In search of key genes associated with endometriosis using bioinformatics approach

Angiotensin II - AT1 receptor signalling regulates the plasminogen-plasmin system in human stromal endometrial cells increasing extracellular matrix degradation, cell migration and inducing a proinflammatory profile

The pivotal role of human endometrial stromal cells (hESCs) in the development of endometriosis lies in their ability to adopt a pro-invasive and proinflammatory profile upon migration to areas outside the uterus. However, the molecular mechanisms involved in these events remain unclear. In this study, we investigated how angiotensin II (Ang II) affects the plasminogen-plasmin system in hESCs, and the mechanisms underlying cell proliferation, migration, matrix degradation, and inflammation. Precursors, receptors, and peptidases involved in angiotensin metabolism increased significantly in Ang II-treated hESCs. The expression and activity of tissue (tPA)- and urokinase (uPA)- type plasminogen activators and the receptor for uPA (uPAR) were induced in the presence of Ang II. The up-regulation of tPA-uPA/uPAR pathway significantly contributes to heightened plasmin production both on the surface of hESCs and in their conditioned media. As a result, the plasmin generation induced by Ang II enhances the degradation of fibrin and matrix proteins, while also boosting hESC viability, proliferation, and migration through the up-regulation of growth factor expression. Notably, Ang II-induced hESC migration was dependent on the generation of active plasmin on cell surface. Ang II regulates oxidative and inflammatory signalling in hESCs primarily via NADPH oxidase and through the up-regulation of proinflammatory cytokines and adhesion molecules. Interestingly, Ang II receptor (AT1R) blockage, decreased plasmin generation, tPA-uPA/uPAR expression and hESC migration. Our results suggest that Ang II/AT1R axis regulates hESC proliferation and migration through tPA-uPA/uPAR pathway activation and plasmin generation. We propose the Ang II/AT1R axis as a potential target for endometriosis treatment.

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.

The involvement of RNA N6-methyladenosine and histone methylation modification in decidualization and endometriosis-associated infertility

Defective decidualization of endometrial stromal cells (ESCs) in endometriosis (EM) patients leads to inadequate endometrial receptivity and EM-associated infertility. Hypoxia is an inevitable pathological process of EM and participates in deficient decidualization of the eutopic secretory endometrium. Enhancer of zeste homology 2 (EZH2) is a methyltransferase which catalyses H3K27Me3, leading to decreased expression levels of target genes. Although EZH2 expression is low under normal decidualization, it is abundantly increased in the eutopic secretory endometrium of EM and is induced by hypoxia. Chromatin immunoprecipitation-PCR results revealed that decidua marker IGFBP1 is a direct target of EZH2, partially explaining the increased levels of histone methylation modification in defected decidualization of EM. To mechanism controlling this, we examined the effects of hypoxia on EZH2 and decidualization. EZH2 mRNA showed decreased m6 A modification and increased expression levels under hypoxia and decidualization combined treatment. Increased EZH2 expression was due to the increased expression of m6 A demethylase ALKBH5 and decreased expression of the m6 A reader protein YTHDF2. YTHDF2 directly bind to the m6 A modification site of EZH2 to promote EZH2 mRNA degradation in ESCs. Moreover, selective Ezh2 depletion in mouse ESCs increased endometrial receptivity and improved mouse fertility by up-regulating decidua marker IGFBP1 expression. This is the first report showing that YTHDF2 can act as a m6 A reader to promote decidualization by decreasing the stability of EZH2 mRNA and further increasing the expression of IGFBP1 in ESCs. Taken together, our findings highlight the critical role of EZH2/H3K27Me3 in decidualization and reveal a novel epigenetic mechanism by which hypoxia can suppress EM decidualization by decreasing the m6 A modification of EZH2 mRNA.

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.

Identification of Potential Active Ingredients and Mechanisms of Cattail Pollen for Treating Infertile Patients With Endometriosis Based on Bioinformatics and Molecular Docking

Introduction: Cattail Pollen is a commonly used Chinese medicine for promoting blood circulation and removing blood stasis in infertility patients with endometriosis, but its ingredients and mechanism of action are still unclear. The aims of this study were to explore the potential active ingredients, targets and mechanisms of Cattail Pollen in treating infertility patients with endometriosis based on bioinformatics and molecular docking. Methods: The GSE120103 dataset was downloaded from the Gene Expression Omnibus (GEO) database to screen out differentially expressed genes. Cytoscape software was constructed to construct the protein–protein interaction network and screen for hub proteins, and molecular docking was performed to identify the binding activity of Cattail Pollen active ingredients and infertility genes. Then, DAVID software was used to perform gene ontology (GO) functional analysis and KEGG pathway enrichment analysis on differentially expressed genes. Results: There were 1320 differentially expressed genes in patients with endometriosis. ADCY5, RLN3, and ADCY6 proteins encoded by genes that were upregulated in infertile patients with endometriosis. Eight active ingredients of Cattail Pollen were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform: naringenin ((2R)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one), arachidonic acid, isorhamnetin, β-sitosterol, kaempferol, Testosterone palmitate, kaempferol-3-O-α-L-rhamnosyl(1→2)-β-D-glucoside and quercetin. Molecular docking identified that the binding activity of arachidonic acid with ADCY5, RLN3, and ADCY6; and testosterone palmitate with ADCY5 and ADCY6 was strong. GO analysis suggested that differentially expressed genes were involved in multiple biological processes, cellular components, and molecular functions. KEGG enrichment analysis found that differentially expressed genes were enriched in neuroactive ligand–receptor interaction, cytokine–cytokine receptor interaction, chemokine signaling pathway, and Jak-STAT signaling pathway. Conclusions: This study discovered the differentially expressed genes of naturally conceived and infertile patients with endometriosis, and clarified the effective ingredients, targets, and potential signaling pathways of Cattail Pollen in the treatment of infertility patients with endometriosis.

Exploration of the core protein network under endometriosis symptomatology using a computational approach

BACKGROUND

Endometriosis is defined by implantation and invasive growth of endometrial tissue in extra-uterine locations causing heterogeneous symptoms, and a unique clinical picture for each patient. Understanding the complex biological mechanisms underlying these symptoms and the protein networks involved may be useful for early diagnosis and identification of pharmacological targets.

METHODS

In the present study, we combined three approaches (i) a text-mining analysis to perform a systematic search of proteins over existing literature, (ii) a functional enrichment analysis to identify the biological pathways in which proteins are most involved, and (iii) a protein-protein interaction (PPI) network to identify which proteins modulate the most strongly the symptomatology of endometriosis.

RESULTS

Two hundred seventy-eight proteins associated with endometriosis symptomatology in the scientific literature were extracted. Thirty-five proteins were selected according to degree and betweenness scores criteria. The most enriched biological pathways associated with these symptoms were (i) Interleukin-4 and Interleukin-13 signaling (p = 1.11 x 10^-16), (ii) Signaling by Interleukins (p = 1.11 x 10^-16), (iii) Cytokine signaling in Immune system (p = 1.11 x 10^-16), and (iv) Interleukin-10 signaling (p = 5.66 x 10^-15).

CONCLUSION

Our study identified some key proteins with the ability to modulate endometriosis symptomatology. Our findings indicate that both pro- and anti-inflammatory biological pathways may play important roles in the symptomatology of endometriosis. This approach represents a genuine systemic method that may complement traditional experimental studies. The current data can be used to identify promising biomarkers for early diagnosis and potential therapeutic targets.

Bioinformatics Analysis Identifies Molecular Markers Regulating Development and Progression of Endometriosis and Potential Therapeutic Drugs

Endometriosis, a common disease that presents as polymorphism, invasiveness, and extensiveness, with clinical manifestations including dysmenorrhea, infertility, and menstrual abnormalities, seriously affects quality of life in women. To date, its underlying etiological mechanism of action and the associated regulatory genes remain unclear. This study aimed to identify molecular markers and elucidate mechanisms underlying the development and progression of endometriosis. Specifically, we downloaded five microarray expression datasets, namely, GSE11691, GSE23339, GSE25628, GSE7305, and GSE105764, from the Gene Expression Omnibus (GEO) database. These datasets, obtained from endometriosis tissues, alongside normal controls, were subjected to in-depth bioinformatics analysis for identification of differentially expressed genes (DEGs), followed by analysis of their function and pathways via gene ontology (GO) and KEGG pathway enrichment analyses. Moreover, we constructed a protein–protein interaction (PPI) network to explore the hub genes and modules, and then applied machine learning algorithms support vector machine-recursive feature elimination and least absolute shrinkage and selection operator (LASSO) analysis to identify key genes. Furthermore, we adopted the CIBERSORTx algorithm to estimate levels of immune cell infiltration while the connective map (CMAP) database was used to identify potential therapeutic drugs in endometriosis. As a result, a total of 423 DEGs, namely, 233 and 190 upregulated and downregulated, were identified. On the other hand, a total of 1,733 PPIs were obtained from the PPI network. The DEGs were mainly enriched in immune-related mechanisms. Furthermore, machine learning and LASSO algorithms identified three key genes, namely, apelin receptor (APLNR), C–C motif chemokine ligand 21 (CCL21), and Fc fragment of IgG receptor IIa (FCGR2A). Furthermore, 16 small molecular compounds associated with endometriosis treatment were identified, and their mechanism of action was also revealed. Taken together, the findings of this study provide new insights into the molecular factors regulating occurrence and progression of endometriosis and its underlying mechanism of action. The identified therapeutic drugs and molecular markers may have clinical significance in early diagnosis of endometriosis.

E3 ubiquitin ligase TRIM24 deficiency promotes NLRP3/caspase-1/IL-1β-mediated pyroptosis in endometriosis

Endometriosis is an inflammation-dependent disease that shares similarities with malignant tumors including attachment and infiltration. Tripartite motif-containing 24 (TRIM24) has been illustrated in inflammatory responses and gynecological tumors, and Nod-like receptor protein 3 (NLRP3) inflammasome has been implicated in endometriosis. However, the involvement of TRIM24 and the role of NLRP3/caspase-1/interleukin-1β (IL-1β)-mediated pyroptosis in endometriosis remain obscure. In this study, we originally detected the decreased expression of TRIM24 in the ectopic endometrium of endometriosis compared with the normal endometrium. Then we measured the promoted protein expression of pyroptotic biomarkers (NLRP3, procaspase-1, caspase-1, pro-IL-1β, and IL-1β) using Western blot analysis and the stimulated secretion of IL-1β and IL-18 by enzyme-linked immunosorbent assay in ectopic human endometrial stromal cells (hESC) compared with normal hESC. TRIM24-small-interfering RNA (siTRIM24) was used to silence TRIM24, whereas TRIM24-pcDNA3.1 was used for overexpressing TRIM24. The migration of hESC was determined by a Transwell migration assay. Coimmunoprecipitation and ubiquitination analyses were conducted to explore the interaction between TRIM24 and NLRP3. Subsequently, we found that TRIM24 negatively regulated NLRP3/caspase-1/IL-1β-mediated pyroptosis and cell migration of hESC, and CY-09, the specific inhibitor of NLRP3, could reverse the promoted pyroptosis and cell migration induced by siTRIM24. Furthermore, TRIM24 interacted with NLRP3 and the upregulation of TRIM24 facilitated the ubiquitination of NLRP3 in ectopic hESC. Our findings suggest that TRIM24 may participate in the progression of endometriosis through the NLRP3/caspase-1/IL-1β-mediated pyroptotic pathway via ubiquitination of NLRP3, which reveals the significant molecular mechanism underlying endometriosis.

Guidelines for biomarker discovery in endometrium: correcting for menstrual cycle bias reveals new genes associated with uterine disorders

Transcriptomic approaches are increasingly used in reproductive medicine to identify candidate endometrial biomarkers. However, it is known that endometrial progression in the molecular biology of the menstrual cycle is a main factor that could affect the discovery of disorder-related genes. Therefore, the aim of this study was to systematically review current practices for considering the menstrual cycle effect and to demonstrate its bias in the identification of potential biomarkers. From the 35 studies meeting the criteria, 31.43% did not register the menstrual cycle phase. We analysed the menstrual cycle effect in 11 papers (including 12 studies) from Gene Expression Omnibus: three evaluating endometriosis, two evaluating recurrent implantation failure, one evaluating recurrent pregnancy loss, one evaluating uterine fibroids and five control studies, which collected endometrial samples throughout menstrual cycle. An average of 44.2% more genes were identified after removing menstrual cycle bias using linear models. This effect was observed even if studies were balanced in the proportion of samples collected at different endometrial stages or only in the mid-secretory phase. Our bias correction method increased the statistical power by retrieving more candidate genes than per-phase independent analyses. Thanks to this practice, we discovered 544 novel candidate genes for eutopic endometriosis, 158 genes for ectopic ovarian endometriosis and 27 genes for recurrent implantation failure. In conclusion, we demonstrate that menstrual cycle progression masks molecular biomarkers, provides new guidelines to unmask them and proposes a new classification that distinguishes between biomarkers of disorder or/and menstrual cycle progression.

Cross-disorder analysis of endometriosis and its comorbid diseases reveals shared genes and molecular pathways and proposes putative biomarkers of endometriosis

RESEARCH QUESTION

Women with endometriosis are considered to be at higher risk of several chronic diseases, such as autoimmune disorders, gynaecological cancers, asthma/atopic diseases and cardiovascular and inflammatory bowel diseases. Could the study of endometriosis-associated comorbidities help to identify potential biomarkers and target pathways of endometriosis?

DESIGN

A systematic review was performed to identify all possible endometriosis-associated comorbid conditions. Next, this list of disorders was coded into MeSH terms, and the gene expression profiles were downloaded from the Phenopedia database and subsequently analysed following a systems biology approach.

RESULTS

The results identified a group of 127 candidate genes that were recurrently expressed in endometriosis and its closest comorbidities and that were defined as 'endometriosis sibling disorders' (ESD). The enrichment analysis showed that these candidate genes are principally involved in immune and drug responses, hormone metabolism and cell proliferation, which are well-known hallmarks of endometriosis. The expression of ESD genes was then validated on independent sample cohorts (n = 207 samples), in which the involvement of 16 genes (AGTR1, BDNF, C3, CCL2, CD40, CYP17A1, ESR1, IGF1, IGF2, IL10, MMP1, MMP7, MMP9, PGR, SERPINE1 and TIMP2) in endometriosis was confirmed. Several of these genes harbour polymorphisms that associate to either endometriosis or its comorbid conditions.

CONCLUSIONS

The study results highlight the molecular processes underlying the aetiopathogenesis of endometriosis and its comorbid conditions, and identify putative endometriosis biomarkers.

Identification of differentially expressed genes and signaling pathways involved in endometriosis by integrated bioinformatics analysis

Endometriosis is a common gynecological disease characterized by the presence and growth of endometrial tissue outside the uterus, including the pelvis and abdominal cavity. This condition causes various clinical symptoms, such as non-menstrual pelvic pain, dysmenorrhea and infertility, seriously affecting the health and quality of life of women. To date, the specific mechanism and the key molecules of endometriosis remain uncertain. The purpose of the present study was to elucidate the mechanisms involved in the development and persistence of the disease. A number of mRNA expression profile datasets (namely GSE11691, GSE23339, GSE25628 and GSE78851) were downloaded from the Gene Expression Omnibus (GEO) database. These gene expression profiles were normalized, and the differentially expressed genes (DEGs) were identified by integrated bioinformatics analysis. A total of 103 DEGs were screened upon excluding the genes that exhibited inconsistency of expression (P<0.05). Furthermore, the Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and construction of protein-protein interaction networks of DEGs were performed using online software. The results revealed that the DEGs were closely associated with cell migration, adherens junction and hypoxia-inducible factor signaling. In addition, immunohistochemical assay results were found to be consistent with the bioinformatics results. The present study may help us understand underlying molecular mechanisms and the development of endometriosis, which has a great clinical significance for early diagnosis of the disease.

Annexin A1 can inhibit the in vitro invasive ability of nasopharyngeal carcinoma cells possibly through Annexin A1/S100A9/Vimentin interaction

Annexin A1 is a member of a large superfamily of glucocorticoid-regulated, calcium- and phospholipid-binding proteins. Our previous studies have shown that the abnormal expression of Annexin A1 is related to the occurrence and development of nasopharyngeal carcinoma (NPC). To understand the roles of Annexin A1 in the tumorigenesis of NPC, targeted proteomic analysis was performed on Annexin A1-associated proteins from NPC cells. We identified 436 proteins associated with Annexin A1, as well as two Annexin A1-interacted key proteins, S100A9 and Vimentin, which were confirmed by co-immunoprecipitation. Gene function classification revealed that the Annexin A1-associated proteins can be grouped into 21 clusters based on their molecular functions. Protein–protein interaction analysis indicated that Annexin A1 /S100A9/Vimentin interactions may be involved in the invasion and metastasis of NPC because they can form complexes in NPC cells. The down-regulation of Annexin A1 in NPC may lead to the overexpression of S100A9/Vimentin, which may increase the possibility of the invasion ability of NPC cells by adjusting the function of cytoskeleton proteins. Results suggested that the biological functions of Annexin A1 in NPC were diverse, and that Annexin A1 can inhibit the in vitro invasive ability of NPC cells through Annexin A1 /S100A9/Vimentin interaction.

Endometriosis research using capture microdissection techniques: Progress and future applications

Endometriosis is a common gynecological disease with high prevalence, while its etiology and pathophysiology have remained to be fully elucidated. Previous evidence suggested that this disorder may be in part or completely of somatic origin. However, traditional endometrial samples may not be ideal for investigation, as target cells, including epithelial and stromal cells, in endometriotic lesions are too sparse to be analyzed. Recently, capture microdissection techniques have been used to overcome these limitations and eliminate tissue heterogeneity in endometriosis research. Therefore, the present review summarized the alterations in epithelial and stromal cells in endometriosis tissues isolated through capture microdissection, outlined recent progress and provided directions for future investigation of the pathogenesis of endometriosis.