Multi-omics biomarkers in endometrial receptivity: from mechanisms to clinical translation.

Background Endometrial receptivity (ER) serves as a critical determinant for successful embryo implantation, yet its molecular complexity and limited clinical assessment methods pose significant challenges. Despite advancements in assisted reproductive technology (ART), recurrent implantation failure (RIF) linked to ER abnormalities persists, creating a need for precise, non-invasive diagnostics. Main body This review outlines ER research, from the biology of the window of implantation (WOI) to the roles of immune components and the microbiome in shaping the receptive microenvironment. Multi-omics integration reveals regulatory networks across transcriptomic, epigenomic, proteomic, and metabolomic levels, with uterine fluid biomarkers emerging as promising non-invasive candidates. The analysis further covers how chronic endometritis (CE), adenomyosis, and polycystic ovary syndrome (PCOS) impair ER: through mechanisms including inflammatory imbalance, microbial dysbiosis, abnormal extracellular matrix remodeling, and hormonal dysregulation. Commercial ER tests face limitations, including insufficient evidence and inconsistent results, which undermine their clinical reliability.

A significant translational gap remains between biomarker discovery and clinical application. Current challenges involve technical standardization and data integration, and poor model generalizability. Future progress requires combining multi-omics with artificial intelligence (AI) to establish standardized clinical pathways, advancing ER assessment into precision medicine, and improving global infertility management. Similar content being viewed by others

The authors thank AJE (https://www.aje.cn/) for editing the English language. Funding This work was supported by grants from Beijing Natural Science Foundation (7234411), the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (3332023008), and China Postdoctoral Science Foundation (2023M740320). Author information Authors and Affiliations Corresponding authors Ethics declarations Ethics approval and consent to participate Not applicable. Conflict of interest The authors declare that the research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. Additional information Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Rights and permissions Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. About this article Cite this article Chen, X., Feng, P., Zhang, J. et al. Multi-omics biomarkers in endometrial receptivity: from mechanisms to clinical translation. J Transl Med (2026). https://doi.org/10.1186/s12967-026-08257-0 Received: Accepted: Published: DOI: https://doi.org/10.1186/s12967-026-08257-0