The Role of Transcriptomic Biomarkers of Endometrial Receptivity in Personalized Embryo Transfer for Patients with Repeated Implantation Failure
Abstract Background: Window of implantation (WOI) displacement was known as one of endometrial origin leading to embryo implantation failure, especially for repeated implantation failure (RIF). A accurately prediction tool of endometrial receptivity (ER) is extraordinary needed to precisely guide the successful embryo implantation. We aimed to establish an RNA-seq based endometrial receptivity test tool (rsERT) using transcriptomic biomarkers, and to evaluate the benefit of personalized embryo transfer (pET) guided by this tool in patients with repeated implantation failure (RIF).Methods: Two-phase strategy including tool establishment with retrospective data and benefit evaluation with prospective, nonrandomized controlled trial. In the first phase, the rsERT was established by sequencing and analyzing the RNA of endometrial tissues from 50 infertile patients with normal window of implantation (WOI) timing. In the second phase, 142 patients with RIF were recruited and grouped by patient self-selection (experimental group, n=56; control group, n=86). pET guided by rsERT in the experimental group, and conventional ET in the control group. Results: The rsERT, comprising 175 biomarker genes, showed an average accuracy of 98.4% by using 10-fold cross-validation. IPR of experimental group (50.0%) was significantly improved compared to that (23.7%) of control group (RR, 2.107; 95% CI, 1.159 to 3.830; P = 0.017) when transferring day 3 embryos. Although not statistically different, IPR of experimental group (63.6%) was still 20 percentage points higher than that (40.7%) of control group (RR, 1.562; 95% CI, 0.898 to 2.718; P = 0.111) when transferring blastocyst. Regression analysis can precisely predict the optimal WOI time by using all samples as training dataset (R2= 0.92).Conclusions: The rsERT was developed to accurately predict WOI period and significantly improve pregnancy outcomes of patients with RIF, indicating the clinical potential of rsERT-guided pET. Optimization of the model made it possible to predict the optimal WOI by one-point sampling.Trial registration: Chinese Clinical Trial Registry: ChiCTR-DDD-17013375. Registered 14 November 2017, http://www.chictr.org.cn/index.aspx