Human endometriosis is associated with plasma cells and overexpression of B lymphocyte stimulator

B Cell Lineage in the Human Endometrium: Physiological and Pathological Implications

Immunocompetent cells of B lineage function in the humoral immunity system in the adaptive immune responses. B cells differentiate into plasmacytes upon antigen-induced activation and produce different subclasses of immunoglobulins/antibodies. Secreted immunoglobulins not only interact with pathogens to inactivate and neutralize them, but also involve the complement system to exert antibacterial activities and trigger opsonization. Endometrium is a mucosal tissue that lines the mammalian uterus and is indispensable for the establishment of a successful pregnancy. The lymphocytes of B cell lineage are a minority in the human cycling endometrium. Human endometrial B cells have therefore been understudied so far. However, the disorders of the female reproductive tract, including chronic endometritis and endometriosis, have highlighted the importance of further research on the endometrial B cell lineage. This review aims to revisit lymphopoiesis, maturation, commitment, and survival of B cells, shedding light on their physiological and pathological implications in the human endometrium.

Evaluation of Thrombomodulin, hsa-miR-18a-5p, and hsa-miR-18b-5p as Potential Prognostic Biomarkers in Uterine Corpus Endometrial Carcinoma

Thrombomodulin (THBD), hsa-miR-18a-5p, and hsa-miR-18b-5p have been frequently mentioned in numerous cancer-related research studies; however, their specific functions in uterine corpus endometrial carcinoma (UCEC) are not well understood. This study aimed to investigate the roles of THBD, hsa-miR-18a-5p, and hsa-miR-18b-5p within a UCEC cohort. We utilized various web-based tools, including GEPIA2, UALCAN, Human Protein Atlas (HPA), TNM Plot, STRING, TargetScan, and ENCORI for our analysis. The expression level of the THBD gene was found to be significantly downregulated (p < 0.05) in UCEC tissue compared to adjacent normal tissue. In contrast, hsa-miR-18a-5p and hsa-miR-18b-5p were both upregulated in UCEC tissue (p < 0.05). Additionally, THBD exhibited a significant hypermethylation level in UCEC tissue (p < 0.05). The elevated expression of hsa-miR-18a-5p was linked to a shorter overall survival (OS) (p = 0.025), while THBD and hsa-miR-18b-5p showed no association with OS (p = 0.87 and p = 0.56, respectively). Notably, THBD expression was significantly negatively correlated with hsa-miR-18a-5p (p = 0.00407), whereas no significant correlation was found between THBD and hsa-miR-18b-5p (p = 0.25). Thus, it can be concluded that increased levels of miR-18a-5p in the UCEC cohort may serve as a negative prognostic marker and a potential therapeutic target. However, further studies are necessary to validate the implications of decreased THBD and increased miR-18b-5p expression levels on the clinical outcomes of these patients.

A transcriptomic analysis of the interplay of ferroptosis and immune filtration in endometriosis and identification of novel therapeutic targets

Endometriosis is an inflammatory disease, involving immune cell infiltration and production of inflammatory mediators. Ferroptosis has recently been recognized as a mode of controlled cell death and the iron overload and peroxidative environment prevailing in the ectopic endometrium facilitates the occurrence of ferroptosis. In the current investigation, gene expression data was obtained from the dataset GSE7305.The variation in infiltration of immune cells amongst the samples with endometriosis and normal tissue was analysed using the CIBERSORTx tool which revealed higher infiltration of T cells gamma delta, macrophages M2, B cells naïve, T cells CD4 memory resting cells, plasma cells, T cells CD8 and mast cells activated in the tissue samples with endometriosis. An overlap of the differentially expressed genes (DEGs) and ferroptosis related genes revealed 32 ferroptosis related DEGs (FR-DEGs). GO and KEGG pathway analysis showed the FR-DEGs to be enriched in ferroptosis. The PPI network of the FR-DEGs was constructed and TP53, HMOX1, CAV1, CDKN1A, CD44, EPAS1, SLC2A1, MAP3K5, GCLC and FANCD2 were identified as the hub genes. Pearson correlation revealed significant correlation between the hub genes and infiltrating immune cells in endometriosis, thereby suggesting existence of a regulatory crosstalk between immune responses and ferroptosis in endometriosis. Hub gene- miRNA network analysis revealed that 7 of the 10 hub genes were targets of 3 miRNAs -hsa-miR-20a-5p, hsa-miR-16-5p and hsa-miR-17-5p, thereby providing further insight into the regulatory mechanisms underlying disease progression. Predictive analysis and cross validation studies revealed TP53 and CDKN1A as common targets of hsa-miR-16-5p, hsa-miR-17-5p, and hsa-miR-20a-5p, thereby revealing their regulatory roles in ferroptosis and immune modulatory pathways relevant to endometriosis. The present study indicates an important role of both immune dysregulation and ferroptosis in the pathogenesis of endometriosis and identifies ferroptosis related hub genes and their miRNA regulators as favourable novel targets for further studies and therapeutic interventions.

How telomere maintenance affects endometriosis development: a preliminary study

Background: Endometriosis results in dysmenorrhea, dyspareunia, chronic pelvic pain and infertility in reproductive-age women. However, no effective treatment methods have been applied to the disease, and the pathogenesis of endometriosis is unclear. Purpose: This study was performed to investigate the association between telomere maintenance and endometriosis development. Materials and methods: The telomere length of the postmenopausal endometria, eutopic endometria and their matched ectopic lesions in the proliferative and secretory phases was detected using fluorescence in situ hybridization (FISH) methods, and the effect of telomere length maintenance on the proliferation of endometrial cells derived from endometriotic patients was determined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay with BIBR1532 treatment. Then all of the telomere maintenance genes were extracted from the Telnet database, and bioinformatics analysis was performed to uncover the role of telomere maintenance genes in endometriosis development. Results: Telomere length was longer in endometriotic patients' eutopic endometria during the proliferative and secretory phases, and treatment with a telomerase inhibitor inhibited the proliferation of epithelial cells and stromal cells. Furthermore, the telomere maintenance genes were enriched in several hormone-related pathways, with several genes differentially expressed between normal endometria and endometria derived from endometriotic patients. The nomogram constructed based on telomere maintenance genes also displayed good predictive value. Conclusions: Telomere maintenance may contribute to the development of endometriosis, with several related genes involved.

MEIS1-mediated Apoptosis via TNFR1 in Endometriosis

Abnormal apoptosis both maintains endometrial cell growth and induces endometrial pathogenesis. The etiology of endometriosis is unclear and no treatment is curative. Therefore, the aim herein was to identify genes involved in the pathogenesis of endometriosis. Using the data from our previous results and RNA sequencing data of normal endometrial tissue and ovarian endometrioma (OMA) tissue, along with Gene Expression Omnibus (GEO) dataset on endometriosis, we identified an apoptotic-related gene, meis homeobox I (MEIS1). Normal endometrium, eutopic endometrium and ectopic endometriotic tissues were used to detect MEIS1. Primary normal endometrial and eutopic endometrial stromal cells were isolated and cultured for exploring the function of MEIS1 and related pathways. A mouse endometriosis model was used to verify the therapeutic effects of MEIS1. The mRNA and protein of MEIS1 in tissues from patients with endometriosis were decreased. Overexpression of MEIS1 induced the apoptosis of primary eutopic endometrium stromal cells by regulating TNFR1. Using Cell Counting Kit 8 (CCK8) assay and EdU assay, we found that knockdown of MEIS1 promoted the proliferation of primary normal endometrium stromal cells. We also observe that upregulated MEIS1 may lead to caspase pathway activation, promoting endometrial cell apoptosis. Furthermore, MEIS1 lentivirus inhibited endometriotic lesion formation and induced apoptosis in the mouse endometriosis model. These cumulative findings suggest that MEIS1 may mediate apoptosis by initiating TNFR1 in endometrial cells via the caspase pathway.

The NLRP3 activation-related signature predicts the diagnosis and indicates immune characteristics in endometriosis

Endometriosis (EMS) is a prevalent gynecological disease that leads to chronic pelvic pain and infertility in women of reproductive age. However, the underlying pathogenic genes and effective treatment for EMS remain unclear. Therefore, this study aims to identify key genes influencing the diagnosis and treatment of EMS. The GSE7307 dataset, comprising 18 EMS and 23 control samples, was obtained from the GEO database. Fourteen differential genes related to NOD-like receptor protein 3 (NLRP3) activation and EMS were extracted from endometrial samples in GSE7307 through differential analysis. GO and KEGG analyses revealed that these genes were primarily involved in the production and regulation of the cytokine IL-1β and the NOD-like receptor signaling pathway. Random Forest (RF) and support vector machine recursive feature elimination algorithms were employed to select four diagnostic markers related to NLRP3 activation (NLRP3, IL-1β, LY96, and PDIA3) for constructing the EMS diagnostic model. These markers were validated using western blotting and tested in GSE7305 and GSE23339 datasets. The AUC values demonstrated the model's robust diagnostic performance. Additionally, the infiltration of immune cells in the samples and the correlation between different immune factors and diagnostic markers were explored. These results suggest that the four diagnostic markers may also play a crucial role in EMS immunity. Finally, the DrugBank database indicated that niclosamide could be effective for NLRP3-targeted therapy. In conclusion, we identified four key diagnostic genes for EMS, and niclosamide emerged as a potential drug for NLRP3-targeted therapy in EMS.

Potential Role of Menstrual Fluid-Derived Small Extracellular Vesicle Proteins in Endometriosis Pathogenesiss

Endometriosis, a chronic debilitating disease affects 1 in 7-10 girls and women, who have symptoms of severe chronic pain and subfertility and significantly impacts the overall quality of life. Currently, no effective early diagnostic methods are available for early stages of endometriosis. We used menstrual fluid-derived small extracellular vesicles (MF-sEVs) from women with self-reported endometriosis (laparoscopically diagnosed, n = 8) and self-reported without endometriosis and no painful periods (n = 9). MF-sEVs were separated using differential ultracentrifugation and characterised using nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM), Western Blot, flow cytometry, mass-proteomics analysis and functional assays. Spherical-shaped sEVs were identified with a median diameter of ∼120 nm, expressing sEV marker proteins. The MF-sEV proteins were classified as endometrial origin. Over 5000 proteins were identified, ∼77% of which were decreased whilst only 22 proteins (largely comprising immunoglobulins) were increased in endometriosis/MF-sEVs compared to control/MF-sEVs. Decreased proteins were involved in nitrogen compound metabolism, immune response, intracellular signal transduction, regulation of programmed cell death, maintenance of cell polarity and actin cytoskeleton organisation. Flow cytometry demonstrated a significant increase in CD86 expression (immune activation marker) in endometriosis/MF-sEVs. Mesothelial cells showed a significant decrease in cellular resistance and junctional protein expression. MF-sEVs are possible contributors to the pathogenesis of endometriosis and may have the potential for early detection of the disease.

CD56-Positive NK Cells and CD138-Positive Plasma Cells in Basal Decidua of Term Placentas in Singleton Pregnancies After Assisted Reproductive Technology Treatment of Endometriosis-Related Infertility

A eutopic endometrium in endometriosis shows altered immune responses, including abnormalities of NK cells and expression of plasma cells, related to reproductive issues. This study investigated the counts of CD56-positive NK cells and CD138-positive plasma cells in the basal decidua of term placentas in singleton pregnancies after endometriosis-related infertility conceived by assisted reproductive technology (ART). This single-center, case-control study involved immunohistochemical analysis of CD56-positive NK cells and CD138-positive plasma cells in basal decidua using primary monoclonal mouse antibodies, followed by secondary antibodies using a standardized protocol. CD56 and CD138 immunohistochemically positive cells were reported as the total cell count for each studied antibody expressed per 1 mm2 of basal decidua (Olympus BX46 and Olympus Image Analyzer). Placental samples containing basal decidua from 36 participants with endometriosis-related infertility who conceived by ART, 31 participants with male factor infertility who conceived by ART and 40 healthy controls were included. Endometriosis decidua showed the lowest median count of CD56-positive NK cells (11.5 / mm2, p = 0.039) in BD compared to male factor group (25 / mm2) and healthy controls (24.5 / mm2). No differences were found for CD138-positive plasma cells counts between study groups. Basal decidua in pregnancies after endometriosis-related infertility showed reduced total count of CD56-positive NK cells, without differences in the CD138-positive plasma cell counts compared to control groups. Future studies should investigate how changes in NK cells throughout pregnancy affect the development of perinatal complications and placental pathologies in women with endometriosis, which could uncover potential diagnostic and therapeutic targets.

Bioinformatic Analysis of m6A Regulator-Mediated RNA Methylation Modification Patterns and Immune Microenvironment Characterization in Endometriosis

Epigenetic regulation plays an essential role in immunity and inflammation in endometriosis. In this study, we aimed to explore differences in m6A regulators between endometriosis patients and normal women and analyze the effect of m6A modification on immune and inflammatory microenvironment. The samples for analysis were downloaded from the Gene Expression Omnibus database, including ectopic endometrium (EC), eutopic endometrium (EU), and normal eutopic endometrium (NM) samples from non-endometriosis women. The validation process involved utilizing our previous RNA-sequencing data. Subsequently, a correlation analysis was performed to ascertain the relationship between m6A and the inflammatory microenvironment profile, encompassing infiltrating immunocytes, immune-inflammation reaction gene sets, and human leukocyte antigen genes. LASSO analyses were used to develop risk signature. The findings of this study indicate that the m6A regulators FTO were observed to be significantly up-regulated, while YTHDF2, CBLL1, and METTL3 were down-regulated in endometriosis tissues. The CIBERSORT analysis revealed that the local inflammatory microenvironment of ectopic lesions plays a crucial role in the development of endometriosis. Notably, M2 macrophages exhibited a significant difference between the EC and NM groups. Moreover, M2 macrophages demonstrated a positive correlation with FTO (0.39) and a negative correlation with CBLL1 (- 0.35). Furthermore, consistent clustering of EC and EU samples resulted in the identification of three distinct cell subtypes. Among different cell subtypes, significant differences were in immunoinfiltrating cells, plasma cells, naive CD4 T cells, memory activated CD4 T cells, gamma delta T cells, resting NK cells and activated NK cells but not in macrophages. Furthermore, the identification of various compounds capable of targeting these m6A genes was achieved. In conclusions, our integrated bioinformatics analysis results demonstrated that m6A-related genes METTL3, CBLL1 and YTHDF2 may be useful biomarkers for endometriosis in ectopic endometrium. The potential therapeutic approach of targeting m6A regulators holds promise for the treatment of endometriosis.

Novel Diagnostic Biomarker BST2 Identified by Integrated Transcriptomics Promotes the Development of Endometriosis via the TNF-α/NF-κB Signaling Pathway

Endometriosis (EMS) is a common gynecological condition with apparent heterogeneity, lack of diagnostic markers, and unclear pathogenesis. A series of bioinformatics methods were employed to explore EMS's pathological mechanisms and potential biomarkers by analyzing the combined datasets of EMS (GSE7305, GSE7307, GSE58198, E-MTAB-694), which included 34 normal, 127 eutopic, and 46 ectopic endometrium samples. Then, wet-laboratory experiments (including Western blot, qRT-PCR, and Immunohistochemistry, Immunofluorescence, CCK-8, EdU, Wound healing, Transwell, and Adhesion assays) were applied to examine the biomarkers' expression and function in primary endometrial stromal cells. Bioinformatic analysis indicated that the core pathogenesis of EMS was dysregulated immune-inflammation and tissue remolding processes. Among the upregulated DEGs, BST2 was screened as a potential diagnostic biomarker in EMS, which associated with the revised American Fertility Society (r-AFS) stage and immune-inflammation processes of EMS. Moreover, BST2's overexpression was affirmed in the RNA and protein levels in EMS tissues. In vitro experiments demonstrated that TNF-α promoted the expression of BST2 in ESCs. And BST2 knockdown inhibited migration, invasion, adhesion, and inflammation except for the proliferation of ESCs, probably via the TNF-α/NF-κB pathway. Through a combination of wet and dry studies, we concluded that the core pathogenesis of endometriosis was dysregulated immune-inflammation and tissue remolding, and BST2 might be a potential diagnostic and therapeutic target in endometriosis.

Identification of Endometriosis Pathophysiologic-Related Genes Based on Meta-Analysis and Bayesian Approach

Endometriosis is a complex disease with diverse etiologies, including hormonal, immunological, and environmental factors; however, its exact pathogenesis remains unknown. While surgical approaches are the diagnostic and therapeutic gold standard, identifying endometriosis-associated genes is a crucial first step. Five endometriosis-related gene expression studies were selected from the available datasets. Approximately, 14,167 genes common to these 5 datasets were analyzed for differential expression. Meta-analyses utilized fold-change values and standard errors obtained from each analysis, with the binomial and continuous datasets contributing to endometriosis presence and endometriosis severity meta-analysis, respectively. Approximately 160 genes showed significant results in both meta-analyses. For Bayesian analysis, endometriosis-related single nucleotide polymorphisms (SNPs), the human transcription factor catalog, uterine SNP-related gene expression, disease-gene databases, and interactome databases were utilized. Twenty-four genes, present in at least three or more databases, were identified. Network analysis based on Pearson's correlation coefficients revealed the HLA-DQB1 gene with both a high score in the Bayesian analysis and a central position in the network. Although ZNF24 had a lower score, it occupied a central position in the network, followed by other ZNF family members. Bayesian analysis identified genes with high confidence that could support discovering key diagnostic biomarkers and therapeutic targets for endometriosis.

The correlation between immune cells and endometriosis: a bidirectional two-sample mendelian randomization study

OBJECTIVES

Endometriosis (EM), a prevalent estrogen-dependent inflammatory disorder affecting women of reproductive age, is characterized by the presence of endometrial-like tissue outside the uterus, resulting in pelvic scarring, pain, and infertility. Although the pathogenesis of EM remains poorly understood, there is growing evidence suggesting the involvement of the immune system in its etiology, pathophysiology, and associated morbidities such as pain, infertility, and adverse pregnancy outcomes. While previous studies have indicated a close relationship between the immune system and EM, the specific underlying mechanism remains incompletely elucidated.

METHODS

Through the utilization of publicly available genetic data, a two-sample Mendelian randomization (MR) analysis was conducted to establish an association between 731 immune cell phenotypes and EM. Comprehensive sensitivity analyses were performed to validate the robustness, heterogeneity, and potential horizontal pleiotropy of the findings.

RESULTS

The MR analysis revealed potential associations between 22 immune cell phenotypes and EM. Conversely, reverse MR analysis identified 11 immune phenotypes demonstrating potential associations between genetic liability in the immune phenotypes and EM.

CONCLUSION

This study provides evidence of a potential correlation between immune cell phenotypes and EM, including the existence of reverse causation. These findings open up new avenues for investigating the underlying mechanisms of EM.

Exploration of Diagnostic Deubiquitinating Enzymes in Endometriosis and Its Immune Infiltration

The mechanism involved in the pathogenesis of endometriosis is poorly understood. The purpose of this study is to identify key deubiquitinating enzymes (DUBs) for endometriosis diagnosis and elucidate the possible mechanism, offering novel insights for noninvasive early diagnosis and treatment. Four gene expression datasets were employed from the Gene Expression Omnibus to identify differentially expressed genes (DEGs) between endometriosis and normal controls. GO and KEGG pathways were performed for enrichment analysis. Calibration curves, ROC, DCA, and clinical impact curves verified the clinical usefulness of the nomogram model. In addition, the ssGSEA method was conducted to estimate 23 types of immune cells. A specific DUB gene signature was constructed with Lasso regression, univariate logistic regression, and SVM analysis. RT-qPCR validated the expression of biomarkers. A total of 85 endometriosis-related DUBs were identified in the eutopic endometrium. Among them, 20 DUBs were found to be correlated with the severity of endometriosis. A diagnostic risk model based on five DUB-related genes (USP21, USP48, ZRANB1, COPS5, and EIF3F) was developed using lasso-cox regression analysis. The nomogram model exhibited a strong predictive ability to diagnose endometriosis. KEGG analysis revealed that ubiquitin-mediated proteolysis was activated in patients suffering from severe symptoms. Analysis of immune cell infiltration revealed a positive correlation between USP21 and multiple immune cells in the eutopic endometrium. However, EIF3F showed an opposite relationship. Dysregulation of DUBs was related to the immune microenvironment in endometriosis. Results from RT-qPCR confirmed the expression of DEGs in clinical samples. In summary, the diagnostic model for endometriosis constructed using five differentially expressed DUB genes demonstrates strong diagnostic capability, suggesting that these genes could serve as potential candidate biomarkers and therapeutic targets.

Reproductomics: Exploring the Applications and Advancements of Computational Tools

Over recent decades, advancements in omics technologies, such as proteomics, genomics, epigenomics, metabolomics, transcriptomics, and microbiomics, have significantly enhanced our understanding of the molecular mechanisms underlying various physiological and pathological processes. Nonetheless, the analysis and interpretation of vast omics data concerning reproductive diseases are complicated by the cyclic regulation of hormones and multiple other factors, which, in conjunction with a genetic makeup of an individual, lead to diverse biological responses. Reproductomics investigates the interplay between a hormonal regulation of an individual, environmental factors, genetic predisposition (DNA composition and epigenome), health effects, and resulting biological outcomes. It is a rapidly emerging field that utilizes computational tools to analyze and interpret reproductive data, with the aim of improving reproductive health outcomes. It is time to explore the applications of reproductomics in understanding the molecular mechanisms underlying infertility, identification of potential biomarkers for diagnosis and treatment, and in improving assisted reproductive technologies (ARTs). Reproductomics tools include machine learning algorithms for predicting fertility outcomes, gene editing technologies for correcting genetic abnormalities, and single cell sequencing techniques for analyzing gene expression patterns at the individual cell level. However, there are several challenges, limitations and ethical issues involved with the use of reproductomics, such as the applications of gene editing technologies and their potential impact on future generations are discussed. The review comprehensively covers the applications and advancements of reproductomics, highlighting its potential to improve reproductive health outcomes and deepen our understanding of reproductive molecular mechanisms.

Integrated bioinformatic analysis reveals the gene signatures, epigenetic roles, and regulatory networks in endometriosis

OBJECTIVES

Endometriosis is a common gynecological disease with a significant economic burden. Growing evidence has suggested the role of aberrant gene expression and epigenetic mechanisms in the pathogenesis of endometriosis. This study aims to identify potential key genes, epigenetic features, and regulatory networks in endometriosis using an integrated bioinformatic approach.

METHODS

Six microarray and RNA-sequencing datasets (GSE23339, GSE7305, GSE25628, GSE51981, GSE120103, GSE87809) were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) of each dataset were analyzed using the GEO2R tool, and their mRNA, miRNA, and lncRNA components were identified subsequently. The common DEGs between datasets were combined, and the Gene ontology (GO) and pathway enrichment were analyzed using the ShinyGo. The protein-protein interaction (PPI) network of DEGs, miRNA, and lncRNA was constructed using STRING and Cytoscape, and then the top 15 hub genes in the PPI network were identified using CytoHubba.

RESULTS

A total of 551 common DEGs were identified from four or more studies, including 292 upregulated and 259 downregulated genes. Besides alterations in protein-coding genes (mRNA), 16 miRNA (5 upregulated and 11 downregulated) were identified from all studies, along with 12 lncRNA (10 upregulated and 2 downregulated) that were common in at least three studies. Enriched DEGs were mainly associated with extracellular matrix (ECM) interaction, P53 signaling pathway, and focal adhesion, which are suggested to play vital roles in the pathogenesis of endometriosis. Through PPI network construction of common DEGs, 178 nodes and 683 edges were obtained, from which 15 hub genes were identified, including CDK1, CCNB1, KIF11, CCNA2, BUB1B, DLGAP5, BUB1, TOP2A, ASPM, CEP55, CENPF, TPX2, CCNB2, KIFC, NCAPG.

CONCLUSIONS

Our in-depth bioinformatics analysis reveals the critical molecular basis underlying endometriosis. The role of identified hub genes, miRNA, and lncRNA may also have an opportunity to be explored as potential biomarkers for endometriosis diagnosis and prognosis.

Identification of a disulfidptosis-related genes signature for diagnostic and immune infiltration characteristics in endometriosis

Endometriosis (EMs) is the prevalent gynecological disease with the typical features of intricate pathogenesis and immune-related factors. Currently, there is no effective therapeutic intervention for EMs. Disulfidptosis, the cell death pattern discovered recently, may show close relationships to immunity and EMs. In this study, bioinformatics analysis was used to investigate the role of disulfide breakdown related genes (DRGs) in EMs. The EMs gene expression matrix was subjected to differential analysis for identifying overlap between differentially expressed genes (DEGs) in EMs and genes associated with disulfide poisoning. Immunoinfiltration analysis was performed. In addition, the association of hub genes with immune cells was examined. Multiple machine learning methods were employed to identify hub genes, construction of predictive models, and validation using external datasets and clinical samples. Totally 15 overlapping genes were identified. Immune-correlation analysis showed that NK cells played a vital role, and these 15 genes were closely related to NK cells. PDLIM1 was further determined as the hub gene through machine learning techniques. Clinical samples and external datasets were adopted for validating the performance in diagnosis. According to the above findings, we built the predictive model, and calculated the AUCs obtained from three external validation datasets to demonstrate the model accuracy. RT-qPCR and IHC analyses were applied to confirm the results. Colony formation was used to verify the effect of PDLIM1 on the proliferation of primary EMs cells. A strong correlation between disulfidptosis and EMs was identified in this study, highlighting its close correlation with the immune microenvironment. Moreover, our results shed new lights on exploring biomarkers and potential therapeutic targets for EMs.

Creatine Promotes Endometriosis by Inducing Ferroptosis Resistance via Suppression of PrP

Endometriosis, a chronic inflammatory disease, significantly impairs the quality of life of women in their reproductive years; however, its pathogenesis remains poorly understood. The accumulation of retrograde menstruation and recurrent bleeding fosters a high-iron environment in ectopic lesions, triggering ferroptosis in ectopic endometrial stromal cells (EESCs), thereby hindering the establishment of endometriosis. However, abnormal EESCs demonstrate resistance to ferroptosis in high-iron environments, promoting the progression of this disease. Here, novel findings on the accumulation of creatine, derived from endogenous synthesis, in both peritoneal fluid and EESCs of patients with endometriosis are presented. Creatine supplementation reduces cellular iron concentrations, mitigating oxidative stress and lipid peroxidation, thereby enhancing cell viability and preventing ferroptosis under high-iron conditions. Utilizing the drug affinity-responsive target stabilization (DARTS) assay, prion protein (PrP) as a potential creatine-sensing protein is identified. Mechanistically, creatine binds to the active site of PrP, inhibits the conversion of trivalent iron to divalent iron, and decreases iron uptake, promoting the tolerance of EESCs to ferroptosis. This interaction contributes to the development of endometriosis. The novel association between creatine and ferroptosis provides valuable insights into the role of creatine in endometriosis progression and highlights its potential as a therapeutic target for endometriosis.

Correlation between the existence of serum autoantibodies and the risk of endometriosis: A systematic review and meta-analysis

Endometriosis is a common condition among women and can cause complications such as abdominal pain, dysmenorrhea, and infertility. One of the potential causes of this disease is autoimmunity. However, evidence regarding the role of autoimmunity is conflicting and inconclusive. The aim of this study was to investigate whether autoantibodies, a sign of autoimmunity, are present in people suffering from endometriosis. Relevant studies up to April 14, 2023 were identified by systematically searching Scopus, PubMed, Web of Science, Embase, and Google Scholar. This meta-analysis includes all qualified case-control studies of human populations that analyzed the association between serum autoantibodies and endometriosis. The odd ratios and 95% confidence intervals were calculated. In addition, heterogeneity and publication bias were examined, and subgroup analyses were performed based on region and target antigens. Forty-one studies were included, comparing 2,825 endometriosis patients with 4,158 healthy controls. The meta-analysis findings indicated a significant association between the presence of autoantibodies in the serum and an increased susceptibility to endometriosis (odds ratio: 4.242, confidence interval 95%: 3.824-4.706, p<0.001). In addition, there was a significant correlation between the presence of endometriosis and serum levels of anti-nuclear antibodies, B2 glycoprotein 1, CA125, carbonic anhydrase 1, cardiolipin, endometrial, laminin-1, smooth muscle, and syntaxin autoantibodies. Upon further analysis, it was found that the serum levels of these autoantibodies were higher in patients with endometriosis from North America than in those from other regions (p=0.001). The study revealed a significant correlation between serum autoantibodies and susceptibility to endometriosis, highlighting autoimmunity as a potential cause.

Dissecting the shared genetic architecture between endometriosis and polycystic ovary syndrome

Background

Previous study suggested evidence for coexistence and similarities between endometriosis and polycystic ovary syndrome (PCOS), but it is unclear regarding the shared genetic architecture and causality underlying the phenotypic similarities observed for endometriosis and PCOS.

Methods

By leveraging summary statistics from public genome-wide association studies regarding endometriosis (European-based: N=470,866) and PCOS (European-based: N=210,870), we explored the genetic correlation that shared between endometriosis and PCOS using linkage disequilibrium score regression. Shared risk SNPs were derived using PLACO (Pleiotropic analysis under composite null hypothesis) and FUMA (Functional Mapping and Annotation of Genetic Associations). The potential causal association between endometriosis and PCOS was investigated using two-sample Mendelian randomization (MR). Linkage disequilibrium score for the specific expression of genes analysis (LDSC-SEG) were performed for tissue enrichment analysis. The expression profiles of the risk gene in tissues were further examined.

Results

A positive genetic association was observed between endometriosis and PCOS. 12 significant pleiotropic loci shared between endometriosis and PCOS were identified. Genetic associations between endometriosis and PCOS were particularly enriched in uterus, endometrium and fallopian tube. Two-sample MR analysis further indicated a potential causative effect of endometriosis on PCOS, and vice versa. Microarray and RNA-seq verified the expressions of SYNE1 and DNM3 were significantly altered in the endometrium of patients with endometriosis or PCOS compared to those of control subjects.

Conclusion

Our study indicates the genetic correlation and shared risk genes between PCOS and endometriosis. These findings provide insights into the potential mechanisms behind their comorbidity and the future development of therapeutics.

Immune pathway through endometriosis to ovarian cancer

Endometriosis is an estrogen-dependent inflammatory disease, defined by the presence of functional endometrial tissue outside of the uterine cavity. This disease is one of the main gynecological diseases, affecting around 10%-15% women and girls of reproductive age, being a common gynecologic disorder. Although endometriosis is a benign disease, it shares several characteristics with invasive cancer. Studies support that it has been linked with an increased chance of developing endometrial ovarian cancer, representing an earlier stage of neoplastic processes. This is particularly true for women with clear cell carcinoma, low-grade serous carcinoma and endometrioid. However, the carcinogenic pathways between both pathologies remain poorly understood. Current studies suggest a connection between endometriosis and endometriosis-associated ovarian cancers (EAOCs) via pathways associated with oxidative stress, inflammation, and hyperestrogenism. This article aims to review current data on the molecular events linked to the development of EAOCs from endometriosis, specifically focusing on the complex relationship between the immune response to endometriosis and cancer, including the molecular mechanisms and their ramifications. Examining recent developments in immunotherapy and their potential to boost the effectiveness of future treatments.

Characterizing the Extracellular Matrix Transcriptome of Endometriosis

In recent years, the matrisome, a set of proteins that make up the extracellular matrix (ECM) or are closely involved in ECM behavior, has been shown to have great importance for characterizing and understanding disease pathogenesis and progression. The matrisome is especially critical for examining diseases characterized by extensive tissue remodeling. Endometriosis is characterized by the extrauterine growth of endometrial tissue, making it an ideal condition to study through the lens of matrisome gene expression. While large gene expression datasets have become more available and gene dysregulation in endometriosis has been the target of several studies, the gene expression profile of the matrisome specifically in endometriosis has not been well characterized. In our study, we explored four Gene Expression Omnibus (GEO) DNA microarray datasets containing eutopic endometrium of people with and without endometriosis. After batch correction, menstrual cycle phase accounted for 53% of variance and disease accounted for 23%; thus, the data were separated by menstrual cycle phase before performing differential expression analysis, statistical and machine learning modeling, and enrichment analysis. We established that matrisome gene expression alone can effectively differentiate endometriosis samples from healthy ones, demonstrating the potential of matrisome gene expression for diagnostic applications. Furthermore, we identified specific matrisome genes and gene networks whose expression can distinguish endometriosis stages I/II from III/IV. Taken together, these findings may aid in developing future in vitro models of disease, offer insights into novel treatment strategies, and advance diagnostic tools for this underserved patient population.

Clinical Characteristics and Local Histopathological Modulators of Endometriosis and Its Progression

Endometriosis (E) and adenomyosis (A) are associated with a wide spectrum of symptoms and may present various histopathological transformations, such as the presence of hyperplasia, atypia, and malignant transformation occurring under the influence of local inflammatory, vascular and hormonal factors and by the alteration of tumor suppressor proteins and the inhibition of cell apoptosis, with an increased degree of lesion proliferation.

MATERIAL AND METHODS

This retrospective study included 243 patients from whom tissue with E/A or normal control uterine tissue was harvested and stained by histochemical and classical immunohistochemical staining. We assessed the symptomatology of the patients, the structure of the ectopic epithelium and the presence of neovascularization, hormone receptors, inflammatory cells and oncoproteins involved in lesion development. Atypical areas were analyzed using multiple immunolabeling techniques.

RESULTS

The cytokeratin (CK) CK7+/CK20- expression profile was present in E foci and differentiated them from digestive metastases. The neovascularization marker cluster of differentiation (CD) 34+ was increased, especially in areas with malignant transformation of E or A foci. T:CD3+ lymphocytes, B:CD20+ lymphocytes, CD68+ macrophages and tryptase+ mast cells were abundant, especially in cases associated with malignant transformation, being markers of the proinflammatory microenvironment. In addition, we found a significantly increased cell division index (Ki67+), with transformation and inactivation of tumor suppressor genes p53, B-cell lymphoma 2 (BCL-2) and Phosphatase and tensin homolog (PTEN) in areas with E/A-transformed malignancy.

CONCLUSIONS

Proinflammatory/vascular/hormonal changes trigger E/A progression and the onset of cellular atypia and malignant transformation, exacerbating symptoms, especially local pain and vaginal bleeding. These triggers may represent future therapeutic targets.

Construction and evaluation of endometriosis diagnostic prediction model and immune infiltration based on efferocytosis-related genes

Background: Endometriosis (EM) is a long-lasting inflammatory disease that is difficult to treat and prevent. Existing research indicates the significance of immune infiltration in the progression of EM. Efferocytosis has an important immunomodulatory function. However, research on the identification and clinical significance of efferocytosis-related genes (EFRGs) in EM is sparse. Methods: The EFRDEGs (differentially expressed efferocytosis-related genes) linked to datasets associated with endometriosis were thoroughly examined utilizing the Gene Expression Omnibus (GEO) and GeneCards databases. The construction of the protein-protein interaction (PPI) and transcription factor (TF) regulatory network of EFRDEGs ensued. Subsequently, machine learning techniques including Univariate logistic regression, LASSO, and SVM classification were applied to filter and pinpoint diagnostic biomarkers. To establish and assess the diagnostic model, ROC analysis, multivariate regression analysis, nomogram, and calibration curve were employed. The CIBERSORT algorithm and single-cell RNA sequencing (scRNA-seq) were employed to explore immune cell infiltration, while the Comparative Toxicogenomics Database (CTD) was utilized for the identification of potential therapeutic drugs for endometriosis. Finally, immunohistochemistry (IHC) and reverse transcription quantitative polymerase chain reaction (RT-qPCR) were utilized to quantify the expression levels of biomarkers in clinical samples of endometriosis. Results: Our findings revealed 13 EFRDEGs associated with EM, and the LASSO and SVM regression model identified six hub genes (ARG2, GAS6, C3, PROS1, CLU, and FGL2). Among these, ARG2, GAS6, and C3 were confirmed as diagnostic biomarkers through multivariate logistic regression analysis. The ROC curve analysis of GSE37837 (AUC = 0.627) and GSE6374 (AUC = 0.635), along with calibration and DCA curve assessments, demonstrated that the nomogram built on these three biomarkers exhibited a commendable predictive capacity for the disease. Notably, the ratio of nine immune cell types exhibited significant differences between eutopic and ectopic endometrial samples, with scRNA-seq highlighting M0 Macrophages, Fibroblasts, and CD8 Tex cells as the cell populations undergoing the most substantial changes in the three biomarkers. Additionally, our study predicted seven potential medications for EM. Finally, the expression levels of the three biomarkers in clinical samples were validated through RT-qPCR and IHC, consistently aligning with the results obtained from the public database. Conclusion: we identified three biomarkers and constructed a diagnostic model for EM in this study, these findings provide valuable insights for subsequent mechanistic research and clinical applications in the field of endometriosis.

Identification of central genes for endometriosis through integration of single-cell RNA sequencing and bulk RNA sequencing analysis

This study aimed to identify the key genes involved in the development of endometriosis and construct an accurate predictive model to provide new directions for the diagnosis and treatment of endometriosis. Using bioinformatics analysis, we employed the single-cell cell communication method to identify the key cell subtypes. By combining chip data and integrating differential analysis, WGCNA analysis, and the least absolute shrinkage and selection operator (LASSO) model, key genes were identified for immune infiltration and functional enrichment analyses. Cell communication analysis identified tissue stem cells as the key subtype. Differential analysis revealed 1879 differentially expressed genes, whereas WGCNA identified 357 module genes. The LASSO model further selects 4 key genes: Adipocyte Enhancer Binding Protein 1(AEBP1), MBNL1, GREM1, and DES. All 4 key genes showed significant correlations with immune cell content. Moreover, these genes were significantly expressed in single cells. The predictive model demonstrated good diagnostic performance. Through scRNA-seq, WGCNA, and LASSO methodologies, DES, GREM1, MBNL1, and AEBP1 emerged as crucial core genes linked to tissue stem cell markers in endometriosis. These genes have promising applications as diagnostic markers and therapeutic targets for endometriosis.

Machine learning algorithms for a novel cuproptosis-related gene signature of diagnostic and immune infiltration in endometriosis

Endometriosis (EMT) is an aggressive disease of the reproductive system, also called "benign cancer". However, effective treatments for EMT are still lacking in clinical practice. Interestingly, immune infiltration is significantly involved in EMT pathogenesis. Currently, no studies have shown the involvement of cuproptosis-related genes (CRGs) in regulating immune infiltration in EMT. This study identified three CRGs such as GLS, NFE2L2, and PDHA1, associated with EMT using machine learning algorithms. These three CRGs were upregulated in the endometrium of patients with moderate/severe EMT and downregulated in patients with infertility. Single sample genomic enrichment analysis (ssGSEA) revealed that these CRGs were closely correlated with autoimmune diseases such as systemic lupus erythematosus. Furthermore, these CRGs were correlated with immune cells such as eosinophils, natural killer cells, and macrophages. Therefore, profiling patients based on these genes aid in a more accurate diagnosis of EMT progression. The mRNA and protein expression levels of GLS, NFE2L2 and PDHA1 were validated by qRT-PCR and WB studies in EMT samples. These findings provide a new idea for the pathology and treatment of endometriosis, suggesting that CRGs such as GLS, NFE2L2 and PDHA1 may play a key role in the occurrence and development of endometriosis.

Machine learning-based integrated identification of predictive combined diagnostic biomarkers for endometriosis

Background: Endometriosis (EM) is a common gynecological condition in women of reproductive age, with diverse causes and a not yet fully understood pathogenesis. Traditional diagnostics rely on single diagnostic biomarkers and does not integrate a variety of different biomarkers. This study introduces multiple machine learning techniques, enhancing the accuracy of predictive models. A novel diagnostic approach that combines various biomarkers provides a new clinical perspective for improving the diagnostic efficiency of endometriosis, holding significant potential for clinical application. Methods: In this study, GSE51981 was used as a test set, and 11 machine learning algorithms (Lasso, Stepglm, glmBoost, Support Vector Machine, Ridge, Enet, plsRglm, Random Forest, LDA, XGBoost, and NaiveBayes) were employed to construct 113 predictive models for endometriosis. The optimal model was determined based on the AUC values derived from various algorithms. These genes were then evaluated using nine machine learning algorithms (Random Forest, SVM, Gradient Boosting Machine, LASSO, XGB, NNET, Generalized Linear Model, KNN, and Decision Tree) to assess significance scores and identify diagnostic genes for each algorithm. The diagnostic value of these genes was further validated in external datasets from GSE7305, GSE11691, and GSE120103. Results: Analysis of the GSE51981 dataset revealed 62 DEGs. The Stepglm [Both] and plsRglm algorithms identified 30 genes with the most potential using the AUC evaluation. Subsequently, nine machine learning algorithms were applied to select diagnostic genes, leading to the identification of five key diagnostic genes using the LASSO algorithm. The ADAT1 gene exhibited the best single-gene predictive performance, with an AUC of 0.785. A combination of genes (FOS, EPHX1, DLGAP5, PCSK5, and ADAT1) achieves an AUC of 0.836 in the test dataset. Moreover, these genes consistently exhibited an AUC exceeding 0.78 in all validation datasets, demonstrating superior predictive performance. Furthermore, correlation analysis with immune infiltration strengthened their predictive value by demonstrating the close relationship of the diagnostic genes with immune infiltrating cells. Conclusion: A combination of biomarkers consisting of FOS, EPHX1, DLGAP5, PCSK5, and ADAT1 can serve as a diagnostic tool for endometriosis, enhancing diagnostic efficiency. The association of these genes with immune infiltrating cells reveals their potential role in the pathogenesis of endometriosis, providing new insights for early detection and treatment.

Unraveling immunotherapeutic targets for endometriosis: a transcriptomic and single-cell analysis

Background

Endometriosis (EMs), a common gynecological disorder, adversely affects the quality of life of females. The pathogenesis of EMs has not been elucidated and the diagnostic methods for EMs have limitations. This study aimed to identify potential molecular biomarkers for the diagnosis and treatment of EMs.

Methods

Differential gene expression (DEG) and functional enrichment analyses were performed using the R language. WGCNA, Random Forest, SVM-REF and LASSO methods were used to identify core immune genes. The CIBERSORT algorithm was then used to analyse the differences in immune cell infiltration and to explore the correlation between immune cells and core genes. In addition, the extent of immune cell infiltration and the expression of immune core genes were investigated using single-cell RNA (scRNA) sequencing data. Finally, we performed molecular docking of three core genes with dienogest and goserelin to screen for potential drug targets.

Results

DEGs enriched in immune response, angiogenesis and estrogen processes. CXCL12, ROBO3 and SCG2 were identified as core immune genes. RT-PCR confirmed that the expression of CXCL12 and SCG2 was significantly upregulated in 12Z cells compared to hESCs cells. ROC curves showed high diagnostic value for these genes. Abnormal immune cell distribution, particularly increased macrophages, was observed in endometriosis. CXCL12, ROBO3 and SCG2 correlated with immune cell levels. Molecular docking suggested their potential as drug targets.

Conclusion

This study investigated the correlation between EMs and the immune system and identified potential immune-related biomarkers. These findings provided valuable insights for developing clinically relevant diagnostic and therapeutic strategies for EMs.

CXADR promote epithelial-mesenchymal transition in endometriosis by modulating AKT/GSK-3β signaling

Endometriosis is a benign high prevalent disease exhibiting malignant features. However, the underlying pathogenesis and key molecules of endometriosis remain unclear. By integrating and analysis of existing expression profile datasets, we identified coxsackie and adenovirus receptor (CXADR), as a novel key gene in endometriosis. Based on the results of immunohistochemistry (IHC), we confirmed significant down-regulation of CXADR in ectopic endometrial tissues obtained from women with endometriosis compared with healthy controls. Further in vitro investigation indicated that CXADR regulated the stability and function of the phosphatases and AKT inhibitors PHLPP2 (pleckstrin homology domain and leucine-rich repeat protein phosphatase 2) and PTEN (phosphatase and tensin homolog). Loss of CXADR led to phosphorylation of AKT and glycogen synthase kinase-3β (GSK-3β), which resulted in stabilization of an epithelial-mesenchymal transition (EMT) factor, SNAIL1 (snail family transcriptional repressor 1). Therefore, EMT processs was induced, and the proliferation, migration and invasion of Ishikawa cells were enhanced. Over-expression of CXADR showed opposite effects. These findings suggest a previously undefined role of AKT/GSK-3β signaling axis in regulating EMT and reveal the involvement of a CXADR-induced EMT, in pathogenic progression of endometriosis.

Identifying Immune Cell Infiltration and Hub Genes Related to M2 Macrophages in Endometriosis by Bioinformatics Analysis

Endometriosis (EM) is a chronic, estrogen-dependent inflammatory disease. Presently, the pathophysiology of EM is still unclear, and numerous studies have established that the immune system plays a major role in the pathophysiology of EM. Six microarray datasets were downloaded from the GEO public database. A total of 151 endometrial samples (72 ectopic endometria and 79 controls) were included in this study. CIBERSORT and ssGSEA were applied to calculate the immune infiltration of EM and control samples. Moreover, we validated four different correlation analyses to explore immune microenvironment of EM and finally identified M2 macrophage-related hub genes and further conducted the specific immunologic signaling pathway analysis by GSEA. The logistic regression model was investigated by ROC and further validated by two external datasets. From the results of the two immune infiltration assays, we concluded that M2 macrophages, regulatory T cells (Tregs), M1 macrophages, activated B cells, T follicular helper cells, activated dendritic cells, and resting NK cells have a significant difference between control and EM tissues. Through multidimensional correlation analysis, we found that macrophages play an important central role in cell-to-cell interactions, especially M2 macrophages. Four immune-related hub genes, namely FN1, CCL2, ESR1, and OCLN, are closely related to M2 macrophages and play a crucial role in the occurrence and immune microenvironment of endometriosis. The combined AUC of ROC prediction model in test and validation sets were 0.9815 and 0.8206, respectively. We conclude that M2 macrophages play a central role in the immune-infiltrating microenvironment of EM.

Potential Significance of Serum Autoantibodies to Endometrial Antigens, α-Enolase and Hormones in Non-Invasive Diagnosis and Pathogenesis of Endometriosis

The objective of the study was to evaluate the profile of serum autoantibodies and their diagnostic and pathogenetic significance in ovarian endometrioma (OEM) and deep infiltrative endometriosis (DIE). The study enrolled 74 patients with endometriosis (Group 1), including 53 patients with OEM (Subgroup 1a); 21 patients with DIE without ovarian lesions (Subgroup 1b); and 27 patients without endometriosis (Group 2). The diagnosis was confirmed by laparoscopic surgery and histologic examination of resected tissues. Antibodies (M, G) to tropomyosin 3 (TPM), tropomodulin 3 (TMOD), α-enolase (ENO), estradiol (E2), progesterone (PG), and human chorionic gonadotropin (hCG) were identified in blood serum using modified ELISA. In endometriosis, antibodies to endometrial antigens, hormones, and ENO were detected more often than antiphospholipid and antinuclear antibodies. Higher levels of IgM to TPM, hCG, E2, and PG and IgG to TMOD, ENO, E2, and hCG were found in Subgroup 1a compared to Group 2. IgM to TPM, hCG, E2, PG, and IgG to E2 and ENO had a high diagnostic value for OEM (AUC > 0.7), with antibodies to TPM having the highest sensitivity and specificity (73.6% and 81.5%). In Subgroup 1b, only the levels of IgM to TPM and hCG were higher than in Group 2. These antibodies had a high diagnostic value for DIE. Thus, endometriosis is associated with autoantibodies to endometrial antigens, α-enolase, steroid, and gonadotropic hormones. A wider spectrum of antibodies is detected in OEM than in DIE. These antibodies have a high diagnostic value for OEM and DIE and potential pathogenetic significance for endometriosis and associated infertility.

Revealing the diagnostic value and immune infiltration of senescence-related genes in endometriosis: a combined single-cell and machine learning analysis

Introduction: Endometriosis is a prevalent and recurrent medical condition associated with symptoms such as pelvic discomfort, dysmenorrhea, and reproductive challenges. Furthermore, it has the potential to progress into a malignant state, significantly impacting the quality of life for affected individuals. Despite its significance, there is currently a lack of precise and non-invasive diagnostic techniques for this condition. Methods: In this study, we leveraged microarray datasets and employed a multifaceted approach. We conducted differential gene analysis, implemented weighted gene co-expression network analysis (WGCNA), and utilized machine learning algorithms, including random forest, support vector machine, and LASSO analysis, to comprehensively explore senescence-related genes (SRGs) associated with endometriosis. Discussion: Our comprehensive analysis, which also encompassed profiling of immune cell infiltration and single-cell analysis, highlights the therapeutic potential of this gene assemblage as promising targets for alleviating endometriosis. Furthermore, the integration of these biomarkers into diagnostic protocols promises to enhance diagnostic precision, offering a more effective diagnostic journey for future endometriosis patients in clinical settings. Results: Our meticulous investigation led to the identification of a cluster of genes, namely BAK1, LMNA, and FLT1, which emerged as potential discerning biomarkers for endometriosis. These biomarkers were subsequently utilized to construct an artificial neural network classifier model and were graphically represented in the form of a Nomogram.

Understanding endometriosis from an immunomicroenvironmental perspective

ABSTRACT

Endometriosis, a heterogeneous, inflammatory, and estrogen-dependent gynecological disease defined by the presence and growth of endometrial tissues outside the lining of the uterus, affects approximately 5-10% of reproductive-age women, causing chronic pelvic pain and reduced fertility. Although the etiology of endometriosis is still elusive, emerging evidence supports the idea that immune dysregulation can promote the survival and growth of retrograde endometrial debris. Peritoneal macrophages and natural killer (NK) cells exhibit deficient cytotoxicity in the endometriotic microenvironment, leading to inefficient eradication of refluxed endometrial fragments. In addition, the imbalance of T-cell subtypes results in aberrant cytokine production and chronic inflammation, which contribute to endometriosis development. Although it remains uncertain whether immune dysregulation represents an initial cause or merely a secondary enhancer of endometriosis, therapies targeting altered immune pathways exhibit satisfactory effects in preventing disease onset and progression. Here, we summarize the phenotypic and functional alterations of immune cells in the endometriotic microenvironment, focusing on their interactions with microbiota and endocrine and nervous systems, and how these interactions contribute to the etiology and symptomology of endometriosis.

Transcriptomic analyses of ovarian clear-cell carcinoma with concurrent endometriosis

Introduction

Endometriosis, a benign inflammatory disease whereby endometrial-like tissue grows outside the uterus, is a risk factor for endometriosis-associated ovarian cancers. In particular, ovarian endometriomas, cystic lesions of deeply invasive endometriosis, are considered the precursor lesion for ovarian clear-cell carcinoma (OCCC).

Methods

To explore this transcriptomic landscape, OCCC from women with pathology-proven concurrent endometriosis (n = 4) were compared to benign endometriomas (n = 4) by bulk RNA and small-RNA sequencing.

Results

Analysis of protein-coding genes identified 2449 upregulated and 3131 downregulated protein-coding genes (DESeq2, P< 0.05, log2 fold-change > |1|) in OCCC with concurrent endometriosis compared to endometriomas. Gene set enrichment analysis showed upregulation of pathways involved in cell cycle regulation and DNA replication and downregulation of pathways involved in cytokine receptor signaling and matrisome. Comparison of pathway activation scores between the clinical samples and publicly-available datasets for OCCC cell lines revealed significant molecular similarities between OCCC with concurrent endometriosis and OVTOKO, OVISE, RMG1, OVMANA, TOV21G, IGROV1, and JHOC5 cell lines. Analysis of miRNAs revealed 64 upregulated and 61 downregulated mature miRNA molecules (DESeq2, P< 0.05, log2 fold-change > |1|). MiR-10a-5p represented over 21% of the miRNA molecules in OCCC with endometriosis and was significantly upregulated (NGS: log2fold change = 4.37, P = 2.43e-18; QPCR: 8.1-fold change, P< 0.05). Correlation between miR-10a expression level in OCCC cell lines and IC50 (50% inhibitory concentration) of carboplatin in vitro revealed a positive correlation (R2 = 0.93). MiR-10a overexpression in vitro resulted in a significant decrease in proliferation (n = 6; P< 0.05) compared to transfection with a non-targeting control miRNA. Similarly, the cell-cycle analysis revealed a significant shift in cells from S and G2 to G1 (n = 6; P< 0.0001). Bioinformatic analysis predicted that miR-10a-5p target genes that were downregulated in OCCC with endometriosis were involved in receptor signaling pathways, proliferation, and cell cycle progression. MiR-10a overexpression in vitro was correlated with decreased expression of predicted miR-10a target genes critical for proliferation, cell-cycle regulation, and cell survival including [SERPINE1 (3-fold downregulated; P< 0.05), CDK6 (2.4-fold downregulated; P< 0.05), and RAP2A (2-3-fold downregulated; P< 0.05)].

Discussion

These studies in OCCC suggest that miR-10a-5p is an impactful, potentially oncogenic molecule, which warrants further studies.

Autoimmune Disease-Related Hub Genes are Potential Biomarkers and Associated with Immune Microenvironment in Endometriosis

Background

Endometriosis, a common gynecological condition, can cause symptoms such as dysmenorrhea, infertility, and abnormal bleeding, which can negatively affect a woman's quality of life. In the current study, the pathophysiological mechanisms of endometriosis are unknown, but this study suggests that endometriosis is associated with dysregulation of the autoimmune system. This study identify hub genes involved in the prevalence, identification and diagnostic value of endometriosis and autoimmune diseases, and explore the central genes and immune infiltrates, the diagnosis of endometriosis provides a new sight of thinking about diagnosis and treatment.

Methods and Results

The relevant datasets for endometriosis GSE141549, GSE7305 and autoimmune disease-related genes (AIDGs) were downloaded from online database. Using the "limma" package and WGCNA to screen out the autoimmune disease related genes and endometriosis related genes, the autoimmune disease gene-related differential genes (AID-DEGs) progressive GO, KEGG enrichment analysis, and then using the protein interaction network and Cytoscape software to select hub genes (CXCL12, PECAM1, NGF, CTGF, WNT5A), using the "pROC" package to analyze the hub genes for the diagnostic value of endometriosis. The difference in the importance of hub genes for the diagnosis of endometriosis was analyzed by machine learning random forest, and the combined diagnostic value of hub genes was analyzed by using the Support Vector Machine (SVM) algorithm. The eutopic (EU) and ectopic endometrium (EC) immune microenvironment of endometriosis was evaluated using CIBERSORT, the correlation of hub genes to the immune microenvironment was analyzed.

Conclusion

The hub genes associated with AIDGs are differentially expressed in EC and EU of endometriosis and possess important value for the diagnosis of endometriosis. The hub genes have a very important impact on the immune microenvironment of endometriosis, which is important for exploring the connection between endometriosis and autoimmune diseases and provides a new insight for the subsequent study of immunotherapy and diagnosis of endometriosis.

Peritoneal autoantibody profiling identifies p53 as an autoantibody target in endometriosis

OBJECTIVE

To map the peritoneal autoantibody (AAb) landscape in women with endometriosis.

DESIGN

Case-control laboratory study.

SETTING

Academic medical and research units.

PATIENT(S)

Women who presented with or without endometriosis.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Using native-conformation and citrullinated modified protein arrays, proteome-wide analysis of AAbs against 1,623 proteins were profiled in peritoneal fluids (PFs) of 25 women with endometriosis and 25 women without endometriosis.

RESULT(S)

In women with endometriosis, the median number of AAbs detected was 4, including AAbs that targeted autoantigens involved in implantation, B-cell activation/development, and aberrant migration and mitogenicity. Forty-six percent of women with endometriosis have ≥5 peritoneal AAbs. Conversely, in women without endometriosis, the median number of detected AAbs was 1. Autoantibodies recognizing tumor suppressor protein p53 were the most commonly detected AAbs, being present in 35% of women with endometriosis, and p53 AAb was associated with a monocyte/macrophage-like PF cytokine signature. Further investigation of the global reactivity of AAbs against citrullinated PF antigens by peptidylarginine deiminase enzymes 1, 2, and 6 revealed anticitrullinated p53 as the only AAb target elevated and citrullinated by all 3 peptidylarginine deiminase isotypes. Furthermore, unsupervised hierarchical clustering and integrative pathway analysis revealed that 60% of women with endometriosis-associated infertility were positive for AAbs, which are involved in platelet-derived growth factor, transforming growth factor-β, RAC1/PAK1/p38/MMP2 signaling, LAT2/NTAL/LAB-mediated calcium mobilization, and integrin-mediated cell adhesion.

CONCLUSION(S)

Together, our data identify peritoneal autoimmunity in a significant subset of women with endometriosis, with implications on infertility and disease pathophysiology. In these patients, p53 was identified as the most frequent PF AAb target, which was present in both the native and citrullinated forms.

Identification and validation of risk score model based on gene set activity as a diagnostic biomarker for endometriosis

Objective

The enigmatic nature of Endometriosis (EMS) pathogenesis necessitates investigating alterations in signaling pathway activity to enhance our comprehension of the disease's characteristics.

Methods

Three published gene expression profiles (GSE11691, GSE25628, and GSE7305 datasets) were downloaded, and the "combat" algorithm was employed for batch correction, gene expression difference analysis, and pathway enrichment difference analysis. The protein-protein interaction (PPI) network was constructed to identify core genes, and the relative enrichment degree of gene sets was evaluated. The Lasso regression model identified candidate gene sets with diagnostic value, and a risk scoring diagnostic model was constructed for further validation on the GSE86534 and GSE5108 datasets. CIBERSORT was used to assess the composition of immune cells in EMS, and the correlation between EMS diagnostic value gene sets and immune cells was evaluated.

Results

A total of 568 differentially expressed genes were identified between eutopic and ectopic endometrium, with 10 core genes in the PPI network associated with cell cycle regulation. Inflammation-related pathways, including cytokine-receptor signaling and chemokine signaling pathways, were significantly more active in ectopic endometrium compared to eutopic endometrium. Diagnostic gene sets for EMS, such as homologous recombination, base excision repair, DNA replication, P53 signaling pathway, adherens junction, and SNARE interactions in vesicular transport, were identified. The risk score's area under the curve (AUC) was 0.854, as indicated by the receiver operating characteristic (ROC) curve, and the risk score's diagnostic value was validated by the validation cohort. Immune cell infiltration analysis revealed correlations between the risk score and Macrophages M2, Plasma cells, resting NK cells, activated NK cells, and regulatory T cells.

Conclusion

The risk scoring diagnostic model, based on pathway activity, demonstrates high diagnostic value and offers novel insights and strategies for the clinical diagnosis and treatment of Endometriosis.

Fusobacterium infection facilitates the development of endometriosis through the phenotypic transition of endometrial fibroblasts

Retrograde menstruation is a widely accepted cause of endometriosis. However, not all women who experience retrograde menstruation develop endometriosis, and the mechanisms underlying these observations are not yet understood. Here, we demonstrated a pathogenic role of Fusobacterium in the formation of ovarian endometriosis. In a cohort of women, 64% of patients with endometriosis but <10% of controls were found to have Fusobacterium infiltration in the endometrium. Immunohistochemical and biochemical analyses revealed that activated transforming growth factor-β (TGF-β) signaling resulting from Fusobacterium infection of endometrial cells led to the transition from quiescent fibroblasts to transgelin (TAGLN)-positive myofibroblasts, which gained the ability to proliferate, adhere, and migrate in vitro. Fusobacterium inoculation in a syngeneic mouse model of endometriosis resulted in a marked increase in TAGLN-positive myofibroblasts and increased number and weight of endometriotic lesions. Furthermore, antibiotic treatment largely prevented establishment of endometriosis and reduced the number and weight of established endometriotic lesions in the mouse model. Our data support a mechanism for the pathogenesis of endometriosis via Fusobacterium infection and suggest that eradication of this bacterium could be an approach to treat endometriosis.

Identification of a Novel Cuproptosis-Related Gene Signature in Eutopic Endometrium of Women with Endometriosis

Endometriosis (EMs) is a life-long endocrine disorder and a common cause for female infertility and pelvic pain. The key characteristics of eutopic endometrium of EMs patients are high proliferative and migratory potentials. Cuproptosis is a recently identified copper- and-mitochondrial-dependent regulated cell death. Regretfully, its role in EMs remains unclear. In this study, Kyoto Encyclopedia of Genes and Genomes analyses of differentially expressed genes (DEGs) indicated strong activation of the PI3K-Akt-mTOR pathway and biological process analysis reported positive regulation of kinase activity. Next, we screened 11 cuproptosis-related DEGs and found all of them were downregulated in the EMs group, which indicated the suppression of cuproptosis in EMs. One key cuproptosis-related gene, PDHA1, was selected via support vector machine, random forest algorithm and lasso regularization to build a risk-scoring model, which was tested in both internal and external validations. In conclusion, the downregulation and kinase activity of PDHA1 may function with the PI3K-Akt-mTOR pathway in some way, which could suppress the cuproptosis level and account for the cancer-like pathology in EMs.

Expression profiles of meiotic genes in male vs. female gonads and gametes: Insights into fertility issues

Gametes are specialized cells that, at fertilization, give rise to a totipotent zygote capable of generating an entire organism. Female and male germ cells undergo meiosis to produce mature gametes; however, sex-specific events of oogenesis and spermatogenesis contribute to specific roles of gametes in reproductive issues. We investigate the differential gene expression (DGE) of meiosis-related genes in human female and male gonads and gametes in normal and pathological conditions. The transcriptome data for the DGE analysis was obtained through the Gene Expression Omnibus repository, comprising human ovary and testicle samples of the prenatal period and adulthood, additionally to male (non-obstructive azoospermia (NOA) and teratozoospermia), and female (polycystic ovary syndrome (PCOS) and advanced maternal age) reproductive conditions. Gene ontology terms related to meiosis were associated with 678 genes, of which 17 genes in common were differentially expressed between the testicle and ovary during the prenatal period and adulthood. Except for SERPINA5 and SOX9, the 17 meiosis-related genes were downregulated in the testicle during the prenatal period and upregulated in adulthood compared to the ovary. No differences were observed in the oocytes of PCOS patients; however, meiosis-related genes were differentially expressed according to the patient’s age and maturity of the oocyte. In NOA and teratozoospermia, 145 meiosis-related genes were differentially expressed in comparison to the control, including OOEP; despite no recognized role in male reproduction, OOEP was co-expressed with genes related to male fertility. Taking together, these results shed light on potential genes that might be relevant to comprehend human fertility disorders.

Endometriosis and inflammatory immune responses: Indian experience

Endometriosis is a public health disorder affecting ∼ 247 million women globally and ∼ 42 million women in India. Women with endometriosis suffer from dysmenorrhea, chronic pelvic pain, dyspareunia, dyschezia, fatigue, depression, and infertility leading to significant socioeconomic impact and morbidity. The etiology of endometriosis is not understood well even after 100 years of research. Currently, there is no permanent cure for endometriosis. The inflammatory immune response is one of the important features of etiopathogenesis of endometriosis and therefore understanding the inflammatory immune response would lead to a better understanding of this enigmatic disorder and may also lead to biomarker discovery for diagnosis of endometriosis. We investigated the autoimmune etiology of endometriosis in the Indian population. Using the proteomics approach, anti-endometrial antibodies (AEAs) were detected in Indian women with endometriosis [anti-endometrial antibodies - tropomyosin 3 (TPM3), stomatin-like protein2 (SLP-2), and tropomodulin 3 (TMOD3)]. The studies on AEAs provided a better understanding of autoimmune mechanisms in endometriosis. All three subtypes of endometriosis; superficial peritoneal, ovarian endometrioma, and deep infiltrating endometriosis were reported in Indian women. In this review, we discuss our experiences of the inflammatory immune response, autoimmunity, comorbidities, and clinical phenotypes in women with endometriosis in India.

Upregulation of SPI1 in Ectopic Endometrium Contributes to an Invasive Phenotype

BACKGROUD AND AIM

Endometriosis is one of the most common gynecological diseases associated with chronic pelvic pain, infertility, and cancer. However, its molecular pathogenesis remains unclear. This study aimed to identify key genes involved in the pathogenesis of endometriosis.

METHODS

Bioinformatic analyses were perfomed to identify key differentially expressed genes (DEGs), transcription factors (TFs), and functionally enriched pathways. Effect of SPI1 on migration, invasion, expression of ADH1B, MYH11, and PLN were analyzed in human endometriotic cells.

RESULTS

By screening three transcriptome datasets from the GEO for overlapping DEGs between eutopic and ectopic endometria in patients with endometriosis, we found that the expression of ADH1B, MYH11, and PLN was markedly upregulated in the ectopic endometrium. Knockdown of ADH1B, MYH11, and PLN significantly inhibited the migration and invasion of human endometriotic 12Z cells. Additionally, gene set enrichment analysis revealed that epithelial-mesenchymal transition gene signature was positively correlated with ADH1B, MYH11, and PLN expression. Notably, the TF SPI1 was found to regulate the expression of these three genes in the endometriotic tissues and 12TZ cells. Moreover, SPI1 expression was associated with the invasion of endometriotic cells and was increased in the ectopic endometrium of patients with endometriosis.

CONCLUSION

These data suggest that SPI1 plays a key role in the progression of endometriosis by regulating ADH1B, MYH11, and PLN expression and may therefore serve as a potential prognostic and therapeutic factor for endometriosis.

Bioinformatics-based analysis of the roles of sex hormone receptors in endometriosis development

Endometriosis is a hormone-dependent disease in women of reproductive age and seriously affects women's health. To analyze the involvement of sex hormone receptors in endometriosis development, we performed bioinformatics analysis using four datasets derived from the Gene Expression Omnibus (GEO) database, which may help us understand the mechanisms by which the sex hormones act in vivo in endometriosis patients. The enrichment analysis and protein-protein interaction (PPI) analysis of the differentially expressed genes (DEGs) revealed that there are different key genes and pathways involved in eutopic endometrium aberrations of endometriosis patients and endometriotic lesions, and sex hormone receptors, including androgen receptor (AR), progesterone receptor (PGR) and estrogen receptor 1 (ESR1), may play important roles in endometriosis development. Androgen receptor (AR), as the hub gene of endometrial aberrations in endometriotic patients, showed positive expression in the main cell types for endometriosis development, and its decreased expression in the endometrium of endometriotic patients was also confirmed by immunohistochemistry (IHC). The nomogram model established based on it displayed good predictive value.

Gene expression analysis in endometriosis: Immunopathology insights, transcription factors and therapeutic targets

Background

Endometriosis is recognized as an estrogen-dependent inflammation disorder, estimated to affect 8%-15% of women of childbearing age. Currently, the etiology and pathogenesis of endometriosis are not completely clear. Underlying mechanism for endometriosis is still under debate and needs further exploration. The involvement of transcription factors and immune mediations may be involved in the pathophysiological process of endometriosis, but the specific mechanism remains to be explored. This study aims to investigate the underlying molecular mechanisms in endometriosis.

Methods

The gene expression profile of endometriosis was obtained from the gene expression omnibus (GEO) database. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were applied to the endometriosis GSE7305 datasets. Cibersort and MCP-counter were used to explore the immune response gene sets, immune response pathway, and immune environment. Differentially expressed genes (DEGs) were identified and screened. Common biological pathways were being investigated using the kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis. Transcription factors were from The Human Transcription Factors. The least absolute shrinkage and selection operator (Lasso) model identified four differential expressions of transcription factors (AEBP1, HOXB6, KLF2, and RORB). Their diagnostic value was calculated by receiver operating characteristic (ROC) curve analysis and validated in the validation cohort (GSE11691, GSE23339). By constructing the interaction network of crucial transcription factors, weighted gene coexpression network analysis (WGCNA) was used to search for key module genes. Metascape was used for enrichment analysis of essential module genes and obtained HOXB6, KLF2. The HOXB6 and KLF2 were further verified as the only two intersection genes according to Support Vector Machine Recursive Feature Elimination (SVM-RFE) and random forest models. We constructed ceRNA (lncRNA-miRNA-mRNA) networks with four potential transcription factors. Finally, we performed molecular docking for goserelin and dienogest with four transcription factors (AEBP1, HOXB6, KLF2, and RORB) to screen potential drug targets.

Results

Immune and metabolic pathways were enriched in GSVA and GSEA. In single sample gene set enrichment analysis (ssGSEA), most immune infiltrating cells, immune response gene sets, and immune response pathways are differentially expressed between endometriosis and non-endometriosis. Twenty-seven transcription factors were screened from differentially expressed genes. Most of the twenty-seven transcription factors were correlated with immune infiltrating cells, immune response gene sets and immune response pathways. Furthermore, Adipocyte enhancer binding protein 1 (AEBP1), Homeobox B6 (HOXB6), Kruppel Like Factor 2 (KLF2) and RAR Related Orphan Receptor B (RORB) were selected out from twenty-seven transcription factors. ROC analysis showed that the four genes had a high diagnostic value for endometriosis. In addition, KLF2 and HOXB6 were found to play particularly important roles in multiple modules (String, WGCNA, SVM-RFE, random forest) on the gene interaction network. Using the ceRNA network, we found that NEAT1 may regulate the expressions of AEBP1, HOXB6 and RORB, while X Inactive Specific Transcript (XIST) may control the expressions of HOXB6, RORB and KLF2. Finally, we found that goserelin and dienogest may be potential drugs to regulate AEBP1, HOXB6, KLF2 and RORB through molecular docking.

Conclusions

AEBP1, HOXB6, KLF2, and RORB may be potential biomarkers for endometriosis. Two of them, KLF2 and HOXB6, are critical molecules in the gene interaction network of endometriosis. Discovered by molecular docking, AEBP1, HOXB6, KLF2, and RORB are targets for goserelin and dienogest.

Histotyping and grading of endometriosis and its association with clinico-pathological parameters

Current clinical staging/grading schemes of endometriosis show poor correlation with clinical symptoms and histopathological confirmation is only in half of the clinically suspected endometriosis. In this study, done over an 8-year period, several histological features were analysed including an attempt to grade the severity of endometriosis histologically based on the number of foci per low power field. The components in each focus, the phasing of the glands and stroma, the type of glands (endometrial type or undifferentiated type), and stromal features were all analysed. This study attempts to histologically grade endometriosis while relating it to the clinical manifestations and anatomical location. Eighty cases of endometriosis were included. Most common clinical presentation was cyclical pain (n = 62) and the most common anatomical location was adnexa (n = 50). Histologically, severe endometriosis (>3 foci) was seen in 37 cases. The components were mixed in 68 cases. Well-differentiated glandular pattern was typical (n = 54), while 6 cases had undifferentiated. Proliferative phase was seen in 38 cases. Fibrosis and inflammation were present in 29 and 42 cases, respectively. Significant vascular proliferation and plasma cell infiltrate was noted (n = 35). The severe grade was significantly associated with fibrosis (p = 0.03) and inflammation (p = 0.014). Endometriotic foci, unlike eutopic endometrium, shows significant plasma cell infiltrate and vascular proliferation.IMPACT STATEMENTWhat is already known on this subject? Endometriosis, a chronic inflammatory condition in reproductive age group women. The currently used clinical staging and grading systems show poor correlation with patient symptoms and treatment outcomes. Endometriosis with classical histopathological features pose no diagnostic difficulty, however, there is poor concordance with histopathology. Atypical endometriosis is proposed as potential precursor for endometriosis related neoplasms, however, it remains as a controversial entity.What do the results of this study add? The study identifies the uncommon histological patterns which may be encountered in biopsy samples from clinically identified endometriotic lesions. The recognition of these patterns will reduce clinico-pathological discrepancies. In keeping with the other grading systems, attempts at histological grading did not show any correlation with location or patient symptoms. Atypical features were seen only in two cases and was likely to be reactive in nature.What are the implications of these findings for clinical practice and/or further research? Undifferentiated glandular pattern is often a under-recognized histological pattern. Histological grading of severity was a novel attempt to correlate with clinical parameters. Significant plasma cell infiltrate and vascular proliferation in endometriotic foci, underscores the quest for novel therapeutic targets. This study suggests that the use of non-invasive diagnostic methods like fibroscan/inflammatory markers to clinically identify severe disease should be investigated further.

Niclosamide targets the dynamic progression of macrophages for the resolution of endometriosis in a mouse model

Due to the vital roles of macrophages in the pathogenesis of endometriosis, targeting macrophages could be a promising therapeutic direction. Here, we investigated the efficacy of niclosamide for the resolution of a perturbed microenvironment caused by dysregulated macrophages in a mouse model of endometriosis. Single-cell transcriptomic analysis revealed the heterogeneity of macrophages including three intermediate subtypes with sharing characteristics of traditional “small” or “large” peritoneal macrophages (SPMs and LPMs) in the peritoneal cavity. Endometriosis-like lesions (ELL) enhanced the differentiation of recruited macrophages, promoted the replenishment of resident LPMs, and increased the ablation of embryo-derived LPMs, which were stepwise suppressed by niclosamide. In addition, niclosamide restored intercellular communications between macrophages and B cells. Therefore, niclosamide rescued the perturbed microenvironment in endometriosis through its fine regulations on the dynamic progression of macrophages. Validation of similar macrophage pathogenesis in patients will further promote the clinical usage of niclosamide for endometriosis treatment.

The Tumor Microenvironment of Clear-Cell Ovarian Cancer

Some patients with advanced clear-cell ovarian cancer (CCOC) respond to immunotherapy; however, little is known about the tumor microenvironment (TME) of this relatively rare disease. Here, we describe a comprehensive quantitative and topographical analysis of biopsies from 45 patients, 9 with Federation Internationale des Gynaecologistes et Obstetristes (FIGO) stage I/II (early CCOC) and 36 with FIGO stage III/IV (advanced CCOC). We investigated 14 immune cell phenotype markers, PD-1 and ligands, and collagen structure and texture. We interrogated a microarray data set from a second cohort of 29 patients and compared the TMEs of ARID1A-wildtype (ARID1Awt) versus ARID1A-mutant (ARID1Amut) disease. We found significant variations in immune cell frequency and phenotype, checkpoint expression, and collagen matrix between the malignant cell area (MCA), leading edge (LE), and stroma. The MCA had the largest population of CD138+ plasma cells, the LE had more CD20+ B cells and T cells, whereas the stroma had more mast cells and αSMA+ fibroblasts. PD-L2 was expressed predominantly on malignant cells and was the dominant PD-1 ligand. Compared with early CCOC, advanced-stage disease had significantly more fibroblasts and a more complex collagen matrix, with microarray analysis indicating "TGFβ remodeling of the extracellular matrix" as the most significantly enriched pathway. Data showed significant differences in immune cell populations, collagen matrix, and cytokine expression between ARID1Awt and ARID1Amut CCOC, which may reflect different paths of tumorigenesis and the relationship to endometriosis. Increased infiltration of CD8+ T cells within the MCA and CD4+ T cells at the LE and stroma significantly associated with decreased overall survival.

Endometrial stromal PRMT5 plays a crucial role in decidualization by regulating NF-κB signaling in endometriosis

Decidualization is a prerequisite for successful embryo implantation, in which elongated fibroblast-like endometrial stromal cells differentiate into more rounded decidual cells. Accumulating evidence has stressed the important role of the defective eutopic endometrium in infertility in endometriosis patients. However, the role of arginine methylation in the process of physiological decidualization and pathological decidualization defects is not clear. Here, we observed that the expression level of PRMT5, the main type II PRMT, was decreased in the endometrium of endometriosis patients, predominantly in stromal cells. Compared with the undecidualized state, PRMT5 was increased in the stromal cells of normal secretory endometrium in humans and in the decidua of normal pregnant mice or mice with artificially induced decidualization. The inhibition of PRMT5 resulted in a significant decrease in uterine weight and decidualization-related regulator expression, including FOXO1, HOXA10 and WNT4, in mice and IGFBP1 and prolactin levels in human endometrial stromal cells. Transcriptome analysis showed that decreased PRMT5 activity led to NF-κB signaling activation by inducing p65 translocation to the nucleus, which was also observed in endometriosis patients. Finally, overexpression of PRMT5 rescued the defective expression of IGFBP1 and prolactin in primary endometrial stromal cells from endometriosis patients. Our results indicate that promotion of PRMT5 may provide novel therapeutic strategies for the treatment of decidualization defects in infertile women, such as those with endometriosis.

Relationship between Oxidative Stress and Endometritis: Exploiting Knowledge Gained in Mares and Cows

The etiopathogenesis of endometritis in mares and cows differs significantly; this could depend on a different sensitivity and reactivity of the uterus but also on endocrine and rearing factors and different stress sources. In both species, microorganisms and the immune system play a primary role in the generation of this pathology. Microbiological and cytological tests support clinical examination and significantly improve diagnostic accuracy. For both species, during the inflammation, immune cells invade the endometrium and release bioactive substances to contrast primary or secondary pathogen contamination. These molecules are traceable to cytokines, chemokines, and prostaglandins as well as reactive oxygen and nitrogen species (ROS and RNS), collectively known as RONS. The RONS-mediated oxidation causes morphological and functional alterations of macromolecules, such as proteins, lipids, and nucleic acids, with the consequent production of derivative compounds capable of playing harmful effects. These bioactive molecules and by-products, which have recently become increasingly popular as diagnostic biomarkers, enter the bloodstream, influencing the functionality of organs and tissues. This review has collected and compared information obtained in cows and mares related to the diagnostic potential of these biomarkers that are assessed by using different methods in samples from either blood plasma or uterine fluid.

Genes Relating to Biological Processes of Endometriosis: Expression Changes Common to a Mouse Model and Patients

Endometriosis is one of the most common gynecological diseases in women of reproductive age. Retrograde menstruation is considered a major reason for the development of endometriosis. The syngeneic transplantation mouse model is an endometriosis animal model that is considered to mimic retrograde menstruation. However, it remains poorly understood which genetic signatures of endometriosis are reflected in this model. Here, we employed an in vivo syngeneic mouse endometriosis model and identified differentially expressed genes (DEGs) between the ectopic and eutopic tissues using microarray analysis. Three gene expression profile datasets, GSE5108, GSE7305, and GSE11691, were downloaded from the Gene Expression Omnibus database and DEGs between ectopic and eutopic tissues from the same patients were identified. Gene ontology analysis of the DEGs revealed that biological processes including cell adhesion, the inflammatory response, the response to mechanical stimulus, cell proliferation, and extracellular matrix organization were enriched in both the model and patients. Of the 195 DEGs common to the model and patients, 154 showed the same expression pattern, and 28 of these 154 DEGs came up when PubMed was searched for each gene along with the terms "endometriosis" and "development". This is the first comparison of the DEGs of the mouse syngeneic endometriosis model and those of patients, and we identified the biological processes common to the model and patients at the transcriptional level. This model may be useful to evaluate the efficacy of drugs which target these biological processes.

Integrated bioinformatics analysis uncovers characteristic genes and molecular subtyping system for endometriosis

Objective: Endometriosis is a chronic inflammatory estrogen-dependent disease with the growth of endometrial tissues outside the uterine cavity. Nevertheless, the etiology of endometriosis is still unclear. Integrated bioinformatics analysis was implemented to reveal the molecular mechanisms underlying this disease.

Methods: A total of four gene expression datasets (GSE7305, GSE11691, GSE23339, and GSE25628) were retrieved from the GEO, which were merged into a meta-dataset, followed by the removal of batch effects via the sva package. Weighted gene co-expression network analysis (WGCNA) was implemented, and endometriosis-related genes were screened under normal and endometriosis conditions. Thereafter, characteristic genes were determined via Lasso analysis. The diagnostic performance was estimated via receiver operating characteristic curves, and epigenetic and post-transcriptional modifications were analyzed. Small molecular compounds were predicted. Unsupervised clustering analysis was conducted via non-negative matrix factorization algorithm. The enriched pathways were analyzed via gene set enrichment analysis or GSVA. Immune features were evaluated according to immune-checkpoints, HLA, receptors, chemokines, and immune cells.

Results: In total, four characteristic genes (BGN, AQP1, ELMO1, and DDR2) were determined for endometriosis, all of which exhibited the favorable efficacy in diagnosing endometriosis. Their aberrant levels were modulated by epigenetic and post-transcriptional modifications. In total, 51 potential drugs were predicted against endometriosis. The characteristic genes exhibited remarkable associations with immunological function. Three subtypes were classified across endometriosis, with different mechanisms and immune features.

Conclusion: Our study reveals the characteristic genes and novel molecular subtyping of endometriosis, contributing to the early diagnosis and intervention in endometriosis.