Bioinformatics Analysis Identifies Key Genes in Recurrent Implantation Failure Based on Immune Infiltration

MUC1 promotes RIF by regulating macrophage ROS-SHP2 signaling pathway to up-regulate inflammatory response and inhibit angiogenesis

OBJECTIVE

To explore the effect of MUC1 on recurrent implantation failure (RIF) and its molecular mechanism.

METHODS

Bioinformation analysis was used to find possible molecular mechanisms of specific genes in the pathogenesis of RIF. The number of M1 and M2 macrophages was measured by flow cytometry. Immunohistochemical staining and western blotting were used to detect the expression of related proteins. Angiogenesis capacity was measured by cell tube-formation assay.

RESULTS

Bioinformatics analysis results suggest that MUC1 may play an important role in RIF. The results of flow cytometry showed that compared with NC group, M1 macrophages increased significantly and M2 macrophages decreased significantly in MUC1 OE group. The results of immunohistochemical staining showed that MUC1 could inhibit the expression of VEGF. Western blotting results showed that MUC1 could significantly increase the expression of P22, P47, gp91, p-TBK1, IFNγ and IL-1β, and decrease the expression of p-SHP2, p-PI3K, p-mTOR, HIF1α and VEGF. After the addition of ROS inhibitor and PI3K inhibitor, the effect of MUC1 on the above proteins was eliminated. The results of tube formation experiments showed that MUC1 could inhibit vascular formation.

CONCLUSION

As a promising biomarker for the diagnosis of RIF, MUC1 can promote RIF by regulating macrophage ROS-SHP2 signaling pathway to up-regulate inflammatory response and inhibit angiogenesis.

Gene profiling reveals the role of inflammation, abnormal uterine muscle contraction and vascularity in recurrent implantation failure

Objective: Recurrent implantation failure (RIF) is now disturbing numerous infertile couples accepting assisted reproductive technology (ART). And the endometrial factors are crucial causes of recurrent implantation failure. However, its mechanism is still unclear. Thus, the aim of this study is to identify altered biologic processes in endometrium that may contribute to recurrent implantation failure. Methods: We recruited two microarray datasets (GSE103465, GSE111974) from Gene Expression Omnibus database (GEO), which contain endometrium from RIF and normal women during implantation period. Using the online tools GEO2R and Venny, we identified Differentially Expressed Genes (DEGs) of selected datasets, and obtained common DEGs. Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) and BioCatar pathway enrichment were conducted with Enrichr platform, "ssgsea" and "ggplot2" package of RStudio. PPI networks and hub gene related TF-gene interaction and TF-miRNA co-regulation networks were built via online tools STRING and NetworkAnalyst. Immune infiltration analysis was performed by CIBERSORT platform. Recurrent implantation failure subgroup identification was achieved through "ConsensusClusterPlus," "tsne," "ssgsea", and "ggpubr" package in RStudio. Diagnostic characteristic ROC curves were constructed via "pROC" and "ggplot2" package of RStudio. Enrichr platform was utilized to find drugs targeting hub genes. Results: 26 common DEGs were confirmed. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes/BioCarta analysis determined common DEGs were mainly enriched in inflammation associated pathways including TNF, NF-κB, IL-4, IL-10, IL-6, and TGF-β signaling pathways. Five hub genes (PTGS2, VCAM1, EDNRB, ACTA2, and LIF) and related TF-gene and TF-miRNA interactions were identified. Immune infiltration analysis indicated the importance of macrophage M2 in recurrent implantation failure patients. Importantly, subgroup identification analysis highlighted that recurrent implantation failure patients can be divided into two subgroups with different phenotypes. Moreover, the ROC curves and drugs may provide new diagnostic and therapeutic thought for recurrent implantation failure.