Molecular classification of endometriosis and disease stage using high-dimensional genomic data

The Impacts of Inflammatory and Autoimmune Conditions on the Endometrium and Reproductive Outcomes

Background: A healthy pregnancy begins with an adequate endometrial state, even before the arrival of a blastocyst. Proper endometrial priming and the development of a tolerogenic decidua are key steps in creating the perfect environment for implantation and pregnancy. In these processes, the involvement of the maternal immune system seems to be of great relevance, modulating the different decidual immune populations to prepare the endometrium for a potential pregnancy. However, certain local pathologies of an inflammatory and autoimmune nature appear to have a direct impact on these phenomena, thus altering patients' reproductive outcomes. Methods: This literature review analyzes original articles, reviews, systematic reviews, and meta-analyses published between 1990 and 2024, concerning the impact of different inflammatory and autoimmune conditions on endometrial status and fertility. The included papers were obtained from Medline (Pubmed) and the Cochrane library. Results: There is evidence that endometriosis, adenomyosis, and chronic endometritis, through the promotion of a chronic inflammatory environment, are capable of altering endometrial immune populations, and, thus, processes essential for early pregnancy. Among other effects, these conditions have been linked to impaired decidualization, alterations in progesterone responsiveness, and hindered placentation. Similarly, antiphospholipid syndrome (APS), thyroid dysfunction, diabetes, and other pathologies related to glucose and gluten metabolism, due to their autoimmune nature, also appear to have a local impact on the uterine environment, affecting reproductive success through different mechanisms, including altered hormonal response and, again, impaired decidualization. Conclusions: The management of inflammatory and autoimmune diseases in assisted reproduction patients is gaining importance due to their direct impact on the endometrium. It is necessary to follow current expert recommendations and established therapeutic approaches in order to improve patients' prospects, ranging from antibiotic treatment in chronic endometritis to heparin and aspirin in APS, as well as hormonal treatments for endometriosis/adenomyosis or a gluten-free diet in celiac disease. All of them and the rest of the therapeutic perspectives, both current and under investigation, are presented throughout this work, assessing the possible improvements for reproductive outcomes.

Identification of potent pan-ephrin receptor kinase inhibitors using DNA-encoded chemistry technology

EPH receptors (EPHs), the largest family of tyrosine kinases, phosphorylate downstream substrates upon binding of ephrin cell surface-associated ligands. In a large cohort of endometriotic lesions from individuals with endometriosis, we found that EPHA2 and EPHA4 expressions are increased in endometriotic lesions relative to normal eutopic endometrium. Because signaling through EPHs is associated with increased cell migration and invasion, we hypothesized that chemical inhibition of EPHA2/4 could have therapeutic value. We screened DNA-encoded chemical libraries (DECL) to rapidly identify EPHA2/4 kinase inhibitors. Hit compound, CDD-2693, exhibited picomolar/nanomolar kinase activity against EPHA2 (Ki: 4.0 nM) and EPHA4 (Ki: 0.81 nM). Kinome profiling revealed that CDD-2693 bound to most EPH family and SRC family kinases. Using NanoBRET target engagement assays, CDD-2693 had nanomolar activity versus EPHA2 (IC50: 461 nM) and EPHA4 (IC50: 40 nM) but was a micromolar inhibitor of SRC, YES, and FGR. Chemical optimization produced CDD-3167, having picomolar biochemical activity toward EPHA2 (Ki: 0.13 nM) and EPHA4 (Ki: 0.38 nM) with excellent cell-based potency EPHA2 (IC50: 8.0 nM) and EPHA4 (IC50: 2.3 nM). Moreover, CDD-3167 maintained superior off-target cellular selectivity. In 12Z endometriotic epithelial cells, CDD-2693 and CDD-3167 significantly decreased EFNA5 (ligand) induced phosphorylation of EPHA2/4, decreased 12Z cell viability, and decreased IL-1β-mediated expression of prostaglandin synthase 2 (PTGS2). CDD-2693 and CDD-3167 decreased expansion of primary endometrial epithelial organoids from patients with endometriosis and decreased Ewing's sarcoma viability. Thus, using DECL, we identified potent pan-EPH inhibitors that show specificity and activity in cellular models of endometriosis and cancer.

Transcriptomic changes in eutopic endometrium and ectopic lesions during endometriosis progression in a mouse model

OBJECTIVE

To identify the transcriptomic changes of ectopic lesions and eutopic endometrial tissues during the progression of endometriosis, we performed transcriptomic analysis in the eutopic endometrium and ectopic lesions.

DESIGN

Laboratory study.

SETTING

Academic medical center.

ANIMALS

Four fertile and 4 subfertile Pgrcre/+Rosa26mTmG/+ mice with endometriosis, and 4 sham mice for each group of endometriosis mice as control. These mice underwent either surgery to induce endometriosis or sham surgery. Fertile sham and mice with endometriosis were used 1 month after surgery, whereas subfertile ones were used 3 months after surgery.

INTERVENTIONS

Early and chronic effects of endometriosis on transcriptomics of ectopic lesions and eutopic endometrium.

MAIN OUTCOME MEASURES

RNA-sequencing analysis and identification of differentially expressed genes and pathways in the ectopic lesions and eutopic uteri from mice with endometriosis and sham mice at day 3.5 of pregnancy.

RESULTS

Our mouse model recapitulates the transcriptomic changes of ectopic lesions in humans. RNA-sequencing analysis was performed in ectopic lesions and eutopic uteri from mice with or without endometriosis during the progression of the disease. Estrogen activity, inflammation, angiogenesis, and fibrosis pathways were consistently elevated in all the ectopic lesions compared with eutopic endometrium. Cholesterol/glucose synthesis and stem cell pluripotency pathways were more enhanced in ectopic lesions from subfertile mice compared with their eutopic endometrium. Dysregulation of infiltration of macrophage, dendritic, T and B cells was validated with the use of immunohistochemistry in ectopic lesions. Multiple ligand-receptor pairs between the ectopic and eutopic endometrium were altered compared with the sham endometrium. Suppressed WNT and EGF pathways were only found in the eutopic endometrium from subfertile not fertile mice compared with sham.

CONCLUSIONS

Our mouse endometriosis model recapitulates the transcriptomics of ectopic lesions in humans. Our transcriptomic analysis during endometriosis progression in our mouse model will help us understand the pathophysiology of endometriosis.

Mining phase separation-related diagnostic biomarkers for endometriosis through WGCNA and multiple machine learning techniques: a retrospective and nomogram study

OBJECTIVE

The objective of this study was to investigate the role of phase separation-related genes in the development of endometriosis (EMs) and to identify potential characteristic genes associated with the condition.

METHODS

We used GEO database data, including 74 non-endometriosis and 74 varying-degree EMs patients. Our approach involved identifying significant gene modules, exploring gene intersections, identifying core genes, and screening for potential EMs biomarkers using weighted gene co-expression network analysis (WGCNA) and various machine learning approaches. We also performed gene set enrichment analysis (GSEA) to understand relevant pathways. This comprehensive approach helps investigate EMs genetics and potential biomarkers.

RESULTS

Nine genes were identified at the intersection, suggesting their involvement in EMs. GSEA linked DEGs to pathways like complement and coagulation cascades, DNA replication, chemokines, apical plasma membrane processes, and diseases such as Hepatitis B, Human T-cell leukemia virus 1 infection, and COVID-19. Five feature genes (FOS, CFD, CCNA1, CA4, CST1) were selected by machine learning for an effective EMs diagnostic nomogram. GSEA indicated their roles in mismatch repair, cell cycle regulation, complement and coagulation cascades, and IL-17 inflammation. Notable differences in immune cell proportions (CD4 T cells, CD8 T cells, DCs, macrophages) were observed between normal and disease groups, suggesting immune involvement.

CONCLUSIONS

This study suggests the potential involvement of phase separation-related genes in the pathogenesis of endometriosis (EMs) and identifies promising biomarkers for diagnosis. These findings have implications for further research and the development of new therapeutic strategies for EMs.

Identifying therapeutic candidates for endometriosis through a transcriptomics-based drug repositioning approach

Existing medical treatments for endometriosis-related pain are often ineffective, underscoring the need for new therapeutic strategies. In this study, we applied a computational drug repurposing pipeline to stratified and unstratified disease signatures based on endometrial gene expression data to identify potential therapeutics from existing drugs, based on expression reversal. Of 3,131 unique genes differentially expressed by at least one of six endometriosis signatures, only 308 (9.8%) were in common; however, 221 out of 299 drugs identified, (73.9%) were shared. We selected fenoprofen, an uncommonly prescribed NSAID that was the top therapeutic candidate for further investigation. When testing fenoprofen in an established rat model of endometriosis, fenoprofen successfully alleviated endometriosis-associated vaginal hyperalgesia, a surrogate marker for endometriosis-related pain. These findings validate fenoprofen as a therapeutic that could be utilized more frequently for endometriosis and suggest the utility of the aforementioned computational drug repurposing approach for 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.

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.

Endometriosis in the era of precision medicine and impact on sexual and reproductive health across the lifespan and in diverse populations

Endometriosis is a common estrogen-dependent disorder wherein uterine lining tissue (endometrium) is found mainly in the pelvis where it causes inflammation, chronic pelvic pain, pain with intercourse and menses, and infertility. Recent evidence also supports a systemic inflammatory component that underlies associated co-morbidities, e.g., migraines and cardiovascular and autoimmune diseases. Genetics and environment contribute significantly to disease risk, and with the explosion of omics technologies, underlying mechanisms of symptoms are increasingly being elucidated, although novel and effective therapeutics for pain and infertility have lagged behind these advances. Moreover, there are stark disparities in diagnosis, access to care, and treatment among persons of color and transgender/nonbinary identity, socioeconomically disadvantaged populations, and adolescents, and a disturbing low awareness among health care providers, policymakers, and the lay public about endometriosis, which, if left undiagnosed and under-treated can lead to significant fibrosis, infertility, depression, and markedly diminished quality of life. This review summarizes endometriosis epidemiology, compelling evidence for its pathogenesis, mechanisms underlying its pathophysiology in the age of precision medicine, recent biomarker discovery, novel therapeutic approaches, and issues around reproductive justice for marginalized populations with this disorder spanning the past 100 years. As we enter the next revolution in health care and biomedical research, with rich molecular and clinical datasets, single-cell omics, and population-level data, endometriosis is well positioned to benefit from data-driven research leveraging computational and artificial intelligence approaches integrating data and predicting disease risk, diagnosis, response to medical and surgical therapies, and prognosis for recurrence.

Global endometrial DNA methylation analysis reveals insights into mQTL regulation and associated endometriosis disease risk and endometrial function

Endometriosis is a leading cause of pain and infertility affecting millions of women globally. Herein, we characterize variation in DNA methylation (DNAm) and its association with menstrual cycle phase, endometriosis, and genetic variants through analysis of genotype data and methylation in endometrial samples from 984 deeply-phenotyped participants. We estimate that 15.4% of the variation in endometriosis is captured by DNAm and identify significant differences in DNAm profiles associated with stage III/IV endometriosis, endometriosis sub-phenotypes and menstrual cycle phase, including opening of the window for embryo implantation. Menstrual cycle phase was a major source of DNAm variation suggesting cellular and hormonally-driven changes across the cycle can regulate genes and pathways responsible for endometrial physiology and function. DNAm quantitative trait locus (mQTL) analysis identified 118,185 independent cis-mQTLs including 51 associated with risk of endometriosis, highlighting candidate genes contributing to disease risk. Our work provides functional evidence for epigenetic targets contributing to endometriosis risk and pathogenesis. Data generated serve as a valuable resource for understanding tissue-specific effects of methylation on endometrial biology in health and disease.

Puzzling Out the Genetic Architecture of Endometriosis: Whole-Exome Sequencing and Novel Candidate Gene Identification in a Deeply Clinically Characterised Cohort

Endometriosis (EM) is a common multifactorial gynaecological disorder. Although Genome-Wide Association Studies have largely been employed, the current knowledge of the genetic mechanisms underlying EM is far from complete, and other approaches are needed. To this purpose, whole-exome sequencing (WES) was performed on a deeply characterised cohort of 80 EM patients aimed at the identification of rare and damaging variants within 46 EM-associated genes and novel candidates. WES analysis detected 63 rare, predicted, and damaging heterozygous variants within 24 genes in 63% of the EM patients. In particular, (1) a total of 43% of patients carried variants within 13 recurrent genes (FCRL3, LAMA5, SYNE1, SYNE2, GREB1, MAP3K4, C3, MMP3, MMP9, TYK2, VEGFA, VEZT, RHOJ); (2) a total of 8.8% carried private variants within eight genes (KAZN, IL18, WT1, CYP19A1, IL1A, IL2RB, LILRB2, ZNF366); (3) a total of 24% carried variants within three novel candidates (ABCA13, NEB, CSMD1). Finally, to deepen the polygenic architecture of EM, a comprehensive evaluation of the analysed genes was performed, revealing a higher burden (p < 0.05) of genes harbouring rare and damaging variants in the EM patients than in the controls. These results highlight new insights into EM genetics, allowing for the definition of novel genotype-phenotype correlations, thereby contributing, in a long-term perspective, to the development of personalised care for EM patients.

New Insights into Genetics of Endometriosis-A Comprehensive Literature Review

This comprehensive review explores the genetic contributions to endometriosis and their potential impact on improving diagnostic techniques. The review begins by defining endometriosis and discussing its prevalence, emphasizing the need for a deeper understanding of the genetic basis of the condition. It highlights recent genome-wide association studies (GWAS) that have identified specific genetic variants associated with endometriosis, shedding light on the molecular pathways and mechanisms involved. The review addresses genetic heterogeneity across different populations and ethnicities, emphasizing the importance of considering population-specific markers in diagnostic approaches. It explores the diagnostic implications of genetic insights, including the potential use of genetic markers for precise and early detection, as well as risk prediction. The review also delves into the integration of genetic information with clinical parameters and imaging findings, and the exploration of multi-omics approaches for a comprehensive understanding of endometriosis. It discusses recent studies on genetic and epigenetic biomarkers, their potential as diagnostic tools, and the need for validation in independent cohorts. The review highlights the impact of new genomic technologies, such as next-generation sequencing, in improving diagnostic accuracy and personalized management. It identifies the challenges and future directions in translating genetic findings into diagnostic tools and emphasizes the transformative potential of genetic insights in endometriosis diagnosis. This review provides a roadmap for future research and underscores the significance of genetic insights in improving diagnostic precision and personalized care for individuals with endometriosis.

CFP1 governs uterine epigenetic landscapes to intervene in progesterone responses for uterine physiology and suppression of endometriosis

Progesterone (P₄) is required for the preparation of the endometrium for a successful pregnancy. P₄ resistance is a leading cause of the pathogenesis of endometrial disorders like endometriosis, often leading to infertility; however, the underlying epigenetic cause remains unclear. Here we demonstrate that CFP1, a regulator of H3K4me3, is required for maintaining epigenetic landscapes of P₄-progesterone receptor (PGR) signaling networks in the mouse uterus. Cfp1^f/f;Pgr-Cre (Cfp1^d/d) mice showed impaired P₄ responses, leading to complete failure of embryo implantation. mRNA and chromatin immunoprecipitation sequencing analyses showed that CFP1 regulates uterine mRNA profiles not only in H3K4me3-dependent but also in H3K4me3-independent manners. CFP1 directly regulates important P₄ response genes, including Gata2, Sox17, and Ihh, which activate smoothened signaling pathway in the uterus. In a mouse model of endometriosis, Cfp1^d/d ectopic lesions showed P₄ resistance, which was rescued by a smoothened agonist. In human endometriosis, CFP1 was significantly downregulated, and expression levels between CFP1 and these P₄ targets are positively related regardless of PGR levels. In brief, our study provides that CFP1 intervenes in the P₄-epigenome-transcriptome networks for uterine receptivity for embryo implantation and the pathogenesis of 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.

Identification of key modules and candidate genes associated with endometriosis based on transcriptome data via bioinformatics analysis

BACKGROUNDS

Endometriosis is a common disease in women, but the signaling pathways and genes involved remain unclear. This study screened genes that were differentially expressed in ectopic endometrium (EC) and eutopic endometrium (EU) in endometriosis and provided clues for subsequent experimental verification.

METHODS

Endometriosis samples were harvested from inpatients that underwent surgery from 2017 to 2019 with pathological evidence of endometriosis. We assessed the mRNA expression profiles in endometriosis and further conducted gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, Gene Set Enrichment Analysis (GSEA) and weighted gene co-expression network analysis (WGCNA) to identify potential biomarkers in endometriosis. Finally, we further validated hub genes using public databases and immunohistochemistry assays.

RESULTS

The upregulated DEGs of ectopic endometrium from endometriosis patients were mainly involved in cell adhesion, MAPK signaling, PI3K-Akt signaling pathways, cytokine receptor interactions, and epithelial-mesenchymal transformation (EMT)-associated signaling pathways. The downregulated DEGs between ectopic endometrium and eutopic endometrium were related to decidualization-associated genes in endometriosis. The correlated gene modules in eutopic endometrial cells were mainly enriched in cell adhesion, embryo implantation and inflammation. The eutopic and ectopic endometrial lesions in endometriosis were involved in the EMT process. Furthermore, we identified 18 co-expression modules during WGCNA analysis. Hub genes in the pale turquoise module were FOSB, JUNB, ATF3, CXCL2, FOS, etc. Significantly enriched KEGG pathways included the TNF, MAPK, foxO, oxytocin, and p53 signaling pathways. Enrichment pathways were directly related to immune surveillance, stem cell self-renewal, and epithelial-mesenchymal transformation. Several pathways and modules of endometriosis are related to cancer-associated pathways, which substantiates the correlation between endometriosis and various gynecological tumors.

CONCLUSIONS

Endometriosis was tightly correlated with EMT and fibrosis mediated by inflammatory immunity, cytokines, estrogen, kinases and protooncogene through transcriptomics. Overall, our findings lay the groundwork for understanding the pathogenesis of endometriosis and its relationship with malignant transformation.

A generalized covariate-adjusted top-scoring pair algorithm with applications to diabetic kidney disease stage classification in the Chronic Renal Insufficiency Cohort (CRIC) Study

BACKGROUND

The growing amount of high dimensional biomolecular data has spawned new statistical and computational models for risk prediction and disease classification. Yet, many of these methods do not yield biologically interpretable models, despite offering high classification accuracy. An exception, the top-scoring pair (TSP) algorithm derives parameter-free, biologically interpretable single pair decision rules that are accurate and robust in disease classification. However, standard TSP methods do not accommodate covariates that could heavily influence feature selection for the top-scoring pair. Herein, we propose a covariate-adjusted TSP method, which uses residuals from a regression of features on the covariates for identifying top scoring pairs. We conduct simulations and a data application to investigate our method, and compare it to existing classifiers, LASSO and random forests.

RESULTS

Our simulations found that features that were highly correlated with clinical variables had high likelihood of being selected as top scoring pairs in the standard TSP setting. However, through residualization, our covariate-adjusted TSP was able to identify new top scoring pairs, that were largely uncorrelated with clinical variables. In the data application, using patients with diabetes (n = 977) selected for metabolomic profiling in the Chronic Renal Insufficiency Cohort (CRIC) study, the standard TSP algorithm identified (valine-betaine, dimethyl-arg) as the top-scoring metabolite pair for classifying diabetic kidney disease (DKD) severity, whereas the covariate-adjusted TSP method identified the pair (pipazethate, octaethylene glycol) as top-scoring. Valine-betaine and dimethyl-arg had, respectively, ≥ 0.4 absolute correlation with urine albumin and serum creatinine, known prognosticators of DKD. Thus without covariate-adjustment the top-scoring pair largely reflected known markers of disease severity, whereas covariate-adjusted TSP uncovered features liberated from confounding, and identified independent prognostic markers of DKD severity. Furthermore, TSP-based methods achieved competitive classification accuracy in DKD to LASSO and random forests, while providing more parsimonious models.

CONCLUSIONS

We extended TSP-based methods to account for covariates, via a simple, easy to implement residualizing process. Our covariate-adjusted TSP method identified metabolite features, uncorrelated from clinical covariates, that discriminate DKD severity stage based on the relative ordering between two features, and thus provide insights into future studies on the order reversals in early vs advanced disease states.

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.

Low STING expression promotes endometrial stromal cell invasion and migration via the STING/IRF-3/IFN-β1 pathway in eutopic endometrium of women with endometriosis

Aims: The primary aim of the current study was to elucidate the function of the stimulator of interferon genes (STING) in the eutopic endometrium of women with endometriosis. Materials and Methods: STING expression and signaling pathways were verified by western blot analysis and immunohistochemistry after si-STING treatment. Cell proliferation and invasion and migration were assessed using 5-ethynyl-2'-deoxyuridine and transwell assays, respectively. Results: Within endometriosis tissues, STING was primarily expressed in the stroma of the eutopic endometrium and glandular epithelium of the ectopic endometrium. However, STING expression was significantly lower in the eutopic endometrium of patients with endometriosis compared to controls (p < 0.05). Additionally, cell proliferation (0.2866 ± 0.01470 vs. 0.6911 ± 0.01796, ^****p < 0.0001), invasion (130.0 ± 6.296 vs. 424.1 ± 22.31, ^****p < 0.0001), and migration (82.93 ± 6.940 vs. 82.93 ± 6.940, ^****p < 0.0001) were significantly increased in the si-STING groups. Moreover, following si-STING transfection, the expression of phosphorylated IRF-3 and TBK1 that are involved in STING/IRF3/IFNb1 signaling pathway decreased. The addition of exogenous IFN-β1 effectively increased stromal cell invasion (IFN-β1-NC vs. IFN-β1-si-STING 274.7 ± 7.767 vs. 135.7 ± 12.63, ***p < 0.0001) and migration (IFN-β1-NC and IFN-β1-si-STING 28.53 ± 3.625 vs. 28.53 ± 3.625, ***p < 0.0001) without significantly impacting cell proliferation (si-STING vs. IFN-1β-si-STING 0.6874 ± 0.02081 vs. 0.7187 ± 0.02638, p = 0.795). Conclusions: The STING signaling pathway plays an important role in endometrial stromal cell proliferation, invasion and migration associated with endometriosis.

Molecular Subclasses of Clear Cell Ovarian Carcinoma and Their Impact on Disease Behavior and Outcomes

PURPOSE

To identify molecular subclasses of clear cell ovarian carcinoma (CCOC) and assess their impact on clinical presentation and outcomes.

EXPERIMENTAL DESIGN

We profiled 421 primary CCOCs that passed quality control using a targeted deep sequencing panel of 163 putative CCOC driver genes and whole transcriptome sequencing of 211 of these tumors. Molecularly defined subgroups were identified and tested for association with clinical characteristics and overall survival.

RESULTS

We detected a putative somatic driver mutation in at least one candidate gene in 95% (401/421) of CCOC tumors including ARID1A (in 49% of tumors), PIK3CA (49%), TERT (20%), and TP53 (16%). Clustering of cancer driver mutations and RNA expression converged upon two distinct subclasses of CCOC. The first was dominated by ARID1A-mutated tumors with enriched expression of canonical CCOC genes and markers of platinum resistance; the second was largely comprised of tumors with TP53 mutations and enriched for the expression of genes involved in extracellular matrix organization and mesenchymal differentiation. Compared with the ARID1A-mutated group, women with TP53-mutated tumors were more likely to have advanced-stage disease, no antecedent history of endometriosis, and poorer survival, driven by their advanced stage at presentation. In women with ARID1A-mutated tumors, there was a trend toward a lower rate of response to first-line platinum-based therapy.

CONCLUSIONS

Our study suggests that CCOC consists of two distinct molecular subclasses with distinct clinical presentation and outcomes, with potential relevance to both traditional and experimental therapy responsiveness. See related commentary by Lheureux, p. 4838.

Clinical use of artificial intelligence in endometriosis: a scoping review

Endometriosis is a chronic, debilitating, gynecologic condition with a non-specific clinical presentation. Globally, patients can experience diagnostic delays of ~6 to 12 years, which significantly hinders adequate management and places a significant financial burden on patients and the healthcare system. Through artificial intelligence (AI), it is possible to create models that can extract data patterns to act as inputs for developing interventions with predictive and diagnostic accuracies that are superior to conventional methods and current tools used in standards of care. This literature review explored the use of AI methods to address different clinical problems in endometriosis. Approximately 1309 unique records were found across four databases; among those, 36 studies met the inclusion criteria. Studies were eligible if they involved an AI approach or model to explore endometriosis pathology, diagnostics, prediction, or management and if they reported evaluation metrics (sensitivity and specificity) after validating their models. Only articles accessible in English were included in this review. Logistic regression was the most popular machine learning method, followed by decision tree algorithms, random forest, and support vector machines. Approximately 44.4% (n = 16) of the studies analyzed the predictive capabilities of AI approaches in patients with endometriosis, while 47.2% (n = 17) explored diagnostic capabilities, and 8.33% (n = 3) used AI to improve disease understanding. Models were built using different data types, including biomarkers, clinical variables, metabolite spectra, genetic variables, imaging data, mixed methods, and lesion characteristics. Regardless of the AI-based endometriosis application (either diagnostic or predictive), pooled sensitivities ranged from 81.7 to 96.7%, and pooled specificities ranged between 70.7 and 91.6%. Overall, AI models displayed good diagnostic and predictive capacity in detecting endometriosis using simple classification scenarios (i.e., differentiating between cases and controls), showing promising directions for AI in assessing endometriosis in the near future. This timely review highlighted an emerging area of interest in endometriosis and AI. It also provided recommendations for future research in this field to improve the reproducibility of results and comparability between models, and further test the capacity of these models to enhance diagnosis, prediction, and management in endometriosis patients.

Histone H3K4me3 breadth in hypoxia reveals endometrial core functions and stress adaptation linked to endometriosis

Trimethylation of histone H3 at lysine 4 (H3K4me3) is a marker of active promoters. Broad H3K4me3 promoter domains have been associated with cell type identity, but H3K4me3 dynamics upon cellular stress have not been well characterized. We assessed this by exposing endometrial stromal cells to hypoxia, which is a major cellular stress condition. We observed that hypoxia modifies the existing H3K4me3 marks and that promoter H3K4me3 breadth rather than height correlates with transcription. Broad H3K4me3 domains mark genes for endometrial core functions and are maintained or selectively extended upon hypoxia. Hypoxic extension of H3K4me3 breadth associates with stress adaptation genes relevant for the survival of endometrial cells including transcription factor KLF4, for which we found increased protein expression in the stroma of endometriosis lesions. These results substantiate the view on broad H3K4me3 as a marker of cell identity genes and reveal participation of H3K4me3 extension in cellular stress adaptation.

The mid-secretory endometrial transcriptomic landscape in endometriosis: a meta-analysis

STUDY QUESTION

Do women with endometriosis have a different endometrial gene expression profile at the time of embryo implantation than women without endometriosis?

SUMMARY ANSWER

The endometrial gene expression profile of women with endometriosis differs from that of women without endometriosis at the mid-secretory phase, although the differences are small.

WHAT IS KNOWN ALREADY

About 50% of women with endometriosis suffer infertility. Several molecular studies have suggested impaired endometrial receptivity in women with endometriosis, while others have detected no dysregulation of endometrial receptivity. Nevertheless, the previous endometrial transcriptome studies comparing women with and without endometriosis have been performed in small sample size with limited statistical power. We set out to systematically search and compile data of endometrial gene expression signatures at the receptive phase in women with endometriosis versus control women. Based on the obtained data, we conducted a meta-analysis of differentially expressed genes in order to raise the power of the analysis for identifying the molecular profiles of receptive phase endometria in endometriosis.

STUDY DESIGN, SIZE, DURATION

A systematic literature search was conducted up to February 2022 following PRISMA criteria and included PubMed, Cochrane and Web of Science databases. For the systematic search, the term ‘endometriosis’ was paired with the terms ‘transcriptomics’, ‘transcriptome’, ‘gene expression’, ‘RNA-seq’, ‘sequencing’ and ‘array’, by using the Boolean operator ‘AND’ to connect them. Articles written in English were screened and interrogated for data extraction.

PARTICIPANTS/MATERIALS, SETTING, METHODS

A meta-analysis was performed on the selected studies to extract the differentially expressed genes described at the mid-secretory phase in women with endometriosis versus women without endometriosis in natural cycles, using the robust rank aggregation method. In total, transcriptome data of 125 women (78 patients and 47 controls) were meta-analysed, with a special focus on endometrial receptivity-specific genes based on commercial endometrial receptivity tests.

MAIN RESULTS AND THE ROLE OF CHANCE

In total, 8 studies were eligible for the quantitative meta-analysis, gathering transcriptome data from the mid-secretory phase endometria of 125 women. A total of 7779 differentially expressed transcripts between the study groups were retrieved (3496 up-regulated and 4283 down-regulated) and were meta-analysed. After stringent multiple correction, there was no differential expression of any single molecule in the endometrium of women with endometriosis versus controls, while enrichment analysis detected that the pathways of chemotaxis and locomotion are dysregulated in endometriosis. Further analysis of endometrial receptivity-specific genes highlighted dysregulation of C4BPA, MAOA and PAEP and enrichment of immune and defence pathways in women with endometriosis.

LIMITATIONS, REASONS FOR CAUTION

Most of the studies included into the meta-analysis were relatively small and had different study designs, which might have contributed to a bias.

WIDER IMPLICATIONS OF THE FINDINGS

The current meta-analysis supports the hypothesis that endometrial receptivity is altered in women with endometriosis, although the changes are small. The molecules and pathways identified could serve as future biomarkers and therapeutical targets in detecting and treating endometriosis-associated infertility.

STUDY FUNDING/COMPETING INTEREST(S)

The authors declare no competing interests. This work was supported by the Spanish Ministry of Education, Culture and Sport [grant FPU15/01193] and the Margarita Salas program for the Requalification of the Spanish University system [grant UJAR01MS]; Spanish Ministry of Economy, Industry and Competitiveness (MINECO) and European Regional Development Fund (FEDER): grants RYC-2016-21199 and ENDORE SAF2017-87526-R; Programa Operativo FEDER Andalucía (B-CTS-500-UGR18; A-CTS-614-UGR20); the Junta de Andalucía [BIO-302; and PAIDI P20_00158]; the University of Jaén [PAIUJA-EI_CTS02_2017]; the University of Granada, Plan Propio de Investigación 2016, Excellence actions: Units of Excellence; Unit of Excellence on Exercise and Health (UCEES), and by the Junta de Andalucía, Consejería de Conocimiento, Investigación y Universidades and European Regional Development Fund (ERDF), ref. SOMM17/6107/UGR; the Estonian Research Council (grant PRG1076); Horizon 2020 innovation (ERIN, grant no. EU952516) of the European Commission and Enterprise Estonia (grant EU48695).

TRIAL REGISTRATION NUMBER

The systematic review was registered at PROSPERO (identifier: CRD42020122054).

Progesterone Actions and Resistance in Gynecological Disorders

Estrogen and progesterone and their signaling mechanisms are tightly regulated to maintain a normal menstrual cycle and to support a successful pregnancy. The imbalance of estrogen and progesterone disrupts their complex regulatory mechanisms, leading to estrogen dominance and progesterone resistance. Gynecological diseases are heavily associated with dysregulated steroid hormones and can induce chronic pelvic pain, dysmenorrhea, dyspareunia, heavy bleeding, and infertility, which substantially impact the quality of women's lives. Because the menstrual cycle repeatably occurs during reproductive ages with dynamic changes and remodeling of reproductive-related tissues, these alterations can accumulate and induce chronic and recurrent conditions. This review focuses on faulty progesterone signaling mechanisms and cellular responses to progesterone in endometriosis, adenomyosis, leiomyoma (uterine fibroids), polycystic ovary syndrome (PCOS), and endometrial hyperplasia. We also summarize the association with gene mutations and steroid hormone regulation in disease progression as well as current hormonal therapies and the clinical consequences of progesterone resistance.

Whole-Tissue Deconvolution and scRNAseq Analysis Identify Altered Endometrial Cellular Compositions and Functionality Associated With Endometriosis

The uterine lining (endometrium) exhibits a pro-inflammatory phenotype in women with endometriosis, resulting in pain, infertility, and poor pregnancy outcomes. The full complement of cell types contributing to this phenotype has yet to be identified, as most studies have focused on bulk tissue or select cell populations. Herein, through integrating whole-tissue deconvolution and single-cell RNAseq, we comprehensively characterized immune and nonimmune cell types in the endometrium of women with or without disease and their dynamic changes across the menstrual cycle. We designed metrics to evaluate specificity of deconvolution signatures that resulted in single-cell identification of 13 novel signatures for immune cell subtypes in healthy endometrium. Guided by statistical metrics, we identified contributions of endometrial epithelial, endothelial, plasmacytoid dendritic cells, classical dendritic cells, monocytes, macrophages, and granulocytes to the endometrial pro-inflammatory phenotype, underscoring roles for nonimmune as well as immune cells to the dysfunctionality of this tissue.

Five immune-related genes as diagnostic markers for endometriosis and their correlation with immune infiltration

Endometriosis (EMS) is a chronic disease that can cause dysmenorrhea, chronic pelvic pain, and infertility, among other symptoms. EMS diagnosis is often delayed compared to other chronic diseases, and there are currently no accurate, easily accessible, and non-invasive diagnostic tools. Therefore, it is important to elucidate the mechanism of EMS and explore potential biomarkers and diagnostic tools for its accurate diagnosis and treatment. In the present study, we comprehensively analyzed the differential expression, immune infiltration, and interactions of EMS-related genes in three Homo sapiens datasets. Our results identified 332 differentially expressed genes (DEGs) associated with EMS. Gene ontology analysis showed that these changes mainly focused on the positive regulation of endometrial cell proliferation, cell metabolism, and extracellular space, and EMS involved the integrin, complement activation, folic acid metabolism, interleukin, and lipid signaling pathways. The LASSO regression model was established using immune DEGs with an area under the curve of 0.783 for the internal dataset and 0.656 for the external dataset. Five genes with diagnostic value, ACKR1, LMNB1, MFAP4, NMU, and SEMA3C, were screened from M1 and M2 macrophages, activated mast cells, neutrophils, natural killer cells, follicular T helper cells, CD8⁺, and CD4⁺ cells. A protein-protein interaction network based on the immune DEGs was constructed, and ten hub genes with the highest scores were identified. Our results may provide a framework for the development of pathological molecular networks in EMS.

Increased Expression of YAP Inhibited the Autophagy Level by Upregulating mTOR Signal in the Eutopic ESCs of Endometriosis

We first reported that the Hippo-YAP signaling pathway plays a critical role in the pathogenesis of endometriosis (EMS). Autophagy is also related to the invasion ability of endometrial cells and is involved in the pathogenesis of EMS through multi-levels. However, the precise regulatory mechanism of YAP on autophagy in the eutopic endometrial stromal cells (ESCs) is still unclear. Primary eutopic ESCs of EMS patients (n = 12) and control patients without EMS (n = 9) were isolated and cultured to investigate the expressions of YAP and mTOR, the role of YAP in autophagy, and the effect of the YAP-autophagy signal on the decidualization of the eutopic ESCs. Endometriosis-related sequencing data (GSE51981) in the GEO database were used to find the genes significantly correlated with YAP. We found 155 genes with significant differences in the interaction with YAP in EMS from the dataset, and the autophagy pathway was significantly enriched. Following on from our previous studies of YAP knockdown, overexpression of YAP resulted in an increased expression of mTOR and decreased ratio of LC3-II/LC3-I and autophagy markers, in the eutopic ESCs; transmission electron microscope observation also showed fewer autophagosomes compared with the control cells. Furthermore, ESCs of the Rapamycin-treated group showed significant decidual-like changes with significantly increased decidual prolactin level at 72 h after in vitro decidualization. These results demonstrate that the increased YAP inhibited the level of autophagy by upregulating the mTOR signal in the eutopic ESCs of endometriosis. The YAP-autophagy signal plays an important role in the pathogenesis of endometriosis-associated infertility.

Cellular junction and mesenchymal factors delineate an endometriosis-specific response of endometrial stromal cells to the mesothelium

Endometriosis is a debilitating gynecologic disorder that affects ∼10% of women of reproductive age. Endometriosis is characterized by growth of endometriosis lesions within the abdominal cavity, generally thought to arise from retrograde menstruation of shed endometrial tissue. While the pathophysiology underlying peritoneal endometriosis lesion formation is still unclear, the interaction between invading endometrial tissue and the peritoneal mesothelial lining is an essential step in lesion formation. In this study, we assessed proteomic differences between eutopic endometrial stromal cells (ESCs) from women with and without endometriosis in response to peritoneal mesothelial cell (PMC) exposure, using single-cell cytometry by time-of-flight (CyTOF). Co-cultured primary eutopic ESCs from women with and without endometriosis with an established PMC line were subjected to immunostaining with a panel of Maxpar CyTOF metal-conjugated antibodies (n = 28) targeting cell junction and mesenchymal markers, which are involved in cell-cell adhesions and epithelial-mesenchymal transition. Exposure of the ESCs to PMCs resulted in a drastic shift in cellular expression profiles in ESCs derived from endometriosis, whereas little effect by PMCs was observed in ESCs from non-endometriosis subjects. The transcription factor SNAI1 was consistently repressed by PMC interactions. ESCs from endometriosis patients are unique in that they respond to PMCs by undergoing changes in adhesive properties and mesenchymal characteristics that would facilitate lesion formation.

Identification and Validation of the Signatures of Infiltrating Immune Cells in the Eutopic Endometrium Endometria of Women With Endometriosis

Endometriosis is an oestrogen-dependent chronic inflammatory process with primary symptoms including dysmenorrhea, chronic pelvic pain, and infertility. The immune environment of the endometrium is essential for successful embryo implantation and ongoing pregnancy. In this study, we assessed the composition, density, and distribution of infiltrating immune cells in the endometria of women with endometriosis. Gene expression profiles of endometrial samples were downloaded from the Gene Expression Omnibus (GEO) database. We found that the TNF signalling pathway, the IL-17 signalling pathway, and the MAPK signalling pathway were significantly enriched in the eutopic endometria of women with endometriosis. The fractions and proportion of infiltrating immune cells were estimated by the CIBERSORT, MCP-counter, and ImmuCellAI methods. We found that the proportions of CD8⁺ T cells, activated NK cells, and follicular helper T cells were significantly higher in the endometria of women with endometriosis than in the endometria of normal controls, while the proportions of M2 macrophages and resting mast cells were significantly lower in the eutopic endometria. In GSE120103 (n = 36), we found that elevated CD8⁺ T cells in endometriosis increased the risk of infertility (P = 0.0019). The area under the receiver operating characteristic (ROC) curve (AUC) of CD8⁺ T cells to distinguish fertile and infertile endometriosis was 0.914. In clinical samples (n = 40), we found that the proportions of CD8⁺ T cells and CD56⁺ NK cells were significantly higher in the eutopic endometria of women with endometriosis than in the endometria of normal controls, while the proportion of CD163⁺ macrophages were lower in the eutopic endometria. The AUCs of CD8⁺ T cells and CD163⁺ macrophages were 0.727 and 0.833, respectively, which indicated that CD8 and CD163 were potential diagnostic markers for endometriosis. In conclusion, our results demonstrated that increased CD8⁺ T cells and CD56⁺ NK cells and decreased CD163⁺ macrophages within the eutopic endometria of women with endometriosis reveal a proinflammatory feature in the endometrial immune environment and that elevated CD8⁺ T cells increase the risk of infertility in women with the disease.

Endometrial DNA damage response is modulated in endometriosis

STUDY QUESTION

Is the DNA damage response (DDR) dysregulated in the eutopic endometrium of women with endometriosis?

SUMMARY ANSWER

Endometrial expression of genes involved in DDR is modulated in women with endometriosis, compared to those without the disease.

WHAT IS KNOWN ALREADY

Ectopic endometriotic lesions are reported to harbour somatic mutations, thereby hinting at dysregulation of DDR and DNA repair pathways. However, it remains inconclusive whether the eutopic endometrium also manifests dysregulated DDR in endometriosis.

STUDY DESIGN, SIZE, DURATION

For this case-control study conducted between 2015 and 2019, eutopic endometrial (E) samples (EE- from women with endometriosis, CE- from women without endometriosis) were collected in either mid-proliferative (EE-MP, n = 23; CE-MP, n = 17) or mid-secretory (EE-MS, n = 17; CE-MS, n = 9) phases of the menstrual cycle. This study compares: (i) DNA damage marker localization, (ii) expression of DDR genes and (iii) expression of DNA repair genes in eutopic endometrial samples from women with and without endometriosis.

PARTICIPANTS/MATERIALS, SETTING, METHODS

The study included (i) 40 women (aged 31.9 ± 0.81 years) with endometriosis and (ii) 26 control women (aged 31.4 ± 1.02 years) without endometriosis. Eutopic endometrial samples from the two groups were divided into different parts for histological analysis, immunohistochemistry, RNA extraction, protein extraction and comet assays. Eighty-four genes of relevance in the DNA damage signalling pathway were evaluated for their expression in eutopic endometrial samples, using RT2 Profiler PCR arrays. Validations of the expression of two GADD (Growth Arrest DNA Damage Inducible) proteins - GADD45A and GADD45G were carried out by immunoblotting. DNA damage was assessed by immunohistochemical localization of γ-H2AFX (a phosphorylated variant of histone H2AX) and 8-OHdG (8-hydroxy-2'-deoxyguanosine). RNA sequencing data from mid-proliferative (EE-MP, n = 4; CE-MP, n = 3) and mid-secretory phase (EE-MS and CE-MS, n = 4 each) endometrial samples were scanned to compare the expression status of all the genes implicated in human DNA repair. PCNA (Proliferating Cell Nuclear Antigen) expression was determined to assess endometrial proliferation. Residual DNA damage in primary endometrial cells was checked by comet assays. Public datasets were also scanned for the expression of DDR and DNA repair genes as our RNASeq data were limited by small sample size. All the comparisons were made between phase-matched endometrial samples from women with and without endometriosis.

MAIN RESULTS AND THE ROLE OF CHANCE

Endometrial expression of DDR genes and intensity of immunolocalized γ-H2AFX were significantly (P < 0.05) higher in EE, compared to CE samples. DDR proteins, especially those belonging to the GADD family, were found to be differentially abundant in EE, as compared to CE. These patterns were evident in both mid-proliferative and mid-secretory phases. Intriguingly, higher DDR was associated with increased cell proliferation in EE-MP, compared to CE-MP. Furthermore, among the differentially expressed transcripts (DETs) encoded by DNA repair genes, the majority showed up-regulation in EE-MP, compared to CE-MP. Interestingly, CE-MP and EE-MP had a comparable percentage (P > 0.05) of cells with residual DNA damage. However, unlike the mid-proliferative phase data, many DETs encoded by DNA repair genes were down-regulated in EE-MS, compared to CE-MS. An analysis of the phase-matched control and endometriosis samples included in the GSE51981 dataset available in the Gene Expression Omnibus database also revealed significant (P < 0.05) alterations in the expression of DDR and DNA repair genes in EE, compared to CE.

LARGE-SCALE DATA

N/A.

LIMITATIONS, REASONS FOR CAUTION

The study was conducted on a limited number of endometrial samples. Also, the study does not reveal the causes underlying dysregulated DDR in the eutopic endometrium of women with endometriosis.

WIDER IMPLICATIONS OF THE FINDINGS

Alterations in the expression of DDR and DNA repair genes indirectly suggest that eutopic endometrium, as compared to its healthy counterpart, encounters DNA damage-inducing stimuli, either of higher strength or for longer duration in endometriosis. It will be worthwhile to identify the nature of such stimuli and also explore the role of higher genomic insults and dysregulated DDR/DNA repair in the origin and/or progression of endometriosis.

STUDY FUNDING/COMPETING INTEREST(S)

The study was supported by the Department of Biotechnology and Indian Council of Medical Research, Government of India. No conflict of interest is declared.

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.

Eutopic endometrium from women with endometriosis and chlamydial endometritis share immunological cell types and DNA repair imbalance: A transcriptome meta-analytical perspective

The aim of this study was to identify the key similarities between the eutopic endometrium of women with endometriosis and chlamydia-induced endometritis taking into account tissue microenvironment heterogeneity, transcript gene profile, and enriched pathways. A meta-analysis of whole transcriptome microarrays was performed using publicly available data, including samples containing both glandular and stromal endometrial components. Control samples were obtained from women without any reported pathological condition. Only samples obtained during the proliferative menstrual phase were included. Cellular tissue heterogeneity was predicted using a method that integrates gene set enrichment and deconvolution approaches. The batch effect was estimated by principal variant component analysis and removed using an empirical Bayes method. Differentially expressed genes were identified using an adjusted p-value < 0.05 and fold change = 1.5. The protein-protein interaction network was built using the STRING database and interaction score over 400. The Molecular Signatures Database was used to analyse the functional enrichment analysis. Both conditions showed similarities in cell types in the microenvironment, particularly CD4⁺ and CD8⁺ Tem cells, NKT cells, Th2 cells, basophils, and eosinophils. With regards to the regulation of cellular senescence and DNA integrity/damage checkpoint, which are commonly enriched pathways, 21 genes were down-regulated and directly related to DNA repair. Compared to the endometriosis samples, some chlamydial endometritis samples presented a lack of enriched immune pathways. Our results suggest that both conditions show similar distributions of microenvironment cell types, the downregulation of genes involved in DNA repair and cell cycle control, and pathways involved in immune response evasion.

Identification of candidate microRNA markers of endometriosis with the use of next-generation sequencing and quantitative real-time polymerase chain reaction

OBJECTIVE

To identify novel candidate diagnostic microRNA (miRNA) markers of endometriosis by means of an unbiased search with confirmation by means of targeted polymerase chain reaction (PCR).

DESIGN

Retrospective cohort.

SETTING

University teaching hospitals.

PATIENT(S)

Women with endometriosis and control women, confirmed with the use of laparoscopy.

INTERVENTIONS(S)

Diagnostic laparoscopy and blood sample.

MAIN OUTCOME MEASURE(S)

Next-generation sequencing (NGS) and quantitative real-time PCR (qRT-PCR).

RESULT(S)

Candidate miRNAs differentially expressed in women with endometriosis compared with control women were identified by means of NGS and selected for qRT-PCR. Plasma samples from another cohort of women with surgically confirmed endometriosis (n = 53) and disease-free control women (n = 53) were checked for hemolysis using spectrophotometry and the ratio of miR-23a and miR-451 by means of qRT-PCR. MicroRNA signatures were quantified by means of qRT-PCR in hemolysis-free plasma samples of case subjects (n = 25) and control subjects (n = 28) with the use of miRcury LNA miRNA. Circulating levels of eight miRNAs (miR-199a-3p, miR-143-3p, miR-340-5p, let-7b-5p, miR-21-5p, miR-17-5p, miR-20a-5p, and miR-103a-3p) were significantly lower in case subjects compared to control subjects. The sensitivity and specificity for individual miRNAs ranged from 0.36 to 1.00 and from 0.43 to 1.00, respectively, but when combined produced sensitivity and specificity of 0.92 and 0.86 with positive (PPV) and (NPV) predictive values of 0.85 and 0.92, respectively. However, combination of five miRNAs (miR-17-5p, miR-20a-5p, miR-199a-3p, miR-143-3p, and let-7b-5p) produced sensitivity and specificity of 0.96 and 0.79 with PPV and NPV of 0.80 and 0.96, respectively.

CONCLUSION(S)

We conclude that a panel of candidate miRNAs was comparable to laparoscopy in distinguishing between women with endometriosis and control women.

TRIM65 Promotes Invasion of Endometrial Stromal Cells by Activating ERK1/2/C-myc Signaling via Ubiquitination of DUSP6

BACKGROUND

Endometriosis (EM) is a benign gynecological disease that shares some characteristics with malignancy, such as proliferation and invasion. So far, the pathogenesis of EM is still unclear. In this study, we investigated whether TRIM65 can play a role in the development of EM.

METHODS

TRIM65 expression levels in eutopic, ectopic, and normal endometrium were detected by quantitative real-time PCR and Western blot. Cell proliferation and invasion of primary endometrial stromal (EMS) cells were detected by CCK-8 and Transwell analysis. The interaction between TRIM65 and DUSP6 or C-myc was measured by coimmunoprecipitation, ubiquitylation, dual luciferase, and chromatin immunoprecipitation analysis.

RESULTS

We found that TRIM65 was identified as an up-regulated gene in ectopic endometrial tissues and EMS cells compared with control groups without EM. TRIM65 expression was positively correlated with the levels of p-ERK1/2, C-myc, matrix metalloproteinase-2, and integrin β1 in ectopic endometrial tissues in patients and mice. TRIM65 promoted the cell proliferation and invasion of EMS cells via the ERK1/2/C-myc pathway through ubiquitination of DUSP6. C-myc promoted TRIM65 expression through inducing TRIM65 promoter activity. Additionally, the increased expression of TRIM65, C-myc, matrix metalloproteinase-2, integrin β1, and p-ERK1/2 and the decreased expression of DUSP6 in ectopic endometrial tissues were significantly suppressed by inhibition of ERK1/2 signaling pathway in ectopic endometrial tissues in experimental mice model.

CONCLUSION

In conclusion, TRIM65 promotes invasion of ectopic EMS cells by activating a feedback loop with the ERK1/2/C-myc signaling pathway and may be a potential therapeutic target for EM.

Clinical utility of the endometrial receptivity analysis in women with prior failed transfers

PURPOSE

To determine the utility of the endometrial receptivity analysis (ERA) in women with prior failed embryo transfers (ET).

METHODS

This was a retrospective study of patients who underwent an ERA test with a subsequent frozen ET. Women were classified based on their indication for an ERA test: (1) ≥ 1 prior failed ET (cases), or (2) as a prophylactic measure (controls). A subset analysis of women with ≥ 3 prior failed transfers was performed. Pregnancy outcomes of the subsequent cycle were examined, including conception, clinical pregnancy, and ongoing pregnancy/live birth.

RESULTS

A total of 222 women were included, 131 (59%) women with ≥ 1 prior failed ET and 91 (41%) controls. Among the 131 women with ≥ 1 prior failed ET, 20 women (9%) had ≥ 3 prior failed ETs. The proportion of non-receptive ERA tests in the three groups were the following: 45% (≥ 1 prior failed ET), 40% (≥ 3 prior failed ETs), and 52% (controls). The results did not differ between cases and controls. The pregnancy outcomes did not differ between women with ≥ 1 prior failed ET and controls. In women with ≥ 3 prior failed ETs, there was a lower ongoing pregnancy/live birth rate (28% vs 54%, P = 0.046).

CONCLUSION

Women with ≥ 1 prior failed ET and ≥ 3 prior failed ETs had a similar prevalence of non-receptive endometrium compared to controls. Women with ≥ 3 prior failed ETs had a lower ongoing pregnancy/live birth rate despite a personalized FET, suggesting that there are additional factors in implantation failure beyond an adjustment in progesterone exposure.

Aberrant reactive aldehyde detoxification by aldehyde dehydrogenase-2 influences endometriosis development and pain-associated behaviors

Endometriosis affects ∼176 million women worldwide, yet on average, women experience pain ∼10 years from symptom onset before being properly diagnosed. Standard treatments (drugs or surgery) often fail to provide long-term pain relief. Elevated levels of reactive aldehydes such as 4-hydroxynonenal (4-HNE) have been implicated in the peritoneal fluid of women with endometriosis and upon accumulation, reactive aldehydes can form protein-adducts and/or generate pain. A key enzyme in detoxifying reactive aldehydes to less reactive forms is the mitochondrial enzyme aldehyde dehydrogenase-2 (ALDH2). Here, we tested the hypothesis that aberrant reactive aldehyde detoxification by ALDH2 underlies endometriosis and its associated pain. We determined, in the eutopic and ectopic endometrium of women with severe (stage IV) peritoneal endometriosis, that ALDH2 enzyme activity was decreased, which was associated with decreased ALDH2 expression and increased 4-HNE adduct formation compared to the eutopic endometrium of controls in the proliferative phase. Using a rodent model of endometriosis and an ALDH2*2 knock-in mouse with decreased ALDH2 activity, we determined that increasing ALDH2 activity with the enzyme activator Alda-1 could prevent endometriosis lesion development as well as alleviate pain-associated behaviors in proestrus. Overall, our findings suggest that targeting the ALDH2 enzyme in endometriosis may lead to better treatment strategies and in the proliferative phase, that increased 4-HNE adduct formation within the endometrium may serve as a less invasive diagnostic biomarker to reduce years of suffering in women.

Endometriosis Is Associated with a Significant Increase in hTERC and Altered Telomere/Telomerase Associated Genes in the Eutopic Endometrium, an Ex-Vivo and In Silico Study

Telomeres protect chromosomal ends and they are maintained by the specialised enzyme, telomerase. Endometriosis is a common gynaecological disease and high telomerase activity and higher hTERT levels associated with longer endometrial telomere lengths are characteristics of eutopic secretory endometrial aberrations of women with endometriosis. Our ex-vivo study examined the levels of hTERC and DKC1 RNA and dyskerin protein levels in the endometrium from healthy women and those with endometriosis (n = 117). The in silico study examined endometriosis-specific telomere- and telomerase-associated gene (TTAG) transcriptional aberrations of secretory phase eutopic endometrium utilising publicly available microarray datasets. Eutopic secretory endometrial hTERC levels were significantly increased in women with endometriosis compared to healthy endometrium, yet dyskerin mRNA and protein levels were unperturbed. Our in silico study identified 10 TTAGs (CDKN2A, PML, ZNHIT2, UBE3A, MCCC2, HSPC159, FGFR2, PIK3C2A, RALGAPA1, and HNRNPA2B1) to be altered in mid-secretory endometrium of women with endometriosis. High levels of hTERC and the identified other TTAGs might be part of the established alteration in the eutopic endometrial telomerase biology in women with endometriosis in the secretory phase of the endometrium and our data informs future research to unravel the fundamental involvement of telomerase in the pathogenesis of endometriosis.

Exploring diagnostic m6A regulators in endometriosis

Endometriosis is an estrogen-dependent inflammatory disorder, usually causing infertility, pelvic pain, and ovarian masses. This study intended to investigate the implication of N6-methyladenosine (m6A) regulators in endometriosis. We acquired 34 normal, 127 eutopic, and 46 ectopic, samples of endometrium from the Gene Expression Omnibus (GSE7305, GSE7307, GSE51981) database and the Array-express (E-MTAB-694) database. These samples were then used to profile the expression of 20 m6A regulators in endometriosis. The results indicated that most dysregulated (19/20) m6A regulators were significantly downregulated in eutopic vs. normal endometrium and also significantly downregulated in ectopic vs. eutopic endometrium. Several dysregulated m6A regulators were common to both contrast matrices: METTL3, YTHDF2, YTHDF3, HNRNPA2B1, HNRNPC, and FTO. Both HNRNPA2B1 and HNRNPC were associated with the severity of endometriosis in eutopic samples, and also exhibited diagnostic potential for endometriosis. HNRNPA2B1 and HNRNPC may influence immune pathways and the infiltration of immune cells in endometriosis. Abnormalities in the gene transcription factors network associated with endometriosis might affect the expression of HNRNPA2B1 and HNRNPC. In conclusion, we observed significant dysregulation of m6A regulators in endometriosis, and found that HNRNPA2B1 and HNRNPC might correlate with the immune response and serve as useful diagnostic biomarkers for endometriosis.

Menstruation: science and society

Women's health concerns are generally underrepresented in basic and translational research, but reproductive health in particular has been hampered by a lack of understanding of basic uterine and menstrual physiology. Menstrual health is an integral part of overall health because between menarche and menopause, most women menstruate. Yet for tens of millions of women around the world, menstruation regularly and often catastrophically disrupts their physical, mental, and social well-being. Enhancing our understanding of the underlying phenomena involved in menstruation, abnormal uterine bleeding, and other menstruation-related disorders will move us closer to the goal of personalized care. Furthermore, a deeper mechanistic understanding of menstruation-a fast, scarless healing process in healthy individuals-will likely yield insights into a myriad of other diseases involving regulation of vascular function locally and systemically. We also recognize that many women now delay pregnancy and that there is an increasing desire for fertility and uterine preservation. In September 2018, the Gynecologic Health and Disease Branch of the Eunice Kennedy Shriver National Institute of Child Health and Human Development convened a 2-day meeting, "Menstruation: Science and Society" with an aim to "identify gaps and opportunities in menstruation science and to raise awareness of the need for more research in this field." Experts in fields ranging from the evolutionary role of menstruation to basic endometrial biology (including omic analysis of the endometrium, stem cells and tissue engineering of the endometrium, endometrial microbiome, and abnormal uterine bleeding and fibroids) and translational medicine (imaging and sampling modalities, patient-focused analysis of menstrual disorders including abnormal uterine bleeding, smart technologies or applications and mobile health platforms) to societal challenges in health literacy and dissemination frameworks across different economic and cultural landscapes shared current state-of-the-art and future vision, incorporating the patient voice at the launch of the meeting. Here, we provide an enhanced meeting report with extensive up-to-date (as of submission) context, capturing the spectrum from how the basic processes of menstruation commence in response to progesterone withdrawal, through the role of tissue-resident and circulating stem and progenitor cells in monthly regeneration-and current gaps in knowledge on how dysregulation leads to abnormal uterine bleeding and other menstruation-related disorders such as adenomyosis, endometriosis, and fibroids-to the clinical challenges in diagnostics, treatment, and patient and societal education. We conclude with an overview of how the global agenda concerning menstruation, and specifically menstrual health and hygiene, are gaining momentum, ranging from increasing investment in addressing menstruation-related barriers facing girls in schools in low- to middle-income countries to the more recent "menstrual equity" and "period poverty" movements spreading across high-income countries.

The Diagnostic Accuracy of Combined Enolase/Cr, CA125, and CA19-9 in the Detection of Endometriosis

Background

The present study was designed to verify the accuracy of the noninvasive biomarkers enolase/Cr, CA125, and CA19-9 as a clinical diagnostic tool for the detection of endometriosis.

Methods

A cross-sectional study was performed at Rasool-e-Akram Hospital affiliated to Iran University of Medical Sciences, Tehran, Iran, from April 2015 to April 2018. Eighty-six women were scheduled to undergo laparoscopy due to chronic pelvic pain, infertility, pelvic mass, and abnormal uterine bleeding. Serum and urine samples of all patients were collected preoperatively. Serum levels of CA125 and CA19-9, and urine levels of enolase-1 were measured. Serum levels of CA125 and CA19-9 were determined by the electrochemiluminescence method (ECL). Urinary enolase-1 was measured by the ELISA method.

Result

Serum levels of CA125 and CA19-9 were significantly higher in the endometriosis group than in controls (p < 0.001, p = 0.004, respectively). Levels of enolase I and enolase/Cr were higher in patients with endometriosis, but the differences were not statistically significant. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of combined enolase/Cr, CA125, and CA19-9 were 65%, 66.6%, 71%, and 60.1%, respectively. The positive likelihood ratio (PLR) and negative likelihood ratio (NLR) of combined enolase/Cr, CA125, and CA19-9 was 1.94 and 0.52, respectively. The area under the ROC curve for enolase/Cr + CA125 + CA19 - 9 was 0.675 (95% confidence interval 0.573-0.710).

Conclusion

The present study revealed that concurrent measurement of enolase-1, CA125, and CA19-9 might be a valuable noninvasive test for the identification of endometriosis.

External validation of putative biomarkers in eutopic endometrium of women with endometriosis using NanoString technology

PURPOSE

To combine different independent endometrial markers to classify the presence of endometriosis.

METHODS

Endometrial biopsies were obtained from 109 women with endometriosis as well as 110 control women. Nine candidate biomarkers independent of cycle phase were selected from the literature and NanoString was performed. We compared differentially expressed genes between groups and generated generalized linear models to find a classifier for the disease.

RESULTS

Generalized linear models correctly detected 68% of women with endometriosis (combining deep infiltrating and ovarian endometriosis). However, we were not able to distinguish between individual types of endometriosis compared to controls. From the 9 tested genes, FOS, MMP7, and MMP11 seem to be important for disease classification, and FOS was the most over-expressed gene in endometriosis.

CONCLUSION(S)

Although generalized linear models may allow identification of endometriosis, we did not obtain perfect classification with the selected gene candidates.

Augmenting the Clinical Data Sources for Enigmatic Diseases: A Cross-Sectional Study of Self-Tracking Data and Clinical Documentation in Endometriosis

BACKGROUND

Self-tracking through mobile health technology can augment the electronic health record (EHR) as an additional data source by providing direct patient input. This can be particularly useful in the context of enigmatic diseases and further promote patient engagement.

OBJECTIVES

This study aimed to investigate the additional information that can be gained through direct patient input on poorly understood diseases, beyond what is already documented in the EHR.

METHODS

This was an observational study including two samples with a clinically confirmed endometriosis diagnosis. We analyzed data from 6,925 women with endometriosis using a research app for tracking endometriosis to assess prevalence of self-reported pain problems, between- and within-person variability in pain over time, endometriosis-affected tasks of daily function, and self-management strategies. We analyzed data from 4,389 patients identified through a large metropolitan hospital EHR to compare pain problems with the self-tracking app and to identify unique data elements that can be contributed via patient self-tracking.

RESULTS

Pelvic pain was the most prevalent problem in the self-tracking sample (57.3%), followed by gastrointestinal-related (55.9%) and lower back (49.2%) pain. Unique problems that were captured by self-tracking included pain in ovaries (43.7%) and uterus (37.2%). Pain experience was highly variable both across and within participants over time. Within-person variation accounted for 58% of the total variance in pain scores, and was large in magnitude, based on the ratio of within- to between-person variability (0.92) and the intraclass correlation (0.42). Work was the most affected daily function task (49%), and there was significant within- and between-person variability in self-management effectiveness. Prevalence rates in the EHR were significantly lower, with abdominal pain being the most prevalent (36.5%).

CONCLUSION

For enigmatic diseases, patient self-tracking as an additional data source complementary to EHR can enable learning from the patient to more accurately and comprehensively evaluate patient health history and status.

Impaired pathogen-induced autophagy and increased IL-1β and TNFα release in response to pathogenic triggers in secretory phase endometrial stromal cells of endometriosis patients

RESEARCH QUESTION

It is not clear whether innate immunity along with autophagy is altered in endometrial cells of patients with endometriosis.

DESIGN

This study evaluated the effects of lipopolysaccharide (LPS) or polyinosinic:polycytidylic acid (poly I:C) stimulation on autophagy induction, pro-IL-1β expression, and secretion of interleukin-1β (IL-1β) and tumour necrosis factor-α (TNFα) in endometrial epithelial and/or stromal cells of patients with endometriosis (EE-endo, ES-endo, respectively), those of patients with hydrosalpinx (EE-hydro, ES-hydro, respectively) and those of healthy fertile women (EE-healthy, ES-healthy, respectively), with and without inhibition of autophagy by autophagy-related (ATG)13 gene small interfering RNA (siRNA).

RESULTS

Stimulation with either LPS or poly I:C triggered autophagy in EE/ES-healthy, whereas no significant induction was observed in either EE/ES-endo or EE/ES-hydro. In EE- and/or ES-healthy, IL-1β and/or TNFα secretion after stimulation with LPS or poly I:C was significantly higher in cells with ATG13 knockdown compared with those with siRNA control (P < 0.03), whereas no significant difference was observed in either EE/ES-endo or EE/ES-hydro. In the secretory phase ES-endo without autophagy inhibition, IL-1β and TNFα secretion were significantly higher compared with those of ES-healthy after stimulation with either LPS or poly I:C for 4 h (P < 0.001) and for 24 h (P < 0.01).

CONCLUSION

Pathogen-induced autophagy was impaired in EE/ES-endo. Increased IL-1β and TNFα release in response to pathogenic triggers in the secretory phase ES-endo may result in the development of an inflammatory uterine microenvironment detrimental to successful embryo implantation.

Determining the Molecular Background of Endometrial Receptivity in Adenomyosis

Background: Adenomyosis is a gynaecological condition with limited evidence of negative impact to endometrial receptivity. It is commonly associated with endometriosis, which has been shown to alter endometrial expression patterns. Therefore, the candidate genes identified in endometriosis could serve as a source to study endometrial function in adenomyosis. Methods: Transcripts/proteins associated with endometrial receptivity in women with adenomyosis or endometriosis and healthy women were obtained from publications and their nomenclature was adopted according to the HUGO Gene Nomenclature Committee (HGNC). Retrieved genes were analysed for enriched pathways using Cytoscape/Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Reactome tools to prioritise candidates for endometrial receptivity. These were used for validation on women with (n = 9) and without (n = 13) adenomyosis. Results: Functional enrichment analysis of 173, 42 and 151 genes associated with endometriosis, adenomyosis and healthy women, respectively, revealed signalling by interleukins and interleukin-4 and interleukin-13 signalling pathways, from which annotated LIF, JUNB, IL6, FOS, IL10 and SOCS3 were prioritised. Selected genes showed downregulated expression levels in adenomyosis compared to the control group, but without statistical significance. Conclusion: This is the first integrative study providing putative candidate genes and pathways characterising endometrial receptivity in women with adenomyosis in comparison to healthy women and women with endometriosis.

Oestrogen receptor pathway activity is associated with outcome in endometrial cancer

BACKGROUND

Oestrogen receptor (ER) expression is a prognostic biomarker in endometrial cancer (EC). However, expression does not provide information about the functional activity of the ER pathway. We evaluated a model to quantify ER pathway activity in EC, and determined the prognostic relevance of ER pathway activity.

METHODS

ER pathway activity was measured in two publicly available datasets with endometrial and EC tissue, and one clinical cohort with 107 samples from proliferative and hyperplastic endometrium and endometrioid-type EC (EEC) and uterine serous cancer (USC). ER pathway activity scores were inferred from ER target gene mRNA levels from Affymetrix microarray data (public datasets), or measured by qPCR on formalin-fixed paraffin-embedded samples (clinical cohort) and related to ER expression and outcome.

RESULTS

ER pathway activity scores differed significantly throughout the menstrual cycle supporting the validity of the pathway test. The highest ER pathway scores were found in proliferative and hyperplastic endometrium and stage I EEC, whereas stage II-IV EEC and USCs had significantly lower levels. Low ER pathway activity was associated with recurrent disease, and added prognostic value in patients with low ER expression.

CONCLUSION

The ER pathway test reflects activity of the ER pathway, and may improve prediction of outcome in EC patients.

A relational database to identify differentially expressed genes in the endometrium and endometriosis lesions

Endometriosis is a common inflammatory estrogen-dependent gynecological disorder, associated with pelvic pain and reduced fertility in women. Several aspects of this disorder and its cellular and molecular etiology remain unresolved. We have analyzed the global gene expression patterns in the endometrium, peritoneum and in endometriosis lesions of endometriosis patients and in the endometrium and peritoneum of healthy women. In this report, we present the EndometDB, an interactive web-based user interface for browsing the gene expression database of collected samples without the need for computational skills. The EndometDB incorporates the expression data from 115 patients and 53 controls, with over 24000 genes and clinical features, such as their age, disease stages, hormonal medication, menstrual cycle phase, and the different endometriosis lesion types. Using the web-tool, the end-user can easily generate various plot outputs and projections, including boxplots, and heatmaps and the generated outputs can be downloaded in pdf-format.

Availability and implementationThe web-based user interface is implemented using HTML5, JavaScript, CSS, Plotly and R. It is freely available from https://endometdb.utu.fi/.

Measurement(s)	RNA • differential expression analysis data • endometriosis
Technology Type(s)	Microarray Analysis • digital curation
Factor Type(s)	age • disease stage • menstrual cycle phase • hormonal medication • endometriosis lesion type • endometrium
Sample Characteristic - Organism	Homo sapiens

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12800642

Endometriosis: current challenges in modeling a multifactorial disease of unknown etiology

Endometriosis is a chronic inflammatory hormone-dependent condition associated with pelvic pain and infertility, characterized by the growth of ectopic endometrium outside the uterus. Given its still unknown etiology, treatments usually aim at diminishing pain and/or achieving pregnancy. Despite some progress in defining mode-of-action for drug development, the lack of reliable animal models indicates that novel approaches are required. The difficulties inherent to modeling endometriosis are related to its multifactorial nature, a condition that hinders the recreation of its pathology and the identification of clinically relevant metrics to assess drug efficacy. In this review, we report and comment endometriosis models and how they have led to new therapies. We envision a roadmap for endometriosis research, integrating Artificial Intelligence, three-dimensional cultures and organ-on-chip models as ways to achieve better understanding of physiopathological features and better tailored effective treatments.