Single-cell transcriptomic analysis of endometriosis

Bioengineering approaches for the endometrial research and application

The endometrium undergoes a series of precise monthly changes under the regulation of dynamic levels of ovarian hormones that are characterized by repeated shedding and subsequent regeneration without scarring. This provides the potential for wound healing during endometrial injuries. Bioengineering materials highlight the faithful replication of constitutive cells and the extracellular matrix that simulates the physical and biomechanical properties of the endometrium to a larger extent. Significant progress has been made in this field, and functional endometrial tissue bioengineering allows an in-depth investigation of regulatory factors for endometrial and myometrial defects in vitro and provides highly therapeutic methods to alleviate obstetric and gynecological complications. However, much remains to be learned about the latest progress in the application of bioengineering technologies to the human endometrium. Here, we summarize the existing developments in biomaterials and bioengineering models for endometrial regeneration and improving the female reproductive potential.

The role of regulatory T-cells in the development of endometriosis

Endometriosis is a benign disease of the female reproductive tract, characterized by the process of chronic inflammation and alterations in immune response. It is estimated to affect 2-19% of women in the general population and is commonly associated with symptoms of chronic pelvic pain and infertility. Regulatory T cells (Treg) are a subpopulation of T lymphocytes that are potent suppressors of inflammatory immune response, essential in preventing destructive immunity in all tissues. In endometriosis, several studies have investigated the possible role of Treg cells in the development of the disease. Most studies to date are heterogeneous in methodology and are based on a small number of cases, which means that it is impossible to define their exact role at present. Based on current knowledge, it seems that disturbed Treg homeostasis, leading to increased systemic and local inflammation within ectopic and eutopic endometrium, is present in women who eventually develop endometriosis. It is also evident that different subsets of human Treg cells have different roles in suppressing the immune response. Recent studies in patients with endometriosis have investigated naive/resting FOXP3lowCD45RA+ Treg cells, which upon T cell receptor stimulation, differentiate into activated/effector FOXP3highCD45RA- Treg cells, characterized by a strong immunosuppressive activity. In addition, critical factors controlling expression of Treg/effector genes, including reactive oxygen species and heme-responsive master transcription factor BACH2, were found to be upregulated in endometriotic lesions. As shown recently for cancer microenvironments, microbial inflammation may also contribute to the local composition of FOXP3+ subpopulations in endometriotic lesions. Furthermore, cytokines, such as IL-7, which control the homeostasis of Treg subsets through the tyrosine phosphorylation STAT5 signalling pathway, have also been shown to be dysregulated. To better understand the role of Treg in the development of endometriosis, future studies should use clear definitions of Tregs along with specific characterization of the non-Treg (FOXP3lowCD45RA-) fraction, which itself is a mixture of follicular Tregs and cells producing inflammatory cytokines.

ARID1A in Gynecologic Precancers and Cancers

The highest frequency of genetic alterations in the tumor suppressor ARID1A occurs in malignancies of the female reproductive tract. The prevalence of ARID1A alterations in gynecologic precancers and cancers is summarized from the literature, and the putative mechanisms of tumor suppressive action examined both in benign/precursor lesions including endometriosis and atypical hyperplasia and in malignancies of the ovary, uterus, cervix and vagina. ARID1A alterations in gynecologic cancers are usually loss-of-function mutations, resulting in diminished or absent protein expression. ARID1A deficiency results in pleiotropic downstream effects related not only to its role in transcriptional regulation as a SWI/SNF complex subunit, but also related to the functions of ARID1A in DNA replication and repair, immune modulation, cell cycle progression, endoplasmic reticulum (ER) stress and oxidative stress. The most promising actionable signaling pathway interactions and therapeutic vulnerabilities of ARID1A mutated cancers are presented with a critical review of the currently available experimental and clinical evidence. The role of ARID1A in response to chemotherapeutic agents, radiation therapy and immunotherapy is also addressed. In summary, the multi-faceted role of ARID1A mutation in precancer and cancer is examined through a clinical lens focused on development of novel preventive and therapeutic interventions for gynecological cancers.

The pathogenesis of endometriosis and adenomyosis: insights from single-cell RNA sequencing†

Endometriosis and adenomyosis are two similar gynecological diseases that are characterized by ectopic implantation and the growth of the endometrial tissue. Previous studies have reported that they share a common pathophysiology in some respects, such as a similar cellular composition and resistance to the progestogen of lesions, but their underlying mechanisms remain elusive. Emerging single-cell ribonucleic acid sequencing (scRNA-seq) technologies allow for the dissection of single-cell transcriptome mapping to reveal the etiology of diseases at the level of the individual cell. In this review, we summarized the published findings in research on scRNA-seq regarding the cellular components and molecular profiles of diverse lesions. They show that epithelial cell clusters may be the vital progenitors of endometriosis and adenomyosis. Subclusters of stromal cells, such as endometrial mesenchymal stem cells and fibroblasts, are also involved in the occurrence of endometriosis and adenomyosis, respectively. Moreover, CD8+ T cells, natural killer cells, and macrophages exhibit a deficiency in clearing the ectopic endometrial cells in the immune microenvironment of endometriosis. It seems that the immune responses are activated in adenomyosis. Understanding the immune characteristics of adenomyosis still needs further exploration. Finally, we discuss the application of findings from scRNA-seq for clinical diagnosis and treatment. This review provides fresh insights into the pathogenesis of endometriosis and adenomyosis as well as the therapeutic targets at the cellular level.

Vitamin D and reproductive disorders: a comprehensive review with a focus on endometriosis

Vitamin D is a fat-soluble steroid hormone that was initially known only for regulating calcium and phosphorus levels and maintaining bone health. However, it was later discovered that many organs express vitamin D metabolizing enzymes and have a ligand for vitamin D, which regulates the expression of an extensive assortment of genes. As a result, vitamin D is indispensable for the proper function of organs, and its deficiency is believed to be a critical factor in symptoms and disorders such as cardiovascular diseases, autoimmune diseases, and cancers. The significance of vitamin D in reproductive tissues was recognized later, and studies have revealed its crucial role in male and female fertility, as well as proper reproductive function during pregnancy. Vitamin D deficiency has been identified as a risk factor for infertility, gonadal cancers, pregnancy complications, polycystic ovary syndrome, and endometriosis. However, data investigating the association between vitamin D levels and reproductive disorders, including endometriosis, have encountered inconsistencies. Therefore, the present study aims to review existing research on the effect of vitamin D on proper reproductive function, and the role of deficiency in reproductive diseases and specifically focuses on endometriosis.

Single-cell analysis reveals insights into epithelial abnormalities in ovarian endometriosis

Ovarian endometriosis is characterized by the growth of endometrial tissue within the ovary, causing infertility and chronic pain. However, its pathophysiology remains unclear. Utilizing high-precision single-cell RNA sequencing, we profile the normal, eutopic, and ectopic endometrium from 34 individuals across proliferative and secretory phases. We observe an increased proportion of ciliated cells in both eutopic and ectopic endometrium, characterized by a diminished expression of estrogen sulfotransferase, which likely confers apoptosis resistance. After translocating to ectopic lesions, endometrial epithelium upregulates nicotinamide N-methyltransferase expression that inhibits apoptosis by promoting deacetylation and subsequent nuclear exclusion of transcription factor forkhead box protein O1, thereby leading to the downregulation of the apoptotic gene BIM. Moreover, epithelial cells in ectopic lesions elevate HLA class II complex expression, which stimulates CD4+ T cells and consequently contributes to chronic inflammation. Altogether, our study provides a comprehensive atlas of ovarian endometriosis and highlights potential therapeutic targets for modulating apoptosis and inflammation.

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.

The rising tide raises all ships

It is easy to feel as if you are alone in academia, especially if you face challenges that not everyone does, or can, understand. Community is essential in facing these challenges, and we each have a role to play in creating a more equitable research community. Here, I discuss the importance of community, finding your village and being part of the academic support system.

Effect of aging on the human myometrium at single-cell resolution

Age-associated myometrial dysfunction can prompt complications during pregnancy and labor, which is one of the factors contributing to the 7.8-fold increase in maternal mortality in women over 40. Using single-cell/single-nucleus RNA sequencing and spatial transcriptomics, we have constructed a cellular atlas of the aging myometrium from 186,120 cells across twenty perimenopausal and postmenopausal women. We identify 23 myometrial cell subpopulations, including contractile and venous capillary cells as well as immune-modulated fibroblasts. Myometrial aging leads to fewer contractile capillary cells, a reduced level of ion channel expression in smooth muscle cells, and impaired gene expression in endothelial, smooth muscle, fibroblast, perivascular, and immune cells. We observe altered myometrial cell-to-cell communication as an aging hallmark, which associated with the loss of 25 signaling pathways, including those related to angiogenesis, tissue repair, contractility, immunity, and nervous system regulation. These insights may contribute to a better understanding of the complications faced by older individuals during pregnancy and labor.

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

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

Ovarian Cancer: From Precursor Lesion Identification to Population-Based Prevention Programs

Epithelial ovarian cancer (EOC) is a heterogeneous group of malignancies, including high-grade serous ovarian cancer (HGSC). HGSC is often diagnosed at advanced stages and is linked to TP53 variants. While BRCA variants elevate risk, most HGSC cases occur in individuals without known genetic variants, necessitating prevention strategies for people without known high-risk genetic variants. Effective prevention programs are also needed due to the lack of traditional screening options. An emerging primary prevention strategy is opportunistic salpingectomy, which involves removing fallopian tubes during another planned pelvic surgery. Opportunistic salpingectomy offers a safe and cost-effective preventative option that is gaining global adoption. With the publication of the first cohort study of patients who underwent salpingectomy, specifically for cancer prevention, attention has turned to broadening opportunities for salpingectomy in addition to more targeted approaches. Prevention opportunities are promising with increasing adoption of salpingectomy and the increased understanding of the etiology of the distinct histotypes of ovarian cancer. Yet, further research on targeted risk-reducing salpingectomy with thoughtful consideration of equity is necessary to reduce death and suffering from ovarian cancer.

A cell abundance analysis based on efficient PAM clustering for a better understanding of the dynamics of endometrial remodelling

BACKGROUND

Single-cell RNA sequencing (scRNA-seq) is a powerful tool for investigating cell abundance changes during tissue regeneration and remodeling processes. Differential cell abundance supports the initial clustering of all cells; then, the number of cells per cluster and sample are evaluated, and the dependence of these counts concerning the phenotypic covariates of the samples is studied. Analysis heavily depends on the clustering method. Partitioning Around Medoids (PAM or k-medoids) represents a well-established clustering procedure that leverages the downstream interpretation of clusters by pinpointing real individuals in the dataset as cluster centers (medoids) without reducing dimensions. Of note, PAM suffers from high computational costs and memory requirements.

RESULTS

This paper proposes a method for differential abundance analysis using PAM as a clustering method and negative binomial regression as a statistical model to relate covariates to cluster/cell counts. We used this approach to study the differential cell abundance of human endometrial cell types throughout the natural secretory phase of the menstrual cycle. We developed a new R package -scellpam-, that incorporates an efficient parallel C++ implementation of PAM, and applied this package in this study. We compared the PAM-BS clustering method with other methods and evaluated both the computational aspects of its implementation and the quality of the classifications obtained using distinct published datasets with known subpopulations that demonstrate promising results.

CONCLUSIONS

The implementation of PAM-BS, included in the scellpam package, exhibits robust performance in terms of speed and memory usage compared to other related methods. PAM allowed quick and robust clustering of sets of cells with a size ranging from 70,000 to 300,000 cells. https://cran.r-project.org/web/packages/scellpam/index.html . Finally, our approach provides important new insights into the transient subpopulations associated with the fertile time frame when applied to the study of changes in the human endometrium during the secretory phase of the menstrual cycle.

ARID1a Gene as a Potential Early Marker to Tackle Endometriosis-Associated Ovarian Cancer

The worries of women with endometriosis - a chronic gynecological disease affecting approximately 10% of women of childbearing age - about the increased risk of ovarian cancer are present worldwide. Endometriosis is a common, often painful, but benign gynecological disease that affects women. However, the pathogenesis remains elusive but is certainly multifactorial. Interestingly, endometriosis shares similarities with cancer. Therefore, women suffering from endometriosis fear an increased risk of ovarian cancer. In addition, these patients suffer from anxiety and depression. Previous studies have provided evidence that epithelial mutations in endometriosis or in the endometrium include certain inactivating mutations responsible for ovarian cancer, such as in the ARID1A gene.

Dissecting mammalian reproduction with spatial transcriptomics

BACKGROUND

Mammalian reproduction requires the fusion of two specialized cells: an oocyte and a sperm. In addition to producing gametes, the reproductive system also provides the environment for the appropriate development of the embryo. Deciphering the reproductive system requires understanding the functions of each cell type and cell-cell interactions. Recent single-cell omics technologies have provided insights into the gene regulatory network in discrete cellular populations of both the male and female reproductive systems. However, these approaches cannot examine how the cellular states of the gametes or embryos are regulated through their interactions with neighboring somatic cells in the native tissue environment owing to tissue disassociations. Emerging spatial omics technologies address this challenge by preserving the spatial context of the cells to be profiled. These technologies hold the potential to revolutionize our understanding of mammalian reproduction.

OBJECTIVE AND RATIONALE

We aim to review the state-of-the-art spatial transcriptomics (ST) technologies with a focus on highlighting the novel biological insights that they have helped to reveal about the mammalian reproductive systems in the context of gametogenesis, embryogenesis, and reproductive pathologies. We also aim to discuss the current challenges of applying ST technologies in reproductive research and provide a sneak peek at what the field of spatial omics can offer for the reproduction community in the years to come.

SEARCH METHODS

The PubMed database was used in the search for peer-reviewed research articles and reviews using combinations of the following terms: 'spatial omics', 'fertility', 'reproduction', 'gametogenesis', 'embryogenesis', 'reproductive cancer', 'spatial transcriptomics', 'spermatogenesis', 'ovary', 'uterus', 'cervix', 'testis', and other keywords related to the subject area. All relevant publications until April 2023 were critically evaluated and discussed.

OUTCOMES

First, an overview of the ST technologies that have been applied to studying the reproductive systems was provided. The basic design principles and the advantages and limitations of these technologies were discussed and tabulated to serve as a guide for researchers to choose the best-suited technologies for their own research. Second, novel biological insights into mammalian reproduction, especially human reproduction revealed by ST analyses, were comprehensively reviewed. Three major themes were discussed. The first theme focuses on genes with non-random spatial expression patterns with specialized functions in multiple reproductive systems; The second theme centers around functionally interacting cell types which are often found to be spatially clustered in the reproductive tissues; and the thrid theme discusses pathological states in reproductive systems which are often associated with unique cellular microenvironments. Finally, current experimental and computational challenges of applying ST technologies to studying mammalian reproduction were highlighted, and potential solutions to tackle these challenges were provided. Future directions in the development of spatial omics technologies and how they will benefit the field of human reproduction were discussed, including the capture of cellular and tissue dynamics, multi-modal molecular profiling, and spatial characterization of gene perturbations.

WIDER IMPLICATIONS

Like single-cell technologies, spatial omics technologies hold tremendous potential for providing significant and novel insights into mammalian reproduction. Our review summarizes these novel biological insights that ST technologies have provided while shedding light on what is yet to come. Our review provides reproductive biologists and clinicians with a much-needed update on the state of art of ST technologies. It may also facilitate the adoption of cutting-edge spatial technologies in both basic and clinical reproductive research.

Single-cell profiling identifies distinct hormonal, immunologic, and inflammatory signatures of endometriosis-constituting cells

Endometriosis consists of ectopic endometrial epithelial cells (EEECs) and ectopic endometrial stromal cells (EESCs) mixed with heterogeneous stromal cells. To address how endometriosis-constituting cells are different from normal endometrium and among endometriosis subtypes and how their molecular signatures are related to phenotypic manifestations, we analyzed ovarian endometrial cyst (OEC), superficial peritoneal endometriosis (SPE), and deep infiltrating endometriosis (DIE) from 12 patients using single-cell RNA-sequencing (scRNA-seq). We identified 11 cell clusters, including EEEC, EESC, fibroblasts, inflammatory/immune, endothelial, mesothelial, and Schwann cells. For hormonal signatures, EESCs, but not EEECs, showed high estrogen signatures (estrogen response scores and HOXA downregulation) and low progesterone signatures (DKK1 downregulation) compared to normal endometrium. In EEECs, we found MUC5B+ TFF3low cells enriched in endometriosis. In lymphoid cells, evidence for both immune activation (high cytotoxicity in NK) and exhaustion (high checkpoint genes in NKT and cytotoxic T) was identified in endometriosis. Signatures and subpopulations of macrophages were remarkably different among endometriosis subtypes with increased monocyte-derived macrophages and IL1B expression in DIE. The scRNA-seq predicted NRG1 (macrophage)-ERBB3 (Schwann cell) interaction in endometriosis, expressions of which were validated by immunohistochemistry. Myofibroblast subpopulations differed according to the location (OECs from fibroblasts and SPE/DIEs from mesothelial cells and fibroblasts). Endometriosis endothelial cells displayed proinflammation, angiogenesis, and leaky permeability signatures that were enhanced in DIE. Collectively, our study revealed that (1) many cell types-endometrial, lymphoid, macrophage, fibroblast, and endothelial cells-are altered in endometriosis; (2) endometriosis cells show estrogen responsiveness, immunologic cytotoxicity and exhaustion, and proinflammation signatures that are different in endometriosis subtypes; and (3) novel endometriosis-specific findings of MUC5B+ EEECs, mesothelial cell-derived myofibroblasts, and NRG1-ERBB3 interaction may underlie the pathogenesis of endometriosis. Our results may help extend pathologic insights, dissect aggressive diseases, and discover therapeutic targets in endometriosis. © 2023 The Pathological Society of Great Britain and Ireland.

Scellpam: an R package/C++ library to perform parallel partitioning around medoids on scRNAseq data sets

BACKGROUND

Partitioning around medoids (PAM) is one of the most widely used and successful clustering method in many fields. One of its key advantages is that it only requires a distance or a dissimilarity between the individuals, and the fact that cluster centers are actual points in the data set means they can be taken as reliable representatives of their classes. However, its wider application is hampered by the large amount of memory needed to store the distance matrix (quadratic on the number of individuals) and also by the high computational cost of computing such distance matrix and, less importantly, by the cost of the clustering algorithm itself.

RESULTS

Therefore, new software has been provided that addresses these issues. This software, provided under GPL license and usable as either an R package or a C++ library, calculates in parallel the distance matrix for different distances/dissimilarities ([Formula: see text], [Formula: see text], Pearson, cosine and weighted Euclidean) and also implements a parallel fast version of PAM (FASTPAM1) using any data type to reduce memory usage. Moreover, the parallel implementation uses all the cores available in modern computers which greatly reduces the execution time. Besides its general application, the software is especially useful for processing data of single cell experiments. It has been tested in problems including clustering of single cell experiments with up to 289,000 cells with the expression of about 29,000 genes per cell.

CONCLUSIONS

Comparisons with other current packages in terms of execution time have been made. The method greatly outperforms the available R packages for distance matrix calculation and also improves the packages that implement the PAM itself. The software is available as an R package at https://CRAN.R-project.org/package=scellpam and as C++ libraries at https://github.com/JdMDE/jmatlib and https://github.com/JdMDE/ppamlib The package is useful for single cell RNA-seq studies but it is also applicable in other contexts where clustering of large data sets is required.

Systems level identification of a matrisome-associated macrophage polarisation state in multi-organ fibrosis

Tissue fibrosis affects multiple organs and involves a master-regulatory role of macrophages which respond to an initial inflammatory insult common in all forms of fibrosis. The recently unravelled multi-organ heterogeneity of macrophages in healthy and fibrotic human disease suggests that macrophages expressing osteopontin (SPP1) associate with lung and liver fibrosis. However, the conservation of this SPP1+ macrophage population across different tissues and its specificity to fibrotic diseases with different etiologies remain unclear. Integrating 15 single-cell RNA-sequencing datasets to profile 235,930 tissue macrophages from healthy and fibrotic heart, lung, liver, kidney, skin, and endometrium, we extended the association of SPP1+ macrophages with fibrosis to all these tissues. We also identified a subpopulation expressing matrisome-associated genes (e.g., matrix metalloproteinases and their tissue inhibitors), functionally enriched for ECM remodelling and cell metabolism, representative of a matrisome-associated macrophage (MAM) polarisation state within SPP1+ macrophages. Importantly, the MAM polarisation state follows a differentiation trajectory from SPP1+ macrophages and is associated with a core set of regulon activity. SPP1+ macrophages without the MAM polarisation state (SPP1+MAM-) show a positive association with ageing lung in mice and humans. These results suggest an advanced and conserved polarisation state of SPP1+ macrophages in fibrotic tissues resulting from prolonged inflammatory cues within each tissue microenvironment.

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.

Molecular Mechanisms of Endometriosis Revealed Using Omics Data

Endometriosis is a gynecological disorder prevalent in women of reproductive age. The primary symptoms include dysmenorrhea, irregular menstruation, and infertility. However, the pathogenesis of endometriosis remains unclear. With the advent of high-throughput technologies, various omics experiments have been conducted to identify genes related to the pathophysiology of endometriosis. This review highlights the molecular mechanisms underlying endometriosis using omics. When genes identified in omics experiments were compared with endometriosis disease genes identified in independent studies, the number of overlapping genes was moderate. However, the characteristics of these genes were found to be equivalent when functional gene set enrichment analysis was performed using gene ontology and biological pathway information. These findings indicate that omics technology provides invaluable information regarding the pathophysiology of endometriosis. Moreover, the functional characteristics revealed using enrichment analysis provide important clues for discovering endometriosis disease genes in future research.

Association between polymorphisms of cytokine genes and endometriosis: A comprehensive systematic review and meta-analysis

INTRODUCTION

There is abundant evidence to suggest that cytokines play a part in the mechanisms responsible for the formation of endometrium heterotopy. Cytokine synthesis is not only determined by the body's immunological reactivity but also by polymorphisms in the immune regulatory genes. The study of these polymorphisms in the immune regulatory genes offers up new possibilities in terms of prognosticating the risk of endometriosis and susceptibility to its treatment. The purpose of this comprehensive systematic review and meta-analysis was to investigate whether or not cytokine gene polymorphisms were linked to an increased chance of endometriosis.

METHODS

By searching MEDLINE, Scopus, and Web of Science databases, the relevant studies were identified. The odds ratio (OR) with 95% confidence interval (CI) was used to assess the association between TNF-α/IL-10/IL-6/TGF-β/IFN-γ/IL-1β gene polymorphisms and endometriosis risk.

RESULTS

A total of 5128 cases and 5334 controls in 32 eligible studies were included in the meta-analysis. Overall, results indicated the negative association between the cytokine gene polymorphisms and endometriosis in the dominant model of TNF-α (rs1799964): [OR] = 0.64, [CI]: 0.46-0.89) and a positive association in IFN-γ a13 allele: OR= 1.45, [CI]: 1.07-1.98; and IL-10 (rs1800872): [OR]= 1.60, [CI]: 1.21-2.12).

CONCLUSION

The present study suggests that IL-10 (rs1800872) and IFN-γ a13 allele may be a risk factors for endometriosis. Also, TNF-α (rs1799964) is associated with decreased susceptibility to endometriosis.

Mast Cell Tryptase and Carboxypeptidase A3 in the Formation of Ovarian Endometrioid Cysts

The mechanisms of ovarian endometrioid cyst formation, or cystic ovarian endometriosis, still remain to be elucidated. To address this issue, we analyzed the involvement of mast cell (MC) tryptase and carboxypeptidase A3 (CPA3) in the development of endometriomas. It was found that the formation of endometrioid cysts was accompanied by an increased MC population in the ovarian medulla, as well as by an MC appearance in the cortical substance. The formation of MC subpopulations was associated with endometrioma wall structures. An active, targeted secretion of tryptase and CPA3 to the epithelium of endometrioid cysts, immunocompetent cells, and the cells of the cytogenic ovarian stroma was detected. The identification of specific proteases in the cell nuclei of the ovarian local tissue microenvironment suggests new mechanisms for the regulatory effects of MCs. The cytoplasmic outgrowths of MCs propagate in the structures of the stroma over a considerable distance; they offer new potentials for MC effects on the structures of the ovarian-specific tissue microenvironment under pathological conditions. Our findings indicate the potential roles of MC tryptase and CPA3 in the development of ovarian endometriomas and infer new perspectives on their uses as pharmacological targets in personalized medicine.

Endometriosis: Update of Pathophysiology, (Epi) Genetic and Environmental Involvement

Endometriosis is a chronic disease caused by ectopic endometrial tissue. Endometriotic implants induce inflammation, leading to chronic pain and impaired fertility. Characterized by their dependence on estradiol (via estrogen receptor β (ESRβ)) and their resistance to progesterone, endometriotic implants produce their own source of estradiol through active aromatase. Steroidogenic factor-1 (SF1) is a key transcription factor that promotes aromatase synthesis. The expression of SF1 and ESRβ is enhanced by the demethylation of their promoter in progenitor cells of the female reproductive system. High local concentrations of estrogen are involved in the chronic inflammatory environment favoring the implantation and development of endometriotic implants. Similar local conditions can promote, directly and indirectly, the appearance and development of genital cancer. Recently, certain components of the microbiota have been identified as potentially promoting a high level of estrogen in the blood. Many environmental factors are also suspected of increasing the estrogen concentration, especially prenatal exposure to estrogen-like endocrine disruptors such as DES and bisphenol A. Phthalates are also suspected of promoting endometriosis but throughmeans other than binding to estradiol receptors. The impact of dioxin or tobacco seems to be more controversial.

Aberrant expression of histone deacetylase 8 in endometriosis and its potential as a therapeutic target

Purpose

To screen Zn2+-dependent histone deacetylase (HDAC) 1-11 in endometriotic cells and then evaluated the HDACs identified from the screening in ovarian endometrioma (OE) and deep endometriotic (DE) lesions, and to evaluate the therapeutic potential of HDAC8 inhibition in mice.

Methods

Quantification of gene and protein expression levels of HDAC1-11 in endometriotic cells stimulated by TGF-β1, and immunohistochemistry analysis of Class I HDACs and HDAC6 in OE/DE lesion samples. The therapeutic potential of HDAC8 inhibition was evaluated by a mouse model of deep endometriosis.

Results

The screening identified Class I HDACs and HDAC6 as targets of interest. Immunohistochemistry analysis found a significant elevation in HDAC8 immunostaining in both OE and DE lesions, which was corroborated by gene and protein expression quantification. For other Class I HDACs and HDAC6, their lesional expression was more subtle and nuanced. HDAC1 and HDAC6 staining was significantly elevated in DE lesions while HDAC2 and HDAC3 staining was reduced in DE lesions. Treatment of mice with induced deep endometriosis with an HDAC8 inhibitor resulted in significantly longer hotplate latency, a reduction of lesion weight by nearly two-thirds, and significantly reduced lesional fibrosis.

Conclusions

These findings highlight the progression-dependent nature of specific HDAC aberrations in endometriosis, and demonstrate, for the first titme, the therapeutic potential of suppressing HDAC8.