Integrative Bioinformatics Analysis of Endometrial Transcriptome Reveals Key Regulatory Networks in Recurrent Implantation Failure
نویسندگان
1 Department of Midwifery, Islamic Azad University, Mahabad Branch, Urmia, Iran.
2 Department of Biotechnology, Iranian Research Organization for Science and Technology (IROST), Tehran, Iran.
3 Department of Medical Genetics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
4 Department of Genetics, Faculty of Advanced Sciences and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
5 Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
6 Department of Molecular Genetics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran.
doi
10.22104/mmb.2025.7743.1175چکیده
Recurrent implantation failure (RIF) is a serious clinical dilemma which occurs in assisted reproductive technologies (ART) in women who are unable to conceive after multiple embryo transfer. RIF molecular mechanisms should be elucidated in order to pursue advancement in ART.This study introduced an integrative bioinformatics approach to study publicly available RNA-Seq data with a specific focus on the endometrial transcriptome of patients with RIF.Two hundred differentially expressed genes (DEGs) were identified and characterized. Out of which, 112 genes were up regulated and 80 genes were down regulated in RIF patients compared to controls. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment showed significant involvement of biological pathways in processes related to remodeling of the extracellular matrix (ECM), immune response and angiogenesis. Similarly, there was a significant involvement of molecular signalling pathways such as the PI3K-Akt signalling pathway and MAPK signalling pathway, which contribute to the overall pathophysiology of RIF. In addition, protein-protein interaction (PPI) network analysis showed several hub genes and functional genes (pathogen nexus) that are important for regulation of cell adhesion, extracellular matrix (ECM) remodeling and angiogenesis, which were identified as ITGB3, MMP9, VEGF and FN1. Gene regulatory network (GRN) models showed several core transcriptional factors, for example NF-kB, TP53 and HIF1A, that regulate the fundamental mechanisms in each domain. Overall, this study provides new insights into the molecular bases underlying RIF and will help profile new biomarkers and therapeutic targets to support a successful pregnancy.
