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

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.

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.

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.

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.

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

Simple Summary

Endometritis is a widespread pathology in mares and cows and one of the leading causes of reproductive efficiency decline. Although localized in the innermost layer of the uterus, this inflammation involves the release of bioactive molecules and by-products related to molecular damage. Among the bioactive substances, a primary role is played by the reactive oxygen and nitrogen species, which, while exerting an antimicrobial effect, can amplify the inflammation, sometimes causing unwanted and self-aggravating effects. Part of these substances enters the bloodstream, with implications that range from sustaining distant effects on organs and tissues to being used as diagnostic biomarkers. The research carried out on this matter in cows and mares has maintained certain independence due to its species specificity. This review aims to collect and analyze the information available in these species to enhance diagnostics and provide new insights to prevent and treat this pathology.

Abstract

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.

Early growth response 1 transcription factor is essential for the pathogenic properties of human endometriotic epithelial cells

Although a non-malignant gynecological disorder, endometriosis displays some pathogenic features of malignancy, such as cell proliferation, migration, invasion and adaptation to hypoxia. Current treatments of endometriosis include pharmacotherapy and/or surgery, which are of limited efficacy and often associated with adverse side effects. Therefore, to develop more effective therapies to treat this disease, a broader understanding of the underlying molecular mechanisms that underpin endometriosis needs to be attained. Using immortalized human endometriotic epithelial and stromal cell lines, we demonstrate that the early growth response 1 (EGR1) transcription factor is essential for cell proliferation, migration and invasion, which represent some of the pathogenic properties of endometriotic cells. Genome-wide transcriptomics identified an EGR1-dependent transcriptome in human endometriotic epithelial cells that potentially encodes a diverse spectrum of proteins that are known to be involved in tissue pathologies. To underscore the utility of this transcriptomic data set, we demonstrate that carbonic anhydrase 9 (CA9), a homeostatic regulator of intracellular pH, is not only a molecular target of EGR1 but is also important for maintaining many of the cellular properties of human endometriotic epithelial cells that are also ascribed to EGR1. Considering therapeutic intervention strategies are actively being developed for EGR1 and CAIX in the treatment of other pathologies, we believe EGR1 and its transcriptome (which includes CA9) will offer not only a new conceptual framework to advance our understanding of endometriosis but will also furnish new molecular vulnerabilities to be leveraged as potential therapeutic options in the future treatment of endometriosis.

ASPN Is a Potential Biomarker and Associated with Immune Infiltration in Endometriosis

Objective: Endometriosis is a benign gynecological disease characterized by distant metastasis. Previous studies have discovered abnormal numbers and function of immune cells in endometriotic lesions. We aimed to find potential biomarkers of endometriosis and to explore the relationship between ASPN and the immune microenvironment of endometriosis. Methods: We obtained the GSE141549 and GSE7305 datasets containing endometriosis and normal endometrial samples from the Gene Expression Omnibus database (GEO). In the GSE141549 dataset, differentially expressed genes (DEGs) were found. The Least Absolute Shrinkage and Selection Operator (Lasso) regression and generalized linear models (GLMs) were used to screen new biomarkers. The expression levels and diagnostic utility of biomarkers were assessed in GSE7305, and biomarker expression levels were further validated using qRT-PCR and western blot. We identified DEGs between high and low expression groups of key biomarkers. Enrichment analysis was carried out to discover the target gene’s biological function. We analyzed the relationship between key biomarker expression and patient clinical features. Finally, the immune cells that infiltrate endometriosis were assessed using the Microenvironment Cell Population-Counter (MCP-counter), and the correlation of biomarker expression with immune cell infiltration and immune checkpoints genes was studied. Results: There were a total of 38 DEGs discovered. Two machine learning techniques were used to identify 10 genes. Six biomarkers (SCG2, ASPN, SLIT2, GEM, EGR1, and FOS) had good diagnostic efficiency (AUC > 0.7) by internal and external validation. We excluded previously reported related genes (SLIT2, EGR1, and FOS). ASPN was the most significantly differentially expressed biomarker between normal and ectopic endometrial tissues, as verified by qPCR. The western blot assay revealed a significant upregulation of ASPN expression in endometriotic tissues. The investigation for DEGs in the ASPN high- and low-expression groups revealed that the DEGs were particularly enriched in extracellular matrix tissue, vascular smooth muscle contraction, cytokine interactions, the calcium signaling pathway, and the chemokine signaling pathway. High ASPN expression was related to r-AFS stage (p = 0.006), age (p = 0.03), and lesion location (p < 0.001). Univariate and multivariate logistic regression analysis showed that ASPN expression was an independent influencing factor in patients with endometriosis. Immune cell infiltration analysis revealed a significant increase in T-cell, B-cell, and fibroblast infiltration in endometriosis lesions; cytotoxic lymphocyte, NK-cell, and endothelial cell infiltration were reduced. Additionally, the percentage of T cells, B cells, fibroblasts, and endothelial cells was favorably connected with ASPN expression, while the percentage of cytotoxic lymphocytes and NK cells was negatively correlated. Immune checkpoint gene (CTLA4, LAG3, CD27, CD40, and ICOS) expression and ASPN expression were positively associated. Conclusions: Increased expression of ASPN is associated with immune infiltration in endometriosis, and ASPN can be used as a diagnostic biomarker as well as a potential immunotherapeutic target in endometriosis.

Integrated bioinformatic analysis of dysregulated microRNA-mRNA co-expression network in ovarian endometriosis

INTRODUCTION

Ovarian endometriosis is a frequently occurring gynecological disease with large socioeconomic impact. Accumulating evidence has suggested that aberrant miRNA-mRNA interactions are involved in the pathogenesis and progression of ovarian endometriosis. This study aims to identify key miRNAs in ovarian endometriosis by using integrated bioinformatic analysis of a dysregulated miRNA-mRNA co-expression network.

MATERIAL AND METHODS

Expression profiling of miRNA and mRNA in three normal endometria and five pairs of ectopic/eutopic endometria from patients with ovarian endometriosis was determined by high-throughput sequencing techniques. The data were then integrated with the public sequencing datasets (GSE105764 and GSE105765) using a non-biased approach and a miRNA-mRNA co-expression regulatory network was constructed by in-depth bioinformatic analysis.

RESULTS

The constructed miRNA-mRNA network included 87 functionally DEMs, 482 target mRNAs and 1850 paired miRNA-mRNA regulatory interactions. Specifically, five miRNAs (miR-141-3p, miR-363-3p, miR-577, miR-767-5p, miR-96-5p) were gradually decreased and two miRNAs (miR-493-5p, miR-592) were gradually increased from normal endometria to eutopic endometria, and then ectopic endometria tissues. Importantly, miR-141-3p, miR-363-3p and miR-96-5p belonged to the miR-200 family, miR-106a-363 cluster and miR-183/96/182 cluster, respectively. Their target mRNAs were mainly associated with cell adhesion, locomotion and binding, which are suggested to play vital regulatory roles in the pathogenesis of ovarian endometriosis.

CONCLUSIONS

Integrated bioinformatic analysis of the miRNA-mRNA co-expression network defines the crucial roles of the miR-200 family, miR-106a-363 cluster and miR-183/96/182 cluster in the pathogenesis of ovarian endometriosis. Further in-depth functional studies are needed to unveil the molecular mechanisms of these miRNAs, and may provide clues for the optimization of therapeutic strategies for ovarian endometriosis.

COVID-19 susceptibility in endometriosis patients: a case control study

PROBLEM

Starting from November 2019, the world has had to face a devastating pandemic caused by SARS-CoV-2. Various studies have identified potential risk factors facilitating the infection, however it hasn't been demonstrated whether endometriosis might represent one of them. The purpose of this study was to evaluate if patients with endometriosis had a higher risk of contracting COVID-19 infection and, in such case, whether they developed a more severe infection than the general population. Furthermore, this study evaluated the possible correlation with the stage of endometriosis, based on the r-ASRM score, and the potential worsening of the disease during the SARS-CoV-2 infection.

METHOD OF STUDY

A case-control study was conducted from March 2020 to April 2021 at Macedonio Melloni Hospital, in Milan. A total of 401 women were recruited. The cases were 201 women with clinical or surgical diagnosis of endometriosis. The control group consisted of 200 women, without the disease. All women completed a self-administered questionnaire which evaluated their demographic and clinical characteristics, as well as a potential diagnosis of Covid-19.

RESULTS

Comparison between the two groups showed that women with endometriosis had a higher frequency of COVID-19 than the control subjects (23% vs 13.5%, P = 0.014), with a greater prevalence of fever (14.4% vs 6%, P = 0.008) and myalgias or arthralgias (11.4% vs 4.5%, P = 0.01). In multivariable logistic regression analyses, women with endometriosis had a higher risk of contracting SARS-CoV-2 infection (OR = 2.11, 95% IC: 1.20-3.80), regardless the stage of the disease.

CONCLUSION

Endometriosis increases the susceptibility to COVID-19, and women who suffer from it should be considered as fragile patients, worthy of prior access to SARS-CoV-2 vaccination campaign. This article is protected by copyright. All rights reserved.

Diagnostic gene biomarkers for predicting immune infiltration in endometriosis

Objective

To determine the potential diagnostic markers and extent of immune cell infiltration in endometriosis (EMS).

Methods

Two published profiles (GSE7305 and GSE25628 datasets) were downloaded, and the candidate biomarkers were identified by support vector machine recursive feature elimination analysis and a Lasso regression model. The diagnostic value and expression levels of biomarkers in EMS were verified by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and western blotting, then further validated in the GSE5108 dataset. CIBERSORT was used to estimate the composition pattern of immune cell components in EMS.

Results

One hundred and fifty-three differential expression genes (DEGs) were identified between EMS and endometrial with 83 upregulated and 51 downregulated genes. Gene sets related to arachidonic acid metabolism, cytokine–cytokine receptor interactions, complement and coagulation cascades, chemokine signaling pathways, and systemic lupus erythematosus were differentially activated in EMS compared with endometrial samples. Aquaporin 1 (AQP1) and ZW10 binding protein (ZWINT) were identified as diagnostic markers of EMS, which were verified using qRT-PCR and western blotting and validated in the GSE5108 dataset. Immune cell infiltrate analysis showed that AQP1 and ZWINT were correlated with M2 macrophages, NK cells, activated dendritic cells, T follicular helper cells, regulatory T cells, memory B cells, activated mast cells, and plasma cells.

Conclusion

AQP1 and ZWINT could be regarded as diagnostic markers of EMS and may provide a new direction for the study of EMS pathogenesis in the future.

Immunopathogenesis of endometriosis: An overview of the role of innate and adaptive immune cells and their mediators

BACKGROUND

Endometriosis is a chronic inflammatory disease associated with the growth and proliferation of endometrial-like tissues outside the uterus. Although the exact etiology and mechanism of the pathogenesis of the disease have not been fully elucidated, the immune system cells and the mediators produced by them can be named as effective factors in the onset and progression of the disease.

AIMS

We aim to attempt to review studies on the role of the immune system in endometriosis to better understand the pathogenesis of endometriosis.

CONTENT

Abundant production of inflammatory mediators by neutrophils and macrophages and reduced cytotoxicity of defined cells promote endometriosis at the early stages of the disease. Following an increase in the inflammation of the environment, the body takes compensatory mechanisms to reduce inflammation and establish homeostasis. For this purpose, the body produces remodeling and anti-inflammatory factors leading to slow conversion of the inflammatory environment into a non-inflammatory environment with proliferative and immunosuppressive properties. Environmental conditions induce M2 macrophages, TH2 cells, and Tregs differentiation, promoting disease progression by producing angiogenic and immunosuppressive factors. However, the exact molecular mechanism involved in changing inflammatory to non-inflammatory conditions is not yet fully understood.

IMPLICATIONS

Due to the common characteristics of endometriotic cells and cancer cells, most potential treatment options for endometriosis have been suggested due to the results of these methods in the treatment of cancer. In this pathway, immune system cells and soluble mediators can be used as targets.

Labile Heme and Heme Oxygenase-1 Maintain Tumor-Permissive Niche for Endometriosis-Associated Ovarian Cancer

Endometriosis, a painful gynecological condition accompanied by inflammation in women of reproductive age, is associated with an increased risk of ovarian cancer. We evaluated the role of peritoneal heme accumulated during menstrual cycling, as well as peritoneal and lesional macrophage phenotype, in promoting an oncogenic microenvironment. We quantified the heme-degrading enzyme, heme oxygenase-1 (HO-1, encoded by Hmox1) in normal peritoneum, endometriotic lesions and endometriosis-associated ovarian cancer (EAOC) of clear cell type (OCCC). HO-1 was expressed primarily in macrophages and increased in endometrioma and OCCC tissues relative to endometriosis and controls. Further, we compared cytokine expression profiles in peritoneal macrophages (PM) and peripheral blood mononuclear cells (PBMC) in women with endometriosis versus controls as a measure of a tumor-promoting environment in the peritoneum. We found elevated levels of HO-1 along with IL-10 and the pro-inflammatory cytokines (IL-1β, IL-16, IFNγ) in PM but not in PBMC from endometriosis patients. Using LysM-Cre:Hmox1flfl conditional knockout mice, we show that a deficiency of HO-1 in macrophages led to the suppression of growth of ID8 ovarian tumors implanted into the peritoneum. The restriction of ID8 ovarian tumor growth was associated with an increased number of Mac3+ macrophage and B cells in LysM-Cre:Hmox1flfl mice compared to controls. Functional experiments in ovarian cancer cell lines show that HO-1 is induced by heme. Low levels of exogenous heme promoted ovarian cancer colony growth in soft agar. Higher doses of heme led to slower cancer cell colony growth in soft agar and the induction of HO-1. These data suggest that perturbation of heme metabolism within the endometriotic niche and in cancer cells themselves may be an important factor that influences tumor initiation and growth.

Molecular Mechanisms Underlying the Association between Endometriosis and Ectopic Pregnancy

Endometriosis is a common inflammatory disease characterized by the presence of endometrial cells outside the uterine cavity. It is estimated that it affects 10% of women of reproductive age. Its pathogenesis covers a wide range of abnormalities, including adhesion, proliferation, and cell signaling disturbances. It is associated with a significant deterioration in quality of life as a result of chronic pelvic pain and may also lead to infertility. One of the most serious complications of endometriosis is an ectopic pregnancy (EP). Currently, the exact mechanism explaining this phenomenon is unknown; therefore, there are no effective methods of prevention. It is assumed that the pathogenesis of EP is influenced by abnormalities in the contraction of the fallopian tube muscles, the mobility of the cilia, and in the fallopian microenvironment. Endometriosis can disrupt function on all three levels and thus contribute to the implantation of the embryo beyond the physiological site. This review takes into account aspects of the molecular mechanisms involved in the pathophysiology of endometriosis and EP, with particular emphasis on the similarities between them.

Bioinformatical analysis of the key differentially expressed genes and associations with immune cell infiltration in development of endometriosis

Background

This study explored the key genes related to immune cell infiltration in endometriosis.

Results

The Gene Expression Omnibus (GEO) datasets (GSE7305, GSE7307, and GSE11691), containing a total of 37 endometriosis and 42 normal tissues, were retrieved and analyzed to determine the differentially expressed genes (DEGs). Gene ontology (GO) annotations and Kyoto Encyclopedia of Genes (KEGG) analysis were performed to identify the pathways that were significantly enriched. The xCell software was used to analyze immune cell infiltration and correlation analyses were performed to uncover the relationship between key genes and immune cells. The analysis identified 1031 DEGs (581 upregulated and 450 downregulated DEGs), while GO analysis revealed altered extracellular matrix organization, collagen-containing extracellular matrix, and glycosaminoglycan binding and KEGG enrichment showed genes related to metabolic pathways, pathways in cancer, phosphatidylinositol 3-kinase-protein kinase B (PI3K-Akt) signaling, proteoglycans in cancer, and the mitogen-activated protein kinase (MAPK) signaling pathway. Furthermore, the protein–protein interaction network revealed 10 hub genes, i.e., IL6, FN1, CDH1, CXCL8, IGF1, CDK1, PTPRC, CCNB1, MKI67, and ESR1. The xCell analysis identified immune cells with significant changes in all three datasets, including CD4⁺ and CD8⁺ T cells, CD8⁺ Tem, eosinophils, monocytes, Th1 cells, memory B-cells, activated dendritic cells (aDCs), and plasmacytoid dendritic cells (pDCs). These 10 hub genes were significantly associated with at least three types of immune cells.

Conclusions

Aberrant gene expression was related to abnormal infiltration of different immune cells in endometriosis and was associated with endometriosis development by affecting the tissue microenvironment and growth of ectopic endometrial cells.

Identification of Candidate Gene Signatures and Regulatory Networks in Endometriosis and its Related Infertility by Integrated Analysis

Endometriosis is a common gynecological disease associated with infertility, and it represents an economic burden worldwide. However, the molecular mechanisms underlying endometriosis development have not yet been fully elucidated. Here, we aimed to identify reliable key genes and the related regulatory network that may be involved in endometriosis. Differentially expressed genes (DEGs) were identified through integrated analysis of four expression datasets of endometriosis from Gene Expression Omnibus. Gene functional analysis and protein-protein interaction network construction were performed to reveal the potential function of DEGs. Subsequently, candidate hub genes were defined and validated in GSE105764 dataset, and the associated regulatory networks were constructed. Additionally, GSE120103 dataset was applied to identify the differential expression between the infertile and fertile groups of patients with stage IV endometriosis. Finally, real-time quantitative polymerase chain reaction analysis was performed to identify the differential expression of hub genes in the collected clinical specimens. Robust rank aggregation integrated analysis determined 158 DEGs. Epithelial cell differentiation was the most significantly enriched biological process, and leukocyte transendothelial migration was the most significantly enriched pathway. Eight hub genes including CLDN3, CLDN5, CLDN7, CLDN11, HOXC8, HOXC6, HOXB6, and HOXB7 were identified, and most of these were validated as abnormally expressed genes in both the infertile group and patients with endometriosis. Transcriptional factors and microRNAs related to these genes were identified. Altogether, our integrated analysis identified critical gene signatures, involved pathways, and regulatory networks, which could provide clinically significant insights into the molecular mechanisms underlying endometriosis and its related infertility.

Identification and analysis of novel endometriosis biomarkers via integrative bioinformatics

Endometriosis is a gynecological disease prevalent in women of reproductive age, and it is characterized by the ectopic presence and growth of the eutopic endometrium. The pathophysiology and diagnostic biomarkers of endometriosis have not yet been comprehensively determined. To discover molecular markers and pathways underlying the pathogenesis of endometriosis, we identified differentially expressed genes (DEGs) in three Gene Expression Omnibus microarray datasets (GSE11691, GSE23339, and GSE7305) and performed gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) network analyses. We also validated the identified genes via immunohistochemical analysis of tissues obtained from patients with endometriosis or healthy volunteers. A total of 118 DEGs (79 upregulated and 39 downregulated) were detected in each dataset with a lower (fold change) FC cutoff (log2|FC| > 1), and 17 DEGs (11 upregulated and six downregulated) with a higher FC cutoff (log2|FC| > 2). KEGG and GO functional analyses revealed enrichment of signaling pathways associated with inflammation, complement activation, cell adhesion, and extracellular matrix in endometriotic tissues. Upregulation of seven genes (C7, CFH, FZD7, LY96, PDLIM3, PTGIS, and WISP2) out of 17 was validated via comparison with external gene sets, and protein expression of four genes (LY96, PDLIM3, PTGIS, and WISP2) was further analyzed by immunohistochemistry and western blot analysis. Based on these results, we suggest that TLR4/NF-κB and Wnt/frizzled signaling pathways, as well as estrogen receptors, regulate the progression of endometriosis. These pathways may be therapeutic and diagnostic targets for endometriosis.

Adipose tissue-derived mesenchymal stem cells reduce endometriosis cellular proliferation through their anti-inflammatory effects

Objective

Endometriosis is a chronic debilitating inflammatory condition characterized by the presence of endometrial tissues outside the uterine cavity. Pelvic soreness and infertility are the usual association. Due to the poor effectiveness of the hormone therapy and the high incidence of recurrence following surgical excision, there is no single effective option for management of endometriosis. Mesenchymal stem cells (MSCs) are multipotent stromal cells studied for their broad immunoregulatory and anti-inflammatory properties; however, their efficiency in endometriosis cases is still a controversial issue. Our study aim was to evaluate whether adipose tissue-derived MSCs (AD-MSCs) could help with endometriosis through their studied anti-inflammatory role.

Methods

Female Wistar rats weighting 180 to 250 g were randomly divided into two groups: group 1, endometriosis group; established by transplanting autologous uterine tissue into rats’ peritoneal cavities and group 2, stem cell treated group; treated with AD-MSCs on the 5th day after induction of endometriosis. The proliferative activity of the endometriosis lesions was evaluated through Ki67 staining. Quantitative estimation of interferon γ, tumor necrosis factor-α, interleukin (IL)-6, IL-1β, IL-10, and transforming growth factor β expression, as well as immunohistochemical detection of CD68 positive macrophages, were used to assess the inflammatory status.

Results

The size and proliferative activity of endometriosis lesions were significantly reduced in the stem cell treated group. Stem cells efficiently mitigated endometriosis associated chronic inflammatory reactions estimated through reduction of CD68 positive macrophages and the expression of the proinflammatory cytokines.

Conclusion

Stem cell therapy can be considered a novel remedy in endometriosis possibly through its anti-inflammatory and antiproliferative properties.

Identification of Key Differentially Methylated/Expressed Genes and Pathways for Ovarian Endometriosis by Bioinformatics Analysis

The goal of this study was to identify genes that were differentially methylated and differentially expressed and their related signaling pathways in ovarian endometriosis tissue. First, the DNA methylation and gene expression profiles in the endometrial tissue of patients with ovarian endometriosis were studied using Illumina 450K methylation microarray analysis and the GSE141549 gene expression dataset. Second, differentially methylated and differentially expressed genes, herein referred to as differentially methylated/expressed genes, were identified and protein-protein interaction networks and functional analysis of these genes were determined. Third, qPCR and immunohistochemistry of patient samples was used to confirm the differential expression of a subset of differentially methylated/expressed genes. Finally, the GSE7305 dataset was used confirm the expression profile of differentially methylated/expressed genes and to determine the potential usefulness of these genes for diagnosis of endometriosis. A total of 37 hypermethylated low-expression genes and 66 hypomethylated high-expression genes were identified in ovarian endometriosis patients. Protein-protein interaction and functional analysis highlighted 8 hypermethylated low-expression genes (KRT19, KRT8, ESR1, PRL, SFN, IL20RA, IL2RB, and PAX8) and 4 hypomethylated high-expression genes (CYP11A1, NR5A1, ME1, and GSTM1). Significantly, both of these gene sets had a diagnostic value for patients with ovarian endometriosis. Signaling pathways that were identified included JAK-STAT (involving IL20RA and IL2RB), prolactin (involving PRL and ESR1), Staphylococcus aureus infection (involving KRT19), viral protein interaction with cytokine and cytokine receptor (involving IL20RA and IL2RB), cytokine-cytokine receptor interaction (involving IL20RA and IL2RB), and drug metabolism-cytochrome P450 (involving GSTM1). The differentially methylated/expressed genes and enriched signaling pathways identified in this study are likely to be associated with the process of ovarian endometriosis.

Occurrence of chronic endometritis in different types of human adenomyosis

Purpose

Human adenomyosis has an adverse effect on female fertility. Exact mechanistic basis is still unclear. We investigated the occurrence of chronic endometritis (CE) in different types of human adenomyosis.

Methods

This is a prospective non‐randomized observational study enrolling patients with focal (n = 30), diffuse (n = 26), intrinsic (n = 23), and extrinsic (n = 10) adenomyosis. Endometrial biopsy samples were collected from hysterectomy specimens. Immunohistochemical analysis was performed using antibody against CD68 (Mφ marker) with biopsy samples of intrinsic/extrinsic adenomyosis and CD138 (Syndecan‐1), a marker of plasma cells, in all biopsy samples.

Results

In GnRHa‐untreated groups, a higher trend in the occurrence of CE, as characterized by infiltration of ≥1 plasma cells in endometrial stroma, was found in women with focal (58.8%, p = 0.0849) and diffuse adenomyosis (60.0%, p = 0.0841) comparing to control women (10.0%). In women with focal adenomyosis, ipsilateral side showed a significantly higher occurrence of CE (58.8%) than on the contralateral side (11.7%) (p = 0.043). Tissue infiltration of macrophages in endometria was significantly higher in intrinsic than in extrinsic adenomyosis (p = 0.03) without showing any significant difference in the occurrence of CE between these two variants of adenomyosis.

Conclusion

A variable occurrence of CE in different types of adenomyosis may be involved in adverse reproductive outcome.