Single-cell analysis of endometrial proliferation and secretory phases in patients with endometriosis and normal population

Single-cell analysis of endometrial proliferation and secretory phases in patients with endometriosis and normal population | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Single-cell analysis of endometrial proliferation and secretory phases in patients with endometriosis and normal population Feng Chen, Shi Tong, Li Juan Huang, Lin Chen, An Yi Teng, Shu Zhi Zhao, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5954285/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The characteristic of endometriosis is that the endometrial tissue grows in non-endometrial parts such as the pelvis and ovaries, leading to infertility and chronic pain. However, its pathophysiology is still unclear. Using high-precision single-cell RNA sequencing, we analyzed the in-situ endometrium of 13 individuals with or without endometriosis, including the proliferative and secretory phases. We have meticulously generated a comprehensive single-cell atlas of the eutopic endometrium from patients with endometriosis. Comparative analysis with the healthy eutopic endometrium has elucidated that the epithelial cells of the ectopic tissue display marked immune-related phenotypes. We have identified the presence of an epithelial-to-mesenchymal transition (EMT) pathway between epithelial cells and fibroblasts within the endometrial tissue of individuals with endometriosis. Furthermore, our research has elucidated the intricate interactive dynamics between immune cells and fibroblasts, epithelial and endothelial cells, potentially shedding light on the underlying pathophysiological mechanisms contributing to endometriosis. Biological sciences/Cell biology Health sciences/Diseases single-cell RNA sequence endometriosis endometrial epithelial cells EMT Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction Endometriosis (EMs) is a complex syndrome characterized by an estrogen-dependent chronic inflammatory process and the growth of functional endometrial tissue outside the uterus[1]. It primarily affects the pelvic region, including the ovaries, peritoneum, ligaments, intestines, and bladder[2]. Approximately 10% of women of reproductive age worldwide (equivalent to 190 million women) are affected by endometriosis, with symptoms including chronic pelvic pain, dysmenorrhea, pain, and infertility[3]. Endometriosis is strongly linked to persistent episodes of ovulation, menstruation, and cycling steroid hormones and the key biologic driver of inflammation is the dependence on estrogen[1,4,5]. The endometrium is the mucous layer of the endometrium, which undergoes dynamic changes during the menstrual cycle driven by the signaling of estrogen and progesterone. Histomorphology divides the menstrual cycle into the menstrual phase, proliferative phase, and secretory phase. Previous studies have shown that there are significant molecular abnormalities in the eutopic endometrium[6–8]. There are several theories to account for the origin of endometriosis and to explain how tissue can be scattered throughout the abdominal cavity. Among the most-examined and most popular theories are retrograde menstruation. However, there is still a lack of detailed understanding regarding which endometrial cell populations and which specific changes are associated with the formation of endometriotic lesions. Although the array of treatments including gonadotropin-releasing hormone (GnRH) antagonists or agonists, aromatase inhibitors, selective estrogen receptor (ER) and progesterone receptor (PR) modulators, and anti-inflammatory medications continues to expand, some patients experience unnecessary side effects, including headaches, weight gain, and irregular bleeding and develop resistance to these medical interventions, leading to recurrences[9]. Consequently, they often require repeated laparoscopic-assisted surgical procedures, which can diminish their quality of life. Recently, a study based on the analysis of single cells reported that there are varying degrees of dysregulation in the endometrial epithelium, stroma, and immunity of women with endometriosis[10,11]. Despite decades of dedicated research, our comprehension of the pathogenesis and etiology of endometriosis remains limited. Therefore, uncovering the deeper pathophysiological mechanisms of endometriosis is crucial for developing more effective treatments. Our research delved into the important role of epithelial cells and immune cells in the pathogenesis of endometriosis by strictly controlling for stage and individual differences, through analyzing the normal and endometriosis endometrium by the Single-cell RNA sequence data [12]. Our research emphasizes the dysregulation of the subtype of epithelial cells within the patient's body, as well as the regulatory role of immune cells. These findings have deepened our understanding of the etiology and pathological characteristics of endometriosis. 2. Methods 2.1 Data Source In the GEO database, searching for "endometriosis" and "Single-cell sequencing" as keywords yielded the dataset GSE214411, which is Single-cell RNA sequence of 138, 057 endometrial cells from 6 endometriosis patients (3 samples from proliferative phase and 3 samples from secretory phase) and 7 control (3 samples from proliferative phase and 4 samples from secretory phase). 2.2 Data Quality Control Use RStudio Server to read and process genomic and transcriptomic data. With the original data nFeature_RNA > 300 & nFeature_RNA < 7000, mitochondrial proportion 1000, and excluding the largest top 3% of cells, the expression amount of erythrocyte genes per cell accounts for < 3% of the total genes as the cell screening criteria, carry out "Log-Normalization" standardization treatment, and remove batch effects through the Harmony package. 2.3 Endometrial Single-Cell Type and Epithelial Cell Subtype Clustering Analysis After reducing the dimensionality of the data using Principal Component Analysis (PCA) and T-Distributed Stochastic Neighbor Embedding (t-SNE) algorithms, the FindVariableFeatures function is used to identify differentially expressed genes (DEGs). The FindClusters function is then used for clustering analysis and visualization, displaying different cell clusters in the endometrium. Using only.pos = TRUE and |avg_log2FC| ≥ 0.25 as data parameters, the Wilcoxon rank sum test is performed, and DEGs are screened through the FindMarkers function. The top 50 DEGs of different single-cell types are selected as reference genes, and endometrial cell types are determined based on the singleR package. The Human Protein Atlas, ACT database, and related literature. Different epithelial cell subtypes are annotated based on marker genes. 2.4 Differential Expression Genes and Functional Analysis of Epithelial Cell Subtypes Using the R package clusterProfiler with parameters set to only.pos = TRUE and |avg_log2FC| ≥ 0.25, DEGs are screened in different epithelial cell subtypes and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. 2.5 Epithelial Cell Subtype Communication Patterns and Pseudotime Analysis Based on the CellChat package and by cross-referencing the ligand-receptor interaction database, analyze the communication network, quantity, and intensity among epithelial cell subtypes to explore the dynamic changes in disease progression. Use the Monocle3 package to reconstruct the differentiation trajectory of endometrial epithelial cells in patients with endometriosis, perform pseudotime analysis to determine the temporal patterns of epithelial cell changes over time, and identify the expression levels of DEGs during different stages of epithelial cell differentiation. 3. Result 3.1 Atlas of the Endometrium in women without and with endometriosis To comprehensively elucidate the composition of endometriotic lesions, we retrieved EMs datasets from the Gene Expression Omnibus (GEO) database and selected GSE214411, which encompasses single-cell RNA sequencing data from 138,057 endometrial cells derived from six proliferative phase samples and seven secretory phase samples[12]. Within this dataset, we focused on samples from six women with endometriosis and seven healthy controls. After rigorous quality control and filtering procedures, a total of 86,381 cells were retained for subsequent analysis (Figure 1A, Figure S1A, S1B). Initially, we employed the SingleR package to automatically annotate the quality-controlled Seurat matrix, enabling a preliminary classification of cell types. To validate these annotation results, we adopted a two-pronged approach: (1) We selected the top 50 differentially expressed genes (DEGs) as marker genes and performed cell annotation using ACT and CellMarker2.0. (2) We utilized the ACT and CellMarker2.0 databases to obtain marker genes for various endometrial epithelial cell types, and examined the expression of these marker genes across different clusters using the "DimPlot" and "VlnPlot" functions (Figure 1A). Our analysis has generated a comprehensive and high-resolution atlas of the eutopic endometrium in both healthy controls and patients with endometriosis. Ultimately, the sample cells were categorized into two major groups: immune and non-immune cells, and most cell types have been re-annotated for cell subtypes (Figure 1B). Apart from granulocytes (only identified in the endometriosis group), other cell types were accurately identified within four tissue types: the endometrium of healthy women, the endometrium of women with EMs (Figures 1C, Figure S1C-D), and these were further subclassified into two menstrual cycle phases, namely the proliferative and secretory phases (Figure 1D). These encompassed seven primary cell types with differentially expressed genes (DEGs), including fibroblasts (HOXA11, SFRP4, MMP11), epithelial cells (EPCAM, SLPI, AGR2), endothelial cells (CLDN5, TM4SF18, ROBO4), NK cells (GNLY, KLRC1, KRT18), T cells (CD2, CD3G, TPSB2), granulocytes (TPSAB1, MS4A2), and monocytes (CD14, MPEG1, CYBB), (Figure 1E, Figure S1E). Subsequently, cells were annotated in details (Figure S1F). 3.2 Characterization of Epithelial Cell Subtypes in Endometriosis The etiology of endometriosis is multifaceted, encompassing sex hormones, immunity, inflammation, genetics, and additional factors, yet its pathogenic mechanisms remain elusive[13]. Consequently, we embarked on an assessment of the cellular heterogeneity within the endometrial epithelial cells of endometriosis (EM). Following strict quality control measures and utilizing high-resolution single-cell reference atlases, including the Human Endometrial Cell Atlas (HECA) and the Human Protein Atlas, with the reference marker genes provided, we annotated glandular proliferative cells, glandular secretory cells and ciliated cells, named as Glandular_proliferative, Glandular_secretory and Ciliated respectively[10,14]. In addition to the aforementioned three cell subtypes, our study identified a distinctive epithelial cell subpopulation that displayed a unique phenotypic profile. This subpopulation exhibited concurrently elevated expression levels of glandular cell markers, alongside similarly high levels of immune cell markers, specifically GNLY, CCL4, and AREG (Figure 2A). Consequently, we have designated this subpopulation as "Epi_immuno" to highlight its differential characteristics (Figure 2B). The execution of a comprehensive Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) on the repertoire of expressed genes serves as robust validation for the precision and reliability of our cellular annotation (Figure S2). We conducted a comparative analysis of the proportions of each subtype of endometriosis with those of normal endometrial epithelial cells. The results revealed significant disparities in the proportions of glandular cells (Glandular_secretory, Glandular_proliferative and Epi_immuno) (Figure 2C-D). We conducted a detailed analysis of each type of gland cell to investigate preexisting alterations contributing to the disease. Glandular_secretory in the endometriosis eutopic endometrium significantly upregulated genes involved in stress response and inflammatory response, such as HSPA6, HSPB8, HSPA1A, NFKB1, and CXCL8(Figure 2E). Consistently, normal endometrial epithelium downregulates the antioxidant stress gene SLC1A1, the neutrophil chemotaxis function gene CXCL14, as well as the genes promoting cell adhesion IGFBP7, IGFBP4, and AGR2(Figure 2E). Glandular_proliferative and Epi_immuno significantly upregulated genes with immune function, such as GNLY, NKG (Figure 2F-G). It was observed that there was no statistically significant difference in the quantity of ciliated cells between the endometriosis group and the normal group during both the proliferative and secretory phases (Figure 3A-B). To investigate potential disparities at the genetic level, a differential analysis was performed on these cells. Upon identifying that significant differences in gene expression of ciliated cells were evident between the normal and endometriosis groups (Figure 3C). It is discernible that endometriotic ciliated cells manifest transcriptional activity of genes implicated in immune response and neoplastic progression, such as NAMPT, NFKBIZ, TNFAIP3, CXCL8, and PLAUR. Our research elucidates that the ciliated cells in the proliferative phase display marked upregulation of the histone-encoding gene HIST1H1C and the cell cycle regulatory gene CCNA1 (Figure 3D-E, Figure S3). In contrast, ciliated cells during the secretory phase exhibit enhanced expression of genes pertinent to steroid hormone biosynthesis, encompassing the sex hormone synthetic genes SCGB1D2 and SULT1E1, alongside genes involved in lipid anabolism and catabolism, specifically ACSL5, STEAP4, and PTGDS (Figure 3D-E, Figure S3). We are inclined to hypothesize that ciliated cells play a pivotal role in mediating the progression of endometriosis. 3.3 Abnormal Epithelial Subpopulation with Autophagy Observed in Patients with EMs In an effort to meticulously delineate the complex interrelationships and phenotypic disparities inherent among multiple epithelial cell subpopulations, we performed a pseudotime analysis. Upon constructing the epithelial cell differentiation trajectory, our observations revealed that the Epi_immuno and Glandular_secretory are situated on the identical branch of the pseudotime analytical trajectory (Figure 4A-B). The finding implies that Epi_immuno plays a pivotal role in modulating the immune response within the endometrial microenvironment through the secretion of immune regulatory factors, thereby potentially contributing to the pathogenesis and progression of endometriosis. Furthermore, it is evident that Glandular_proliferative and Ciliated exhibit a shared differentiation inception, albeit with disparate cellular destinies (Figure 4A-B). Subsequently, by analyzing the trajectory plot, we successfully identified the cells in both the secretory and proliferative phases. Notably, our observations revealed that the ciliated cells within the endometrium seemingly maintain a dynamic equilibrium, which exhibits considerable variations across distinct menstrual cycles (Figure 4B-C). To investigate the disparities between the Epi_immuno and Glandular_secretory, we performed GO and KEGG enrichment analysis on DEGs between glandular secretory cells and Epi_immuno cells. GO analysis reveals that the enriched genes are intimately associated with biological activities pertaining to RNA synthesis metabolism and stress response, including ncRNA processing, tRNA metabolic processes, response to oxidative stress and macroautophagy (Figure 4D-E). The results obtained from the KEGG analysis indicate that the majority of enriched pathways are associated with autophagy, including mitophagy and macroautophagy (Figure 4F？G 没有G). Our findings indicated that the enriched DEGs exhibit a strong correlation with pathways involved in cellular secretion and immunology activities. As previously mentioned, it is postulated that Ciliated sustains a dynamic equilibrium at the cellular level, with the ciliated cells within endometriotic lesions exhibiting significant expression of genes associated with immunity and tumor progression. Furthermore, Cellular Component (CC) of GO analysis reveals that the primary regions of gene expression are predominantly confined to the centrioles and cilium basal bodies (Figure 5A). The results of GO analysis, particularly in terms of biological processes (BP) and molecular functions (MF), and KEGG analysis, further demonstrated that ciliated cells are predominantly implicated in the biological activities associated with cilia function as well as microtubule assembly and motility (Figure 5B-D). 3.4 Fibroblasts and Immune cells: Profound Contributors to EMT-Associated Pathways An in-depth investigation into the subpopulations and cell proportions of fibroblasts was carried out (Figure 6A-B). Upon conducting Gene Set Enrichment Analysis (GSEA) on endometriosis samples, we identified fibroblasts, notably the Fib_CADPS, as key players in endometriosis-related pathways, including EMT and angiogenesis[15] (Figure 6C). To delve deeper into the specific functional role of Fib, we embarked on a comprehensive and meticulous analysis. The spatial and temporal attributes exhibited by distinct subtypes of fibroblasts exhibit a significant degree of overlap (Figure 6D-F). Furthermore, we have conducted a comprehensive analysis of the differential gene expression profiles within the fibroblast group, adopting multiple perspectives to ensure a robust and nuanced understanding of the underlying molecular mechanisms (Figure 7A-C). The expression of the ancestral gene SFRP1, known for its regulatory role in cell growth, development, and transformation within endometriotic fibroblasts, exhibits significant downregulation (Figure 7A). From the perspective of differentially expressed genes, Fib_CADPS and Fib_PBK appear to exhibit similar characteristics (Figure 7B). In light of the aforementioned findings, we are poised to investigate the modulatory effects of endometriotic fibroblasts on EMT. We conducted a Gene Set Enrichment Analysis (GSEA) across all cellular subtypes present within the endometrium, followed by a "UCell" scoring assessment. Our findings revealed that fibroblasts exhibit significantly higher activity in this particular pathway compared to other cell types (Figure 7D-E, Figure S4A). Within the angiogenic pathway, fibroblasts exhibit a pivotal function (Figure 7F). Genes associated with the EMT exhibit a substantial enrichment score within immune cell populations (Figure 7E). This observation implies that the pathogenesis of endometriosis is likely influenced not solely by alterations within fibroblasts themselves, but also by the regulatory actions of immune cells. In an effort to delineate the precise epithelial cell populations and fibroblasts engaged in the EMT pathway, we meticulously examined the transcriptional dynamics of established EMT biomarkers within these cellular constituents (Figure 7G-H). KRT8 represents one of the most classical EMT marker genes. The reduced expression of CDH1, along with the overexpression of CDH2 and VIM, can induce EMT. SNAI1 acts as a regulatory factor in this process, binding to the enhancer of CDH1 and the promoter of KRT8. Epithelial cells, encompassing proliferating glandular and ciliated cell populations, exhibit a propensity to undergo mesenchymal transition, differentiating into fibroblasts (Figure 7G). 3. 5 Cell Communication Networks of Fibroblasts, Epithelial, and Immune Cells Contribute to EMT EMT represents a reversible phenomenon wherein epithelial cells experience a loss of polarity and cell-cell adhesion, undergo a transformation to a mesenchymal morphology, and subsequently acquire migratory and invasive capabilities[16]. Pathways such as WNT, TGFβ, VEGF, and NOTCH , as well as their regulators, are all implicated in EMT[17–19]. Therefore, we analyzed how epithelial cells and fibroblasts, immune cells collaborate in these pathways. Initially, we delineated the pathways implicated in each distinct cell type (Figure 8A-B). Our findings indicate that almost cell types within the endometrium of endometriosis are involved in signaling pathways, which can be categorized into three distinct patterns: Pattern 1 primarily involves cell groups such as Th17, CTL, and FOXP3+ Treg, which are associated with non-canonical WNT (ncWNT) and VEGF signaling pathways. Pattern 2 mainly encompasses cell groups like Fib_PLA2G2A and Fib_PBK, linked to TGFb and NOTCH signaling pathways. Lastly, Pattern 3 involves cell groups including Glandular_secretory and Ciliated cells, which are related to the WNT signaling pathway (Figure 8A). Our primary focus will be on Pattern 1. Fibroblasts, specifically the Fib_CAPDS subtype, orchestrate the VEGF and WNT signaling cascades via the secretion of diverse VEGF and WNT ligands that dock onto cognate receptors expressed on immune effector cells, predominantly monocytes and granulocytes (Figure 8D-H). Fib_CADPS engages with monocytes and granulocytes through PGF-VEGFR1 and WNT3A-(FZD+LRG5) pathways, thereby participating in the VEGF and WNT signaling cascades (Figure 8D). The recipient cells of the aforementioned transmitted signals are exclusively confined to endothelial cell subsets classified under pattern 3, along with epithelial cells with the exception of the Epi_immuno subtype (Figure 8B). Fib_HTR1F, Endo_VWF, and Endo_SEMA3G are implicated in the transmission of NOTCH signals, specifically NOTCH1 and NOTCH3, NOTCH1 and NOTCH4, and NOTCH1 and NOTCH4, respectively, thereby regulating diverse subpopulations of fibroblasts, endothelial cells, and epithelial cells. Notably, Fib_HTR1F functions concurrently as a signal sender, receiver, and mediator (Figure 9A-B). The exchange of information among these cells is facilitated through the reciprocal recognition of ligand-receptor complexes, including but not limited to JAG1-NOTCH1, JAG1-NOTCH2, and JAG1-NOTCH3 interactions (Figure 9C, Figure S4B). In the context of the WNT, ncWNT, and VEGF signaling pathways, fibroblasts function as key signal-emitting cells, orchestrating the activities of other cellular constituents within the intima (Figure S4D-H). Furthermore, within the TGF-β signaling pathway, adaptive NK cells emerge as pivotal signal mediators. This finding further substantiates the existence of a complex interplay and tight coupling between immune and non-immune cells within the intimal layer (Figure 9D-E). 4. Discussion Inflammatory, chemical, immunologic, epigenetic, and genetic changes have been discovered in eutopic endometria of patients with endometriosis compared to healthy women. Existing research primarily focuses on the individual alterations of non-immune cells and immune cells in the endometrium of patients with endometriosis, or the regulatory effects of immune cells on non-immune cells[20,21]. We have discovered that there is a transformation between epithelial cells and fibroblasts. We carried out single - cell transcriptome analysis on endometrial cells in order to obtain a better understanding of the pathogenesis of this disease and to explore the dynamic changes and immune environment of endometrial cells in the eutopic endometrium of endometriosis. Our single-cell transcriptome analysis included 13 samples from healthy individuals(6 samples) and women with endometriosis (7 samples), and further emphasized the key role of non-immune cells, especially epithelial cells and fibroblasts in the pathophysiology of endometriosis. Our atlas provides significant advantages for the comprehensive study of endometriosis. Compared with previous atlases, this study has generated a higher resolution cell landscape, which helps to identify more accurate cell states[22,23]. By analyzing dataset GSE214411, which successfully acquired normal and eutopic endometrial tissues during congruent phases, our study has effectively mitigated potential confounding factors related to phase-specific variations[12]. Consequently, this approach has enabled us to precisely identify the underlying aberrations inherent to the eutopic endometrium. Our investigative endeavors have elucidated that perturbations in epithelial cell subpopulations may be implicated in the etiopathogenesis of endometriosis. The human endometrium, predominantly consisting of endometrial epithelial and stromal cells, demonstrates exceptional plasticity and is subject to continuous cycles of injury and subsequent regeneration[24,25]. Hence, a perturbation in this equilibrium could precipitate the onset and progression of endometriosis[26]. The "Theory of Decidua in Situ Determination" rooted in Sampson's retrograde menstruation implantation hypothesis, posits that endometrial tissue refluxed into the pelvic cavity must undergo processes such as adhesion, invasion, and angiogenesis to implant, grow, and form lesions. The characteristics of the endometrium at its original site play a pivotal role in this process [27,4]. In patients with endometriosis, the endometrial epithelial cells progress through a proliferative phase primarily characterized by proliferating glandular cells, transitioning into a secretory phase predominantly governed by glandular secretory cells, which may or may not exhibit immune attributes. Ciliated cells are present throughout the entire endometrial transformation cycle, encompassing the menstrual cycle. The genes expressed by ciliated cells in individuals with endometriosis are associated with immune responses and in the proliferative and secretory phases are also not the same. Current research indicates that ciliated cells might constitute one of the etiological mechanisms underlying endometriosis[11]. Our investigation conclusively demonstrated that EMT is indeed present within the eutopic endometrium of individuals afflicted with endometriosis. We have identified that specific subtypes of epithelial cells play a role in the process of macroautophagy. Macroautophagy is considered to play a housekeeping role in maintaining cellular homeostasis and helps to eliminate misfolded proteins, damaged organelles and lipid droplets, enabling cells to function continuously and properly [28].To date, an extensive body of literature has substantiated the association between EMT and endometriosis[15,29,30]. Nonetheless, the precise mechanisms underlying this correlation, as well as the specific cellular and molecular participants involved, remain the subject of ongoing research and investigation. SFRP1, functioning as an antagonist of the WNT signaling pathway, undergoes downregulation that potentially facilitates EMT within the endometrium[31]. This phenomenon is attributed to the pivotal role of the WNT pathway as one of the key mediators of EMT[32]. Fib_CADPS exhibits elevated expression levels during the proliferative phase of the endometrium and remains consistently expressed throughout the entire differentiation stage, thereby underscoring its potential functional significance that warrants further investigation. In general, the adequate proportion, precise and orderly intercellular communication among the constituent cells (epithelial cells, fibroblasts, immune cells and endothelial cells) is conducive to the dynamic equilibrium and homeostasis of the endometrium. The variations between the eutopic endometrial epithelial cells and fibroblasts facilitate the physiological cyclical alterations of the endometrium, but once anomalies such as EMT arise, they will be correlated with the onset and progression of endometriosis. This process is not solitary, and both immune cells and endothelial cells will be involved in it. Consequently, a thorough and meticulous analysis of the cell subpopulations in the endometrium will aid us in identifying the etiology of the progression of endometriosis and pave the way for novel diagnostic and therapeutic tactics. For instance, selecting targeted factors to aim at abnormal cells or factors so as to modulate the disordered microenvironment of the endometrium, thereby mitigating the incidence of endometriosis. 5. Limitation Despite the capacity of our high-resolution atlas to offer profound insights into the pathogenesis of endometriosis, its utility is somewhat constrained by the limited diversity of endometrial tissue types and cell counts included in our dataset. This limitation impedes our ability to identify a more extensive array of cell subtypes that may be implicated in the disease process. Furthermore, our analysis has exclusively focused on eutopic endometrial samples, necessitating the incorporation of ectopic endometrial data from affected individuals to achieve a more holistic comprehension of the condition. Such an approach could potentially uncover additional pathological mechanisms underlying endometriosis. Additionally, our study has categorized the endometrium into only two phases—proliferative and secretory—potentially overlooking crucial stage-specific nuances that may be vital for a thorough understanding of the disease. Moreover, the specific types of endometriosis present in the study participants remain unknown, introducing the possibility of diverse pathological mechanisms among different endometriotic subtypes. Future investigations should endeavor to expand the sample size, refine the classification criteria for endometriosis, and encompass a broader spectrum of menstrual stages. These enhancements will collectively contribute to a more comprehensive and nuanced understanding of the pathological intricacies associated with endometriosis. Declarations Funding This work was supported by National Natural Science Foundation of China (82472727), National Key Research Programmes (2022YFC2704204), Natural Science Foundation of Shanghai 2023 "Science and Technology Innovation Action Plan" (23ZR1451600) Consent for publication: Not applicable. Author's contributions: CF, ZST, ZSZ, WM and YY analyzed and interpreted the data. HLJ, CL and TAY collected information. 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Matsuzaki, Side population in human uterine myometrium displays phenotypic and functional characteristics of myometrial stem cells, Proceedings of the National Academy of Sciences 104 (2007) 18700–18705. https://doi.org/10.1073/pnas.0704472104. C.E. Gargett, H.P.T. Nguyen, L. Ye, Endometrial regeneration and endometrial stem/progenitor cells, Rev Endocr Metab Disord 13 (2012) 235–251. https://doi.org/10.1007/s11154-012-9221-9. L.K. Symons, J.E. Miller, V.R. Kay, R.M. Marks, K. Liblik, M. Koti, C. Tayade, The Immunopathophysiology of Endometriosis, Trends in Molecular Medicine 24 (2018) 748–762. https://doi.org/10.1016/j.molmed.2018.07.004. J.A. Sampson, Peritoneal endometriosis due to the menstrual dissemination of endometrial tissue into the peritoneal cavity, Am. J. Obstet. Gynecol. 14 (1927) 422–469. https://doi.org/10.1016/S0002-9378(15)30003-X. Y. Li, R. Liu, J. Wu, X. Li, Self-eating: Friend or foe? The emerging role of autophagy in fibrotic diseases, Theranostics 10 (2020) 7993–8017. https://doi.org/10.7150/thno.47826. Y. Xiong, Y. Liu, W. Xiong, L. Zhang, H. Liu, Y. Du, N. Li, Hypoxia-inducible factor 1α-induced epithelial–mesenchymal transition of endometrial epithelial cells may contribute to the development of endometriosis, Human Reproduction 31 (2016) 1327–1338. https://doi.org/10.1093/humrep/dew081. D. Wang, Y. Luo, G. Wang, Q. Yang, CircATRNL1 promotes epithelial–mesenchymal transition in endometriosis by upregulating Yes-associated protein 1 in vitro, Cell Death Dis 11 (2020) 1–13. https://doi.org/10.1038/s41419-020-02784-4. P.W. Finch, X. He, M.J. Kelley, A. Üren, R.P. Schaudies, N.C. Popescu, S. Rudikoff, S.A. Aaronson, H.E. Varmus, J.S. Rubin, Purification and molecular cloning of a secreted, frizzled-related antagonist of wnt action, Proceedings of the National Academy of Sciences 94 (1997) 6770–6775. https://doi.org/10.1073/pnas.94.13.6770. K. Steinestel, S. Eder, A.J. Schrader, J. Steinestel, Clinical significance of epithelial-mesenchymal transition, Clinical and Translational Medicine 3 (2014) 17. https://doi.org/10.1186/2001-1326-3-17. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFigures.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5954285","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":416655601,"identity":"6a1bb7bf-ace3-4fb2-8008-fa1beb71cc67","order_by":0,"name":"Feng Chen","email":"","orcid":"","institution":"Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Chen","suffix":""},{"id":416655602,"identity":"f33736c1-d004-4b07-a8a0-931f2eca7924","order_by":1,"name":"Shi Tong","email":"","orcid":"","institution":"Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Shi","middleName":"","lastName":"Tong","suffix":""},{"id":416655603,"identity":"9b9db917-ed4e-420d-bc47-658c56f65b85","order_by":2,"name":"Li Juan Huang","email":"","orcid":"","institution":"Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"Juan","lastName":"Huang","suffix":""},{"id":416655604,"identity":"164292ae-ee5c-4ff9-9cb6-9d5c3d718378","order_by":3,"name":"Lin Chen","email":"","orcid":"","institution":"Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Chen","suffix":""},{"id":416655605,"identity":"4d044b48-7e91-4974-849c-2cb64641512d","order_by":4,"name":"An Yi Teng","email":"","orcid":"","institution":"Department of Obstetrics and Gynecology, Shanghai Songjiang District Maternal and Child Health Care Hospital","correspondingAuthor":false,"prefix":"","firstName":"An","middleName":"Yi","lastName":"Teng","suffix":""},{"id":416655606,"identity":"76d1559b-803d-43c5-bac4-94ea7442b94a","order_by":5,"name":"Shu Zhi Zhao","email":"","orcid":"","institution":"Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Shu","middleName":"Zhi","lastName":"Zhao","suffix":""},{"id":416655607,"identity":"f000bc8b-c115-4bfa-833c-4ff7f7574770","order_by":6,"name":"Min Wang","email":"","orcid":"","institution":"Department of General Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Wang","suffix":""},{"id":416655608,"identity":"5e5caf2f-a031-4dcb-a3db-c678ce32c388","order_by":7,"name":"Ye Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIie3LsQqCUBTG8SPBbcnmI1H2CEZjL3NdctG5xUQoblO70NArODYawnVxjhsIObkFrg1B9QQdt6D7n77h+wHodD/cBBBYNzLvTtyYTJwiZvg4rb3jYXepIawIpMyYtS+LIK3KlQOyIRDFGZpCBin6SzTinEBuNbOeQnp2QiYK2MgUIQflSRqxSnezGItsliqfIZcEMizy8/UuIttOvAbbkECmmbFFgM9z4AD/DgDsGHotQPSe/ZoCdDqd7g97AY6gPmrbRyHPAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Ye","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2025-02-04 01:53:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5954285/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5954285/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78224741,"identity":"d0807ef3-46f3-4de3-a686-0ccd9d65ecb0","added_by":"auto","created_at":"2025-03-11 06:52:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":321292,"visible":true,"origin":"","legend":"\u003cp\u003eSingle-Cell RNA-seq Analysis Pipeline and Cellular Type Distribution. \u003cstrong\u003eA.\u003c/strong\u003e Schematic representation of the research workflow; \u003cstrong\u003eB.\u003c/strong\u003eUMAP projection of scRNA-seq data from 13 individuals and 86,381 cells, classified by cellular state. \u003cstrong\u003eC.\u003c/strong\u003e Bar chart showing the cellular composition of 13 endometrial biopsy tissues from the normal group (n=7) and the endometriosis group (n=6) in scRNA-seq data; \u003cstrong\u003eD. \u003c/strong\u003eBar chart showing the cellular composition of 13 endometrial biopsy tissues from the proliferative phase (n=7) and the secretory phase (n=6) in scRNA-seq data. \u003cstrong\u003eE.\u003c/strong\u003eHeatmap displaying the normalized, log-transformed, and variance-scaled expression of genes (x-axis) across all cell types (y-axis) in scRNA-seq data.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5954285/v1/d9d6c0896c7b6e9fab3bc750.png"},{"id":78224155,"identity":"5790fb5e-32d2-45c1-9440-71396c0091fe","added_by":"auto","created_at":"2025-03-11 06:44:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":218517,"visible":true,"origin":"","legend":"\u003cp\u003eImmune Gene Expression and Cellular Type Analysis in Endometriosis.\u003cstrong\u003e A.\u003c/strong\u003e Violin plot showing the expression levels of immune genes among various subpopulations of epithelial cells in the endometriosis group. \u003cstrong\u003eB. \u003c/strong\u003eThe scRNA - seq data of cells in the endometriosis group are projected onto a UMAP based on cell states. \u003cstrong\u003eC.\u003c/strong\u003e Bar chart showing the composition of cells in the secretory and proliferative phases in the scRNA - seq data of the endometriosis group across Glandular_secretory, Glandular_proliferative, Epi_immuno, and Ciliated cell types. \u003cstrong\u003eD.\u003c/strong\u003e Bar chart showing the composition of cells in the secretory and proliferative phases in the cRNA - seq data of the normal group within Glandular_secretory, Glandular_proliferative, Epi_immuno, and Ciliated cell types. \u003cstrong\u003eE.\u003c/strong\u003e Volcano plot showing the up - and down - regulation of gene expression of Glandular_secretory in the endometrium of endometriosis and the normal endometrium. \u003cstrong\u003eF.\u003c/strong\u003e Volcano plot showing the up - and down - regulation of gene expression of Glandular_proliferative in the endometrium of endometriosis and the normal endometrium. \u003cstrong\u003eG. \u003c/strong\u003eVolcano plot showing the up - and down - regulation of gene expression of Epi_immuno in the endometrium of endometriosis and the normal endometrium.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5954285/v1/15320f25339a4d49309fe935.png"},{"id":78224158,"identity":"ff3a5fdd-41f7-45d9-ad1a-1fa9cd58eaec","added_by":"auto","created_at":"2025-03-11 06:44:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":176606,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of Ciliated Cell Characteristics in Endometriosis and Normal Tissues. \u003cstrong\u003eA.\u003c/strong\u003eScatter plot showing the difference in the proportion of ciliated cells between the proliferative and secretory phases in endometriosis groups (t-test). \u003cstrong\u003eB. \u003c/strong\u003eScatter plot showing the difference in the proportion of ciliated cells between the proliferative and secretory phases in normal groups (t-test). \u003cstrong\u003eC. \u003c/strong\u003eViolin plot showing the top 10 differentially expressed genes (DEGs) in ciliated cells between endometriosis and normal groups. \u003cstrong\u003eD. \u003c/strong\u003eVolcano plot showing the upregulation and downregulation of gene expression in ciliated cells between the proliferative and secretory phases in endometriosis groups. \u003cstrong\u003eE.\u003c/strong\u003eViolin plot showing the differential gene expression levels in the secretory and proliferative phases between normal and endometriosis groups.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5954285/v1/6e55f4ad3d946b6a8ea06453.png"},{"id":78224156,"identity":"53cfb30d-db8b-4874-81f4-259e5ebc6970","added_by":"auto","created_at":"2025-03-11 06:44:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":242114,"visible":true,"origin":"","legend":"\u003cp\u003eSingle-Cell Analysis of Endometriosis Reveals Pseudotime Trajectories and Differential Gene Expression. \u003cstrong\u003eA.\u003c/strong\u003e The pseudotime analysis plot displays the differentiation time. \u003cstrong\u003eB.\u003c/strong\u003e Pseudotime analysis plot showing the differentiation trajectories of various subtypes of endometriosis epithelial cells. \u003cstrong\u003eC.\u003c/strong\u003e Pseudotime analysis plot showing the cell trajectories classified by proliferative phase cells and secretory phase cells. \u003cstrong\u003eD.\u003c/strong\u003e Bar chart showing the results of GO enrichment analysis for differentially expressed genes of Epi_immuno and Glandular_secretory. \u003cstrong\u003eE. \u003c/strong\u003eEnrichment cluster circle plot showing the results of GO enrichment analysis for biological processes of differentially expressed genes of Epi_immuno and Glandular_secretory. \u003cstrong\u003eF. \u003c/strong\u003eCorrelation network diagram displays the KEGG analysis results of differentially enriched genes of Epi_immuno and Glandular_secretory in relation to their respective functional sets/pathway sets.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5954285/v1/6c22a191a4407be925727dfe.png"},{"id":78224744,"identity":"08f015ed-4a16-45b3-9a9a-8242a209861a","added_by":"auto","created_at":"2025-03-11 06:52:19","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":204738,"visible":true,"origin":"","legend":"\u003cp\u003eComprehensive Analysis of Ciliated Cells GO and KEGG Pathway Enrichment, and Gene Expression Profiles. \u003cstrong\u003eA.\u003c/strong\u003e Chord diagram illustrates the cellular localization outcomes of GO enrichment analysis for differentially expressed genes between Ciliated and Glandular_proliferative samples. \u003cstrong\u003eB.\u003c/strong\u003e Bubble chart presents the results of GO enrichment analysis for differentially expressed genes in Ciliated and Glandular_proliferative samples. \u003cstrong\u003eC.\u003c/strong\u003eEnrichment cluster circle graph displays the biological process results of GO enrichment analysis for differentially expressed genes between Ciliated and Glandular_proliferative samples. \u003cstrong\u003eD. \u003c/strong\u003eBar chart exhibits the KEGG analysis outcomes of differentially enriched genes between Epi_immuno and Glandular_secretory samples.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5954285/v1/6e684f5f276c133f5be01107.png"},{"id":78224743,"identity":"421dac2e-7fc2-4d7d-b437-0be841ea52a6","added_by":"auto","created_at":"2025-03-11 06:52:19","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":376416,"visible":true,"origin":"","legend":"\u003cp\u003eSingle-Cell RNA- Seq Analysis of Endometriosis Fibroblasts Reveals Heterogeneity and Functional Pathways. \u003cstrong\u003eA.\u003c/strong\u003e Perform UMAP projection on the scRNA-seq data of each subtype of endometriosis - related fibroblasts based on cell states. \u003cstrong\u003eB. \u003c/strong\u003eBar charts of the composition of secretory and proliferative phase cells in the endometriosis group's scRNA-seq data among Fib_PLA2G2A, Fib_PBK, Fib_HTR1F, and Fib_CADPS cell types. \u003cstrong\u003eC.\u003c/strong\u003e Heatmap showing the contributions of enriched genes of all endometriosis - related cell types in the GSEA pathway. \u003cstrong\u003eD. \u003c/strong\u003ePseudotime analysis plot displays the differentiation time and the differentiation trajectories of each subtype of fibroblasts. \u003cstrong\u003eE.\u003c/strong\u003e Pseudotime analysis plot and the network waterfall plot show the differentiation trajectories of each subtype of fibroblasts. \u003cstrong\u003eF. \u003c/strong\u003ePseudotime analysis plot shows the differentiation trajectories of each subtype of fibroblasts obtained by faceting according to cell types.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5954285/v1/3c2389a40ce0ac7be27e735a.png"},{"id":78224742,"identity":"7402e30c-ef1f-45f8-bbbc-32ea380e67c4","added_by":"auto","created_at":"2025-03-11 06:52:19","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":270897,"visible":true,"origin":"","legend":"\u003cp\u003eComprehensive Single-Cell RNA- Seq Analysis of Fibroblast Heterogeneity in Endometriosis. \u003cstrong\u003eA. \u003c/strong\u003eViolin plot demonstrates the expression of the top 10 differentially expressed genes in fibroblasts between the normal group and the endometriosis group. \u003cstrong\u003eB. \u003c/strong\u003eViolin plot exhibits the expression of the top 10 differentially expressed genes across various subtypes of fibroblasts. \u003cstrong\u003eC. \u003c/strong\u003eViolin plot illustrates the expression of the top 10 differentially expressed genes in endometriosis - derived fibroblasts during the proliferative and secretory phases. \u003cstrong\u003eD.\u003c/strong\u003eDensity plot displays the contributions of each cell subtype in the endometriosis group to the EMT pathway (Ucell score). \u003cstrong\u003eE. \u003c/strong\u003eMountain plot presents the contributions of each cell subtype in the endometriosis group to the EMT pathway (Ucell score). \u003cstrong\u003eF.\u003c/strong\u003e Semi - violin plot shows the contributions of each cell subtype in the endometriosis group to the angiogenesis pathway (Ucell score). \u003cstrong\u003eG. \u003c/strong\u003ePseudotime analysis scatter plot reveals the expression trajectories of CDH1, CDH2, SNAI1, and VIM across different subtypes of epithelial cells. \u003cstrong\u003eH.\u003c/strong\u003e Pseudotime analysis scatter plot displays the expression trajectories of CDH1, CDH2, SNAI1, and VIM among various subtypes of fibroblasts.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-5954285/v1/097065a345bcc4a44d9d503d.png"},{"id":78224163,"identity":"d6eef8e0-4581-458f-9f1e-832064655d76","added_by":"auto","created_at":"2025-03-11 06:44:19","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":211363,"visible":true,"origin":"","legend":"\u003cp\u003eCell Communication and Signaling Pathway Analysis in Endometriosis. \u003cstrong\u003eA. \u003c/strong\u003eRiver plot illustrates the relationships between the effector signals of various cell types in endometriosis and the ncWNT, VEGF, TGF - β, NOTCH, and WNT pathways. \u003cstrong\u003eB. \u003c/strong\u003eRiver plot demonstrates the relationships between the afferent signals of different cell types in endometriosis and the ncWNT, VEGF, TGF - β, NOTCH, and WNT pathways. \u003cstrong\u003eC. \u003c/strong\u003eHeatmap shows the correlations between the effector and afferent signals of each cell type and the ncWNT, VEGF, TGF - β, NOTCH, and WNT pathways. \u003cstrong\u003eD. \u003c/strong\u003eBubble plot displays the ligand - receptor interactions between immune cells and non - immune cells. \u003cstrong\u003eE.\u003c/strong\u003e Chord diagram presents the regulatory intensity of immune cells on non - immune cells in the WNT pathway. \u003cstrong\u003eF.\u003c/strong\u003e Chord diagram exhibits the regulatory intensity of immune cells on non - immune cells in the NOTCH pathway. \u003cstrong\u003eG.\u003c/strong\u003e Chord diagram reveals the regulatory intensity of immune cells on non - immune cells in the VEGF pathway. \u003cstrong\u003eH. \u003c/strong\u003eChord diagram showcases the regulatory intensity of immune cells on non - immune cells in the TGF - β pathway.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-5954285/v1/9bef3c048e25c336084fee0f.png"},{"id":78224161,"identity":"84fc3fb5-6c10-4d16-8e42-8356f8ce3f41","added_by":"auto","created_at":"2025-03-11 06:44:19","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":139349,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of Signaling Pathway Networks and Cell Communication in Endometriosis. \u003cstrong\u003eA. \u003c/strong\u003eHeatmap illustrates the roles of various cell types in the NOTCH pathway. \u003cstrong\u003eB. \u003c/strong\u003eViolin plot demonstrates the expression levels of NOTCH pathway - related genes across different cell types. \u003cstrong\u003eC. \u003c/strong\u003eBubble chart displays the ligand - receptor pairs involved in the interactions between endothelial cells and fibroblasts. \u003cstrong\u003eD. \u003c/strong\u003eHeatmap shows the roles of different cell types in the TGF - β pathway. \u003cstrong\u003eE. \u003c/strong\u003eHeatmap indicates the communication intensities among different cell types within the TGF - β pathway. \u003cstrong\u003eF. \u003c/strong\u003eBar chart represents the contribution strengths of each ligand - receptor pair in the TGF - β pathway.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-5954285/v1/df49a682d6cd2129afc46638.png"},{"id":78226444,"identity":"9430e302-93c8-4867-b92c-f7e43c6fa8a3","added_by":"auto","created_at":"2025-03-11 07:00:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2507408,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5954285/v1/3e5ecba7-1a3f-4112-8254-ca2a68aa84ac.pdf"},{"id":78224159,"identity":"b4346923-5abd-4c80-b07c-0e9f1554061e","added_by":"auto","created_at":"2025-03-11 06:44:19","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1320497,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-5954285/v1/fd881c27d94717ce97a1b98f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Single-cell analysis of endometrial proliferation and secretory phases in patients with endometriosis and normal population","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eEndometriosis (EMs) is a complex syndrome characterized by an estrogen-dependent chronic inflammatory process and the growth of functional endometrial tissue outside the uterus[1]. It primarily affects the pelvic region, including the ovaries, peritoneum, ligaments, intestines, and bladder[2]. Approximately 10% of women of reproductive age worldwide (equivalent to 190 million women) are affected by endometriosis, with symptoms including chronic pelvic pain, dysmenorrhea, pain, and infertility[3]. Endometriosis is strongly linked to persistent episodes of ovulation, menstruation, and cycling steroid hormones and the key biologic driver of inflammation is the dependence on estrogen[1,4,5]. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe endometrium is the mucous layer of the endometrium, which undergoes dynamic changes during the menstrual cycle driven by the signaling of estrogen and progesterone. Histomorphology divides the menstrual cycle into the menstrual phase, proliferative phase, and secretory phase. Previous studies have shown that there are significant molecular abnormalities in the eutopic endometrium[6–8]. There are several theories to account for the origin of endometriosis and to explain how tissue can be scattered throughout the abdominal cavity. Among the most-examined and most popular theories are retrograde menstruation. However, there is still a lack of detailed understanding regarding which endometrial cell populations and which specific changes are associated with the formation of endometriotic lesions.\u003c/p\u003e\n\u003cp\u003eAlthough the array of treatments including gonadotropin-releasing hormone (GnRH) antagonists or agonists, aromatase inhibitors, selective estrogen receptor (ER) and progesterone receptor (PR) modulators, and anti-inflammatory medications continues to expand, some patients experience unnecessary side effects, including headaches, weight gain, and irregular bleeding and develop resistance to these medical interventions, leading to recurrences[9]. Consequently, they often require repeated laparoscopic-assisted surgical procedures, which can diminish their quality of life. Recently, a study based on the analysis of single cells reported that there are varying degrees of dysregulation in the endometrial epithelium, stroma, and immunity of women with endometriosis[10,11]. Despite decades of dedicated research, our comprehension of the pathogenesis and etiology of endometriosis remains limited. Therefore, uncovering the deeper pathophysiological mechanisms of endometriosis is crucial for developing more effective treatments.\u003c/p\u003e\n\u003cp\u003eOur research delved into the important role of epithelial cells and immune cells in the pathogenesis of endometriosis by strictly controlling for stage and individual differences, through analyzing the normal and endometriosis endometrium by the Single-cell RNA sequence data [12]. Our research emphasizes the dysregulation of the subtype of epithelial cells within the patient's body, as well as the regulatory role of immune cells. These findings have deepened our understanding of the etiology and pathological characteristics of endometriosis.\u0026nbsp;\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Data Source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the GEO database, searching for \u0026quot;endometriosis\u0026quot; and \u0026quot;Single-cell sequencing\u0026quot; as keywords yielded the dataset GSE214411, which is Single-cell RNA sequence of 138, 057 endometrial cells from 6 endometriosis patients (3 samples from proliferative phase and 3 samples from secretory phase) and 7 control (3 samples from proliferative phase and 4 samples from secretory phase).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Data Quality Control\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUse RStudio Server to read and process genomic and transcriptomic data. With the original data nFeature_RNA \u0026gt; 300 \u0026amp; nFeature_RNA \u0026lt; 7000, mitochondrial proportion \u0026lt; 10%, UMI count content per cell sequenced \u0026gt; 1000, and excluding the largest top 3% of cells, the expression amount of erythrocyte genes per cell accounts for \u0026lt; 3% of the total genes as the cell screening criteria, carry out \u0026quot;Log-Normalization\u0026quot; standardization treatment, and remove batch effects through the Harmony package.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Endometrial Single-Cell Type and Epithelial Cell Subtype Clustering Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter reducing the dimensionality of the data using Principal Component Analysis (PCA) and T-Distributed Stochastic Neighbor Embedding (t-SNE) algorithms, the FindVariableFeatures function is used to identify differentially expressed genes (DEGs). The FindClusters function is then used for clustering analysis and visualization, displaying different cell clusters in the endometrium. Using only.pos = TRUE and |avg_log2FC| \u0026ge; 0.25 as data parameters, the Wilcoxon rank sum test is performed, and DEGs are screened through the FindMarkers function. The top 50 DEGs of different single-cell types are selected as reference genes, and endometrial cell types are determined based on the singleR package. The Human Protein Atlas, ACT database, and related literature. Different epithelial cell subtypes are annotated based on marker genes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Differential Expression Genes and Functional Analysis of Epithelial Cell Subtypes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing the R package clusterProfiler with parameters set to only.pos = TRUE and |avg_log2FC| \u0026ge; 0.25, DEGs are screened in different epithelial cell subtypes and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Epithelial Cell Subtype Communication Patterns and Pseudotime Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the CellChat package and by cross-referencing the ligand-receptor interaction database, analyze the communication network, quantity, and intensity among epithelial cell subtypes to explore the dynamic changes in disease progression. Use the Monocle3 package to reconstruct the differentiation trajectory of endometrial epithelial cells in patients with endometriosis, perform pseudotime analysis to determine the temporal patterns of epithelial cell changes over time, and identify the expression levels of DEGs during different stages of epithelial cell differentiation.\u003c/p\u003e"},{"header":"3. Result","content":"\u003cp\u003e\u003cstrong\u003e3.1 Atlas of the Endometrium in women without and with endometriosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo comprehensively elucidate the composition of endometriotic lesions, we retrieved EMs datasets from the Gene Expression Omnibus (GEO) database and selected GSE214411, which encompasses single-cell RNA sequencing data from 138,057 endometrial cells derived from six proliferative phase samples and seven secretory phase samples[12]. Within this dataset, we focused on samples from six women with endometriosis and seven healthy controls. After rigorous quality control and filtering procedures, a total of 86,381 cells were retained for subsequent analysis (Figure 1A, Figure S1A, S1B). Initially, we employed the SingleR package to automatically annotate the quality-controlled Seurat matrix, enabling a preliminary classification of cell types. To validate these annotation results, we adopted a two-pronged approach: (1) We selected the top 50 differentially expressed genes (DEGs) as marker genes and performed cell annotation using ACT and CellMarker2.0. (2) We utilized the ACT and CellMarker2.0 databases to obtain marker genes for various endometrial epithelial cell types, and examined the expression of these marker genes across different clusters using the \"DimPlot\" and \"VlnPlot\" functions (Figure 1A).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur analysis has generated a comprehensive and high-resolution atlas of the eutopic endometrium in both healthy controls and patients with endometriosis. Ultimately, the sample cells were categorized into two major groups: immune and non-immune cells, and most cell types have been re-annotated for cell subtypes (Figure 1B). Apart from granulocytes (only identified in the endometriosis group), other cell types were accurately identified within four tissue types: the endometrium of healthy women, the endometrium of women with EMs (Figures 1C, Figure S1C-D), and these were further subclassified into two menstrual cycle phases, namely the proliferative and secretory phases (Figure 1D). These encompassed seven primary cell types with differentially expressed genes (DEGs), including fibroblasts (HOXA11, SFRP4, MMP11), epithelial cells (EPCAM, SLPI, AGR2), endothelial cells (CLDN5, TM4SF18, ROBO4), NK cells (GNLY, KLRC1, KRT18), T cells (CD2, CD3G, TPSB2), granulocytes (TPSAB1, MS4A2), and monocytes (CD14, MPEG1, CYBB), (Figure 1E, Figure S1E). Subsequently, cells were annotated in details (Figure S1F).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Characterization of Epithelial Cell Subtypes in Endometriosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe etiology of endometriosis is multifaceted, encompassing sex hormones, immunity, inflammation, genetics, and additional factors, yet its pathogenic mechanisms remain elusive[13]. Consequently, we embarked on an assessment of the cellular heterogeneity within the endometrial epithelial cells of endometriosis (EM). Following strict quality control measures and utilizing high-resolution single-cell reference atlases, including the Human Endometrial Cell Atlas (HECA) and the Human Protein Atlas, with the reference marker genes provided, we annotated glandular proliferative cells, glandular secretory cells and ciliated cells, named as Glandular_proliferative, Glandular_secretory and Ciliated respectively[10,14]. In addition to the aforementioned three cell subtypes, our study identified a distinctive epithelial cell subpopulation that displayed a unique phenotypic profile. This subpopulation exhibited concurrently elevated expression levels of glandular cell markers, alongside similarly high levels of immune cell markers, specifically GNLY, CCL4, and AREG (Figure 2A). Consequently, we have designated this subpopulation as \"Epi_immuno\" to highlight its differential characteristics (Figure 2B). The execution of a comprehensive Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) on the repertoire of expressed genes serves as robust validation for the precision and reliability of our cellular annotation (Figure S2).\u003c/p\u003e\n\u003cp\u003eWe conducted a comparative analysis of the proportions of each subtype of endometriosis with those of normal endometrial epithelial cells. The results revealed significant disparities in the proportions of glandular cells (Glandular_secretory, Glandular_proliferative and Epi_immuno) (Figure 2C-D). We conducted a detailed analysis of each type of gland cell to investigate preexisting alterations contributing to the disease. Glandular_secretory in the endometriosis eutopic endometrium significantly upregulated genes involved in stress response and inflammatory response, such as HSPA6, HSPB8, HSPA1A, NFKB1, and CXCL8(Figure 2E). Consistently, normal endometrial epithelium downregulates the antioxidant stress gene SLC1A1, the neutrophil chemotaxis function gene CXCL14, as well as the genes promoting cell adhesion IGFBP7, IGFBP4, and AGR2(Figure 2E). Glandular_proliferative and Epi_immuno significantly upregulated genes with immune function, such as GNLY, NKG (Figure 2F-G).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIt was observed that there was no statistically significant difference in the quantity of ciliated cells between the endometriosis group and the normal group during both the proliferative and secretory phases (Figure 3A-B). To investigate potential disparities at the genetic level, a differential analysis was performed on these cells. Upon identifying that significant differences in gene expression of ciliated cells were evident between the normal and endometriosis groups (Figure 3C). It is discernible that endometriotic ciliated cells manifest transcriptional activity of genes implicated in immune response and neoplastic progression, such as NAMPT, NFKBIZ, TNFAIP3, CXCL8, and PLAUR. Our research elucidates that the ciliated cells in the proliferative phase display marked upregulation of the histone-encoding gene HIST1H1C and the cell cycle regulatory gene CCNA1 (Figure 3D-E, Figure S3). In contrast, ciliated cells during the secretory phase exhibit enhanced expression of genes pertinent to steroid hormone biosynthesis, encompassing the sex hormone synthetic genes SCGB1D2 and SULT1E1, alongside genes involved in lipid anabolism and catabolism, specifically ACSL5, STEAP4, and PTGDS (Figure 3D-E, Figure S3). We are inclined to hypothesize that ciliated cells play a pivotal role in mediating the progression of endometriosis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Abnormal Epithelial Subpopulation with\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAutophagy\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eObserved in Patients with EMs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; In an effort to meticulously delineate the complex interrelationships and phenotypic disparities inherent among multiple epithelial cell subpopulations, we performed a pseudotime analysis. Upon constructing the epithelial cell differentiation trajectory, our observations revealed that the Epi_immuno and Glandular_secretory are situated on the identical branch of the pseudotime analytical trajectory (Figure 4A-B). The finding implies that Epi_immuno plays a pivotal role in modulating the immune response within the endometrial microenvironment through the secretion of immune regulatory factors, thereby potentially contributing to the pathogenesis and progression of endometriosis. Furthermore, it is evident that Glandular_proliferative and Ciliated exhibit a shared differentiation inception, albeit with disparate cellular destinies (Figure 4A-B). Subsequently, by analyzing the trajectory plot, we successfully identified the cells in both the secretory and proliferative phases. Notably, our observations revealed that the ciliated cells within the endometrium seemingly maintain a dynamic equilibrium, which exhibits considerable variations across distinct menstrual cycles (Figure 4B-C).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo investigate the disparities between the Epi_immuno and Glandular_secretory, we performed GO and KEGG enrichment analysis on DEGs between glandular secretory cells and Epi_immuno cells. GO analysis reveals that the enriched genes are intimately associated with biological activities pertaining to RNA synthesis metabolism and stress response, including ncRNA processing, tRNA metabolic processes, response to oxidative stress and macroautophagy (Figure 4D-E). The results obtained from the KEGG analysis indicate that the majority of enriched pathways are associated with autophagy, including mitophagy and macroautophagy (Figure 4F？G\u0026nbsp;没有G). Our findings indicated that the enriched DEGs exhibit a strong correlation with pathways involved in cellular secretion and immunology activities.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs previously mentioned, it is postulated that Ciliated sustains a dynamic equilibrium at the cellular level, with the ciliated cells within endometriotic lesions exhibiting significant expression of genes associated with immunity and tumor progression. Furthermore, Cellular Component (CC) of GO analysis reveals that the primary regions of gene expression are predominantly confined to the centrioles and cilium basal bodies (Figure 5A). The results of GO analysis, particularly in terms of biological processes (BP) and molecular functions (MF), and KEGG analysis, further demonstrated that ciliated cells are predominantly implicated in the biological activities associated with cilia function as well as microtubule assembly and motility (Figure 5B-D).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4\u003c/strong\u003e \u003cstrong\u003eFibroblasts and Immune cells: Profound Contributors to EMT-Associated Pathways\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn in-depth investigation into the subpopulations and cell proportions of fibroblasts was carried out (Figure 6A-B). Upon conducting Gene Set Enrichment Analysis (GSEA) on endometriosis samples, we identified fibroblasts, notably the Fib_CADPS, as key players in endometriosis-related pathways, including EMT and angiogenesis[15] (Figure 6C). To delve deeper into the specific functional role of Fib, we embarked on a comprehensive and meticulous analysis. The spatial and temporal attributes exhibited by distinct subtypes of fibroblasts exhibit a significant degree of overlap (Figure 6D-F).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, we have conducted a comprehensive analysis of the differential gene expression profiles within the fibroblast group, adopting multiple perspectives to ensure a robust and nuanced understanding of the underlying molecular mechanisms (Figure 7A-C). The expression of the ancestral gene SFRP1, known for its regulatory role in cell growth, development, and transformation within endometriotic fibroblasts, exhibits significant downregulation (Figure 7A). From the perspective of differentially expressed genes, Fib_CADPS and Fib_PBK appear to exhibit similar characteristics (Figure 7B).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn light of the aforementioned findings, we are poised to investigate the modulatory effects of endometriotic fibroblasts on EMT. We conducted a Gene Set Enrichment Analysis (GSEA) across all cellular subtypes present within the endometrium, followed by a \"UCell\" scoring assessment. Our findings revealed that fibroblasts exhibit significantly higher activity in this particular pathway compared to other cell types (Figure 7D-E, Figure S4A). Within the angiogenic pathway, fibroblasts exhibit a pivotal function (Figure 7F). Genes associated with the EMT exhibit a substantial enrichment score within immune cell populations (Figure 7E). This observation implies that the pathogenesis of endometriosis is likely influenced not solely by alterations within fibroblasts themselves, but also by the regulatory actions of immune cells.\u003c/p\u003e\n\u003cp\u003eIn an effort to delineate the precise epithelial cell populations and fibroblasts engaged in the EMT pathway, we meticulously examined the transcriptional dynamics of established EMT biomarkers within these cellular constituents (Figure 7G-H). KRT8 represents one of the most classical EMT marker genes. The reduced expression of CDH1, along with the overexpression of CDH2 and VIM, can induce EMT. SNAI1 acts as a regulatory factor in this process, binding to the enhancer of CDH1 and the promoter of KRT8. Epithelial cells, encompassing proliferating glandular and ciliated cell populations, exhibit a propensity to undergo mesenchymal transition, differentiating into fibroblasts (Figure 7G).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.\u003c/strong\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Cell Communication Networks of Fibroblasts, Epithelial, and Immune Cells Contribute to EMT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEMT represents a reversible phenomenon wherein epithelial cells experience a loss of polarity and cell-cell adhesion, undergo a transformation to a mesenchymal morphology, and subsequently acquire migratory and invasive capabilities[16]. Pathways such as WNT, TGFβ, VEGF, and NOTCH , as well as their regulators, are all implicated in EMT[17–19]. Therefore, we analyzed how epithelial cells and fibroblasts, immune cells collaborate in these pathways. Initially, we delineated the pathways implicated in each distinct cell type (Figure 8A-B). Our findings indicate that almost cell types within the endometrium of endometriosis are involved in signaling pathways, which can be categorized into three distinct patterns: Pattern 1 primarily involves cell groups such as Th17, CTL, and FOXP3+ Treg, which are associated with non-canonical WNT (ncWNT) and VEGF signaling pathways. Pattern 2 mainly encompasses cell groups like Fib_PLA2G2A and Fib_PBK, linked to TGFb and NOTCH signaling pathways. Lastly, Pattern 3 involves cell groups including Glandular_secretory and Ciliated cells, which are related to the WNT signaling pathway (Figure 8A).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur primary focus will be on Pattern 1. Fibroblasts, specifically the Fib_CAPDS subtype, orchestrate the VEGF and WNT signaling cascades via the secretion of diverse VEGF and WNT ligands that dock onto cognate receptors expressed on immune effector cells, predominantly monocytes and granulocytes (Figure 8D-H). Fib_CADPS engages with monocytes and granulocytes through PGF-VEGFR1 and WNT3A-(FZD+LRG5) pathways, thereby participating in the VEGF and WNT signaling cascades (Figure 8D). The recipient cells of the aforementioned transmitted signals are exclusively confined to endothelial cell subsets classified under pattern 3, along with epithelial cells with the exception of the Epi_immuno subtype (Figure 8B).\u003c/p\u003e\n\u003cp\u003eFib_HTR1F, Endo_VWF, and Endo_SEMA3G are implicated in the transmission of NOTCH signals, specifically NOTCH1 and NOTCH3, NOTCH1 and NOTCH4, and NOTCH1 and NOTCH4, respectively, thereby regulating diverse subpopulations of fibroblasts, endothelial cells, and epithelial cells. Notably, Fib_HTR1F functions concurrently as a signal sender, receiver, and mediator (Figure 9A-B). The exchange of information among these cells is facilitated through the reciprocal recognition of ligand-receptor complexes, including but not limited to JAG1-NOTCH1, JAG1-NOTCH2, and JAG1-NOTCH3 interactions (Figure 9C, Figure S4B). In the context of the WNT, ncWNT, and VEGF signaling pathways, fibroblasts function as key signal-emitting cells, orchestrating the activities of other cellular constituents within the intima (Figure S4D-H). Furthermore, within the TGF-β signaling pathway, adaptive NK cells emerge as pivotal signal mediators. This finding further substantiates the existence of a complex interplay and tight coupling between immune and non-immune cells within the intimal layer (Figure 9D-E).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eInflammatory, chemical, immunologic, epigenetic, and genetic changes have been discovered in eutopic endometria of patients with endometriosis compared to healthy women. Existing research primarily focuses on the individual alterations of non-immune cells and immune cells in the endometrium of patients with endometriosis, or the regulatory effects of immune cells on non-immune cells[20,21]. We have discovered that there is a transformation between epithelial cells and fibroblasts. We carried out single - cell transcriptome analysis on endometrial cells in order to obtain a better understanding of the pathogenesis of this disease and to explore the dynamic changes and immune environment of endometrial cells in the eutopic endometrium of endometriosis.\u003c/p\u003e\n\u003cp\u003eOur single-cell transcriptome analysis included 13 samples from healthy individuals(6 samples) and women with endometriosis (7 samples), and further emphasized the key role of non-immune cells, especially epithelial cells and fibroblasts in the pathophysiology of endometriosis. Our atlas provides significant advantages for the comprehensive study of endometriosis. Compared with previous atlases, this study has generated a higher resolution cell landscape, which helps to identify more accurate cell states[22,23]. By analyzing dataset GSE214411, which successfully acquired normal and eutopic endometrial tissues during congruent phases, our study has effectively mitigated potential confounding factors related to phase-specific variations[12]. Consequently, this approach has enabled us to precisely identify the underlying aberrations inherent to the eutopic endometrium.\u003c/p\u003e\n\u003cp\u003eOur investigative endeavors have elucidated that perturbations in epithelial cell subpopulations may be implicated in the etiopathogenesis of endometriosis. The human endometrium, predominantly consisting of endometrial epithelial and stromal cells, demonstrates exceptional plasticity and is subject to continuous cycles of injury and subsequent regeneration[24,25]. Hence, a perturbation in this equilibrium could precipitate the onset and progression of endometriosis[26]. The \u0026quot;Theory of Decidua in Situ Determination\u0026quot; rooted in Sampson\u0026apos;s retrograde menstruation implantation hypothesis, posits that endometrial tissue refluxed into the pelvic cavity must undergo processes such as adhesion, invasion, and angiogenesis to implant, grow, and form lesions. The characteristics of the endometrium at its original site play a pivotal role in this process [27,4]. In patients with endometriosis, the endometrial epithelial cells progress through a proliferative phase primarily characterized by proliferating glandular cells, transitioning into a secretory phase predominantly governed by glandular secretory cells, which may or may not exhibit immune attributes. Ciliated cells are present throughout the entire endometrial transformation cycle, encompassing the menstrual cycle. The genes expressed by ciliated cells in individuals with endometriosis are associated with immune responses and in the proliferative and secretory phases are also not the same. Current research indicates that ciliated cells might constitute one of the etiological mechanisms underlying endometriosis[11].\u003c/p\u003e\n\u003cp\u003eOur investigation conclusively demonstrated that EMT is indeed present within the eutopic endometrium of individuals afflicted with endometriosis. We have identified that specific subtypes of epithelial cells play a role in the process of macroautophagy. Macroautophagy is considered to play a housekeeping role in maintaining cellular homeostasis and helps to eliminate misfolded proteins, damaged organelles and lipid droplets, enabling cells to function continuously and properly [28].To date, an extensive body of literature has substantiated the association between\u003cs\u003e\u0026nbsp;\u003c/s\u003eEMT and endometriosis[15,29,30]. Nonetheless, the precise mechanisms underlying this correlation, as well as the specific cellular and molecular participants involved, remain the subject of ongoing research and investigation. SFRP1, functioning as an antagonist of the WNT signaling pathway, undergoes downregulation that potentially facilitates EMT within the endometrium[31]. This phenomenon is attributed to the pivotal role of the WNT pathway as one of the key mediators of EMT[32]. Fib_CADPS exhibits elevated expression levels during the proliferative phase of the endometrium and remains consistently expressed throughout the entire differentiation stage, thereby underscoring its potential functional significance that warrants further investigation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn general, the adequate proportion, precise and orderly intercellular communication among the constituent cells (epithelial cells, fibroblasts, immune cells and endothelial cells) is conducive to the dynamic equilibrium and homeostasis of the endometrium. The variations between the eutopic endometrial epithelial cells and fibroblasts facilitate the physiological cyclical alterations of the endometrium, but once anomalies such as EMT arise, they will be correlated with the onset and progression of endometriosis. This process is not solitary, and both immune cells and endothelial cells will be involved in it. Consequently, a thorough and meticulous analysis of the cell subpopulations in the endometrium will aid us in identifying the etiology of the progression of endometriosis and pave the way for novel diagnostic and therapeutic tactics. For instance, selecting targeted factors to aim at abnormal cells or factors so as to modulate the disordered microenvironment of the endometrium, thereby mitigating the incidence of endometriosis.\u003c/p\u003e"},{"header":"5. Limitation","content":"\u003cp\u003eDespite the capacity of our high-resolution atlas to offer profound insights into the pathogenesis of endometriosis, its utility is somewhat constrained by the limited diversity of endometrial tissue types and cell counts included in our dataset. This limitation impedes our ability to identify a more extensive array of cell subtypes that may be implicated in the disease process. Furthermore, our analysis has exclusively focused on eutopic endometrial samples, necessitating the incorporation of ectopic endometrial data from affected individuals to achieve a more holistic comprehension of the condition. Such an approach could potentially uncover additional pathological mechanisms underlying endometriosis. Additionally, our study has categorized the endometrium into only two phases—proliferative and secretory—potentially overlooking crucial stage-specific nuances that may be vital for a thorough understanding of the disease. Moreover, the specific types of endometriosis present in the study participants remain unknown, introducing the possibility of diverse pathological mechanisms among different endometriotic subtypes. Future investigations should endeavor to expand the sample size, refine the classification criteria for endometriosis, and encompass a broader spectrum of menstrual stages. These enhancements will collectively contribute to a more comprehensive and nuanced understanding of the pathological intricacies associated with endometriosis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by National Natural Science Foundation of China (82472727), National Key Research Programmes (2022YFC2704204), Natural Science Foundation of Shanghai 2023 \"Science and Technology Innovation Action Plan\" (23ZR1451600)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor's contributions: \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCF, ZST, ZSZ, WM and YY analyzed and interpreted the data. HLJ, CL and TAY collected information. CF, ZST, ZSZ, WM and YY worked equally as major contributors in writing the manuscript. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eP. Vercellini, P. Vigan\u0026ograve;, E. Somigliana, L. Fedele, Endometriosis: pathogenesis and treatment, Nat Rev Endocrinol 10 (2014) 261\u0026ndash;275. https://doi.org/10.1038/nrendo.2013.255.\u003c/li\u003e\n \u003cli\u003eA.W. Horne, S.A. Missmer, Pathophysiology, diagnosis, and management of endometriosis, BMJ 379 (2022) e070750. https://doi.org/10.1136/bmj-2022-070750.\u003c/li\u003e\n \u003cli\u003eK.T. Zondervan, C.M. Becker, S.A. Missmer, Endometriosis, N Engl J Med 382 (2020) 1244\u0026ndash;1256. https://doi.org/10.1056/NEJMra1810764.\u003c/li\u003e\n \u003cli\u003eS.E. Bulun, Endometriosis, N. Engl. J. Med. 360 (2009) 268\u0026ndash;279. https://doi.org/10.1056/NEJMra0804690.\u003c/li\u003e\n \u003cli\u003eS.J. Han, S.Y. Jung, S.-P. Wu, S.M. Hawkins, M.J. Park, S. Kyo, J. Qin, J.P. Lydon, S.Y. Tsai, M.-J. Tsai, F.J. DeMayo, B.W. 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He, M.J. Kelley, A. \u0026Uuml;ren, R.P. Schaudies, N.C. Popescu, S. Rudikoff, S.A. Aaronson, H.E. Varmus, J.S. Rubin, Purification and molecular cloning of a secreted, frizzled-related antagonist of wnt\u0026thinsp;action, Proceedings of the National Academy of Sciences 94 (1997) 6770\u0026ndash;6775. https://doi.org/10.1073/pnas.94.13.6770.\u003c/li\u003e\n \u003cli\u003eK. Steinestel, S. Eder, A.J. Schrader, J. Steinestel, Clinical significance of epithelial-mesenchymal transition, Clinical and Translational Medicine 3 (2014) 17. https://doi.org/10.1186/2001-1326-3-17.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"single-cell RNA sequence, endometriosis, endometrial epithelial cells, EMT","lastPublishedDoi":"10.21203/rs.3.rs-5954285/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5954285/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The characteristic of endometriosis is that the endometrial tissue grows in non-endometrial parts such as the pelvis and ovaries, leading to infertility and chronic pain. However, its pathophysiology is still unclear. Using high-precision single-cell RNA sequencing, we analyzed the in-situ endometrium of 13 individuals with or without endometriosis, including the proliferative and secretory phases. We have meticulously generated a comprehensive single-cell atlas of the eutopic endometrium from patients with endometriosis. Comparative analysis with the healthy eutopic endometrium has elucidated that the epithelial cells of the ectopic tissue display marked immune-related phenotypes. We have identified the presence of an epithelial-to-mesenchymal transition (EMT) pathway between epithelial cells and fibroblasts within the endometrial tissue of individuals with endometriosis. Furthermore, our research has elucidated the intricate interactive dynamics between immune cells and fibroblasts, epithelial and endothelial cells, potentially shedding light on the underlying pathophysiological mechanisms contributing to endometriosis.","manuscriptTitle":"Single-cell analysis of endometrial proliferation and secretory phases in patients with endometriosis and normal population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-11 06:44:14","doi":"10.21203/rs.3.rs-5954285/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a9c54fb5-c165-420a-8bf3-b5852cbe2a92","owner":[],"postedDate":"March 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":44421555,"name":"Biological sciences/Cell biology"},{"id":44421556,"name":"Health sciences/Diseases"}],"tags":[],"updatedAt":"2025-03-11T06:44:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-11 06:44:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5954285","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5954285","identity":"rs-5954285","version":["v1"]},"buildId":"B-jG_2CBjPDmsCi4Wdhf-","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}