Multi-omics analysis reveals shared diagnostic and therapeutic targets in endometriosis and recurrent implantation failure

Endometrial receptivity is essential for successful pregnancy, and endometriosis is widely recognized as a disruptor of this process. Poor endometrial receptivity is also a key factor contributing to recurrent implantation failure. Although some molecular mechanisms related to endometrial receptivity have been identified, their specific roles in endometriosis and recurrent implantation failure remain unclear. This study aimed to elucidate the shared molecular mechanisms affecting endometrial receptivity in endometriosis and recurrent implantation failure using multi-omics data analysis. We sourced datasets from the NCBI GEO database and employed weighted gene co-expression network analysis to identify gene modules associated with these conditions, followed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Single-cell Sequencing analysis and immunofluorescence were used for expression analysis. We identified 3690 and 4892 upregulated genes and 2675 and 5065 downregulated genes in endometriosis and recurrent implantation failure, respectively. Functional enrichment analysis and validation identified 15 hub genes including SRPRB, SLC35B1, and SLC25A6. Receiver operating characteristic curve analysis demonstrated that these genes are associated with high diagnostic accuracy. Single-cell Sequencing analysis indicated that these genes are predominantly expressed in basal epithelial cells, with RBM3 being particularly prominent. This study provides new insights into the molecular mechanisms underlying endometrial receptivity and identifies potential targets for the diagnosis and treatment of endometriosis and recurrent implantation failure.

Core genes; Diagnostic biomarkers; Endometrial receptivity; Endometriosis; Recurrent implantation failure; Weighted gene co-expression network analysis.