Deep immunophenotyping reveals endometriosis is marked by dysregulation of the mononuclear phagocytic system in endometrium and peripheral blood

A total of 34 fresh endometrial tissues (Control = 14, Endometriosis = 20) and 26 blood samples (Control = 9, Endometriosis = 17) were collected from women with and without endometriosis undergoing surgery (total n = 60). Clinical features of the patients (cycle phase, diagnosis, and stage of disease) are listed in Additional file 1: Table S1. Diagnosis was made by the physician and pathologists at the University of California, San Francisco (UCSF), and stage of disease was determined following the rASRM classification system (stages I and II were determined as mild and III and IV as severe stages) [8]. Women without visualized endometriosis at the time of surgery or without a history of endometriosis were defined as controls. Women with any type of cancer and/or endometrial hyperplasia were also excluded. Some patients exhibited non-malignant gynecologic disorders such as leiomyomas or uterine polyps. Cycle phase was determined by following Noyes et al. system of classification of endometrial histology [9]. Clinical features of the patients were collected only by authorized personnel by using the REDCap Database, after informed written consent. Only patients of reproductive age (18–49 years old) were included in the study. In addition, patients presenting with immune-related comorbidities, such as systemic lupus erythematosus (SLE), endometritis, or other immune disorders, were excluded, as well as those positive for HIV, HVB, and HVC. Moreover, patients were not exposed to hormone therapies for at least 3 months prior to biospecimen collection. Finally, women under any treatment containing iodine were also excluded from the study, as this element interferes with the CyTOF instrument. All samples were obtained between 2019 and 2021 under the auspices of the UCSF Institutional Review Board Procotol #: IRB#10-03964, using the WERF EPHect standardized protocols for tissue collection, and processing, and clinical annotation [10]. All patient data were de-identified and followed HIPAA and the Convention of the Declaration of Helsinki.

First, we designed a CyTOF broad panel to identify the important cell types in endometrial tissue of women with endometriosis compared to controls. This panel consisted of 42 markers and is shown in Additional file 2: Table S2. Then, we designed a 40-parameter CyTOF panel that includes mostly myeloid surface markers as well as functional markers, including efferocytosis and phagocytosis, activation, and inhibition markers (Additional file 2: Table S2). For the broad panel, all 42 antibodies were conjugated in house. For the myeloid panel, sixteen of the 40 antibodies required in-house conjugation to their corresponding metal isotope. Metals were conjugated according to the manufacturer’s instructions (Fluidigm, South San Francisco, CA, USA). Briefly, this process comprises loading the metal to a polymer (incubation of 1 h at RT). The unconjugated antibody is transferred into a 50-kDA Amicon Ultra 500 V-bottom filter (Fisher Scientific, Hampton, NH, USA) and reduced at 37 °C with 1:125 dilution of Tris (2-carboxyethyl) phosphine hydrochloride (TCEP) (Thermo Fisher, Waltham, MA, USA) for 30 min. Then, the column is washed twice with buffer C (Fluidigm, South San Francisco, CA, USA) and the metal-loaded polymer is suspended in 200 μl of C-buffer in the 3-kDA Amicon Ultra 500-ml V-bottom filter (Fisher Scientific, Hampton, NH, USA). The suspension is then transferred to the 50-kDa filter containing the antibody and incubated for 1.5 h at 37 °C. After the incubation time, antibodies are washed three times with W-buffer (Fluidigm, South San Francisco, CA, USA) and quantified for protein content by Nanodrop. Once the concentration was determined, the antibodies were resuspended with Antibody Stabilizer (Boca Scientific, Dedham, MA, USA) at a concentration of 0.2 mg/ml and stored at 4 °C. The rest of the antibodies were commercially available (Fluidigm, South San Francisco, CA, USA). Optimal concentrations of all antibodies were performed by different rounds of titrations.

The staining protocol was optimized to use each antibody in aliquots of 6 million cells as previously described [11]. Samples were thawed and washed with FACS buffer. Then, cells were counted and since some samples had fewer than 6 million cells, they were barcoded before the staining with the antibodies, following the manufacturer’s instructions (Fluidigm, South San Francisco, CA, USA). Briefly, each sample was incubated with 10 μl of each barcode and perm buffer (Fluidigm, South San Francisco, CA, USA) for 30 min at RT, and then samples were combined and split into different tubes for the first day of staining. For the staining, samples were blocked using rat, mouse, and human serum for 15 min on ice. They were then washed and stained with the primary cocktail of antibodies for 45 min at 4 °C. After this incubation time, cells were washed and fixed using 2% paraformaldehyde (PFA) diluted in CyPBS. Cells were incubated overnight at 4 °C and the next day were washed with perm buffer (Fluidigm, South San Francisco, CA, USA), washed with CyPBS, and blocked with rat and mouse serum for 15 min on ice. They were then washed, and the intracellular staining was performed. Cells were resuspended with the intracellular cocktail of antibodies for 45 min on ice and were washed and incubated for 20 min at RT with Ir-intercalator (Biolegend CNS, San Diego, CA, USA), prepared at a dilution of 1:500 in 2% fresh PFA. After the incubation time, cells were washed and kept at 4 °C overnight. Finally, on the third day, cells were washed with cell staining media (CSM, Fluidigm, South San Francisco, CA, USA), then with water, and then with cell acquisition solution (CAS, Fluidigm, South San Francisco, CA, USA) at RT. Subsequently, cells were counted, resuspended in 1× EQ^TM calibration beads (Fluidigm, South San Francisco, CA, USA) and CAS and samples were run in the CyTOF®2 instrument (Fluidigm, South San Francisco, CA, USA).

The fcs. files obtained from the instrument were concatenated, normalized to EQ^TM calibration beads, and de-barcoded using CyTOF software (Fluidigm, South San Francisco, CA, USA). This study is comprised of eight different sample groups: control (Ctrl) and endometriosis (Endo) eutopic endometrium (EM) in the proliferative (PE) and secretory (SE) phases (Ctrl_EM_PE, Ctrl_EM_SE, Endo_EM_PE, Endo_EM_SE) and control and blood (PBMCs) in the proliferative and secretory phases (Ctrl_PBMC_PE, Ctrl_PBMC_SE, Endo_PBMC_PE, Endo_PBMC_SE). Normalized data from the broad panel were imported to FlowJo (BD, Franklin Lakes, NJ, USA) to perform manual gating, and we performed unsupervised analysis of the manually gated CD45⁺ cells. We also performed manual gating of the different populations obtained from the focused panel and 8 populations were obtained and are shown in Additional file 3: Fig. S1. Then, unsupervised analysis of the manually gated myeloid cells of interest (including macrophages, monocytes, dendritic cells, and plasmacytoid dendritic cells) was also performed. Finally, statistical analyses for specific markers and populations of the focused panel were performed by manual gating to validate the results from the unsupervised analysis. The datasets generated and analyzed during the current study are available in the Dryad repository (doi:10.7272/Q6Q52MVQ).

Clustering analysis (which include all samples analyzed in the study; controls and cases with endometriosis in both proliferative and secretory phases of the cycle) revealed 11 distinct immune clusters and one cluster of putative endothelial cells, the latter of which has been observed to express CD45 at low levels in some tissues [16]. The 11 immune cell clusters correspond to macrophages, natural killer cells (NK), neutrophils, and subsets of CD4⁺ T cells including Temra (effector memory T cells that re-express CD45RA after antigenic stimulation), CD8⁺ T cells, CD16⁺ NK, CD69⁺ NK, B cells, γδ T cells, and class I conventional dendritic cells (cDC1) (Fig. 1). Briefly, T cells were identified by the high expression of CD3. Their subsets were identified by the high expression of CD4 (T cells CD4+) and CD8 (T cells CD8+), CD45RA (Temra), and γδTCR (γδ T cells). B cells were identified by the expression of CD19. Cells expressing high levels of CD15 and CD126 were classified as neutrophils. Macrophages were identified by the high expression of HLA-DR, CD11c, CD36, and CD14, and they were negative for CD3, CD56, and CD19, among others. We found three clusters of natural killer cells (NK). We identified them as they are all are negative for the lineage markers CD3 and CD14 but express different levels of CD56. In addition, the close proximity of clusters 1, 7, and 8 on the UMAP indicates similarities among the three clusters. So, to differentiate among the three NK cells subsets, we named them with the expression of the most distinguishing markers based on the literature. First, Cluster 1 (CD56+ CD16− NK) is CD56+ and CD16−, which corresponds to infiltrating natural killers (from blood); cluster 7 (CD16+ NK) corresponds to endometrial natural killers (CD56 dim and CD16 bright, markers consistent with activation; and third, those that highly express CD69 (CD69+ NK), a marker previously described in tissue-resident NK cells [17]. Endothelial cells were defined by the high-level expression of BDCA3, as it is known that these cells highly express this marker [18, 19]. Cluster 11 was annotated and defined as cDC1 due to its expression of BDCA3, CD36, CD11c, and HLA-DR and being negative for CD3, CD4, CD14, and BDCA1, which are gold standard markers for cDC1 in humans. Nonetheless, the high BDCA3 expression in endothelial cells and the normalization across the column in the heatmap obscure the expression of BDCA3 in cluster 11 (Fig. 2b). The proportion of each population in all conditions (control and endometriosis in both phases of the cycle) is shown in Additional file 6: Fig. S4. Populations displaying significant differences in abundance between controls and cases across the menstrual cycle are presented in Fig. 2A. The distribution of all populations in both controls and cases is shown in Additional file 7: Fig. S5. In controls, the abundance of cDC1 significantly increased in the secretory phase of the cycle as did macrophages albeit insignificantly, while in women with endometriosis, both populations significantly decreased (Fig. 2A). In addition, while B cells tended to decrease in the secretory phase in controls, this population significantly more abundant in samples acquired during the secretory phase from cases (Fig. 2A). Furthermore, we found statistically significant differences between abundance of specific populations in cases and controls. We observed increased abundance of macrophages and neutrophils in the proliferative phase and decreased CD69+ NK, B cells, and γδ Tcells in the proliferative phase in cases vs controls (Fig. 2B).

Increased abundance of subsets of macrophages and neutrophils in endometrium of women with endometriosis in the proliferative phase (Fig. 2B) indicates more inflammation in tissues from women with disease compared to controls. This observation suggesting that myeloid populations may be involved in disease prompted the development of a mononuclear phagocyte-focused panel to study these populations in more detail.

We then combined phenotypic and functional markers of the mononuclear phagocyte populations including activation/inhibition markers, phagocytosis markers, and efferocytosis markers. By using manual gating, we first excluded T cells, NK, and granulocytes and then performed the unsupervised analysis on the remaining cells. The unsupervised clustering yielded 13 unique cell populations (Fig. 3), including one which was characterized by an absence of expression of any mononuclear phagocyte markers and was therefore excluded for further analysis, as it may be a potential B cells cluster. In this manner, we identified 12 clusters in the endometrial tissue (analysis made with all samples; cases and controls in both proliferative and secretory phases). We found three clusters corresponding to classical monocytes (CD44⁺ classical monocytes, HLA-DR⁺ classical monocytes, and HLA-DPB1⁺ classical monocytes) defined by a high expression of CD14 and CD36, and low expression of CD16; three macrophage clusters (CD206⁺ macrophages, CD91⁺ macrophages, and ALXR⁺ macrophages) defined by the expression of CD11c, CD64, and CD206; two clusters of non-classical monocytes (CX3CR1⁺ non-classical monocytes and non-classical monocytes) defined by their CD16 expression and low expression of CD14. In the case of the dendritic cells’ classification, the focused panel did not contain a great number of specific markers for subsets of dendritic cells, such as CD141 or CD1c, which made more difficult their identification. However, it included CD1a, CD11c, CD123, CD14, and CD16 which allowed their broad identification. Consequently, we used a hybrid strategy to identify DCs subsets. We first isolated plasmacytoid dendritic cells (pDCs) using the gold standard classification of lineage negative (CD3, CD56, CD14, CD16−, and CD11c−) and expression of HLA-DR+, CD11c−, CD16−, and CD123+ markers. Regarding classical dendritic cells, we had not included in this panel the markers BDCA1 (CD1c) and BDCA3 (CD141), classical markers for cDC2 and cDC1, respectively. Nevertheless, based on the literature, cDCs are CD14dim, and CD11c+ (also shown in Additional file 3: Fig. S1), which is the case for the three clusters of dendritic cells that we have identified named dendritic cells, TGM2+ dendritic cells and CD1a+ dendritic cells. In addition, we added dendritic cell markers in the focused panel that we believed could be involved in endometriosis. It is well known that dendritic cells can express CD1a+ [20]. This marker is believed to be an immature marker for DCs while CD83+ is a marker of mature DCs. As it was previously described that in endometrium of women with endometriosis, immature DCs (CD1a+) were more abundant than CD83+ mature DCs [21], these two markers were included in the focused panel. We identified a cluster (cluster 5) with high expression of CD1a, indicating that these may be immature dendritic cells. On the other hand, TGM2+ is also expressed in DCs [22] and it is believed to be involved in dendritic cell-T cell interaction. However, it is inevitable that the relationship between those subsets and the classical cDC1 and cDC2 will need to be established. The expression levels of all markers for each population are shown in Fig. 3B and in Table 1.

As the data in endometrium revealed differences in macrophages, some monocytes, and dendritic cells in women with versus without endometriosis, PBMCs were then analyzed using the focused panel to evaluate possible comparable dysregulation and if these populations could be an indicator of disease. Because only differences in the proliferative phase of the cycle were observed in endometrium, the analysis was restricted to samples from this cycle phase. After the clustering analysis, 11 populations were identified, corresponding to three clusters of classical monocytes (classical monocytes, activated classical monocytes, and highly activated classical monocytes) defined by their expression of CD14 (high) and CD16 (low) and the expression of activation markers, such as HLA-DR and CD44; three clusters of intermediate monocytes (intermediate monocytes, activated intermediate monocytes, and highly activated intermediate monocytes) also identified by the expression of both CD14 and CD16 and activation markers; three clusters of non-classical monocytes (non-classical monocytes, activated non-classical monocytes, and highly activated non-classical monocytes) defined by their expression of CD14 (low) and CD16 (high) and activation markers; one cluster of dendritic cells, defined by their expression of HLA-DR, CD11c, among others; and one cluster of pDCs, identified by their high expression of CD123. The specific expression of all markers from the panel in each population are shown in Fig. 7 and Table 2.

Association analysis performed in the proliferative phase of the menstrual cycle revealed an increased proportion of activated non-classical monocytes and pDCs in blood from women with endometriosis compared to controls and a decrease of classical monocytes, intermediate monocytes, and non-activated non-classical monocytes (Fig. 8A). However, significant differences in markers between controls and cases were not found, suggesting that previous differences in marker expression found in endometrium may be tissue specific.

Finally, to evaluate if there could be an association of immune populations in blood with severity of the disease, association analysis of stages of endometriosis in blood were performed. The results showed that classical monocytes (highly activated and activated), intermediate monocytes (intermediate monocytes; activated and highly activated), and dendritic cells are more abundant in peripheral blood from women with mild versus severe disease, suggesting that there is recruitment of monocytes to sites of inflammation in women with endometriosis. In contrast, highly activated non-classical monocytes were significantly higher in the setting of severe disease (Fig. 8B), and, interestingly, this population was considerably more abundant in endometriosis than in control patients (Fig. 8C), which could serve as a biomarker of disease and, specifically, severity of endometriosis.

Our results showing higher abundance of endometrial macrophages in the proliferative phase in women with versus without endometriosis are in accordance with other studies [26]. Also, overexpression of MCP-1 (CCL2) and IL-1β in endometrium of women with endometriosis [27] suggests increased infiltration of monocytes that differentiate to macrophages in this tissue in women with disease (Fig. 9). Our results show that CD91⁺ macrophages are more abundant and have different dynamics throughout the cycle in cases versus controls. CD91 participates in the efferocytosis of apoptotic cells—a crucial function during endometrial shedding. Notably, we found that endometrial CD91⁺ macrophages and CD1a⁺ dendritic cells overexpress SIRPα—which acts to inhibit efferocytosis by these cells—in women with endometriosis compared to controls. Healthy cells express “don’t-eat-me” signals, exposing different markers, such as CD47, that, when exposed, are recognized by SIRPα, and prevent engulfment by initiating a cascade of events leading to the inhibition of phagocytosis. Such engulfment is promoted by the calreticulin/CD91 pathway as an “eat-me” signal. In many cancers, calreticulin is exposed in the cell surface that would indicate an “eat-me” signal. However, this process does not occur in cancer, and why this molecule is exposed in cancerous cells is still unclear [28]. We found that macrophages that overexpress SIRPα in endometriosis are CD91⁺. Even if they express the latter, these observations suggest that their phagocytic capacity may be compromised by concomitant overexpression of SIRPα, suggesting that endometrial cells in women with endometriosis behave similarly to cancer cells, sending signals that interfere with the CD91 pathway in macrophages preventing efferocytosis. Thus, the overexpression of this marker in specific myeloid cells may be a consequence of aberrant functionality of eutopic endometrial cells in women with endometriosis. Xie et al. demonstrated that in vitro cultured macrophages treated with endometrial homogenates from women with endometriosis had significantly increased SIRPα expression, not observed when the macrophages were treated with homogenates of endometrium from women without disease [29], also suggesting that signals from eutopic endometrium affect the phagocytic capacity of macrophages. Another study evaluated the effect of this pathway in endometrial stromal cells from endometrium of women with endometriosis and in endometriosis lesions in vitro [30]. Co-culture of PBMCs and lesion-derived stromal cells resulted in upregulation of SIRPα in macrophages, further supporting paracrine endometrial cell interactions in macrophage dysfunction and disease establishment. Notably, we found that endometrial CD1a⁺ dendritic cells also overexpress SIRPa in women with versus those without endometriosis, indicating that other endometrial phagocytic cells may also be dysregulated in women with endometriosis. Decreased phagocytic capacity in macrophages and dendritic cells may allow aberrant endometrial cells to escape immunologic surveillance during tissue shedding, leading to establishing pelvic endometriosis (Fig. 9). Sampson’s theory of the origin of endometriosis proposes that endometrial cells shed during menses survive and migrate to the peritoneal cavity through retrograde menstruation, where they implant and develop endometriotic lesions [31]. Our results, together with the above studies, suggest that endometrial macrophages have defective phagocytic capacity in women with versus without endometriosis, opening opportunities for mining new targets to prevent development and/or progression of the disease as well as endometrial dysfunction. Expression of calreticulin in endometrial cells in women with endometriosis and the effects in the calreticulin/CD91 pathway warrant further study to confirm this paradigm.

In addition, our findings that CD91⁺ endometrial macrophages are more abundant and overexpress CD64 in women with endometriosis and in mild versus severe stage disease suggest a more enhanced pro-inflammatory phenotype in mild disease due to the expression of CD64. Therapeutic targeting of CD64 expressed on pro-inflammatory macrophages, proposed for other chronic inflammatory diseases, may be useful in the context of endometriosis [32].

Discovery herein has revealed that in addition to endometrial immune populations, specific PBMC populations differ in women with versus without endometriosis. Importantly, classical and intermediate monocytes are in lower abundance and pDCs and activated non-classical monocytes are more abundant in blood from women with versus without disease. These findings are in line with a recent study that described decreased phagocytic function of monocytes in blood from patients with endometriosis before surgery, and normalization after lesion removal, compared to controls undergoing surgery but without endometriosis [33]. In addition, proliferation of endometrial cells in vitro from women with endometriosis is significantly enhanced by blood monocytes, whereas monocytes from healthy patients inhibit their proliferation [34], indicating factors influencing these cells act as enhancers or suppressors of endometriotic lesion development. Our results that classical and intermediate monocytes are less abundant in blood from patients with endometriosis are consistent with increased recruitment of monocytes to sites of inflammation, e.g., to the peritoneal cavity, where endometriotic lesions are commonly found, and to the uterine endometrium, where we also observed a higher proportion of macrophages in women with disease in the proliferative phase. In addition, these populations may have less phagocytic function and thus play a role in deficient clearance of ectopic endometrial tissue, resulting in endometriotic lesion development (Fig. 9). While the above studies by others did not differentiate findings in the setting of mild and severe disease or different types of monocytes, our results show that this effect is more profound in severe disease, where there are significantly less circulating classical and intermediate monocytes than in mild disease, suggesting this defective function is enhanced in more advanced disease.

Notably, we found an increase of activated non-classical monocytes and pDCs in blood of women with endometriosis versus controls and that the former were more associated with advanced stage disease. Suen et al. demonstrated in a murine model that IL-10 secreted from pDCs promotes endometriotic lesion development through aberrant angiogenesis early in disease establishment [35]. Our results show that pDCs are associated with disease but not stage. This is in contrast to the mouse model, where the association with early disease establishment can be assessed experimentally, unlike human endometriosis where the evolution cannot be reliably assessed. It is well known that pDCs are involved in some autoimmune diseases and play a pivotal role in the development of autoantibodies through impaired type I interferon (type I INF) production [36], enhancing systemic autoimmunity [37]. Endometriosis is a chronic inflammatory disease that shares many similarities with autoimmune disorders [38], including production of autoantibodies [3]. A recent metanalysis by Shigesi et al. found a greater risk of autoimmune diseases in patients with endometriosis, including systemic lupus erythematosus, Sjögren’s syndrome, rheumatoid arthritis, celiac disease, multiple sclerosis, inflammatory bowel disease, autoimmune thyroid disorders, and Addison’s disease [39]. In addition, more severe endometriosis is being associated with concomitant autoimmune diseases [40]. Thus, it is of great interest to determine the precise role of pDCs in endometriosis pathophysiology and the role of systemic cytokines, such as INF family members, to better understand common immunopathology between endometriosis and autoimmune diseases. Interestingly, in the autoimmune disorder neuromyelitis optica spectrum disorder (NMOSD), non-classical monocytes have a higher frequency than in controls in blood [41]. Non-classical monocytes are believed to be patrolling and anti-inflammatory innate immune cells. However, their roles in chronic diseases, such as in multiple sclerosis or systemic lupus erythematosus, are less clear as their functions can be protective as well as positively associated with disease burden [42]. Given our observation of their greater abundance in blood of women with endometriosis and, specifically, in those with severe disease, and as endometriosis is a chronic inflammatory disorder, further study of the functional roles of this population and mining biomarkers of disease severity warrants further investigation. Although the patients in the current study did not have autoimmune comorbidities, further analysis of abundance and function of non-classical monocytes and pDCs, as well as their cytokine production in patients with endometriosis, having or not concomitant autoimmune diseases, is of interest, especially as the role of these populations in endometriosis remains unresolved.

Some of the limitations of the study include a limited sample size, especially in the secretory phase of the menstrual cycle. As mentioned above, this may be a reason why we found only differences in the proliferative phase. Although in this study, we show differences in the latter, a larger sample size in all phases would further confirm differences highlighted by our discovery cohort. Another limitation of the study is that the focused panel did not contain a B cell-specific marker. As we observed differences in B cell frequency by using the broad panel, indication that B cells may also have a role in disease would require further investigation. Along the same line, while we were able to identify coarsely dendritic cell populations, additional choice of markers specific for this population would be needed to deeply characterize and distinguish between known subsets such as cDC1 and cDC2. Therefore, the design of the focused panel caused some limitations for cell identification of specific cell subtypes. Finally, due to the differential proteomic profile between blood and endometrium-associated classical monocytes, we cannot directly relate them between the different biospecimen compartments. We therefore have maintained a different nomenclature of monocytes between endometrium and blood to avoid unsupported conclusions. It would be important to relate these different classical monocytes in the different compartments in the future, which may require experiments using animal models to dissect classical monocyte ontogeny.

Although we had some limitations in the study, to our knowledge, this cohort size represents the largest cohort of endometrial samples from women with and without endometriosis analyzed by mass cytometry reported to date. Applying two different panels enabled us to identify populations that could be involved in endometriosis, and the second panel allowed deep phenotyping the MPC system at the protein level for the first time in eutopic endometrium of women with and without endometriosis. Considering the heterogeneity of the disease and the immune complexity, further single-cell studies, e.g., using more focused panels for other immune populations and endometrial cells, will help to better understand the immune system in endometriosis.