, 88% specificity) due to the lack of dependence of the variables using Spearman correlation analysis (r=0.02, p=0.9) and the statistical significance of all values included in the model (p<0.05).

Conclusion: The effectiveness of ART treatment can be improved owing to the individual approach in determining the implantation window during IVF in women receiving CHT and identifying the level of small ncRNAs in UF. The use of the logistic regression model which was developed in this study is limited in clinical practice due to the lack of information about the implantation potential of the blastocyst transferred into the uterine cavity. It is the poor quality of the embryo itself rather than the absence of the receptive endometrium that may result in a negative outcome of the ART program. Simultaneous determination of endometrial receptivity and embryo implantation potential on the basis of the small ncRNA profile can lead to a decrease in the percentage of false-negative results and improve the quality of the model. It is necessary to increase the training set of participants and to check the accuracy of the constructed models on an independent test set.