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

A combined proteomic and metabolomic analysis of the early aborted embryonic tissues with maternal COVID-19 infection

COVID-19 still spreads worldwide, and repeated infections are hard to avoid. Maternal infection during pregnancy is associated with adverse maternal and neonatal outcomes. Our study used a multi-omics profiling method to explore the proteome and metabolome alteration in early embryonic development after COVID-19 infection. A total of 30 chorionic tissues after artificial abortion (15 infection and 15 no-infection samples) were collected, and the UHPLC-MS/MS and LC-MS/MS were applied in the present study. As a result, 311 significantly differentially expressed proteins were identified. The function annotations revealed that the thermogenesis pathway is the most significantly enriched signaling pathway; PRKAG2, IGF1R, and RPS6KB2 were identified as the hub proteins. There were 359 metabolites significantly altered after infection. The functional annotations revealed that amino acid metabolism was significantly affected, especially beta-alanine metabolism, glutamate metabolism, and histidine metabolism pathways. The metabolites in ovarian steroidogenesis showed a down-regulating trend in the infection group. Finally, we combined the results of proteins and metabolomics analysis. The biosynthesis of the cofactors pathway was identified as significantly enriched in both proteomics and metabolomics datasets. Our findings provide a network of protein regulation and metabolite perturbation during early embryonic development with COVID-19 infection. Our findings can provide valuable insights for further exploration of the complex mechanism of COVID-19-associated pregnancy complications and outcomes. SIGNIFICANCE: COVID-19 has developed into the most prominent and deadliest pandemic respiratory disease in the world, and repeated infections are complicated to avoid. COVID-19 infection during pregnancy increases the risk of adverse maternal and neonatal outcomes, such as preterm birth and stillbirth. However, previous studies mainly focused on its effect on pregnant women, such as the clinical characteristics and gestation outcomes. There is no relevant report about the effects of virus infection on embryos in early pregnancy. The effects of COVID-19 infection changes of the proteins and metabolites during early embryonic development are undefined. Our findings provide an association between protein regulation, metabolite perturbation, and COVID-19 infection, which can provide valuable insights for further exploration of the complex mechanism COVID-19 COVID-19-associated pregnancy complications and adverse pregnancy outcomes.

Cell type and region-specific transcriptional changes in the endometrium of women with RIF identify potential treatment targets

Recurrent implantation failure (RIF) is a devastating condition that leaves many undergoing fertility treatment childless. The human endometrium is receptive to a blastocyst for a brief period, the window of implantation. Critical knowledge underpinning biological processes leading to RIF, essential for effective treatment, is lacking. We employed spatial transcriptomics to define region- and cell-type-specific differences in endometrial gene expression in luteinizing hormone timed biopsies between women with RIF (n = 8) and fertile controls (FC) (n = 8). Differentially expressed genes (DEGs) were identified when comparing endometrial regions between FC and RIF (685 luminal epithelium, 293 glandular epithelium, 419 subluminal stroma, 264 functionalis stroma, 1,125 subluminal stromal CD45+ leukocytes, and 1,049 functionalis stromal CD56+ leukocytes). Only 57 DEGs were common to all subregions and cell types, which highlights that multiple DEGs are lost when the endometrium is examined as a single entity. When RIF-specific DEGs were leveraged against knowledge from mouse genetic models, genes associated with aberrant embryo implantation phenotypes were observed, mostly in immune cell populations. Dysregulated pathways in specific endometrial regions included the "WNT signaling pathway," altered in the functionalis and subluminal stroma. "Response to estradiol" and "ovulation cycle" pathways were dysregulated in the subluminal stroma. In silico drug screening identified potential compounds that can reverse the RIF gene expression profile (e.g., raloxifene, bisoprolol). Our findings, in a well-characterized cohort, highly endorse consideration of each endometrial region and cell type as separate entities. Ignoring individual regions and composite cell populations will overlook important aberrations, forego potential treatment targets, and lead to research waste pursuing clinically irrelevant treatment options.

Identification of m6A methyltransferase-related WTAP and ZC3H13 predicts immune infiltrates in glioblastoma

Glioblastoma (GBM) is a prevalent and highly fatal primary malignant brain tumor. N6-methyladenosine (m6A) modification plays a critical role in the development of brain tumor. WTAP and ZC3H13 have been identified across various species. Immune contexture, which includes the tumor microenvironment (TME), plays a significant role in cancer progression and treatment. This study aimed to explore the potential impact between WTAP and ZC3H13 on the immunological characteristics of GBM. We utilized data from TCGA-GBM, GEO and CGGA datasets to obtain platform and probe data. Patients with GBM were stratified into two clusters based on the expression of WTAP and ZC3H13 using consensus clustering approach. Immune infiltration within the tumor microenvironment was assessed using ESTIMATE, CIBERSORT and ssGSEA methodologies. Functional disparities were determined through gene set enrichment analysis (GSEA). Tumor mutation burden (TMB) and immune checkpoint inhibitors (ICIs) were also analyzed. Co-expression network analysis (WGCNA) was used to identify genes associated with WTAP/ZC3H13 and immunity. Validation was performed using GEO and CGGA datasets. Our analysis revealed that cluster1 exhibited higher WTAP expression but lower ZC3H13 expression compared to cluster2. Cluster1 showed higher levels of immune infiltration and TMB compared to cluster2. WGCNA identified 15 genes closely associated with WTAP/ZC3H13 expression and immune scores, notably CTLA4, CD27, ICOS, and LAG3. Our results suggested that WTAP and ZC3H13 influence on immune contexture of GBM, providing new insights into tumor immunity in GBM.

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.