Abstract
Insufficient endometrial receptivity is a major factor leading to implantation failure (IF), and the traditional way of morphological observation of endometrium cannot determine the condition of receptivity sufficiently. Considering that long-noncoding RNAs (lncRNAs) regulate endometrial receptivity and competing endogenous RNA (ceRNA) mechanism works in plenty of biological processes, ceRNA is likely to function in the pathology of IF. In the present study, we aim to construct an implantation failure related lncRNA-mRNA network (IFLMN), and to identify the key lncRNAs as the candidates for predicting endometrial receptivity. The global background network was constructed based on the presumed lncRNA-miRNA and miRNA-mRNA pairs obtained from lncRNASNP and miRTarBase. Differentially expressed genes (DEGs) of IF were calculated using the data of GSE26787, and then re-annotated as differentially expressed mRNAs (DEMs) and lncRNAs (DELs). IFLMN was constructed by hypergeometric test, including 255 lncRNA-mRNA pairs, 10 lncRNAs, and 212 mRNAs. Topological analysis determined the key lncRNAs with the highest centroid. Functional enrichment analyses were performed by unsupervised clustering, GO classification, KEGG pathway, and co-expression module analyses, achieving six key lncRNAs and their ceRNA sub-networks, which were involved in immunological activity, growth factor binding, vascular proliferation, apoptosis, and steroid biosynthesis in uterus and prepared endometrium for embryo implantation. Sixteen endometrial samples were collected during mid-luteal phase, including 8 recurrent implantation failure (RIF) or recurrent miscarriage (RM) women and 8 controls who conceived successfully. Quantitative real-time PCR was performed to compare the expression of the above six lncRNAs, which validated that the expression of all these lncRNAs was significantly elevated in endometrium of RIF/RM patients. Further studies are needed to investigate the underlying mechanism, and the lncRNAs may be developed into predictive biomarkers for endometrial receptivity.