Analysis of key candidate genes and pathways of endometriosis pathophysiology by a genomics-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.

Identification of potential diagnostic biomarkers and therapeutic targets for endometriosis based on bioinformatics and machine learning analysis

PURPOSE

Endometriosis (EMs) is a major gynecological condition in women. Due to the absence of definitive symptoms, its early detection is very challenging; thus, it is crucial to find biomarkers to ease its diagnosis and therapy. Here, we aimed to identify potential diagnostic and therapeutic targets for EMs by constructing a regulatory network and using machine learning approaches.

METHODS

Three Gene Expression Omnibus (GEO) datasets were merged, and differentially expressed genes (DEGS) were identified after preprocessing steps. Using the DEGs, a transcription factor (TF)-mRNA-miRNA regulatory network was constructed, and hub genes were detected based on four different algorithms in CytoHubba. The hub genes were used to build a GaussianNB diagnostic model and also in docking analysis that were performed using Discovery Studio and AutoDock Vina software.

RESULTS

A total of 119 DEGs were identified between EMs and non-EMs samples. A regulatory network consisting of 52 mRNAs, 249 miRNAs, and 37 TFs was then constructed. The diagnostic model was introduced using the hub genes selected from the network (GATA6, HMOX1, HS3ST1, NFASC, and PTGIS) that its area under the curve (AUC) was 0.98 and 0.92 in the training and validation cohorts, respectively. Based on docking analysis, two chemical compounds, rofecoxib and retinoic acid, had potential therapeutic effects on EMs.

CONCLUSION

In conclusion, this study identified potential diagnostic and therapeutic targets for EMs which demand more experimental confirmations.

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.

Multi-omics analysis reveals the interaction between the complement system and the coagulation cascade in the development of endometriosis

Endometriosis (EMS) is a disease that shows immune dysfunction and chronic inflammation characteristics, suggesting a role of complement system in its pathophysiology. To find out the hub genes and pathways involved in the pathogenesis of EMs, three raw microarray datasets were recruited from the Gene Expression Omnibus database (GEO). Then, a series of bioinformatics technologies including gene ontology (GO), Hallmark pathway enrichment, protein-protein interaction (PPI) network and gene co-expression correlation analysis were performed to identify hub genes. The hub genes were further verified by the Real-time quantitative polymerase chain reaction (RT-PCR) and Western Blot (WB). We identified 129 differentially expressed genes (DEGs) in EMs, of which 78 were up-regulated and 51 were down-regulated. Through GO functional enrichment analysis, we found that the DEGs are mainly enriched in cell adhesion, extracellular matrix remodeling, chemokine regulation, angiogenesis regulation, epithelial cell proliferation, et al. In Hallmark pathway enrichment analysis, coagulation pathway showed great significance and the terms in which included the central complement factors. Moreover, the genes were dominating in PPI network. Combined co-expression analysis with experimental verification, we found that the up-regulated expression of complement (C1S, C1QA, C1R, and C3) was positively related to tissue factor (TF) in EMs. In this study, we discovered the over expression complement and the positive correlation between complement and TF in EMs, which suggested that interaction of complement and coagulation system may play a role within the pathophysiology of EMS.

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.

Involvement of angiotensin II receptor type 1/NF-κB signaling in the development of endometriosis

Endometriosis (EM) is a common disease in women; however, the signaling pathways and related genes underlying the mechanisms of EM remain unclear. The present study aimed to investigate the role of angiotensin II receptor type 1 (AGTR1) in the pathogenesis of EM. Human EM tissues were collected, and the expression levels of AGTR1 and NF-κB in the tissues were analyzed using immunochemistry and western blotting, while the estrogen levels in the EM tissues were determined by ELISA. In vitro human endometrial stromal cells were used to investigate the expression levels of AGTR1 following exposure to estrogen; the interaction between AGTR1 and NF-κB was determined using reverse transcription-quantitative PCR and western blotting; and the effects of AGTR1 on cell proliferation, as well as the apoptotic and migratory abilities of the cells were evaluated using WST-1 assays, wound healing assays and flow cytometry, respectively. It was observed that both the expression levels of AGTR1 and the activity of NF-κB were increased in human EM tissues and stromal cells, and this activation of AGTR1 subsequently increased the activity of NF-κB. Moreover, estrogen was found to regulate the expression levels of AGTR1 in stromal cells. The activation of AGTR1 was demonstrated to promote cell proliferation and migration, in addition to preventing cells from undergoing apoptosis. In conclusion, the present study suggested that the increased activity of the AGTR1-NF-κB axis following the decreased exposure to estrogen may be important for the pathogenesis of EM. In addition, AGTR1 may be a potential therapeutic target for the treatment of EM.

Bioinformatic analysis reveals the importance of epithelial-mesenchymal transition in the development of endometriosis

Background: Endometriosis is a frequently occurring disease in women, which seriously affects their quality of life. However, its etiology and pathogenesis are still unclear. Methods: To identify key genes/pathways involved in the pathogenesis of endometriosis, we recruited 3 raw microarray datasets (GSE11691, GSE7305, and GSE12768) from Gene Expression Omnibus database (GEO), which contain endometriosis tissues and normal endometrial tissues. We then performed in-depth bioinformatic analysis to determine differentially expressed genes (DEGs), followed by gene ontology (GO), Hallmark pathway enrichment and protein-protein interaction (PPI) network analysis. The findings were further validated by immunohistochemistry (IHC) staining in endometrial tissues from endometriosis or control patients. Results: We identified 186 DEGs, of which 118 were up-regulated and 68 were down-regulated. The most enriched DEGs in GO functional analysis were mainly associated with cell adhesion, inflammatory response, and extracellular exosome. We found that epithelial-mesenchymal transition (EMT) ranked first in the Hallmark pathway enrichment. EMT may potentially be induced by inflammatory cytokines such as CXCL12. IHC confirmed the down-regulation of E-cadherin (CDH1) and up-regulation of CXCL12 in endometriosis tissues. Conclusions: Utilizing bioinformatics and patient samples, we provide evidence of EMT in endometriosis. Elucidating the role of EMT will improve the understanding of the molecular mechanisms involved in the development of endometriosis.