Unraveling the H19/GAS1 axis in recurrent implantation failure: A potential biomarker for diagnosis and insight into immune microenvironment alteration.

Recurrent implantation failure (RIF) presents a significant clinical challenge due to the lack of established diagnostic and therapeutic guidelines. Emerging evidence underscores the crucial role of competitive endogenous RNA (ceRNA) regulatory networks in non-cancerous female reproductive disorders, yet the intricacies and operational characteristics of these networks in RIF are not fully understood. This study aims to demystify the ceRNA regulatory network and identify potential biomarkers for its diagnosis. We analyzed expression profiles of three RNA types (long noncoding RNAs [lncRNAs], microRNAs [miRNAs], and mRNAs) sourced from the GEO database, leading to the identification of the H19-hsa-miR-301a-3p-GAS1 ceRNA network. This network demonstrates significant diagnostic relevance for RIF. Notably, the H19/GAS1 axis within this ceRNA network, identified through correlation analysis, emerged as a promising diagnostic marker, as evidenced by operating receiver operator characteristic (ROC) curve analysis. Further investigation into the binding potential of miR-301a-3p with H19 and GAS1 revealed a close association of these genes with endometrial disorders and embryo loss, as per the Comparative Toxicogenomics Database. Additionally, our immune infiltration analysis revealed a lower proportion of T cells gamma delta (γδ) in RIF, along with distinct differences in the expression of immune cell type-specific markers between fertile patients and those with RIF. We also observed a correlation between aberrant expression of H19/GAS1 and these immune markers, suggesting that the H19/GAS1 axis might play a role in modifying the immune microenvironment, contributing to the pathogenesis of RIF. In conclusion, the ceRNA-based H19/GAS1 axis holds promise as a novel diagnostic biomarker for RIF, potentially enhancing our understanding of its underlying mechanisms and improving the success rates of implantation.