Macrophages originated IL33/ST2 inhibits ferroptosis in endometriosis via the ATF3/SLC7A11 axis

Macrophages originated IL33/ST2 inhibits ferroptosis in endometriosis via the ATF3/SLC7A11 axis | 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 Macrophages originated IL33/ST2 inhibits ferroptosis in endometriosis via the ATF3/SLC7A11 axis Zongfeng Zhang, Qiong Wu, Zongwen Liang, Jing Jiang, Xiaoming Feng, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2835730/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Oct, 2023 Read the published version in Cell Death & Disease → Version 1 posted You are reading this latest preprint version Abstract Endometriosis is a gynecological inflammatory disease which linked with immune cells, specifically macrophages. And IL-33 secreted from macrophages is known to accelerate the progression of endometriosis. The periodic and repeated bleeding in endometriosis leads to a microenvironment with an excess of iron that is conducive to ferroptosis, a process related to intracellular ROS production, lipid peroxidation and mitochondrial damage. Hence, it is suggested that eESCs may have specific mechanisms to inhibit ferroptosis. However, it is currently unclear whether IL-33 directly regulates ferroptosis to influence the disease course in endometriosis. In this study, eESCs co-cultured with macrophages or stimulated with IL-33/ST2 were observed increased cell viability and migration. Additionally, IL-33/ST2 lessened intracellular iron and lipid peroxidation in eESCs exposed to erastin treatment. Furthermore, IL-33/ST2 treatment resulted in a notable elevation of SLC7A11 expression in eESCs due to its negative transcription factor ATF3 down-regulation, thereby suppressing ferroptosis. The P38/JNK pathway activated by IL-33/ST2 was also found to inhibit transcription factor ATF3. Therefore, we concluded that IL-33/ST2 constrains ATF3's role in suppressing SLC7A11 transcription via the P38/JNK pathway. The findings reveal that macrophage-derived IL-33 induces an upregulation of SLC7A11 in eESCs through the p38/JNK/ATF3 pathway, ultimately resulting in protection against ferroptosis in endometriosis. Moreover, we conducted an experiment in mouse endometriosis models that showed that a combination of IL-33-Ab and erastin treatment alleviated the disease, showing the promise of combining immunotherapy and ferroptosis therapy. Health sciences/Pathogenesis/Inflammation/Chronic inflammation Biological sciences/Immunology/Cell death and immune response Health sciences/Diseases/Reproductive disorders Biological sciences/Immunology/Cytokines/Interleukins Biological sciences/Biochemistry/Lipids/Membrane lipids Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Endometriosis is a chronic inflammatory disease that affects nearly 10% of females of reproductive age worldwide[1]. Multiple theories, including ectopic implantation, coelomic metaplasia, and immune factors, have been proposed to elucidate the pathophysiology of endometriosis[2]. Notable adaptations in the local immune microenvironment of endometriosis lesions have been detected, including the infiltration and differentiation of diverse immune cells and the aggregation of chemokines and cytokines[3]. Macrophages are reported to be one of the predominant cells present in ectopic endometrial lesions, and interleukin-1β (IL-1β) promotes ectopic endometrial stromal cells (eESCs) proliferation[4, 5]. IL-8-Ab reduced the volume of lesions and ameliorated fibrosis and adhesion in monkeys endometriosis models[6]. The interplay between infiltrated immune cells and eESCs prompts genetic and epigenetic modifications in the eESCs. Subsequently, these adaptations in eESCs result in molecular changes and dysfunction in immune cells. Interleukin-33 (IL-33), a member of the IL-1β family, is secreted by macrophages. Previous studies have indicated that IL-33 has the potential to stimulate tumor cells proliferation and neovascularization in ovarian cancer[7]. Knockout of IL-33 in mouse endometriosis models has led to a significant decrease in endometriotic lesion volume[8]. It is also worth mentioning that IL-33 induces macrophage anti-inflammatory polarization and stimulates the formation of Splenic red pulp macrophages (RPMs) that regulate erythrocyte homeostasis and support iron recycling[9, 10]. Our team has also discovered a significant promoting effect of macrophages on endometriosis[11]. We thus postulate that macrophage-derived IL-33 may regulate eESCs survival, which ultimately advance the progression of endometriosis. However, the the complete role of IL-33 in development of endometriosis requires further exploration. Ferroptosis is a newly discovered programmed cell death process characterized by iron-dependent accumulation of reactive oxygen species (ROS) and lipid peroxidation[12, 13]. The key molecule in ferroptosis, SLC7A11, is a component of the L-Cystine/L-Glutamic Acid reverse transporter system (Xct) which mediates the transmembrane transport of glutamate and cysteine. Cysteine from the extracellular space triggers glutathione (GSH) synthesis, maintaining the GSH/GSSG redox balance. Glutathione peroxidase 4 (GPX4) also plays a critical role in ferroptosis by efficiently reducing lipid hydroperoxides that accumulate in the membrane of cells undergoing ferroptosis[14, 15, 16]. A study reported that macrophages within pancreatic ductal adenocarcinoma (PDAC) exhibit ferroptosis, which suppresses macrophage defense against tumor cells[17]. Although, in endometriotic lesions, period bleeding and accumulation of antiquated blood establish a iron-enriched microenvironment, eESCs exhibited more tolerance to ferroptosis, leading researchers hypothesizing that there are certain mechanisms in eESCs that confer resistance to ferroptosis[18]. However, the specific mechanisms remain unclear. This study explores the functional significance of ferroptosis in the pathogenesis of endometriosis. Our results reveal that the cytokine IL-33, secreted by macrophages, plays a crucial role in upregulating the expression of SLC7A11 by inhibiting ATF3 in eESCs. This activity hinders eESCs ferroptosis and thereby facilitates the development of endometriosis. In addition, we established a mouse model of endometriosis and employed a collaborative therapy involving IL-33 antibodies and a ferroptosis inhibitor, erastin. This innovative approach successfully combines immunotherapy and ferroptosis therapy for the treatment of the disease. Results IL-33/ST2 expression increased in eESCs when co-cultured with macrophages Recent researches have shown that females with endometriosis exhibit elevated levels of Interleukin-33 (IL-33) in circulation when compared to healthy females[19]. This finding piqued our curiosity about the effect IL-33 has on the progression of endometriosis. To verify the expression of IL-33 and ST2 (interleukin receptor-like 1), a widely accepted receptor of IL-33, in endometriosis (EMs), we employed immunohistochemistry (IHC) assays in both normal endometrial (EN) and ectopic endometrial tissues (EC)[20]. Figure 1A illustrates that the concentration of IL-33 in EC tissues was significantly higher when compared with that in EN tissues (Fig. 1A). The RT-qPCR results support this finding (Fig. 1B). At the cellular level, we successfully extracted, cultured and identified ectopic endometrial stromal cells (eESCs) and normal endometrial stromal cells (nESCs) (Supplementary Fig. 1). Western blot and RT-qPCR data both indicate a significant increase in the expression levels of IL-33 and ST2 in eESCs when compared with nESCs (Fig. 1C, D). The findings are further supported by results from the immunofluorescence assay (IF) performed both on eESCs and nESCs, which revealed an increase in fluorescence intensity of IL-33 and ST2 in eESCs (Figure. 1H). The widely accepted theory suggests that the alternation of immune micro-environment specifically macrophage differentiation, plays a critical role in the development of endometriosis[21]. Considering the mechanism responsible for the upregulation of IL-33 expression, we note that various immune cells, including macrophages, can produce IL-33. And based on our previous studies which indicate that macrophages are enriched around eESCs, we speculate macrophages may be responsible for the high levels of IL-33 and ST2 in eESCs[11, 22]. To test this hypothesis, we induced acute monocytic leukemia cells (THP-1 cells) differentiation into macrophages using PMA (200nM) in succession (Supplementary Fig. 2). The ELISA assay demonstrated that the concentration of IL-33 was higher in macrophage cell medium than in eESCs cell medium (Supplementary Fig. 3), confirming that macrophages can secrete IL-33. We then co-cultured IL-33 knockdown eESCs with macrophages and measured the level of IL-33 in eESCs lysate using ELISA assays. The outcomes showed a notable increase in IL-33 levels among the group of eESCs co-cultured with macrophages, suggesting that IL-33 produced by macrophages can be transported into eESCs through intercellular communication (Fig. 1E). In addition, both western blot and RT-qPCR assays exhibited an increase in IL-33 and ST2 expression in initial eESCs that were co-cultured with macrophages, but not in eESCs alone (Fig. 1F, G). These findings suggest that macrophages enhance the level of IL-33 in eESCs not only through intercellular transmission but also by inducing eESCs to produce IL-33 autonomously. The results of these experiments reveal that macrophages induce higher levels of IL-33 and ST2 in eESCs. IL33/ST2 increased the survival rate and migration ability of eESCs To elucidate the role of IL-33 secreted by macrophages on eESCs, human recombinant IL-33 protein (rIL-33) was added to the culture medium of eESCs at different concentrations (0-2.5-5-10-20 μM). Then we evaluated cell viability after 12, 24, and 48 hours respectively to determine the optimal concentration and time parameters. The 10μl/ml concentration of IL-33 for 24 hours showed the most substantial increase in cell viability, and this mode was used in subsequent experiments (Fig. 2A). Additionally, eESCs were transfected with siRNA targeting ST2, and the efficiency of transfection was confirmed by employing both RT-qPCR and Western-blotting methods (Fig. 2B, C). Next, eESCs were treated with rIL-33 or macrophage co-culture. The cell migration ability was evaluated using the transwell assay, and both treatments showed a significant increase in eESCs migration (Fig. 2D, E). Furthermore, upon the knockdown of ST2, the migration capability of eESCs was attenuated (Fig. 2F, G). Furthermore, the cell colony formation assay showed that both rIL-33 and macrophage co-culture treatment markedly improved eESCs viability. Conversely, si-ST2 eESCs revealed reduced cell viability, as evidenced by the results of this assay. (Fig. 2H). Collectively, these experimental findings suggest that IL-33 plays a critical role in the survival and migration of eESCs. IL33/ST2 inhibited ferroptosis in eESCs. Endometriosis involves various forms of cell death, including apoptosis, necroptosis, autophagy, and ferroptosis[23]. To examine whether IL-33 promotes eESCs survival by regulating cell death, we compared the effects of various cell death inhibitors on si-IL33-treated eESCs. As presented in Figure. 3A, only ferrostatin-1 had a significant effect in rescuing the si-IL33-induced decline in eESC viability, while well-known apoptosis and necroptosis inhibitors ZVAD-FMK and necrostatin-1 showed little impact (Fig. 3A). Therefore, we presume that IL-33 may elevate eESC survival by inhibiting ferroptosis. Next, we tested the expression levels of ferroptosis markers in eESCs treated with rIL-33 or siST2. The addition of rIL-33 group showed elevated levels of SLC7A11 and GPX4 but reduced levels of ACSL4 compared to the control group. Conversely, in the ST2 knockdown group, and the ferroptosis inhibitor Ferrostatin-1 (Fer-1) rescued these effects (Fig. 3B). To further explore IL33's influence on ferroptosis progression, we treated eESCs with erastin to induce ferroptosis (Fig. 3C). But the addition of IL-33 rescued the increase in Fe2+ concentration induced by erastin. And the protective effect of IL-33 disappeared in the ST2 knockdown group (Fig. 3D). Additionally, as ferroptosis is closely associated with lipid peroxidation, we investigated the effects of IL-33 on lipid peroxidation induced by ferroptosis in eESCs. As shown in Figure. 3E, the fluorescence intensity in eESCs decreased after rIL-33 was added. On the other hand, the si-ST2 transfection attenuated the effect of IL-33 in reducing lipid peroxidation (Fig. 3E). MDA, a lipid peroxidation product, increased in the erastin group but was restrained by rIL-33 (Fig. 3F). Furthermore, erastin exhaustion depleted GSH, a classic antioxidant in eESCs, while the addition of IL-33 restored it (Fig. 3G). However, the protective effect of IL-33 was not observed in the ST2 knockdown group (Fig. 3 F, G). Ferroptosis is closely linked to mitochondrial dysfunction and reduced mitochondrial redox capacity. Through transmission electron microscopy (TEM), we observed that erastin-treated eESCs exhibited significant mitochondrial structural alterations such as atrophy and increased membrane density, whereas IL-33 protected mitochondrial structure from ferroptosis-induced damage (Fig. 3H). Overall, the results demonstrated the anti-ferroptosis role of IL-33/ST2 in eESCs. IL33/ST2 inhibited ferroptosis through regulating SLC7A11 expression in eESCs To investigate the underlying mechanism of how IL-33 inhibits ferroptosis in eESCs, we conducted a correlation analysis between IL-33 and several ferroptosis marker molecules. The Pearson's test confirmed a statistically significant association between IL-33 and SLC7A11 expression (Fig. 4A). Although we also observed a significant correlation between IL-33 and GPX4 expression (Supplementary Fig. 4), however, studies have previously revealed GPX4 as a downstream component of the SLC7A11 pathway during the ferroptosis process. Therefore, we focused on investigating the function of SLC7A11 in our subsequent studies. The expression of SLC7A11 was notably enhanced following treatment with rIL-33 (Fig. 3D). Given that SLC7A11 plays a crucial role in forming the Glutamate cysteine transporter system (Xct) which is responsible for GSH synthesis, we supplemented eESCs with GSH to present the result of excessive expression of SLC7A11 (Fig. 4B). To further investigate the role that SLC7A11 plays in the process of IL-33 inhibiting ferroptosis, we knocked down SLC7A11 in eESCs. Consequently, cell viability was considerably reduced, and rIL-33 was unable to rescue the declining cell viability (Fig. 4C, D). Moreover, the addition of GSH rescued the reduced cell viability induced by si-ST2 (Fig. 4E). Theses data suggested that SLC7A11 has a downstream effect of the IL-33 pathway. In support of these findings, the Western blot results showed an increased protein level of GPX4 in the si-SLC7A11 group, further confirming the involvement of SLC7A11 in the IL-33-mediated suppression of ferroptosis. Additionally, the Western blot analysis indicated that GSH could prevent ferroptosis in eESCs by modulating the alternation in ferroptosis marker molecules induced by si-ST2 treatment (Fig. 4F). These results were further substantiated through the evaluation of MDA content, GSH levels, intracellular Fe2+ concentration, and lipid peroxidation (Fig. 4G, H, I, J). Overall, our results demonstrated that IL-33/ST2 inhibits ferroptosis by modulating SLC7A11 expression in eESCs. IL33/ST2 promoted SLC7A11 expression through regulating ATF3 To explore the mechanism responsible for the IL-33/ST2-mediated activation of SLC7A11 in endometriosis, we first identified differentially expressed genes (DEGs) from the dataset of endometriosis obtained from the GEO database (GSE19834). This dataset compared the gene expression profiles of eESCs cultured alone and eESCs co-cultured with macrophages. A Venn diagram analysis was then conducted to screen for ferroptosis marker genes (listed in the FerroDb database) among the DEGs identified through this comparison. This analysis revealed IL-33 and ATF3 as two significant regulators of ferroptosis in endometriosis (Fig. 5A). ATF3 is a negative transforming factor involved in various diseases[24, 25]. And ATF3 was found to regulate SLC7A11 expression[26]. Hence, we aimed to test if ATF3 participates in the IL-33-actived process of SLC7A11 expression in endometriosis. Our findings illustrated that the level of ATF3 was lower in EC tissues than in EN tissues (Fig. 5B), and ATF3 protein level in eESCs was also lower than that in nESCs (Fig. 5C). Interestingly, when rIL-33 was added to eESCs, the protein level of ATF3 was further reduced. This indicates that IL-33 negatively regulates ATF3 (Fig. 5D). To determine the precise role that ATF3 plays in the regulatory process of IL-33 on SLC7A11, we conducted single knockdowns of ATF3, as well as dual knockdowns of ST2 and ATF3 in eESCs. The Western blot results demonstrated that si-ATF3 was effective in reversing the decrease in SLC7A11 and GPX4 expression induced by si-ST2 (Fig. 5G, F). Next, the ChIP-seq analysis revealed the substantial presence of ATF3-binding peaks in the promoter sites of SLC7A11. Such findings indicate that ATF3 plays a crucial role in controlling the transcription of SLC7A11 by binding with high affinity to its promoter (data derived from GSM1917770, ENCSR632DCH_2, GSM803508, GSM803503) (Fig. 5E). We then performed chromatin immunoprecipitation assays (ChIP) to confirm the direct binding of ATF3 and the SLC7A11 promoter (Fig. 5H). Collectively, we have confirmed that ATF3 serves as a negative transcription factor that impedes IL-33/ST2 from elevating SLC7A11. IL33/ST2 inhibited ATF3 through the P38/JNK signaling pathway The above results indicate that IL-33/ST2 can stimulate SLC7A11 expression by down-regulating ATF3. However, an important question followed is how IL-33/ST2 modulates the expression of ATF3. By analyzing the interacting protein partners of ATF3 through the String online database, we discovered a strong correlation between ATF3 and P38 MAPK (Fig. 6A). A study proposed that Phlorofucofuroeckol A (PFF-A) has anti-cancer properties by inducing ATF3 expression via the p38 MAPK/JNK-mediated pathway in human colorectal cancer cells[27]. Further evidence from Spohn indicates that stimulation of HaCaT cells with thapsigargin triggers a signaling pathway that activates JNK and biosynthesis of ATF3 activity in keratinocytes. Based on these evidences, it is plausible that ATF3 may be regulated by the p38 MAPK/JNK pathway[28]. We further investigated the effects of rIL-33 on the P38 MAPK/JNK signaling pathway. Intriguingly, our findings revealed that treatment with rIL-33 suppressed the phosphorylation of both P38 MAPK and JNK (Fig. 6B). Moreover, our findings suggested that a specific inhibitor of p38 MAPK phosphorylation, SB202190, elicited a similar decrease in ATF3 expression as observed with IL-33 treatment. Furthermore, in eESCs treated with SB202190, we observed that ATF3 levels did not decrease, as observed in the si-ST2 treatment group (Fig. 6C). Importantly, the results of tests measuring MDA content, GSH levels, intracellular Fe2+ concentration, and lipid peroxidation consistently showed that SB202190 has the ability to reverse the ST2 knockdown’ effect in inducing ferroptosis. (Fig. 6D-G). In summary, our findings suggest that IL-33/ST2 can suppress ATF3 by modulating the P38 MAPK/JNK signaling pathway, thereby promoting SLC7A11 expression. Collaborative treatment of IL-33-Ab and erastin alleviated endometriosis in mice model We have shown that knockdown of IL-33 inhibits proliferation, migration, and ferroptosis of EESCs in vitro, so we hypothesize that IL-33-Ab can also promote ferroptosis and reduce ectopic lesions in vivo. Surprisingly, our previous results have shown that Erastin can significantly reduce ectopic lesions. We therefore propose a novel strategy for combining erastin with IL-33-Ab to achieve synergistic therapy. This innovative approach promises a new direction for managing endometriosis. To achieve this objective, we successfully established mice models of endometriosis and divided them into four groups: control, erastin, IL-33-Ab, and IL-33-Ab plus erastin group as represented in Figure 7A (Fig. 7A). Notably, both the application of IL-33-Ab and erastin restrained the development of endometriosis. Moreover, their combined treatment was found to be more efficient in reducing the severity of the disease (Figure 7B, C, E, F). Hematoxylin and eosin (HE) staining revealed contrasting tissue structures of endometriosis in the four groups (Fig. 7G). Additionally, IHC assays demonstrated a decline in the expression levels of ST2 and SLC7A11 in the IL-33-Ab and erastin treatment groups, while their combination group exhibited a more significant effect (Fig. 7H, I). By exploring the effect of IL-33-Ab and erastin in inducing ferroptosis in mice models of endometriosis, our findings indicate their potential for treating endometriosis. Furthermore, the combined treatment of IL-33-Ab and erastin on an endometriosis mouse model resulted in a reinforced therapeutic effect for the disease. This inspires a novel therapeutic strategy and lays the foundation for research in the field of the collaboration of immunotherapy and ferroptosis therapy. Discussion Endometriosis has been found to be associated with various factors, including hereditary, retrograde menstruation, coelomic epithelial metaplasia, and immune factors[ 30 ]. Research has indicated that macrophages play a crucial role in promoting colonization of endometriosis lesions by facilitating angiogenesis and matrix remodeling[ 31 ]. Our team has previously discovered that CCL20/CCR6 signaling axis mediated macrophages can promote proliferation and migration of ESCs by blocking autophagic flux in endometriosis[ 22 ]. Here, we found that interleukin-33 (IL-33) has a significant high expression in eESCs co-cultured with macrophages, contributing to eESCs' survival and migration. This suggests that IL-33 derived from macrophages promotes the progression of endometriosis. Different types of cell death is associated with endometriosis, such as necroptosis, autophagy, apoptosis, and ferroptosis[ 24 ]. The accumulation of endometrial debris and period bleeding creates an iron overload environment that promotes ferroptosis[ 32 ]. But it seems that eESCs are more tolerant of high iron concentration[ 33 ]. The role of ferroptosis in endometriosis has not yet been systematically examined. Our study revealed that Fer-1 can effectively hinder the altered expression of ferroptosis markers brought by si-ST2. Treatment with rIL-33 also restricted ferroptosis in eESCs previously treated with erastin, as evidenced by the reduced levels of Fe2+, lipid peroxidation, MDA, increased level of GSH and specific mitochondrial structural change. In addition, we conducted a screening of several molecules that were significantly altered following IL-33 treatment and identified a tight correlation between SLC7A11 and IL-33. The protective effect of IL-33 against ferroptosis was resisted by knockout of SLC7A11. And the introduction of GSH helped to rescue eESCs from the ferroptosis trend initiated by si-ST2. Our data validated that rIL-33 upregulates the expression of SLC7A11 and blocks erastin-induced ferroptosis. We next looked into the regulators of SLC7A11. Bioinformatics analysis revealed that activating transcription factor 3 (ATF3) is one of the differentially expressed genes in eESCs co-cultured with macrophages and that ATF3 has a significant association with ferroptosis. ATF3 is a transcription factor known to regulate the expression of various molecules. ATF3 deficiency has been linked to prostate tumorigenesis induced by the inhibition of Pten in mice[ 34 ]. We indeed found out that IL-33 induced a significant decrease in ATF3 expression in eESCs. Our study also revealed that the knockdown of ATF3 led to a significant increase in SLC7A11 expression, thereby reversing the negative effect of si-ST2 on SLC7A11. Besides, using ChIP assays, we verified the interaction of ATF3 with SLC7A11 promoter. Taken together, our data suggest that IL-33/ST2 regulates ferroptosis by inhibiting the downregulation effect of ATF3 on SLC7A11. Another intriguing finding of our study is the restrained activation of the p38 MAPK/JNK pathway in eESCs treated by rIL-33. Previous research has highlighted the role of p38 MAPK/JNK in enhancing ATF3 expression[ 35 ]. We also found that rIL-33 treatment had a similar inhibitory effect on ATF3 expression as the treatment with p38 MAPK inhibitor SB202190. And SB202190 treatment was able to reverse the elevated levels of ATF3 observed in si-ST2 eESCs. Furthermore, through measuring the levels of Fe2+, lipid peroxidation, MDA, and GSH, we confirmed the SB202190's protective effects against Ferroptosis triggered by si-ST2 in eESCs. In summary, our study has shed light on the mechanism of the promotive effect of IL-33/ST2 in EMs, which involves the regulation of SLC7A11 expression via the p38/JNK/ATF3 signaling pathway, thereby hindering ferroptosis. During the progression of ferroptosis, certain molecules are released into the extracellular environment, recruiting immune cells. This strengthens the body's immune defense system and have therapeutic effects for endometriosis. Accordingly, some researchers have proposed combining immunotherapy with ferroptosis-inducing treatments as a potential approach. For instance, Niu et al. reported that ferroptosis inducers can enhance the sensitivity of "cold" tumors to immune therapy[ 36 ]. While a combination of the ferroptosis inducer RSL-3 and dihydroartemisinin (DHA), an immunotherapy medicine targeting PD-L1, was designed for the treatment of pancreatic ductal adenocarcinoma (PDAC)[ 37 ]. Here, we propose a novel therapy approach for endometriosis that combines ferroptosis inducer erastin and IL-33-Ab as ferroptosis-immunotherapy. IL-33-Ab not only inhibits the tolerance for ferroptosis of eESCs but also stimulates macrophage polarization into the pro-inflammatory M1 sub-type, thereby enhancing the body's immune defense against eESCs. Moreover, erastin promotes the progression of ferroptosis in eESCs[ 23 ]. To evaluate the efficacy of this therapy mode, we established mice endometriosis model and treated them with IL-33-Ab and erastin. In mice models of endometriosis, we found that IL-33-Ab inhibited endometriosis development, and the combination of IL-33-Ab with erastin further amplified this effect. The findings imply that ferroptosis-immunotherapy has the potential to serve as a therapeutic strategy for managing endometriosis. Our study also has limitation. Due to delayed clinical visits, most of the samples collected are from patients with middle to late-stage endometriosis. Further studies including patients in earlier stages are necessary to gain a more comprehensive understanding of endometriosis progression. In summary, we propose for the first time that IL-33 derived from macrophages can inhibit ferroptosis in eESCs by elevating SLC7A11 expression through the p38/JNK/ATF3 pathway. Our study provides a fresh perspective for understanding the pathology mechanism of endometriosis and developing novel treatment strategies. Materials and methods Cells culture Primary cells were isolated from endometriosis tissues using previously described protocols[ 11 ]. Briefly, the tissues were cut into 1 mm³ pieces and were then digested using type IV collagenase (0.2% Sigma, USA) for 60 minutes at 37℃. The primary cells were cultured in Dulbecco's modified Eagle's medium (DMEM) containing 15% fetal bovine serum (FBS; Biological Industries, Israel) and 1% penicillin-streptomycin (Gibco, USA) at 37°C with 5% CO2. Primary cells were identified using immunofluorescent staining (Supplementary Fig. 1). The acute monocytic leukemia cell line (THP-1 cells), were purchased from ScienCell, and they were cultured in Roswell Park Memorial Institute 1640 (RPMI-1640) medium supplemented with 10% FBS and 1% penicillin-streptomycin (Biological Industries, Israel). THP-1 cells were treated with PMA (200nM; Sigma) for 48 hours to induce cell polarization. Immunohistochemical staining (IHC) The sections were incubated overnight and then immersed in xylene and ethanol to deparaffinization. Primary antibodies were incubated for overnight at 4°C, followed by incubation with secondary antibodies for 20 minutes at ambient temperature (as listed in Table 1 ). The sections were then stained using DAB dye (CWBIO, Beijing, China) and hematoxylin. Finally, the slides were then covered with cover-slips. Table 1 Details of antibody used in experiments Antigen Catalog number Dilution Source Species IF IL−33 66235−1-Ig 1:200 Proteintech Mouse Vimentin 10366−1-AP 1:50 Proteintech Rabbit Cytokeratin 7 15539−1-AP 1:50 Proteintech Rabbit CD11b 66519−1-Ig 1:200 Proteintech Mouse CD68 28058−1-AP 1:200 Proteintech Rabbit WB Β-actin 60008−1-Ig 1:20000 Proteintech Mouse IL−33 66235−1-Ig 1:1000 Proteintech Mouse ST2 60112−1-Ig 1:20000 Proteintech Mouse ACSL4 22401−1-AP 1:1000 Proteintech Rabbit SLC7A11 26864−1-AP 1:1000 Proteintech Rabbit GPX4 14432−1-AP 1:5000 Proteintech Rabbit ATF3 DF3110 1:1000 Affinity Rabbit JNK 66210−1-Ig 1:5000 Proteintech Mouse p-JNK 80024−1-RR 1:1000 Proteintech Rabbit p38 14064−1-AP 1:1000 Proteintech Rabbit p-p38 28796−1-AP 1:1000 Proteintech Rabbit α-tublin 66031−1-Ig 1:50000 Proteintech Mouse GAPDH 10494−1-AP 1:5000 Proteintech Rabbit IHC IL33 12372−1-AP 1:200 Proteintech Rabbit ST2 60112−1-Ig 1:200 Proteintech Mouse ATF3 DF3110 1:100 Affinity Rabbit ST2 (Mouse) 11920−1-AP 1:400 Proteintech Rabbit SLC7A11 (Mouse) 26864−1-AP 1:200 Proteintech Rabbit WB western blot, IHC immunohistochemistry, IF Immunofuorescence, IL-33 Interleukin-33, ST2 interleukin receptor-like 1 (IL1R-L1), ACSL4 acyl-CoA synthetase long-chain family member 4, SLC7A11 solute carrier family 7 member 11, GPX4 glutathione peroxidase 4, ATF3 activating transcription factor, JNK c-Jun N-terminal protein kainse, p-JNK phosphorylated c-Jun N-terminal protein kainse, p38/p38 MAPK, p38 mitogen activated protein kinases, p-p38 phosphorylated p38 mitogen activated protein kinases. Quantitative real-time PCR (qRT-PCR) Total RNA was extracted from cells or tissues using Trizol (Invitrogen, USA), isopropyl alcohol, chloroform, and 75% ethanol. Reverse transcription of RNA (500 ng) was accomplished using a cDNA synthesis kit according to the manufacturer's protocol. Thereafter, cDNA (20 ng) was employed as a template for qRT-PCR using the Top Green qPCR SuperMix kit (TransGen Biotech, China). The primer were obtained from GENEWIZ (GENEWIZ, China), and listed in Table 2 . Table 2 Sequences of primers used for qRT-PCR analysis Gene Forward primer sequence Reverse primer sequence Β-actin TCCATGAAGTGACG TACTCCTGCTTGCTGATCCACAC IL33 GATGGGAAGAAGGTG ATGGTG TTG TGAAGGACGAAGAAGGC ST2 CAACTGGACAGCACCTCTTG GGTAATCACCTGCGTCCT SLC7A11 CCCTTTGCTCTCATACCCATC GACTTTCCTCTTCAGCTGCACTT ATF3 GGAGTGCCTGCAGAAAGAGT CCATTCTGAGCCCGGACAAT IL33 Interleukin-33, ST2 interleukin receptor-like 1 (IL1R-L1), SLC7A11 solute carrier family 7 member 11, ATF3 activating transcription factor, qRT-PCR reverse transcription and quantitative real-time PCR. Western blotting (WB) Cells or tissues were lysed using RIPA lysis buffer and 1% PMSF (Beyotime Biotechnology, China). The protein samples was performed using the BCA protein assay kit (Beyotime Biotechnology, China). Samples were loaded into 10% SDS-PAGE gels (Epizyme, China) and then transfer onto PVDF membranes (Millipore, USA). The membrane was blocked using 5% skim milk powder solution for 2 hours, after which it was incubated with primary antibodies (as listed in Table 1 ) overnight at 4℃ and then with secondary antibodies for 2 hours at room temperature. The blots were visualized using ECL reagent (Epizyme, China). ELISA Cell culture media from each group were collected and centrifuged at 500 g for 5 minutes. Interleukin-33 (IL-33) concentrations in the culture media supernatant were measured via an ELISA kit (Proteintech, USA) in accordance with the manufacturer’s instructions. Immunofluorescence (IF) Cells were fixed and subsequently blocked for 30 minutes using 5% goat serum albumin (Beyotime Biotechnology, China). The tissue sections were incubated overnight at 4℃ with specific primary antibodies (as listed in Table 1 ), and with fluorescent secondary antibodies for 1 hour at room temperature. Fluorescence images were captured using a fluorescence microscope (Nikon, Tokyo, Japan). Cell viability assessment The cells viability measured by CCK-8 reagent following the manufacturer’s instructions (Beyotime Biotechnology, China). The absorbance readings were taken at 450 nm using a plate reader. Colony formation assay Cells were subjected to 7-day culture, subsequently, staining was performed for 30 minutes using crystal violet dye. Imaging was carried out using an iPhone 12, and ImageJ software was then utilized to analyze the obtained data. Transwell migration assay Cells were seeded at a density of 1x104/mL in the upper chamber of the 8 µm transwell insert utilizing 100 µL of serum-free DMEM. The lower chamber was filled with 600 µL of DMEM containing 15% FBS. After a 24-hour incubation, the cells were fixed and stained. Wound healing assay We created a scratch in the cells monolayer by a 200 µL pipette. We recorded images of the scratch area under a microscope immediately after creating the scratch and at 24 and 48 hours later. Cell transfection We transfected cells with small interfering RNA (siRNA) using the Lipofectamine 3000 transfection kit (Invitrogen, USA) according to the manufacturer's instructions. Ribobio (Ribobio, China) synthesized all specific siRNAs and siRNA controls. The target sequence of siRNA was as follows: sicon, 5ʹ-TTCTCCGAACGTGTCACGT-3ʹ; siST2-1, 5ʹ-TCTAAUGUCACTAAAUAACUT-3ʹ; siST2-2, 5ʹ-GCGAAUGUCACCAUAUAUATT-3ʹ; siST2-3, 5ʹ-GCCCATGUCATTAAAUAUCAT-3ʹ; siSLC7A11-1, 5ʹ-CCGGCCTGTCACTATTT-3ʹ; siSLC7A11-2, 5ʹ-GGAAGAGATTCAAGTATTA-3ʹ; siSLC7A11-3, 5ʹ-GGAGCTTTCTCGAGAAAG-3ʹ; siATF3-1, 5ʹ-CCGCCTTTCATCTGGATTCTA-3ʹ; siATF3-2, 5ʹ-GCTGAACTGAAGGCTCAGATT-3ʹ. siATF3-3, 5ʹ-GCTGCAAAGTGCCGAAACA-3ʹ. Measurement of intracellular iron We used the FerroOrange kit (Dojindo, Japan) to detect intracellular Fe2 + levels in eESCs. The cells were incubated with a serum-free medium containing 1 µM FerroOrange reagent at 37℃ and 5% CO2 for 30 minutes. We obtained fluorescence images of the cells using a confocal microscope. Lipid peroxidation determination To quantify levels of lipid peroxidation, we used the LiperFluo and MDA Assay Kit from Dojindo (Dojindo, Japan) and Beyotime Biotechnology (Beyotime, China), respectively. For LiperFluo, we added LiperFluo reagent (5 µM) diluted in DMEM to the treated cells and incubated them for 30 minutes at 37℃ and 5% CO2. We evaluated lipid peroxidation levels using fluorescence microscopy (Nikon, Tokyo, Japan) by capturing photographs of the cells. For the MDA assay, cell lysis buffer for Western and IP (Beyotime Biotechnology, China) was used to lyse the cells on ice for 30 minutes. The absorbance was then measured at 532 nm using a plate reader in line with the manufacturer's instructions. Measurement of GSH We measured intracellular GSH levels in the treated cells using a GSH assay kit from Solarbio (Solarbio, Beijing, China). We lysed the cells entirely by performing four consecutive freeze-thaw cycles. We then mixed the cell lysate with the GSH reagent and measured the OD value of the resulting mixture at 412 nm using a plate reader. Transmission Electron Microscope (TEM) Samples were fixed with 2.5% glutaraldehyde (Servicebio, China) following a previously established protocol. After dehydration, we cut the samples into thin slices, which were then stained with uranyl acetate and lead citrate for contrast enhancement. Finally, we captured TEM images of the samples using the Hitachi TEM system (Japan). ChIP We used the DNA ChIP Assay Kit (Beyotime Biotechnology, China) to immunoprecipitate DNA according to the manufacturer's instructions. Collected cells samples fragments were diluted in ChIP dilution buffer, followed by incubation with Protein A + G Agarose/Salmon Sperm at 4ºC for 30 minutes. We later incubated the samples with anti-ATF3 antibody (Affinity, DF3110) or normal rabbit IgG overnight at 4℃. We purified the samples using a DNA purification kit from Beyotime Biotechnology (China). Finally, we used RT-qPCR to quantify the predicted DNA sequences in the immunoprecipitated samples. The primers used were as follows: SLC7A11, forward 5’-TTGAGCAACAAGCTCCTCCT-3’, reverse 5’-CAAACCAGCTCAGCTTCCTC-3’ Mouse endometriosis model Female C57BL/6 mice (7 weeks old) were randomly sorted into four groups (n = 6), endometriosis group, endometriosis + erastin group, endometriosis + IL-33-Ab group, and endometriosis + erastin + IL-33-Ab group. The endometriosis models were established as described previously[ 11 ]. Briefly, the uterus from a estradiol (0.2 ml/mouse) stimulated donor mouse, was minced into 1 mm 3 fragments and immediately injected subcutaneously into the peritoneal cavity of two recipient mice. The mice were respectively subjected to subcutaneous injections into the abdominal cavity with 300 µL of erastin (20 mg/kg) (MCE, Shanghai, China) alone or combined with IL-33-Ab 50 µg (R&D Systems, USA), or normal saline (Fig. 7 A). At day 10 post-surgery, all mice were sacrificed, The lesion volume was calculated using the formula V = 1/2Aa2; A: long radius, a: short radius. Ethical approval for all animal research was granted by the Institutional Animal Research Ethics Committee of Harbin Medical University. Statistical analysis Each experiment was conducted independently, with a total of three replicates. Statistical was analyzed using GraphPad Prism 8 (San Diego, USA), and were presented as mean with standard deviation (SD). The Student's t-test, one-way ANOVA test, and Two-way ANOVA were employed for comparing data in different experimental groups. Statistical significance was determined as p < 0.05. Non-significant differences were designated as "ns" ( p ≥ 0.05), whereas **** p < 0.0001, *** p < 0.001, ** p < 0.01, * p < 0.05 represents significant differences. Declarations ACKNOWLEDGEMENTS This work was supported by grants from the National Natural Science Foundation of China (82071619, 81671430 ). Conflict of interest disclosure: The authors have no conflicts of interest. Author Contribution Statement: Qiong Wu and ZongWen Liang contributed to the study design, experimental operation, manuscript writing, and literature review. JL, Honglin Wang, Ning Wang , Yingying Cao were responsible for clinical specimen collection and the establishment of animal modeling. YG, Zhi Li, Jing JIang and Xiaoming Feng were responsible for data gathering and analysis. ZZ participated in the study design and coordinated all aspects of the study. Ethics approval statement: This research was approved by the Ethical Committee of the Second Affiliated Hospital of Harbin Medical University. Funding statement: This researched was funded by National Natural Science Foundation of China No.82071619 and No.81671430. Data Availability Statement: The original contributions presented in the study are included in the article/ Supplementary Material, further inquiries can be directed to the corresponding author. References Zondervan KT, Becker CM, Missmer SA. Endometriosis. N Engl J Med. 2020;382(13):1244-56. Ye L, Whitaker LHR, Mawson RL, Hickey M. Endometriosis. Bmj. 2022;379(null):e068950. Vallvé-Juanico J, George AF, Sen S, Thomas R, Shin MG, Kushnoor D, et al. Deep immunophenotyping reveals endometriosis is marked by dysregulation of the mononuclear phagocytic system in endometrium and peripheral blood. BMC Med. 2022;20(1):158. Yoshino O, Izumi G, Shi J, Osuga Y, Hirota Y, Hirata T, et al. 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Mol oncol. 2016;10(1):113-25. Kato T, Yasuda K, Matsushita K, Ishii KJ, Hirota S, Yoshimoto T, et al. Interleukin-1/-33 Signaling Pathways as Therapeutic Targets for Endometriosis. Front Immunol. 2019;10:2021. Fu AK, Hung KW, Yuen MY, Zhou X, Mak DS, Chan IC, et al. IL-33 ameliorates Alzheimer's disease-like pathology and cognitive decline. Proc Natl Acad Sci U S A. 2016;113(19):E2705-13. Lu Y, Basatemur G, Scott IC, Chiarugi D, Clement M, Harrison J, et al. Interleukin-33 Signaling Controls the Development of Iron-Recycling Macrophages. IMMUNITY. 2020;52(5):782-93 e5. Gou Y, Li X, Li P, Zhang H, Xu T, Wang H, et al. Estrogen receptor β upregulates CCL2 via NF-κB signaling in endometriotic stromal cells and recruits macrophages to promote the pathogenesis of endometriosis. Hum reprod. 2019;34(4):646-58. Friedmann Angeli JP, Krysko DV, Conrad M. Ferroptosis at the crossroads of cancer-acquired drug resistance and immune evasion. NATURE REVIEWS CANCER. 2019;19(7):405-14. Tang R, Xu J, Zhang B, Liu J, Liang C, Hua J, et al. Ferroptosis, necroptosis, and pyroptosis in anticancer immunity. J Hematol Oncol. 2020;13(1):110. Li Y, Zeng X, Lu D, Yin M, Shan M, Gao Y. Erastin induces ferroptosis via ferroportin-mediated iron accumulation in endometriosis. Hum Reprod. 2021;36(4):951-64. Zhang M, Zhang T, Song C, Qu J, Gu Y, Liu S, et al. Guizhi Fuling Capsule ameliorates endometrial hyperplasia through promoting p62-Keap1-NRF2-mediated ferroptosis. J Ethnopharmacol. 2021;274:114064. Riegman M, Sagie L, Galed C, Levin T, Steinberg N, Dixon SJ, et al. Ferroptosis occurs through an osmotic mechanism and propagates independently of cell rupture. Nat Cell Biol. 2020;22(9):1042-8. Dai E, Han L, Liu J, Xie Y, Zeh HJ, Kang R, et al. Ferroptotic damage promotes pancreatic tumorigenesis through a TMEM173/STING-dependent DNA sensor pathway. Nature Communications. 2020;11(1). Kobayashi H, Yamashita Y, Iwase A, Yoshikawa Y, Yasui H, Kawai Y, et al. The ferroimmunomodulatory role of ectopic endometriotic stromal cells in ovarian endometriosis. Fertil Steril. 2012;98(2):415-22 e1-12. Liew FY, Girard JP, Turnquist HR. Interleukin-33 in health and disease. Nat Rev Immunol. 2016;16(11):676-89. Sanada S, Hakuno D, Higgins LJ, Schreiter ER, McKenzie AN, Lee RT. IL-33 and ST2 comprise a critical biomechanically induced and cardioprotective signaling system. J Clin Invest. 2007;117(6):1538-49. Erlebacher A. Immunology of the maternal-fetal interface. Annu Rev Immunol. 2013;31:387-411. Tan J, Xu T, Gou Y, Wang H, Liang Z, Cao Y, et al. CCL20/CCR6 axis mediates macrophages to promote proliferation and migration of ESCs by blocking autophagic flux in endometriosis. Stem Cell Res Ther. 2022;13(1):294. Samimi M, Pourhanifeh MH, Mehdizadehkashi A, Eftekhar T, Asemi Z. The role of inflammation, oxidative stress, angiogenesis, and apoptosis in the pathophysiology of endometriosis: Basic science and new insights based on gene expression. 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Thapsigargin induces expression of activating transcription factor 3 in human keratinocytes involving Ca2+ ions and c-Jun N-terminal protein kinase. Mol Pharmacol. 2010;78(5):865-76. Horne AW, Saunders PTK. SnapShot: Endometriosis. CELL. 2019;179(7):1677- e1. He D, Xu H, Zhang H, Tang R, Lan Y, Xing R, et al. Disruption of the IL-33-ST2-AKT signaling axis impairs neurodevelopment by inhibiting microglial metabolic adaptation and phagocytic function. IMMUNITY. 2022;55(1):159-73 e9. Tang D, Kang R, Berghe TV, Vandenabeele P, Kroemer G. The molecular machinery of regulated cell death. Cell res. 2019;29(5):347-64. Wan Y, Song Y, Chen J, Kong J, Gu C, Huang J, et al. Upregulated Fibulin-1 Increased Endometrial Stromal Cell Viability and Migration by Repressing EFEMP1-Dependent Ferroptosis in Endometriosis. Biomed res int. 2022;2022(null):4809415. Wang Z, Xu D, Ding HF, Kim J, Zhang J, Hai T, et al. Loss of ATF3 promotes Akt activation and prostate cancer development in a Pten knockout mouse model. ONCOGENE. 2015;34(38):4975-84. Shi Q, Hu B, Yang C, Zhao L, Wu J, Qi N. ATF3 Promotes Arsenic-Induced Apoptosis and Oppositely Regulates DR5 and Bcl-xL Expression in Human Bronchial Epithelial Cells. Int J Mol Sci. 2021;22(8). Niu X, Chen L, Li Y, Hu Z, He F. Ferroptosis, necroptosis, and pyroptosis in the tumor microenvironment: Perspectives for immunotherapy of SCLC. Semin cancer biol. 2022;86(Pt 3):273-85. Wang Y, Chen F, Zhou H, Huang L, Ye J, Liu X, et al. Redox Dyshomeostasis with Dual Stimuli-Activatable Dihydroartemisinin Nanoparticles to Potentiate Ferroptotic Therapy of Pancreatic Cancer. Small Methods. 2022;null(null):e2200888. Luo Q, Fan Y, Lin L, Wei J, Li Z, Li Y, et al. Interleukin-33 Protects Ischemic Brain Injury by Regulating Specific Microglial Activities. NEUROSCIENCE. 2018;385:75-89. Additional Declarations There is no duality of interest Supplementary Files SupplementaryFigurelegends.docx SupplementaryFigure1.tif SupplementaryFigure2.tif SupplementaryFigure3.tif SupplementaryFigure4.tif Cite Share Download PDF Status: Published Journal Publication published 11 Oct, 2023 Read the published version in Cell Death & Disease → 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-2835730","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":195930572,"identity":"d3dce0d7-a1cb-4efe-860f-c0b76940617d","order_by":0,"name":"Zongfeng 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University","correspondingAuthor":false,"prefix":"","firstName":"Yingying","middleName":"","lastName":"Cao","suffix":""}],"badges":[],"createdAt":"2023-04-19 09:01:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2835730/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2835730/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41419-023-06182-4","type":"published","date":"2023-10-11T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":40475776,"identity":"599699cf-4f97-49f6-9a8d-075bf5496e6d","added_by":"auto","created_at":"2023-07-24 14:04:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":908905,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIL-33/ST2 expression increased in eESCs when co-cultured with macrophages\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Representative immunohistochemical images staining with IL-33 and ST2 in normal endometrial tissue (EN) and ectopic endometriosis lesion tissue (EC). (original magnification 200× or 400×)\u003c/p\u003e\n\u003cp\u003e(B) Quantitative RT-PCR (qRT-PCR) was used to determine the mRNA levels of IL-33 and ST2 in EN and EC (n=8).\u003c/p\u003e\n\u003cp\u003e(C) Western blot was used to detect the protein levels of IL-33 and ST2 in normal endometrial stromal cells (nESCs) and ectopic endometrial stromal cells (eESCs).\u003c/p\u003e\n\u003cp\u003e(D) Quantitative RT-PCR (qRT-PCR) was used to determine the mRNA levels of IL-33 and ST2 in nESCs and eESCs.\u003c/p\u003e\n\u003cp\u003e(E) ELISA analysis of IL-33 in eESCs with or without macrophages co-culture treatment.\u003c/p\u003e\n\u003cp\u003e(F) Quantitative RT-PCR (qRT-PCR) was used to determine the mRNA levels of IL-33 and ST2 in eESCs with or without macrophages co-culture treatment.\u003c/p\u003e\n\u003cp\u003e(G) Western blot was used to detect the protein levels of IL-33 and ST2 in eESCs with or without macrophages co-culture treatment.\u003c/p\u003e\n\u003cp\u003e(H) Representative immunofuorescence (IF) images of IL-33 (red) in nESCs and eESCs, Nuclei were stained with DAPI (blue). (original magnification 200×)\u003c/p\u003e\n\u003cp\u003eData are presented as the mean ± SD, n=3 independent experiments. Statistical analysis was performed using Student’s t test. ****\u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001, ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05. IL-33 Interleukin-33, ST2 interleukin receptor-like 1 (IL1R-L1), M macrophages, con control.\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-2835730/v1/73a3886a955ff34439f9e8c6.png"},{"id":40477087,"identity":"88b836f7-37a5-4baa-8dd0-ae213003ed20","added_by":"auto","created_at":"2023-07-24 14:12:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2341064,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIL33/ST2 increased the survival rate and migration ability of eESCs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) The eESCs were treated with specified concentrations of human recombinant IL-33 protein (rIL-33) (25, 50, 100, and 200 ng/ml) for different times: 12, 24, 48, and 72 hours. CCK-8 assay was performed to detect cell viability in different groups.\u003c/p\u003e\n\u003cp\u003e(B) Quantitative RT-PCR (qRT-PCR) was used to determine the relative levels of IL-33 and ST2 mRNA in eESCs transfected with si-ST2 (50nM), si-con (50nM), or empty reagent for 48 hours.\u003c/p\u003e\n\u003cp\u003e(C) Western blot was used to determine the protein levels of IL-33 and ST2 in eESCs transfected with si-ST2 (50nM) or si-con (50nM) for 48 hours.\u003c/p\u003e\n\u003cp\u003e(D) Transwell migrantion assay was performed to detect the migrant ability of eESCs treated with or without macrophages co-culture. Cartoon picture showed the experimental progress. (original magnification 200×)\u003c/p\u003e\n\u003cp\u003e(E, F) Transwell migrantion assay was performed in rIL-33 (25 ng/ml) treated eESCs (E) and si-ST2 (50 nM) transfected eESCs (F). (original magnification 200×).\u003c/p\u003e\n\u003cp\u003e(G) The wound healing assay was conducted in eESCs transfected with si-ST2 (50nM) and control group. (original magnification 40×).\u003c/p\u003e\n\u003cp\u003e(H) Cloning assay was performed in si-ST2 (50 nM) transfected eESCs treated with rIL-33 (25 ng/ml) or macrophages co-culture. (original magnification 40×).\u003c/p\u003e\n\u003cp\u003eData are presented as the mean ± SD, n=3 independent experiments. Statistical analysis was performed using Student’s t test (B, C, D, G) or 2way ANOVA (H). ****\u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001, ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001, *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, ns, non-significant. sicon negative control siRNA, siST2 siRNA targeting ST2, M macrophages co-culture treatment.\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-2835730/v1/5618e9f554a47cbb48009262.png"},{"id":40477092,"identity":"cbbcca29-0f9d-44d3-a08c-9b258f720d36","added_by":"auto","created_at":"2023-07-24 14:12:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1287696,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIL33/ST2 inhibited ferroptosis in eESCs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Cell viability was detected by CCK-8 assay in si-ST2 (50 nM) transfected eESCs with different inhibitors treatment (erasin, 10 μM; Ferrostatin-1, 1 μM; ZVAD-FMK, 10 μM; Nerostatin, 10 μM) for 24 hours.\u003c/p\u003e\n\u003cp\u003e(B) Western blot was used to detect the protein levels of ACSL4, SLC7A11, and GPX4 in different groups of eESCs treated with rIL-33 (25 ng/ml), si-ST2 (50nM), or si-ST2 (50nM)+Ferrostatin-1 (1 μM).\u003c/p\u003e\n\u003cp\u003e(C) Cell viability was measured by CCK-8 assay in eESCs treated with different concentration of erasin (5, 10, 15, and 20 μM) for 12, 24, or 48 hours.\u003c/p\u003e\n\u003cp\u003e(D) Intracellular Fe\u003csup\u003e2+ \u003c/sup\u003ewere detected through treating eESCs by 1μM FerroOrange after indicated treatment: rIL33(25 ng/ml) and/or erastin (10 μM) and/or si-ST2 (50 nM) (original magnification 200×).\u003c/p\u003e\n\u003cp\u003e(A) LiperFluo reagent (5 μM) were used to detect intracellular lipid peroxidation levels in eESCs with indicated treatment (same as treatment in D). (original magnification 200×).\u003c/p\u003e\n\u003cp\u003e(F, G) The MDA levels (F) and GSH levels (G) in eESCs were measured after specified treatment(same as treatment in D).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(H) Transmission Electron Microscope (TEM) was used to observe the morphological changes of eESCs mitochondria. black arrowheads: normal mitochondria. white arrowheads: shrunken mitochondria. The scale bar = 5.0 μm (Upper row). The scale bar = 2.0 μm (Lower row).\u003c/p\u003e\n\u003cp\u003eData are presented as the mean ± SD, n=3 independent experiments. Statistical analysis was performed using Student’s t test (A) or one-way ANOVA (B, F, G). ****\u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001, ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, ns, non-significant.\u003c/p\u003e\n\u003cp\u003eFer-1 Ferrostatin-1, Nec Necrostatin-1, ZVAD-FMK, benzyloxycarbonyl-Val-Ala-Asp (OMe)-fluoromethylketone, ACSL4 acyl-CoA synthetase long-chain family member 4, SLC7A11 solute carrier family 7 member 11, GPX4 glutathione peroxidase 4, MDA malondialdehyde, GSH glutathione.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-2835730/v1/b46fd38bb525b880079253a6.png"},{"id":40475783,"identity":"9fd9afb5-803b-4263-9567-cc207cb6b206","added_by":"auto","created_at":"2023-07-24 14:04:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1178270,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIL33/ST2 inhibited ferroptosis through regulating SLC7A11 expression in eESCs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Pearson’s test was used to analyze the relationship between the expression levels of IL-33 and SLC7A11 mRNA in EC tissues (n=8).\u003c/p\u003e\n\u003cp\u003e(B) EESCs were treated with specified concentrations of GSH (0.5, 1.0, 1.5, 2.0, 2.5, and 3.0 mM) for 2 or 24 hours. CCK-8 assay was used to detect cell viability.\u003c/p\u003e\n\u003cp\u003e(C) Western blot was used to determine the efficiency of siRNA-mediated knockdown of SLC7A11\u0026nbsp; in eESCs (50 nM).\u003c/p\u003e\n\u003cp\u003e(D-H) EESCs underwent indicated treatment: rIL-33(25 ng/ml) and/or transfection with si-SLC7A11 (50 nM); GSH (1.5 mM) and/or transfection with si-ST2 (50 nM).\u003c/p\u003e\n\u003cp\u003e(D, E) Cell viability was detected by CCK-8 assay.\u003c/p\u003e\n\u003cp\u003e(F) Western blot was used to detect the protein levels of SLC7A11, and GPX4.\u003c/p\u003e\n\u003cp\u003e(G, H) Determination of intracellular MDA (G) and GSH levels (H).\u003c/p\u003e\n\u003cp\u003e(I) FerroOrange reagent (1 μM) was used to measure intracellular Fe\u003csup\u003e2+\u003c/sup\u003econcentration. (original magnification 200×).\u003c/p\u003e\n\u003cp\u003e(J) LiperFluo reagent (5 μM) was used to determine intracellular lipid peroxidation level. (original magnification 200×).\u003c/p\u003e\n\u003cp\u003eData are presented as the mean ± SD, n=3 independent experiments. Statistical analysis was performed using Student’s t test (C) or one-way ANOVA (D, E, G, H) or Two way ANOVA (F). ****\u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001, ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, ns, non-significant. siSLC, siRNA targeting SLC7A11.\u003c/p\u003e","description":"","filename":"figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-2835730/v1/2e6fad4299f2bd811ca35544.png"},{"id":40479200,"identity":"ad7db422-0123-4149-8de6-9e89c83539f7","added_by":"auto","created_at":"2023-07-24 14:28:15","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":377062,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e5IL33/ST2 promoted SLC7A11 expression through regulating ATF3\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Venn graph showed the intersection of the differential expression gene in Macrophage co-culture treated eESCs and Ferroptosis marker (data originated from GSE 19834 and FerroDb).\u003c/p\u003e\n\u003cp\u003e(B) Representative immunohistochemical images staining with ATF3 in normal endometrial tissue (n=8) and ectopic endometriosis lesion tissue (n=8) (original magnification 200×).\u003c/p\u003e\n\u003cp\u003e(C) Western blot was used to detect the protein levels of ATF3 in nESCs and eESCs.\u003c/p\u003e\n\u003cp\u003e(D) Western blot was used to detect the protein levels of ATF3 in eESCs treated with and without rIL-33 (25 ng/ml).\u003c/p\u003e\n\u003cp\u003e(E) The ChIP-seq data previously reported were reanalyzed.(GSM1917770, ENCSR632DCH_2, GSM803508, GSM803503)\u003c/p\u003e\n\u003cp\u003e(F) Western blot was used to detect the protein levels of SLC7A11 and GPX4 in different groups: si-control (50 nM), si-ATF3 (50 nM), si-ST2 (50 nM) and double transfection of si-ATF3 (50 nM) and si-ST2 (50 nM).\u003c/p\u003e\n\u003cp\u003e(G) Western blot was used to determine the knockdown efficiency of si-ATF3 in eESCs.\u003c/p\u003e\n\u003cp\u003e(H) Chromatin immunoprecipitation assay (CHIP) was used to verify the binding region of ATF3 and SLC7A11 promoter.\u003c/p\u003e\n\u003cp\u003eData are presented as the mean ± SD, n=3 independent experiments. Statistical analysis was performed using Student’s t test. ****\u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001, ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01. ATF3, activating transcription factor. siATF3 siRNA targeting ATF3, siAT+siST siRNA targeting ATF and siRNA targeting ST2.\u003c/p\u003e","description":"","filename":"figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-2835730/v1/b1154546b0b4613db87ca267.png"},{"id":40477086,"identity":"eb8399af-4257-4e5a-83ac-8cca8f6cec25","added_by":"auto","created_at":"2023-07-24 14:12:15","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":480773,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIL33/ST2 inhibited ATF3 via P38/JNK pathway\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Bubble chart showed the predicted ATF3 interaction protein (data originated from String database).\u003c/p\u003e\n\u003cp\u003e(B) Western blot was used to detect the protein levels of JNK, P38, phosphorylated JNK, and phosphorylated P38 in eESCs treated with and without rIL-33 (25 ng/ml).\u003c/p\u003e\n\u003cp\u003e(C) Western blot was used to detect the protein levels of ATF3 in eESCs treated with si-ST2 and/or SB202190 (P38 inhibitor) (20 μM).\u003c/p\u003e\n\u003cp\u003e(D, E) Determination of MDA (D) and GSH (E) levels in eESCs treated with the specified treatment for 24 hours: ; SB202190(20 μM); si-ST2 and si-ST2+SB202190 (20 μM).\u003c/p\u003e\n\u003cp\u003e(F, G) FerroOrange (F) and LiperFluo (G) were used to determine intracellular Fe\u003csup\u003e2+ \u003c/sup\u003econcentration and lipid peroxidation levels in si-ST2 transfected eESCs treated with or without SB202190. (original magnification 200×).\u003c/p\u003e\n\u003cp\u003eData are presented as the mean ± SD, n=3 independent experiments. Statistical analysis was performed using one-way ANOVA. ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, ns, non-significant. JNK, c-Jun N-terminal protein kainse. P38, p38 MAPK, p38 mitogen activated protein kinases. p-JNK, phosphorylated c-Jun N-terminal protein kainse. p-p38, phosphorylated p38 mitogen activated protein kinases. GAPDH, Glyceraldehyde-3-phosphate dehydrogenase. SB, SB202190, P38 inhibitor.\u003c/p\u003e","description":"","filename":"figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-2835730/v1/3048de157823c84bf5e6e468.png"},{"id":40475778,"identity":"8d9dd835-d6ca-4049-b11f-25be64e0b48f","added_by":"auto","created_at":"2023-07-24 14:04:15","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":2485791,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCollaborative treatment of IL-33-Ab and erastin alleviated endometriosis in mice model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Schematic diagram showing endometriosis mice endometriosis model establishment and therapy process.\u003c/p\u003e\n\u003cp\u003e(B, C) Representative photo of ectopic lesions in four groups (n=6) at day 10.\u003c/p\u003e\n\u003cp\u003e(D) Line chart for the mice weight in four groups (n=6) at different time points, which showed no significant change.\u003c/p\u003e\n\u003cp\u003e(E, F) Comparison of the volume (E) and weight (F) of endometriosis ectopic lesions in four groups at day 10.\u003c/p\u003e\n\u003cp\u003e(G) Hematoxylin-eosin staining (H\u0026amp;E staining) showing that glandular and stromal structures of endometriosis ectopic lesions in four groups.(original magnification 200×).\u003c/p\u003e\n\u003cp\u003e(H, I) Representative immunohistochemical images staining with ST2 (H) and SLC7A11 (I) in four groups endometriosis ectopic lesions.(original magnification 200×).\u003c/p\u003e\n\u003cp\u003eData are presented as the mean ± SD, n=3 independent experiments. Statistical analysis was performed using Two way ANOVA (D) and one-way ANOVA (E, F). ****\u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001, ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001, *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, ns, non-significant. E2, 17-β-estradiol-3-benzoate. \u003cem\u003ei\u003c/em\u003e.\u003cem\u003ep\u003c/em\u003e. intraperitoneal injection. era, erastin.\u003c/p\u003e","description":"","filename":"figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-2835730/v1/d4272a5eb9a89f1be90fc9e4.png"},{"id":40477091,"identity":"2364bb69-f898-467a-a1e3-b682e33fd884","added_by":"auto","created_at":"2023-07-24 14:12:15","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":4067212,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCartoon illustration of IL-33/ST2 derived from macrophages inhibiting ferroptosis of ESCs via p38/JNK/ATF3/SLC7A11 pathway\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-2835730/v1/38151fb5f1f168cb5632e052.png"},{"id":44412785,"identity":"5daf4f5f-3105-44ce-9acd-803d672b81e1","added_by":"auto","created_at":"2023-10-11 07:07:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4966256,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2835730/v1/f12fcec8-2c98-4141-bc74-8c1e3f1b46fe.pdf"},{"id":40478160,"identity":"c757b758-fb18-43ce-b876-16a03ffe83b2","added_by":"auto","created_at":"2023-07-24 14:20:15","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":10513,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"SupplementaryFigurelegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-2835730/v1/8f7592aca0cd1301a4f04fea.docx"},{"id":40480690,"identity":"c55d51bf-6acd-401e-87b9-977eb98dfc38","added_by":"auto","created_at":"2023-07-24 14:36:15","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":437368,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-2835730/v1/ee918f20103e7c8993aa8ba6.tif"},{"id":40475788,"identity":"cde7babe-5c02-425d-9315-a059a21674ec","added_by":"auto","created_at":"2023-07-24 14:04:17","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":634404,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-2835730/v1/2ba8788954472d64f1cd8a73.tif"},{"id":40475785,"identity":"e95ddf49-39a3-4071-833c-82e116836eb9","added_by":"auto","created_at":"2023-07-24 14:04:15","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":95446,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure3.tif","url":"https://assets-eu.researchsquare.com/files/rs-2835730/v1/fae4258d44422ce4923d6133.tif"},{"id":40475787,"identity":"0400705f-1334-45ab-aef4-16e327c25e80","added_by":"auto","created_at":"2023-07-24 14:04:16","extension":"tif","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":144258,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure4.tif","url":"https://assets-eu.researchsquare.com/files/rs-2835730/v1/08bbf76951e6b0f3531ca780.tif"}],"financialInterests":"There is no duality of interest","formattedTitle":"Macrophages originated IL33/ST2 inhibits ferroptosis in endometriosis via the ATF3/SLC7A11 axis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEndometriosis is a chronic inflammatory disease that affects nearly 10% of females of reproductive age worldwide[1]. Multiple theories, including ectopic implantation, coelomic metaplasia, and immune factors, have been proposed to elucidate the pathophysiology of endometriosis[2]. Notable adaptations in the local immune microenvironment of endometriosis lesions have been detected, including the infiltration and differentiation of diverse immune cells and the aggregation of chemokines and cytokines[3]. Macrophages are reported to be one of the predominant cells present in ectopic endometrial lesions, and interleukin-1\u0026beta; (IL-1\u0026beta;) promotes ectopic endometrial stromal cells (eESCs) proliferation[4, 5]. IL-8-Ab reduced the volume of lesions and ameliorated fibrosis and adhesion in monkeys endometriosis models[6]. The interplay between infiltrated immune cells and eESCs prompts genetic and epigenetic modifications in the eESCs. Subsequently, these adaptations in eESCs result in molecular changes and dysfunction in immune cells.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInterleukin-33 (IL-33), a member of the IL-1\u0026beta; family, is secreted by macrophages. Previous studies have indicated that IL-33 has the potential to stimulate tumor cells proliferation and neovascularization in ovarian cancer[7]. Knockout of IL-33 in mouse endometriosis models has led to a significant decrease in endometriotic lesion volume[8]. It is also worth mentioning that IL-33 induces macrophage anti-inflammatory polarization and stimulates the formation of Splenic red pulp macrophages (RPMs) that regulate erythrocyte homeostasis and support iron recycling[9, 10]. Our team has also discovered a significant promoting effect of macrophages on endometriosis[11]. We thus postulate that macrophage-derived IL-33 may regulate eESCs survival, which ultimately advance the progression of endometriosis. However, the the complete role of IL-33 in development of endometriosis requires further exploration.\u003c/p\u003e\n\u003cp\u003eFerroptosis is a newly discovered programmed cell death process characterized by iron-dependent accumulation of reactive oxygen species (ROS) and lipid peroxidation[12, 13]. The key molecule in ferroptosis, SLC7A11, is a component of the L-Cystine/L-Glutamic Acid reverse transporter system (Xct) which mediates the transmembrane transport of glutamate and cysteine. Cysteine from the extracellular space triggers glutathione (GSH) synthesis, maintaining the GSH/GSSG redox balance. Glutathione peroxidase 4 (GPX4) also plays a critical role in ferroptosis by efficiently reducing lipid hydroperoxides that accumulate in the membrane of cells undergoing ferroptosis[14, 15, 16]. A study reported that macrophages within pancreatic ductal adenocarcinoma (PDAC) exhibit ferroptosis, which suppresses macrophage defense against tumor cells[17]. Although, in endometriotic lesions, period bleeding and accumulation of antiquated blood establish a iron-enriched microenvironment, eESCs exhibited more tolerance to ferroptosis, leading researchers hypothesizing that there are certain mechanisms in eESCs that confer resistance to ferroptosis[18]. However, the specific mechanisms remain unclear.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study explores the functional significance of ferroptosis in the pathogenesis of endometriosis. Our results reveal that the cytokine IL-33, secreted by macrophages, plays a crucial role in upregulating the expression of SLC7A11 by inhibiting ATF3 in eESCs. This activity hinders eESCs ferroptosis and thereby facilitates the development of endometriosis. In addition, we established a mouse model of endometriosis and employed a collaborative therapy involving IL-33 antibodies and a ferroptosis inhibitor, erastin. This innovative approach successfully combines immunotherapy and ferroptosis therapy for the treatment of the disease.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eIL-33/ST2 expression increased in eESCs when co-cultured with macrophages\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRecent researches have shown that females with endometriosis\u0026nbsp;exhibit elevated levels\u0026nbsp;of Interleukin-33 (IL-33) in circulation when compared to healthy females[19]. This finding piqued our curiosity about the effect IL-33 has on the progression of endometriosis. To verify the expression of IL-33 and ST2 (interleukin receptor-like 1), a widely accepted receptor of IL-33, in endometriosis (EMs), we employed immunohistochemistry (IHC) assays in both normal endometrial (EN) and ectopic endometrial tissues (EC)[20]. Figure 1A illustrates that the concentration of IL-33 in EC tissues was significantly higher when compared with that in EN tissues (Fig.\u0026nbsp;1A). The RT-qPCR results support this finding (Fig.\u0026nbsp;1B).\u0026nbsp;At\u0026nbsp;the cellular level, we successfully extracted, cultured and identified ectopic endometrial stromal cells (eESCs) and normal endometrial stromal cells (nESCs) (Supplementary Fig.\u0026nbsp;1). Western blot and RT-qPCR data both indicate a significant increase in the expression levels of IL-33 and ST2 in eESCs when compared with nESCs (Fig.\u0026nbsp;1C, D). The findings are further supported by results from the immunofluorescence assay (IF) performed both on eESCs and nESCs, which revealed an increase in fluorescence intensity of IL-33 and ST2 in eESCs (Figure.\u0026nbsp;1H).\u003c/p\u003e\n\u003cp\u003eThe widely accepted theory suggests that the alternation of immune micro-environment specifically macrophage differentiation, plays a critical role in the development of endometriosis[21]. Considering the mechanism responsible for the upregulation of IL-33 expression, we note that various immune cells, including macrophages, can produce IL-33. And based on our previous studies which indicate that macrophages are enriched around eESCs, we speculate macrophages may be responsible for the high levels of IL-33 and ST2 in eESCs[11, 22]. To test this hypothesis, we induced acute monocytic leukemia cells (THP-1 cells) differentiation into macrophages using PMA (200nM) in succession (Supplementary Fig.\u0026nbsp;2). The ELISA assay demonstrated that the concentration of IL-33 was higher in macrophage cell medium than in eESCs cell medium (Supplementary Fig. 3), confirming that macrophages can secrete IL-33. We then co-cultured IL-33 knockdown eESCs with macrophages and measured the level of IL-33 in eESCs lysate using ELISA assays. The outcomes showed a notable increase in IL-33 levels among the group of eESCs co-cultured with macrophages, suggesting that IL-33 produced by macrophages can be transported into eESCs through intercellular communication (Fig. 1E). In addition, both western blot and RT-qPCR assays exhibited an increase in IL-33 and ST2 expression in initial eESCs that were co-cultured with macrophages, but not in eESCs alone\u0026nbsp;(Fig.\u0026nbsp;1F, G). These findings suggest that macrophages enhance the level of IL-33 in eESCs not only through intercellular transmission but also by inducing eESCs to produce IL-33 autonomously. The results of these experiments reveal that macrophages induce higher levels of IL-33 and ST2 in eESCs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIL33/ST2 increased the survival rate and migration ability of eESCs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo elucidate the role of IL-33 secreted by macrophages on eESCs, human recombinant IL-33 protein (rIL-33) was added to the culture medium of eESCs at different concentrations (0-2.5-5-10-20 μM). Then we evaluated cell viability after 12, 24, and 48 hours respectively to determine the optimal concentration and time parameters. The 10μl/ml concentration of IL-33 for 24 hours showed the most substantial increase in cell viability, and this mode was used in subsequent experiments (Fig.\u0026nbsp;2A). Additionally, eESCs were transfected with siRNA targeting ST2, and the efficiency of transfection was confirmed by employing both RT-qPCR and Western-blotting methods (Fig.\u0026nbsp;2B, C).\u0026nbsp;Next, eESCs were treated with rIL-33 or macrophage co-culture. The cell migration ability was evaluated using the transwell assay, and both treatments showed a significant increase in eESCs migration (Fig.\u0026nbsp;2D, E). Furthermore, upon the knockdown of ST2, the migration capability of eESCs was attenuated\u0026nbsp;(Fig.\u0026nbsp;2F, G).\u0026nbsp;Furthermore, the cell colony formation assay showed that both rIL-33 and macrophage co-culture treatment markedly improved eESCs viability. Conversely, si-ST2 eESCs revealed reduced cell viability, as evidenced by the results of this assay. (Fig.\u0026nbsp;2H).\u0026nbsp;Collectively, these experimental findings suggest that IL-33 plays a critical role in the survival and migration of eESCs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIL33/ST2 inhibited ferroptosis in eESCs.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEndometriosis involves various forms of cell death, including apoptosis, necroptosis, autophagy, and ferroptosis[23]. To examine whether IL-33 promotes eESCs survival by regulating cell death, we compared the effects of various cell death inhibitors on si-IL33-treated eESCs. As presented in Figure. 3A, only ferrostatin-1 had a significant effect in rescuing the si-IL33-induced decline in eESC viability, while well-known apoptosis and necroptosis inhibitors ZVAD-FMK and necrostatin-1 showed little impact (Fig.\u0026nbsp;3A).\u0026nbsp;Therefore, we presume that IL-33 may elevate eESC survival by inhibiting ferroptosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNext, we tested the expression levels of ferroptosis markers in eESCs treated with rIL-33 or siST2. The addition of rIL-33 group showed elevated levels of SLC7A11 and GPX4 but reduced levels of ACSL4 compared to the control group. Conversely, in the ST2 knockdown group, and the ferroptosis inhibitor Ferrostatin-1 (Fer-1) rescued these effects (Fig.\u0026nbsp;3B).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo further explore IL33's influence on ferroptosis progression, we treated eESCs with erastin to induce ferroptosis (Fig.\u0026nbsp;3C). But the addition of IL-33 rescued the increase in Fe2+ concentration induced by erastin. And the protective effect of IL-33 disappeared in the ST2 knockdown group (Fig.\u0026nbsp;3D).\u0026nbsp;Additionally, as ferroptosis is closely associated with lipid peroxidation, we investigated the effects of IL-33 on lipid peroxidation induced by ferroptosis in eESCs. As shown in Figure. 3E, the fluorescence intensity in eESCs decreased after rIL-33 was added. On the other hand, the si-ST2 transfection attenuated the effect of IL-33 in reducing lipid peroxidation (Fig.\u0026nbsp;3E). MDA, a lipid peroxidation product, increased in the erastin group but was restrained by rIL-33 (Fig.\u0026nbsp;3F).\u0026nbsp;Furthermore, erastin exhaustion depleted GSH, a classic antioxidant in eESCs, while the addition of IL-33 restored it (Fig. 3G). However, the protective effect of IL-33 was not observed in the ST2 knockdown group (Fig. 3\u0026nbsp;F, G).\u003c/p\u003e\n\u003cp\u003eFerroptosis is closely linked to mitochondrial dysfunction and reduced mitochondrial redox capacity. Through transmission electron microscopy (TEM), we observed that erastin-treated eESCs exhibited significant mitochondrial structural alterations such as atrophy and increased membrane density, whereas IL-33 protected mitochondrial structure from ferroptosis-induced damage\u0026nbsp;(Fig.\u0026nbsp;3H).\u0026nbsp;Overall, the results demonstrated the anti-ferroptosis role of IL-33/ST2 in eESCs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIL33/ST2 inhibited ferroptosis through regulating SLC7A11 expression in eESCs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the underlying mechanism of how IL-33 inhibits ferroptosis in eESCs, we conducted a correlation analysis between IL-33 and several ferroptosis marker molecules. The Pearson's test confirmed a statistically significant association between IL-33 and SLC7A11\u0026nbsp;expression (Fig.\u0026nbsp;4A).\u0026nbsp;Although we also observed a significant correlation between IL-33 and GPX4 expression (Supplementary Fig.\u0026nbsp;4), however, studies have previously revealed GPX4 as a downstream component of the SLC7A11 pathway during the ferroptosis process. Therefore, we focused on investigating the function of SLC7A11 in our subsequent studies.\u0026nbsp;The expression of SLC7A11 was notably enhanced following treatment with rIL-33\u0026nbsp;(Fig.\u0026nbsp;3D).\u0026nbsp;Given that SLC7A11 plays a crucial role in forming the Glutamate cysteine transporter system (Xct) which is responsible for GSH synthesis, we supplemented eESCs with GSH to present the result of excessive expression of SLC7A11\u0026nbsp;(Fig.\u0026nbsp;4B).\u003c/p\u003e\n\u003cp\u003eTo further investigate the role that SLC7A11 plays in the process of IL-33 inhibiting ferroptosis, we knocked down SLC7A11 in eESCs. Consequently, cell viability was considerably reduced, and rIL-33 was unable to rescue the declining cell viability (Fig.\u0026nbsp;4C, D). Moreover, the addition of GSH rescued the reduced cell viability induced by si-ST2\u0026nbsp;(Fig.\u0026nbsp;4E). Theses data suggested that SLC7A11 has a downstream effect of the IL-33 pathway.\u0026nbsp;In support of these findings, the Western blot results showed an increased protein level of GPX4 in the si-SLC7A11 group, further confirming the involvement of SLC7A11 in the IL-33-mediated suppression of ferroptosis.\u0026nbsp;Additionally, the Western blot analysis indicated that GSH could prevent ferroptosis in eESCs by modulating the alternation in ferroptosis marker molecules induced by si-ST2\u0026nbsp;treatment (Fig.\u0026nbsp;4F). These results were further substantiated through the evaluation of \u0026nbsp;MDA content, GSH levels, intracellular Fe2+ concentration, and lipid peroxidation\u0026nbsp;(Fig.\u0026nbsp;4G, H, I, J).\u0026nbsp;Overall, our results demonstrated that IL-33/ST2 inhibits ferroptosis by modulating SLC7A11 expression in eESCs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIL33/ST2 promoted SLC7A11 expression through regulating ATF3\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo explore the mechanism responsible for the IL-33/ST2-mediated activation of SLC7A11 in endometriosis, we first identified differentially expressed genes (DEGs) from the dataset of endometriosis obtained from the GEO database (GSE19834). This dataset compared the gene expression profiles of eESCs cultured alone and eESCs co-cultured with macrophages. A Venn diagram analysis was then conducted to screen for ferroptosis marker genes (listed in the FerroDb database) among the DEGs identified through this comparison. This analysis revealed IL-33 and ATF3 as two significant regulators of ferroptosis in endometriosis (Fig.\u0026nbsp;5A).\u0026nbsp;ATF3 is a negative transforming factor involved in various diseases[24, 25]. And ATF3 was found to regulate SLC7A11 expression[26]. Hence, we aimed to test if ATF3 participates in the IL-33-actived process of SLC7A11 expression in endometriosis. Our findings illustrated that the level of ATF3 was lower in EC tissues than in EN tissues\u0026nbsp;(Fig.\u0026nbsp;5B), and ATF3 protein level in eESCs was also lower than that in nESCs\u0026nbsp;(Fig.\u0026nbsp;5C). Interestingly, when rIL-33 was added to eESCs, the protein level of ATF3 was further reduced. This indicates that IL-33 negatively regulates ATF3 (Fig.\u0026nbsp;5D).\u003c/p\u003e\n\u003cp\u003eTo determine the precise role that ATF3 plays in the regulatory process of IL-33 on SLC7A11, we conducted single knockdowns of ATF3, as well as dual knockdowns of ST2 and ATF3 in eESCs. The Western blot results demonstrated that si-ATF3 was effective in reversing the decrease in SLC7A11 and GPX4 expression induced\u0026nbsp;by\u0026nbsp;si-ST2 (Fig.\u0026nbsp;5G, F).\u0026nbsp;Next, the ChIP-seq analysis revealed the substantial presence of ATF3-binding peaks in the promoter sites of SLC7A11. Such findings indicate that ATF3 plays a crucial role in controlling the transcription of SLC7A11 by binding with high affinity to its promoter (data derived from GSM1917770, ENCSR632DCH_2, GSM803508, GSM803503)\u0026nbsp;(Fig.\u0026nbsp;5E).\u0026nbsp;We then performed chromatin immunoprecipitation assays (ChIP) to confirm the direct binding of ATF3 and the SLC7A11 promoter (Fig.\u0026nbsp;5H).\u0026nbsp;Collectively, we have confirmed that ATF3 serves as a negative transcription factor that impedes IL-33/ST2 from elevating SLC7A11.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIL33/ST2 inhibited ATF3 through the P38/JNK signaling pathway\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe above\u0026nbsp;results indicate that IL-33/ST2 can stimulate SLC7A11 expression by down-regulating ATF3. However, an important question followed is how IL-33/ST2 modulates the expression of ATF3. By analyzing the interacting protein partners of ATF3 through the String online database, we discovered a strong correlation between ATF3 and P38 MAPK (Fig.\u0026nbsp;6A). A study proposed that Phlorofucofuroeckol A (PFF-A) has anti-cancer properties by inducing ATF3 expression via the p38 MAPK/JNK-mediated pathway in human colorectal cancer cells[27]. Further evidence from Spohn indicates that stimulation of HaCaT cells with thapsigargin triggers a signaling pathway that activates JNK and biosynthesis of ATF3 activity in keratinocytes. Based on these evidences, it is plausible that ATF3 may be regulated by the p38 MAPK/JNK pathway[28].\u0026nbsp;We further investigated the effects of rIL-33 on the P38 MAPK/JNK signaling pathway. Intriguingly, our findings revealed that treatment with rIL-33 suppressed the phosphorylation of both P38 MAPK and JNK (Fig.\u0026nbsp;6B). Moreover, our findings suggested that a specific inhibitor of p38 MAPK phosphorylation, SB202190, elicited a similar decrease in ATF3 expression as observed with IL-33 treatment. Furthermore, in eESCs treated with SB202190, we observed that ATF3 levels did not decrease, as observed in the si-ST2 treatment group \u0026nbsp;(Fig.\u0026nbsp;6C).\u0026nbsp;Importantly, the results of tests measuring MDA content, GSH levels, intracellular Fe2+ concentration, and lipid peroxidation consistently showed that SB202190 has the ability to reverse the ST2 knockdown’ effect in inducing ferroptosis.\u0026nbsp;(Fig.\u0026nbsp;6D-G).\u0026nbsp;In summary, our findings suggest that IL-33/ST2 can suppress ATF3 by modulating the P38 MAPK/JNK signaling pathway, thereby promoting SLC7A11 expression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCollaborative treatment of IL-33-Ab and erastin alleviated endometriosis in mice model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe have shown that knockdown of IL-33 inhibits proliferation, migration, and ferroptosis of EESCs in vitro, so we hypothesize that IL-33-Ab can also promote ferroptosis and reduce ectopic lesions in vivo. Surprisingly, our previous results have shown that Erastin can significantly reduce ectopic lesions. We therefore propose a novel strategy for combining erastin with IL-33-Ab to achieve synergistic therapy. This innovative approach promises a new direction for managing endometriosis.\u003c/p\u003e\n\u003cp\u003eTo achieve this objective, we successfully established mice models of endometriosis and divided them into four groups: control, erastin, IL-33-Ab, and IL-33-Ab plus erastin group as represented in Figure 7A (Fig. 7A). Notably, both the application of IL-33-Ab and erastin restrained the development of endometriosis. Moreover, their combined treatment was found to be more efficient in reducing the severity of the disease (Figure 7B, C, E, F). Hematoxylin and eosin (HE) staining revealed contrasting tissue structures of endometriosis in the four groups (Fig. 7G). Additionally, IHC assays demonstrated a decline in the expression levels of ST2 and SLC7A11 in the IL-33-Ab and erastin treatment groups, while their combination group exhibited a more significant effect (Fig. 7H, I). By exploring the effect of IL-33-Ab and erastin in inducing ferroptosis in mice models of endometriosis, our findings indicate their potential for treating endometriosis. Furthermore, the combined treatment of IL-33-Ab and erastin on an endometriosis mouse model resulted in a reinforced therapeutic effect for the disease. This inspires a novel therapeutic strategy and lays the foundation for research in the field of the collaboration of immunotherapy and ferroptosis therapy.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eEndometriosis has been found to be associated with various factors, including hereditary, retrograde menstruation, coelomic epithelial metaplasia, and immune factors[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Research has indicated that macrophages play a crucial role in promoting colonization of endometriosis lesions by facilitating angiogenesis and matrix remodeling[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Our team has previously discovered that CCL20/CCR6 signaling axis mediated macrophages can promote proliferation and migration of ESCs by blocking autophagic flux in endometriosis[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHere, we found that interleukin-33 (IL-33) has a significant high expression in eESCs co-cultured with macrophages, contributing to eESCs' survival and migration. This suggests that IL-33 derived from macrophages promotes the progression of endometriosis.\u003c/p\u003e \u003cp\u003eDifferent types of cell death is associated with endometriosis, such as necroptosis, autophagy, apoptosis, and ferroptosis[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The accumulation of endometrial debris and period bleeding creates an iron overload environment that promotes ferroptosis[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. But it seems that eESCs are more tolerant of high iron concentration[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The role of ferroptosis in endometriosis has not yet been systematically examined.\u003c/p\u003e \u003cp\u003eOur study revealed that Fer-1 can effectively hinder the altered expression of ferroptosis markers brought by si-ST2. Treatment with rIL-33 also restricted ferroptosis in eESCs previously treated with erastin, as evidenced by the reduced levels of Fe2+, lipid peroxidation, MDA, increased level of GSH and specific mitochondrial structural change.\u003c/p\u003e \u003cp\u003eIn addition, we conducted a screening of several molecules that were significantly altered following IL-33 treatment and identified a tight correlation between SLC7A11 and IL-33. The protective effect of IL-33 against ferroptosis was resisted by knockout of SLC7A11. And the introduction of GSH helped to rescue eESCs from the ferroptosis trend initiated by si-ST2. Our data validated that rIL-33 upregulates the expression of SLC7A11 and blocks erastin-induced ferroptosis.\u003c/p\u003e \u003cp\u003eWe next looked into the regulators of SLC7A11. Bioinformatics analysis revealed that activating transcription factor 3 (ATF3) is one of the differentially expressed genes in eESCs co-cultured with macrophages and that ATF3 has a significant association with ferroptosis. ATF3 is a transcription factor known to regulate the expression of various molecules. ATF3 deficiency has been linked to prostate tumorigenesis induced by the inhibition of Pten in mice[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. We indeed found out that IL-33 induced a significant decrease in ATF3 expression in eESCs. Our study also revealed that the knockdown of ATF3 led to a significant increase in SLC7A11 expression, thereby reversing the negative effect of si-ST2 on SLC7A11. Besides, using ChIP assays, we verified the interaction of ATF3 with SLC7A11 promoter. Taken together, our data suggest that IL-33/ST2 regulates ferroptosis by inhibiting the downregulation effect of ATF3 on SLC7A11.\u003c/p\u003e \u003cp\u003eAnother intriguing finding of our study is the restrained activation of the p38 MAPK/JNK pathway in eESCs treated by rIL-33. Previous research has highlighted the role of p38 MAPK/JNK in enhancing ATF3 expression[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. We also found that rIL-33 treatment had a similar inhibitory effect on ATF3 expression as the treatment with p38 MAPK inhibitor SB202190. And SB202190 treatment was able to reverse the elevated levels of ATF3 observed in si-ST2 eESCs. Furthermore, through measuring the levels of Fe2+, lipid peroxidation, MDA, and GSH, we confirmed the SB202190's protective effects against Ferroptosis triggered by si-ST2 in eESCs. In summary, our study has shed light on the mechanism of the promotive effect of IL-33/ST2 in EMs, which involves the regulation of SLC7A11 expression via the p38/JNK/ATF3 signaling pathway, thereby hindering ferroptosis.\u003c/p\u003e \u003cp\u003eDuring the progression of ferroptosis, certain molecules are released into the extracellular environment, recruiting immune cells. This strengthens the body's immune defense system and have therapeutic effects for endometriosis.\u003c/p\u003e \u003cp\u003eAccordingly, some researchers have proposed combining immunotherapy with ferroptosis-inducing treatments as a potential approach. For instance, Niu et al. reported that ferroptosis inducers can enhance the sensitivity of \"cold\" tumors to immune therapy[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. While a combination of the ferroptosis inducer RSL-3 and dihydroartemisinin (DHA), an immunotherapy medicine targeting PD-L1, was designed for the treatment of pancreatic ductal adenocarcinoma (PDAC)[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHere, we propose a novel therapy approach for endometriosis that combines ferroptosis inducer erastin and IL-33-Ab as ferroptosis-immunotherapy. IL-33-Ab not only inhibits the tolerance for ferroptosis of eESCs but also stimulates macrophage polarization into the pro-inflammatory M1 sub-type, thereby enhancing the body's immune defense against eESCs. Moreover, erastin promotes the progression of ferroptosis in eESCs[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo evaluate the efficacy of this therapy mode, we established mice endometriosis model and treated them with IL-33-Ab and erastin. In mice models of endometriosis, we found that IL-33-Ab inhibited endometriosis development, and the combination of IL-33-Ab with erastin further amplified this effect. The findings imply that ferroptosis-immunotherapy has the potential to serve as a therapeutic strategy for managing endometriosis.\u003c/p\u003e \u003cp\u003eOur study also has limitation. Due to delayed clinical visits, most of the samples collected are from patients with middle to late-stage endometriosis. Further studies including patients in earlier stages are necessary to gain a more comprehensive understanding of endometriosis progression.\u003c/p\u003e \u003cp\u003eIn summary, we propose for the first time that IL-33 derived from macrophages can inhibit ferroptosis in eESCs by elevating SLC7A11 expression through the p38/JNK/ATF3 pathway. Our study provides a fresh perspective for understanding the pathology mechanism of endometriosis and developing novel treatment strategies.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCells culture\u003c/h2\u003e \u003cp\u003ePrimary cells were isolated from endometriosis tissues using previously described protocols[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Briefly, the tissues were cut into 1 mm\u0026sup3; pieces and were then digested using type IV collagenase (0.2% Sigma, USA) for 60 minutes at 37℃. The primary cells were cultured in Dulbecco's modified Eagle's medium (DMEM) containing 15% fetal bovine serum (FBS; Biological Industries, Israel) and 1% penicillin-streptomycin (Gibco, USA) at 37\u0026deg;C with 5% CO2. Primary cells were identified using immunofluorescent staining (Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eThe acute monocytic leukemia cell line (THP-1 cells), were purchased from ScienCell, and they were cultured in Roswell Park Memorial Institute 1640 (RPMI-1640) medium supplemented with 10% FBS and 1% penicillin-streptomycin (Biological Industries, Israel). THP-1 cells were treated with PMA (200nM; Sigma) for 48 hours to induce cell polarization.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemical staining (IHC)\u003c/h2\u003e \u003cp\u003eThe sections were incubated overnight and then immersed in xylene and ethanol to deparaffinization. Primary antibodies were incubated for overnight at 4\u0026deg;C, followed by incubation with secondary antibodies for 20 minutes at ambient temperature (as listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The sections were then stained using DAB dye (CWBIO, Beijing, China) and hematoxylin. Finally, the slides were then covered with cover-slips.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDetails of antibody used in experiments\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntigen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCatalog number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDilution\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eIF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL\u0026minus;33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66235\u0026minus;1-Ig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMouse\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVimentin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10366\u0026minus;1-AP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRabbit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCytokeratin 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15539\u0026minus;1-AP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRabbit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD11b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66519\u0026minus;1-Ig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMouse\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28058\u0026minus;1-AP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRabbit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eWB\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΒ-actin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60008\u0026minus;1-Ig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:20000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMouse\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL\u0026minus;33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66235\u0026minus;1-Ig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMouse\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eST2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60112\u0026minus;1-Ig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:20000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMouse\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACSL4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22401\u0026minus;1-AP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRabbit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLC7A11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26864\u0026minus;1-AP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRabbit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGPX4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14432\u0026minus;1-AP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:5000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRabbit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eATF3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDF3110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAffinity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRabbit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJNK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66210\u0026minus;1-Ig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:5000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMouse\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-JNK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80024\u0026minus;1-RR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRabbit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14064\u0026minus;1-AP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRabbit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-p38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28796\u0026minus;1-AP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRabbit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eα-tublin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66031\u0026minus;1-Ig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:50000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMouse\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGAPDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10494\u0026minus;1-AP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:5000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRabbit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eIHC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12372\u0026minus;1-AP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRabbit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eST2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60112\u0026minus;1-Ig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMouse\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eATF3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDF3110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAffinity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRabbit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eST2 (Mouse)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11920\u0026minus;1-AP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRabbit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLC7A11 (Mouse)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26864\u0026minus;1-AP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRabbit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eWB western blot, IHC immunohistochemistry, IF Immunofuorescence, IL-33 Interleukin-33, ST2 interleukin receptor-like 1 (IL1R-L1), ACSL4 acyl-CoA synthetase long-chain family member 4, SLC7A11 solute carrier family 7 member 11, GPX4 glutathione peroxidase 4, ATF3 activating transcription factor, JNK c-Jun N-terminal protein kainse, p-JNK phosphorylated c-Jun N-terminal protein kainse, p38/p38 MAPK, p38 mitogen activated protein kinases, p-p38 phosphorylated p38 mitogen activated protein kinases.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative real-time PCR (qRT-PCR)\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted from cells or tissues using Trizol (Invitrogen, USA), isopropyl alcohol, chloroform, and 75% ethanol. Reverse transcription of RNA (500 ng) was accomplished using a cDNA synthesis kit according to the manufacturer's protocol. Thereafter, cDNA (20 ng) was employed as a template for qRT-PCR using the Top Green qPCR SuperMix kit (TransGen Biotech, China). The primer were obtained from GENEWIZ (GENEWIZ, China), and listed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSequences of primers used for qRT-PCR analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward primer sequence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReverse primer sequence\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΒ-actin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCCATGAAGTGACG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTACTCCTGCTTGCTGATCCACAC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGATGGGAAGAAGGTG ATGGTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTTG TGAAGGACGAAGAAGGC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eST2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAACTGGACAGCACCTCTTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGTAATCACCTGCGTCCT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLC7A11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCCTTTGCTCTCATACCCATC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGACTTTCCTCTTCAGCTGCACTT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eATF3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGGAGTGCCTGCAGAAAGAGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCCATTCTGAGCCCGGACAAT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eIL33 Interleukin-33, ST2 interleukin receptor-like 1 (IL1R-L1), SLC7A11 solute carrier family 7 member 11, ATF3 activating transcription factor, qRT-PCR reverse transcription and quantitative real-time PCR.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eWestern blotting (WB)\u003c/h2\u003e \u003cp\u003eCells or tissues were lysed using RIPA lysis buffer and 1% PMSF (Beyotime Biotechnology, China). The protein samples was performed using the BCA protein assay kit (Beyotime Biotechnology, China). Samples were loaded into 10% SDS-PAGE gels (Epizyme, China) and then transfer onto PVDF membranes (Millipore, USA). The membrane was blocked using 5% skim milk powder solution for 2 hours, after which it was incubated with primary antibodies (as listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) overnight at 4℃ and then with secondary antibodies for 2 hours at room temperature. The blots were visualized using ECL reagent (Epizyme, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eELISA\u003c/h2\u003e \u003cp\u003eCell culture media from each group were collected and centrifuged at 500 g for 5 minutes. Interleukin-33 (IL-33) concentrations in the culture media supernatant were measured via an ELISA kit (Proteintech, USA) in accordance with the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eImmunofluorescence (IF)\u003c/h2\u003e \u003cp\u003eCells were fixed and subsequently blocked for 30 minutes using 5% goat serum albumin (Beyotime Biotechnology, China). The tissue sections were incubated overnight at 4℃ with specific primary antibodies (as listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), and with fluorescent secondary antibodies for 1 hour at room temperature. Fluorescence images were captured using a fluorescence microscope (Nikon, Tokyo, Japan).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eCell viability assessment\u003c/h2\u003e \u003cp\u003eThe cells viability measured by CCK-8 reagent following the manufacturer\u0026rsquo;s instructions (Beyotime Biotechnology, China). The absorbance readings were taken at 450 nm using a plate reader.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eColony formation assay\u003c/h2\u003e \u003cp\u003eCells were subjected to 7-day culture, subsequently, staining was performed for 30 minutes using crystal violet dye. Imaging was carried out using an iPhone 12, and ImageJ software was then utilized to analyze the obtained data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eTranswell migration assay\u003c/h2\u003e \u003cp\u003eCells were seeded at a density of 1x104/mL in the upper chamber of the 8 \u0026micro;m transwell insert utilizing 100 \u0026micro;L of serum-free DMEM. The lower chamber was filled with 600 \u0026micro;L of DMEM containing 15% FBS. After a 24-hour incubation, the cells were fixed and stained.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eWound healing assay\u003c/h2\u003e \u003cp\u003eWe created a scratch in the cells monolayer by a 200 \u0026micro;L pipette. We recorded images of the scratch area under a microscope immediately after creating the scratch and at 24 and 48 hours later.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eCell transfection\u003c/h2\u003e \u003cp\u003eWe transfected cells with small interfering RNA (siRNA) using the Lipofectamine 3000 transfection kit (Invitrogen, USA) according to the manufacturer's instructions. Ribobio (Ribobio, China) synthesized all specific siRNAs and siRNA controls. The target sequence of siRNA was as follows: sicon, 5ʹ-TTCTCCGAACGTGTCACGT-3ʹ; siST2-1, 5ʹ-TCTAAUGUCACTAAAUAACUT-3ʹ; siST2-2, 5ʹ-GCGAAUGUCACCAUAUAUATT-3ʹ; siST2-3, 5ʹ-GCCCATGUCATTAAAUAUCAT-3ʹ; siSLC7A11-1, 5ʹ-CCGGCCTGTCACTATTT-3ʹ; siSLC7A11-2, 5ʹ-GGAAGAGATTCAAGTATTA-3ʹ; siSLC7A11-3, 5ʹ-GGAGCTTTCTCGAGAAAG-3ʹ; siATF3-1, 5ʹ-CCGCCTTTCATCTGGATTCTA-3ʹ; siATF3-2, 5ʹ-GCTGAACTGAAGGCTCAGATT-3ʹ. siATF3-3, 5ʹ-GCTGCAAAGTGCCGAAACA-3ʹ.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eMeasurement of intracellular iron\u003c/h2\u003e \u003cp\u003eWe used the FerroOrange kit (Dojindo, Japan) to detect intracellular Fe2\u0026thinsp;+\u0026thinsp;levels in eESCs. The cells were incubated with a serum-free medium containing 1 \u0026micro;M FerroOrange reagent at 37℃ and 5% CO2 for 30 minutes. We obtained fluorescence images of the cells using a confocal microscope.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eLipid peroxidation determination\u003c/h2\u003e \u003cp\u003eTo quantify levels of lipid peroxidation, we used the LiperFluo and MDA Assay Kit from Dojindo (Dojindo, Japan) and Beyotime Biotechnology (Beyotime, China), respectively. For LiperFluo, we added LiperFluo reagent (5 \u0026micro;M) diluted in DMEM to the treated cells and incubated them for 30 minutes at 37℃ and 5% CO2. We evaluated lipid peroxidation levels using fluorescence microscopy (Nikon, Tokyo, Japan) by capturing photographs of the cells. For the MDA assay, cell lysis buffer for Western and IP (Beyotime Biotechnology, China) was used to lyse the cells on ice for 30 minutes. The absorbance was then measured at 532 nm using a plate reader in line with the manufacturer's instructions.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eMeasurement of GSH\u003c/h2\u003e \u003cp\u003eWe measured intracellular GSH levels in the treated cells using a GSH assay kit from Solarbio (Solarbio, Beijing, China). We lysed the cells entirely by performing four consecutive freeze-thaw cycles. We then mixed the cell lysate with the GSH reagent and measured the OD value of the resulting mixture at 412 nm using a plate reader.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eTransmission Electron Microscope (TEM)\u003c/h2\u003e \u003cp\u003eSamples were fixed with 2.5% glutaraldehyde (Servicebio, China) following a previously established protocol. After dehydration, we cut the samples into thin slices, which were then stained with uranyl acetate and lead citrate for contrast enhancement. Finally, we captured TEM images of the samples using the Hitachi TEM system (Japan).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eChIP\u003c/h2\u003e \u003cp\u003e We used the DNA ChIP Assay Kit (Beyotime Biotechnology, China) to immunoprecipitate DNA according to the manufacturer's instructions. Collected cells samples fragments were diluted in ChIP dilution buffer, followed by incubation with Protein A\u0026thinsp;+\u0026thinsp;G Agarose/Salmon Sperm at 4\u0026ordm;C for 30 minutes. We later incubated the samples with anti-ATF3 antibody (Affinity, DF3110) or normal rabbit IgG overnight at 4℃. We purified the samples using a DNA purification kit from Beyotime Biotechnology (China). Finally, we used RT-qPCR to quantify the predicted DNA sequences in the immunoprecipitated samples. The primers used were as follows: SLC7A11, forward 5\u0026rsquo;-TTGAGCAACAAGCTCCTCCT-3\u0026rsquo;, reverse 5\u0026rsquo;-CAAACCAGCTCAGCTTCCTC-3\u0026rsquo;\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eMouse endometriosis model\u003c/h2\u003e \u003cp\u003eFemale C57BL/6 mice (7 weeks old) were randomly sorted into four groups (n\u0026thinsp;=\u0026thinsp;6), endometriosis group, endometriosis\u0026thinsp;+\u0026thinsp;erastin group, endometriosis\u0026thinsp;+\u0026thinsp;IL-33-Ab group, and endometriosis\u0026thinsp;+\u0026thinsp;erastin\u0026thinsp;+\u0026thinsp;IL-33-Ab group. The endometriosis models were established as described previously[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Briefly, the uterus from a estradiol (0.2 ml/mouse) stimulated donor mouse, was minced into 1 mm\u003csup\u003e3\u003c/sup\u003e fragments and immediately injected subcutaneously into the peritoneal cavity of two recipient mice. The mice were respectively subjected to subcutaneous injections into the abdominal cavity with 300 \u0026micro;L of erastin (20 mg/kg) (MCE, Shanghai, China) alone or combined with IL-33-Ab 50 \u0026micro;g (R\u0026amp;D Systems, USA), or normal saline (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). At day 10 post-surgery, all mice were sacrificed, The lesion volume was calculated using the formula V\u0026thinsp;=\u0026thinsp;1/2Aa2; A: long radius, a: short radius. Ethical approval for all animal research was granted by the Institutional Animal Research Ethics Committee of Harbin Medical University.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eEach experiment was conducted independently, with a total of three replicates. Statistical was analyzed using GraphPad Prism 8 (San Diego, USA), and were presented as mean with standard deviation (SD). The Student's t-test, one-way ANOVA test, and Two-way ANOVA were employed for comparing data in different experimental groups. Statistical significance was determined as \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Non-significant differences were designated as \"ns\" (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026ge;\u0026thinsp;0.05), whereas ****\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, ***\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 represents significant differences.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the National Natural Science Foundation of China (82071619, 81671430 ).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest disclosure:\u0026nbsp;\u003c/strong\u003eThe authors have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution Statement:\u003c/strong\u003eQiong Wu and ZongWen Liang contributed to the study design, experimental operation, manuscript writing, and literature review. JL, Honglin Wang, Ning Wang , Yingying Cao were responsible for clinical specimen collection and the establishment of animal modeling. YG, Zhi Li, Jing JIang and Xiaoming Feng were responsible for data gathering and analysis. ZZ participated in the study design and coordinated all aspects of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval statement:\u003c/strong\u003eThis research was approved by the Ethical Committee of the Second Affiliated Hospital of Harbin Medical University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement:\u003c/strong\u003eThis researched was funded by National Natural Science\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFoundation of China No.82071619 and No.81671430.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003eThe original contributions presented in the study are included in the article/ Supplementary Material, further inquiries can be directed to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZondervan KT, Becker CM, Missmer SA. Endometriosis. 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NEUROSCIENCE. 2018;385:75-89.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cell-death-and-disease","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddis","sideBox":"Learn more about [Cell Death \u0026 Disease](http://www.nature.com/cddis/)","snPcode":"41419","submissionUrl":"https://mts-cddis.nature.com/cgi-bin/main.plex","title":"Cell Death \u0026 Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-2835730/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2835730/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEndometriosis is a gynecological inflammatory disease which linked with immune cells, specifically macrophages. And IL-33 secreted from macrophages is known to accelerate the progression of endometriosis. The periodic and repeated bleeding in endometriosis leads to a microenvironment with an excess of iron that is conducive to ferroptosis, a process related to intracellular ROS production, lipid peroxidation and mitochondrial damage. Hence, it is suggested that eESCs may have specific mechanisms to inhibit ferroptosis. However, it is currently unclear whether IL-33 directly regulates ferroptosis to influence the disease course in endometriosis. In this study, eESCs co-cultured with macrophages or stimulated with IL-33/ST2 were observed increased cell viability and migration. Additionally, IL-33/ST2 lessened intracellular iron and lipid peroxidation in eESCs exposed to erastin treatment. Furthermore, IL-33/ST2 treatment resulted in a notable elevation of SLC7A11 expression in eESCs due to its negative transcription factor ATF3 down-regulation, thereby suppressing ferroptosis. The P38/JNK pathway activated by IL-33/ST2 was also found to inhibit transcription factor ATF3. Therefore, we concluded that IL-33/ST2 constrains ATF3's role in suppressing SLC7A11 transcription via the P38/JNK pathway. The findings reveal that macrophage-derived IL-33 induces an upregulation of SLC7A11 in eESCs through the p38/JNK/ATF3 pathway, ultimately resulting in protection against ferroptosis in endometriosis. Moreover, we conducted an experiment in mouse endometriosis models that showed that a combination of IL-33-Ab and erastin treatment alleviated the disease, showing the promise of combining immunotherapy and ferroptosis therapy.\u003c/p\u003e","manuscriptTitle":"Macrophages originated IL33/ST2 inhibits ferroptosis in endometriosis via the ATF3/SLC7A11 axis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-07-24 14:04:10","doi":"10.21203/rs.3.rs-2835730/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cell-death-and-disease","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddis","sideBox":"Learn more about [Cell Death \u0026 Disease](http://www.nature.com/cddis/)","snPcode":"41419","submissionUrl":"https://mts-cddis.nature.com/cgi-bin/main.plex","title":"Cell Death \u0026 Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"397fd687-ddcb-4f9e-a073-671f1c87d2fd","owner":[],"postedDate":"July 24th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":21085934,"name":"Health sciences/Pathogenesis/Inflammation/Chronic inflammation"},{"id":21085935,"name":"Biological sciences/Immunology/Cell death and immune response"},{"id":21085936,"name":"Health sciences/Diseases/Reproductive disorders"},{"id":21085937,"name":"Biological sciences/Immunology/Cytokines/Interleukins"},{"id":21085938,"name":"Biological sciences/Biochemistry/Lipids/Membrane lipids"}],"tags":[],"updatedAt":"2023-10-11T07:07:52+00:00","versionOfRecord":{"articleIdentity":"rs-2835730","link":"https://doi.org/10.1038/s41419-023-06182-4","journal":{"identity":"cell-death-and-disease","isVorOnly":false,"title":"Cell Death \u0026 Disease"},"publishedOn":"2023-10-11 04:00:00","publishedOnDateReadable":"October 11th, 2023"},"versionCreatedAt":"2023-07-24 14:04:10","video":"","vorDoi":"10.1038/s41419-023-06182-4","vorDoiUrl":"https://doi.org/10.1038/s41419-023-06182-4","workflowStages":[]},"version":"v1","identity":"rs-2835730","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2835730","identity":"rs-2835730","version":["v1"]},"buildId":"WvIrzKhiLBfengagbw6Ux","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}