Exploration of  the mechanisms of Cyperi Rhizoma in the treatment of endometriosis through GEO datasets, network pharmacology, and molecular docking studies

Exploration of the mechanisms of Cyperi Rhizoma in the treatment of endometriosis through GEO datasets, network pharmacology, and molecular docking studies | 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 Research Article Exploration of the mechanisms of Cyperi Rhizoma in the treatment of endometriosis through GEO datasets, network pharmacology, and molecular docking studies Xingyi Fang, Yi Gong, Jinjing Li, Yanbin Jin, Yongwei Limeng, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2667223/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Cyperi rhizoma (CR) has traditionally been used to treat endometriosis (EMS), but its molecular mechanism remains unclear. To address this, we used a multi-faceted approach that included analysis of GEO datasets, network pharmacology, molecular docking and in vitro experiments.CR components and their potential targets were identified using TCMSP and PubChem, while GEO datasets, GeneCards, and DisGeNET were used to retrieve EMS-related targets. Compound-target and protein-protein interaction networks were constructed using Cytoscape and STRING, respectively, and hub genes were identified using CytoHubba. Enrichment analysis and molecular docking were performed, and RT-qPCR and Western blotting were used to assess protein expression levels. According to our research, there are 18 active CR components and 34 possible anti-EMS targets. Network analysis identified quercetin and kaempferol as potential key chemicals and revealed IL6, MMP9, CCL2, CXCL8, ICAM1, L10, VCAM1, IL18, SELE and TIMP1 as central hub genes in the network. GO, KEGG and GSEA analyses showed that ICAM1 and VCAM1 are involved in "positive regulation of cell adhesion", TNF signalling pathway, NF-kappa B signalling pathway and "GO_INFLAMMATORY_RESPONSE". Analysis of the GEO datasets revealed that ICAM1 and VCAM1 were upregulated in endometriosis compared to controls. Molecular docking showed that quercetin and kaempferol have strong binding affinities for these proteins. RT-qPCR and Western blotting analyses showed that CR treatment suppressed ICAM1 and VCAM1 expression, leading to reduced inflammation and adhesion in endometriosis-associated symptoms. Thus, these results provide a novel rationale for the potential of CR in the treatment of EMS. endometriosis Cyperi Rhizoma GEO datasets network pharmacology molecular docking ICAM1 VCAM1 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1 Introduction Endometriosis (EMS) is an estrogen-dependent, chronic inflammatory gynaecological disorder characterised by the growth of endometrial-like tissue outside the uterine cavity[ 1 ]. Endometriosis, which affects over 10% of women of reproductive age, is a significant contributor to infertility, but its aetiology remains unclear. The conventional approach to treating endometriosis is surgical removal of the lesions and hormonal suppression, but these treatments are often associated with side effects and a high rate of recurrence[ 2 ]. Against this backdrop, complementary and alternative medicine (CAM) has recently gained popularity due to its low side effects and high efficacy[ 3 ]. Cyperi Rhizoma (CR), the dried rhizome of Cyperus rotundus L. of the plant family Cyperaceae, has a long history of clinical use and is referred to as the 'holy medicine' in gynaecology[ 4 ]. Pharmacological studies have shown that CR has multiple properties, including antioxidant, anti-inflammatory, antidepressant, antipyretic, analgesic, antitumour, hypoglycaemic and antibacterial effects. These properties make CR a widely used therapeutic option for the treatment of a variety of diseases in the nervous system, cardiovascular system, digestive system, uterus and other systems in the clinical setting[ 5 ][ 6 ][ 7 ]. According to a recent analysis of 12,986 herbal prescriptions for the treatment of endometriosis in China, CR was the most commonly used single herb, appearing in 18.8% of all prescriptions[ 8 ].CR's therapeutic impact and mechanism for EMS, however, are yet unknown. In order to investigate the underlying mechanisms of the potential benefits of CR in alleviating the symptoms of EMS, a multidisciplinary approach was used, incorporating GEO datasets, network pharmacology, molecular docking, and in vitro experiments(see Fig. 1 ). These findings provide a novel theoretical basis for the clinical use of CR in the treatment of EMS. 2 Materials And Methods 2.1. Active ingredients of Cyperi Rhizoma and CR-related target screening Information on the components of CR was obtained from the Traditional Chinese Medicine Systems Pharmacology database ( https://tcmsp-e.com/ ). TCMSP is one of the world's biggest databases of Chinese herbal medicine, including information on the links between herbs, natural chemicals, target proteins, and disorders[ 9 ]. The TCMSP used oral bioavailability (OB) of ≥ 30 percent and drug likeness (DL) of ≥ 0.18 to screen possible active components of CR. When evaluating the efficacy of a drug, one of the key parameters assessed is its oral bioavailability (OB), which represents the fraction of an orally administered drug that reaches the systemic circulation[ 10 ]. In drug design, the word "druglikeness" (DL) is used to define a substance's druglikeness in terms of factors such as bioavailability, and it assists in optimizing pharmacokinetic and pharmacological aspects[ 11 ]. To identify potential targets, the active ingredients were searched in the TCMSP and PubChem databases ( https://pubchem.ncbi.nlm.nih.gov/ ). PubChem is a public chemical database that is used by both scientists and the general public. This database compiles chemical data from a variety of sources and arranges it into several data sets[ 12 ]. 2.2. EMS-related target screening The identification of EMS-relevant targets was performed using the Gene Expression Omnibus (GEO) database, the GeneCards database and the DisGeNET database. RNA-sequencing dataset GSE105764 from the GEO database, which contained 8 paired eutopic (EU) and ectopic (EC) endometrium samples based on GPL20301 (Illumina HiSeq 4000)[ 13 ]. Identification of differentially expressed genes (DEGs) between EC and EU samples was performed using the 'edgeR' package. Genes meeting specific cutoff criteria of FDR 2.0 were defined as DEGs. GeneCards is a comprehensive library of functions in the fields of proteomics, genomics, and transcriptomics[ 14 ]. DisGeNET is a public-access database of genes and variants linked to human illnesses[ 15 ]. A Venn diagram was then constructed using the genes obtained. The genes that overlapped were grouped together as candidate targets. 2.3. Construction of the “Compound-Target” Network The compounds and associated genes were fed into the Cytoscap 3.7.2 software, resulting in the generation of a compound target interaction network. Cytoscape 3.7.2 is a freely available open source network visualisation software[ 16 ]. The most critical compound in the network was discovered using the CytoNCA plug-in for Cytoscape[ 17 ]. 2.4. Protein-Protein Interaction Network To facilitate further research, protein-protein interaction (PPI) information was obtained by importing potential targets into String, with the species set to Homo sapiens and the medium confidence level set to 0.4. The MCC algorithm has been used in the 'cytoHubba' program of Cytoscape 3.7.2 to discover the 10 most prominent hub genes[ 18 ]. 2.5. Enrichment analyses GO and KEGG enrichment analysis was performed using the R package "clusterProfiler" [ 19 ]. A p-value of less than 0.05 was used as the criterion for significance. The GO enrichment analysis focused primarily on identifying the biological processes (BP), cellular components (CC), and molecular functions (MF) associated with genes. The KEGG pathway analysis was performed to discover the biological pathways that are associated with the genes. To gain a deeper understanding of the underlying molecular mechanisms of our target candidates, Gene Set Enrichment Analyses (GSEA) were performed using the R package "gsva"[ 20 ]. 2.6. External dataset verifies the expression of characteristic genes GSE7305 was an EMS-related chip dataset comprising 10 healthy subjects, and 10 patients with endometriosis. Based on the relative gene expression data derived from the GSE7305 dataset, we further validated the expression levels of the hub genes previously identified in the GSE105764 dataset. 2.7. Molecular docking validation Based on the insights gained from the Compound-Target network analysis, high priority compounds and biological targets were selected for molecular docking studies using AutoDock Vina. The 2D molecular structures of the active compounds and critical proteins were obtained using the TCMSP databases and the RCSB PDB ( http://www.rcsb.org/ ). The energy minimization of the molecular structures and the conversion to the mol2 format were performed using ChemBio3D. Docking validation was then performed using both Autodock 1.5.6 and AutoDock Vina. The molecular docking patterns were visualized using Pymol (version 2.2.0) and further analyzed using the Discovery Studio Client software (version 19.1.0). 2.8. Preparation of plant material extract Cyperus rotundus rhizomes were obtained from a local market in Haikou, China. The dried and ground plant material was extracted with ethanol. Cyperi rhizoma extract (CRE) powder was dissolved in dimethyl sulfoxide (DMSO) and filtered through a 0.22 µm filter. 2.9. Cell Culture Human endometrial stromal cells (HESCs) were obtained from the college of Life Science of Xiamen University (Xiamen, China). HESCs were cultured in DMEM/F-12 supplemented with 10% (v/v) fetal bovine serum and 1% penicillin-streptomycin (100 U/mL, Gibco) at 37°C and 5% CO2. 2.10. Western blotting analysis The cells were rinsed with PBS. Protein lysis buffer was used for extraction. Protein concentration was determined by the BCA assay. Cell lysates were combined with 5X SDS sample buffer, boiled for 4 minutes, and separated by 10% SDS-PAGE analysis. Proteins were transferred to polyvinylidene difluoride membranes after electrophoresis. The polyvinylidene difluoride membranes were blocked with 2% bovine serum albumin (BSA) for 30 minutes. The membranes were then washed and incubated overnight at 4°C in a solution containing specific primary antibodies, Tris-buffered saline, 2% BSA, and 0.1% Tween-20 (TBS-T). The polyvinylidene difluoride membranes were washed three times in a row to remove any residual primary antibody and then incubated for two hours with horseradish peroxidase-conjugated secondary antibody (at dilutions ranging from 1:1000 to 1:2000). After a careful washing protocol of three times with TBS-T, the presence of immunopositive bands was detected using the ECL chemiluminescent detection system. The acquired data were then analyzed using the ImageQuant Las-4000 imaging platform. 2.11. Quantitative real-time RT-PCR The qPCR Eastep® Super Total RNA Extraction Kit (Promega, Fitchburg, WI, USA) was used to extract total RNA from the cells. Complementary DNA was then synthesized from total RNA using ChamQ Universal SYBR™ qPCR Master Mix (Vazyme Biotechnology, Nanjing, China) according to the manufacturer's protocol. The polymerase chain reaction (PCR) was performed using ChamQ Universal SYBR qPCR Master Mix in the presence of SYBR Green I fluorescent dye. The amount of product was determined by the comparative threshold cycle (CT) value. The data were quantitatively analyzed using the 2−∆∆ CT method. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) amplification was performed using the following qRT-PCR primer sets: ICAM-1_S (5′-CCG TGA ATG TGC TCT CCC-3′) and ICAM-1_AS (5′-ATT TCT TGA TCT TCC GCT GG-3′); VCAM-1_S (5′-CAG GTG GAG CTC TAC TCA TTC C-3′) and VCAM-1_AS (5′-GAA TAG TCT CCC CCT TAA GTA ATT C-3′). The amplification of the GAPDH gene for normalisation purposes was performed using a set of primers designated GAPDH_S (5′-GAA GAT GGT GAT GGG ATT TC-3′) and GAPDH_AS (5′-GAA GGT GAA GGT CGG AGT-3′). 2.12. Statistical analyses Bioinformatic analysis was performed using the R programming language, with comparisons between groups performed using the Wilcoxon test. A p-value of less than 0.05 was considered indicative of statistical significance unless otherwise stated. 3. Results 3.1 Active ingredients of Cyperi Rhizoma and CR-related target screening A screening of the TCMSP database using OB ≥ 30% and DL ≥ 0.18 as criteria revealed the presence of 18 active compounds in Cyperi Rhizoma that met the established standards(see Table 1 ). A comprehensive search of the TCMSP and PubChem databases identified 467 targets in Cyperi Rhizoma. Table 1 Information on 18 effective compounds of Cyperi Rhizoma Molecule ID Molecule Name OB (%) DL MOL003044 Chryseriol 35.85 0.27 MOL000354 isorhamnetin 49.60 0.31 MOL003542 8-Isopentenyl-kaempferol 38.04 0.39 MOL000358 beta-sitosterol 36.91 0.75 MOL000359 sitosterol 36.91 0.75 MOL004027 1,4-Epoxy-16-hydroxyheneicos-1,3,12,14,18-pentaene 45.1 0.24 MOL004053 Isodalbergin 35.45 0.20 MOL004058 Khell 33.19 0.19 MOL004059 khellol glucoside 74.96 0.72 MOL010489 Resivit 30.84 0.27 MOL004068 rosenonolactone 79.84 0.37 MOL004071 Hyndarin 73.94 0.64 MOL004074 stigmasterol glucoside_qt 43.83 0.76 MOL004077 sugeonyl acetate 45.08 0.20 MOL000422 kaempferol 41.88 0.24 MOL000449 Stigmasterol 43.83 0.76 MOL000006 luteolin 36.16 0.25 MOL000098 quercetin 46.43 0.28 OB: oral bioavailability, DL:drug likeness 3.2 EMS-related target screening and Venn analysis Using the criteria of |log2 FC| > 2 and adjusting P-value < 0.05, 1975 differentially expressed genes (DEGs, 1053 upregulated and 922 downregulated) were obtained from the GSE105764 sequencing dataset(see Fig. 2 A). A search of the DisGeNET and GeneCards databases using the keyword "endometriosis" resulted in the identification of 1188 and 2750 EMS-related targets, respectively. The Venny tool was used to analyze the overlap between phytomedicine targets and disease-related genes, resulting in the identification of 34 genes that could potentially serve as targets for Cyperi Rhizoma therapy in endometriosis. These genes included 26 that were shown to be upregulated and 8 that were downregulated in EMS (see Fig. 2 B,Table 2 ). The expression levels of the 34 differentially expressed genes (DEGs) are shown in a heatmap format in Fig. 2 C. Table 2 Differential gene expression analysis of GSE105764. Gene symbol LogFC P-Value FDR Change CD163 4.360768041 2.15E-28 2.39E-26 up ICAM1 2.91363036 4.58E-23 2.91E-21 up VCAM1 3.793684837 2.39E-21 1.22E-19 up IL10 4.305851467 5.13E-17 1.53E-15 up CCL2 3.447944366 4.41E-16 1.14E-14 up AKR1B1 2.021567977 8.07E-15 1.77E-13 up TIMP1 3.31034405 8.16E-15 1.78E-13 up CYP19A1 8.647443725 2.42E-12 3.76E-11 up SELE 4.060620414 7.66E-12 1.11E-10 up BDNF 3.052340528 6.79E-11 8.44E-10 up TNFRSF1B 2.048841521 4.67E-10 5.04E-09 up MMP9 4.857544356 4.23E-08 3.28E-07 up NOS2 2.684821621 9.27E-08 6.81E-07 up CXCL12 2.450653688 2.04E-07 1.40E-06 up CYP1B1 2.368375739 3.25E-07 2.15E-06 up PRKCB 2.002892676 5.87E-07 3.71E-06 up PLAU 2.371894372 1.29E-06 7.59E-06 up CD40LG 3.263178217 8.38E-06 4.12E-05 up APOE 2.043017016 8.86E-06 4.33E-05 up MPO 2.733416304 1.52E-05 7.11E-05 up IL18 2.08313355 6.59E-05 0.000268371 up SLC2A4 2.041949264 0.000128062 0.000487682 up CXCL8 3.346397603 0.000412842 0.001387641 up MMP1 4.289169724 0.000575944 0.001878686 up IL6 2.124402372 0.00087151 0.002720124 up MMP3 5.283576581 0.001939556 0.00551061 up ESR1 -3.566021217 1.19E-14 2.54E-13 down CLDN4 -5.925801462 2.17E-14 4.45E-13 down MET -3.992218865 3.77E-14 7.44E-13 down PGR -2.366958516 4.12E-07 2.68E-06 down BIRC5 -2.390144421 4.60E-05 0.000194662 down CDK1 -2.244934986 5.69E-05 0.000235401 down SLPI -3.26481389 0.000328801 0.001137384 down DPP4 -2.343411098 0.002334849 0.006464018 down 3.3 The “Compound-Target” Network A "Compound-Target" network was constructed by integrating the active compounds and potential targets in Cytoscape 3.7.2(see Fig. 3 ). The network illustrates the multiple effects of the active ingredients in Cyperi Rhizoma on endometriosis. CytoNCA analysis revealed that the top two active compounds were quercetin and kaempferol(see Table 3 ). The results of the analysis suggest that quercetin and kaempferol may play a critical role in mediating the anti-endometriosis effects of Cyperi Rhizoma. Table 3 The top 10 compounds and hub genes. Molecule Name Degree Node name MCC Score quercetin 23.0 IL6 2.05E + 09 kaempferol 20.0 MMP9 2.05E + 09 luteolin 19.0 CCL2 2.05E + 09 isorhamnetin 15.0 CXCL8 2.05E + 09 beta-sitosterol 13.0 ICAM1 2.05E + 09 Stigmasterol 12.0 IL10 2.05E + 09 Chryseriol 7.0 VCAM1 2.05E + 09 Hyndarin 6.0 IL18 2.05E + 09 8-Isopentenyl-kaempferol 5.0 SELE 2.04E + 09 sitosterol 1.0 TIMP1 1.96E + 09 3.4 Protein-Protein Interaction Network To construct the PPI network, 34 potential targets were imported into the STRING database(see Fig. 4 A). The protein-protein interaction data showed a total of 34 nodes and 228 edges with an average degree of 13.4, reflecting a well-connected network structure. Analysis using the Cytoscape plugin cytoHubba and the Maximum Correlation Coefficient (MCC) algorithm revealed the top ten most significant genes in the network, including IL6, MMP9, CCL2, CXCL8, ICAM1, IL10, VCAM1, IL18, SELE, and TIMP1(see Fig. 4 B, Table 3 ). 3.5 Enrichment analyses We performed a functional and pathway enrichment analysis of 34 genes using the clusterProfiler R package to gain insight into the molecular mechanisms involved. The GO biological process (GO-BP) category was mainly involved in “regulation of inflammatory response”, “positive regulation of cell adhesion”, etc(see Fig. 5 A,Table 4 ). The GO cellular component (GO-CC) category was mainly involved in “external side of plasma membrane”, “collagen-containing extracellular matrix”, etc. The GO molecular function (GO-MF) category was mainly involved in “receptor ligand activity”, “integrin binding”, etc. The results of the KEGG pathway analysis revealed significant associations with pathways such as the TNF pathway and the NF-kappa B pathway, among others(see Fig. 5 B,Table 4 ). Gene set enrichment analysis (GSEA) across the MSigDB.v7.0 revealed significant enrichment in “GO_LEUKOCYTE_MIGRATION” and “GO_INFLAMMATORY_RESPONSE” (see Fig. 5 C,Table 4 ). A Sankey diagram was used to directly illustrate the relationships between the enrichment analyses results and the genes involved(see Fig. 5 D). Table 4 Enrichment analyses. ID Term Adj_pval Genes BP GO:0050727 regulation of inflammatory response 3.88E-07 IL10, CYP19A1, SELE, TNFRSF1B, MMP9, APOE, IL18, IL6, MMP3, ESR1 GO:0045785 positive regulation of cell adhesion 6.83E-06 VCAM1, IL10, CCL2, SELE, CXCL12, CD40LG, IL18, IL6, DPP4 CC GO:0009897 external side of plasma membrane 0.001510618 CD163, ICAM1, VCAM1, SELE, CXCL12, CD40LG, SLC2A4 GO:0062023 collagen-containing extracellular matrix 0.005911366 ICAM1, TIMP1, MMP9, CXCL12, APOE, SLPI MF GO:0048018 receptor ligand activity 8.06E-07 IL10, CCL2, TIMP1, BDNF, CXCL12, CD40LG, IL18, CXCL8, IL6, DPP4 GO:0005178 integrin binding 0.002815111 ICAM1, VCAM1, CXCL12, CD40LG KEGG hsa04668 TNF signaling pathway 2.78E-07 ICAM1, VCAM1, CCL2, SELE, TNFRSF1B, MMP9, IL6, MMP3 hsa04064 NF-kappa B signaling pathway 2.57E-06 ICAM1, VCAM1, CXCL12, PRKCB, PLAU, CD40LG, CXCL8 GSEA msigdb.v7.0 GO_LEUKOCYTE_MIGRATION 0.04728902 CYP19A1,MMP9,IL10,MMP1,SELE,VCAM1,CCL2,CXCL8 GO_INFLAMMATORY_RESPONSE 0.04728902 CYP19A1,MMP3,MMP9,CD163,IL10,SELE,VCAM1,CCL2,CXCL8,TIMP1,CD40LG 3.6. External dataset verifies the expression of characteristic genes Using the Chip dataset (GSE7305), we conducted a validation study. Our results show that the expression levels of ICAM1 and VCAM1 are increased in endometriosis, which is consistent with the results obtained from the sequencing dataset(GSE105764)(see Fig. 6 ). 3.6 Molecular docking validation The "Compound-Target" network's top two active components (quercetin and kaempferol) bind adhesion molecules (ICAM1 and VCAM1) to various degrees (see Fig. 7 ). According to Pymol 2.2.0. (3D structure) and Discovery Studio 2019 Client (2D structure) results, quercetin stably bound to the active site of ICAM1 through GLU-284, LYS-305, and LYS-287 on the ICAM1 target protein, and stably bound to the active site of VCAM1 through SER-41, TRP-35, and VAL-47 on the VCAM1 target protein. Kaempferol stably bound to the active site of ICAM1 through LYS-305 and GLU-301 on the ICAM1 target protein, and stably bound to the active site of VCAM1 through LYS-46, VAL-47, and VAL-190 on the VCAM1 target protein(see Table 5 ). 3.7 CR suppressed ICAM1 and VCAM1 expression To investigate the effect of CR on the adhesion capacity of ectopic endometrial cells, we performed RT-qPCR and Western blot analyses to assess the mRNA and protein expression of adhesion molecules (VCAM1 and ICAM1) in endometrial cells in different groups. Exposure of endometriotic stromal cells to TNF-α(10 ng/ml) for 16 hours significantly increased total cellular ICAM1 and VCAM1 protein levels. Pretreatment with CR (50 µg/ml) for 1 hour significantly attenuated the TNF-α-induced upregulation of ICAM1 and VCAM1 protein expression in total cellular content. 4 Discussion Endometriosis is a pathological condition characterised by the presence and growth of endometrial cells outside the uterine cavity[ 21 ]. The complexity of the pathophysiology of endometriosis is due to the interaction of genetic, hormonal, inflammatory and immune factors[ 22 ]. The presence of diverse immune cells in the peritoneal cavity environment enhances the invasive and adhesive properties of endometrial cells[ 23 ]. Stimulation of the inflammatory response results in the secretion of cytokines and chemokines into the peritoneal cavity, leading to the creation of a microenvironment that facilitates the growth of ectopic endometrial tissue by promoting local angiogenesis and inhibiting the process of endometrial apoptosis[ 24 ]. Adhesion, invasion and angiogenesis are integral components of the pathogenesis of endometriosis and form the basis of our TCM-based therapeutic approach[ 25 ]. According to traditional medicine in Vietnam and Taiwan, the use of a decoction made from the CR plant is known to have therapeutic benefits for women suffering from infertility and dysmenorrhoea as a result of endometriosis[ 26 ][ 27 ]. The CR plant contains biologically active compounds, including flavonoids, with potential immunomodulatory, analgesic, anti-inflammatory and antioxidant properties[ 28 ]. However, the exact mechanism of CR's therapeutic effect on endometriosis-related symptoms remains to be elucidated. In this study, a systematic network pharmacology analysis was conducted to explore the mechanism of CR in the treatment of symptoms of endometriosis. Components with oral bioavailability (OB) values ≥ 30% and drug-likelihood (DL) values ≥ 0.18 in CR demonstrated high absorption in the body. As a result, 18 bioactive compounds and 34 potential targets for the treatment of endometriosis with Cyperi Rhizoma were predicted, providing the possibility to elucidate the pharmacological processes of CR. Quercetin and kaempferol have been identified as the predominant bioactive compounds in CR. Quercetin and kaempferol, two members of the flavonoid family of polyphenolic compounds, have been classified in the subclass of flavonols[ 29 ]. The flavonoids present in CR have been shown to exhibit a number of biologically significant activities, including scavenging the stable radical DPPH, chelating metal ions, scavenging the reactive nitrogen species NO and hydroxyl radicals, and demonstrating antioxidant activity[ 30 ]. In addition, quercetin has been shown to inhibit proliferation and induce cell cycle arrest in endometriotic cells[ 31 ]. In a rat model of endometriosis, combination treatment with quercetin and metformin was found to induce regression of endometrial implants, likely due to its anti-estrogenic and anti-inflammatory properties[ 32 ]. The top ten core nodes identified in the PPI network analysis were IL6, MMP9, CCL2, CXCL8, ICAM1, IL10, VCAM1, IL18, SELE and TIMP1. The inflammatory cytokines IL-6, CCL2, CXCL8, IL10 and IL18 were associated with endometriosis. In the context of endometriosis, it has been proposed that the shed endometrial tissue migrating into the peritoneal cavity may trigger an inflammatory response, with factors released by inflammatory cells (as well as the stromal component of the refluxed endometrium) potentially inducing proliferation of endometrial epithelial cells[ 33 ]. The role of matrix metalloproteinase (MMP) activity is thought to be important in the early stages of endometriosis progression. Disturbances in the balance between matrix metalloproteinases (MMPs), such as MMP9, and their tissue inhibitors (TIMPs), such as TIMP1, could be detrimental and potentially promote the progression of endometriosis[ 34 ]. VCAM1 and ICAM1 have been shown to play a role in the inflammatory process by facilitating the adhesion of monocytes to endothelial cells[ 35 ]. The ratio of soluble VCAM1 to soluble ICAM1 is a promising biomarker for the diagnosis of endometriosis[ 36 ]. GO enrichment analysis highlighted "regulation of inflammatory response" and "positive regulation of cell adhesion". The results of the KEGG and GSEA enrichment analyses support the results of the GO analysis, indicating a relationship between the inflammatory response and the activation of the TNF signalling pathway, as well as the GO_INFLAMMATORY_RESPONSE. Our analysis showed that ICAM1 and VCAM1 are involved in the "positive regulation of cell adhesion", the TNF signalling pathway, the NF-kappa B signalling pathway and the "GO_INFLAMMATORY_RESPONSE". Analysis of the chip datasets (GSE7305) showed that ICAM1 and VCAM1 were significantly upregulated in endometriosis, which was consistent with the findings from the sequencing datasets (GSE105764). Molecular docking results showed efficient binding of ICAM1 and VCAM1 to the flavonoids quercetin and kaempferol. Additionally, our in vitro experiments showed that CR significantly suppressed the expression of ICAM1 and VCAM1 in HESCs induced by TNF-α stimulation. In conclusion, CR has been shown to have anti-inflammatory and anti-adhesive properties in EMS, resulting in a significant reduction in the expression levels of VCAM1 and ICAM1. However, our study had some limitations. Previous studies have shown that NF-κB signaling induces the high expression of key adhesion molecules in the ectopic endometrium, including ICAM1, and vascular VCAM1[ 37 ]. CR maybe reduce the inflammatory response and adhesive ability of endometriotic cells, possibly via the NF-κB signaling pathway. So, further experiments and analysis are needed to validate our predicted results. 5 Conclusions Our study showed that CR contains 18 bioactive components and 34 potential therapeutic targets. Quercetin and kaempferol were the main active compounds in CR that produced therapeutic effects against EMS. IL6, MMP9, CCL2, CXCL8, ICAM1, IL10, VCAM1, IL18, SELE and TIMP1 emerged as key hub genes. GO, KEGG and GSEA analysis showed that ICAM1 and VCAM1 are involved in "positive regulation of cell adhesion", TNF signalling pathway, NF-kappa B signalling pathway and "GO_INFLAMMATORY_RESPONSE". GEO chip and sequencing data revealed significant upregulation of ICAM1 and VCAM1 in ectopic endometrial tissue from EMS. In addition, both quercetin and kaempferol were shown to have strong binding affinities for ICAM1 and VCAM1 in molecular docking. The results of RT-qPCR and Western blotting experiments showed that CR effectively reduced TNF-α-induced expression of ICAM1 and VCAM1 in human endometriotic stromal cells. Our results provide a novel basis for exploring the potential of CR as a preventive and therapeutic approach to EMS in humans. Declarations Data Availability The data used to support the results of the study are included in the published paper. Conflicts of Interest The authors of this paper have no potential conflicts of interest. Authors’ Contributions and Consent to participate Yuanhua Huang and Yanlin Ma were responsible for the conception and design of the study and the experiments, while data collection was performed by Jinjing Li, Yanbin Jin and Yongwei Limeng. Xingyi Fang and Yi Gong designed the experiments and drafted the manuscript. The final version of the manuscript was approved by all authors. Funding Statement This study was financially supported by the Hainan Provincial Natural Science Foundation (No. ZDKJ2021037), the China Postdoctoral Science Foundation (No. 2021M691466) and the National Natural Science Foundation of China (No. 8220061871). Ethics approval The Medical Ethics Committee of the First Affiliated Hospital of Hainan Medical University reviewed and approved our project for implementation, confirming its compliance with all relevant laws and regulations. Consent for publication All authors have consented to the publication of this article. Availability of data and material The data is transparent and can be made publicly available for publication. Code availability Not applicable. References Nirgianakis K, Egger K, Kalaitzopoulos DR et al. 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Hu DB, Lu ZD, Wu XX. Research Progress on the Chemical Constituonts and Pharmacological Activity of Traditimal Chinese Medicine Nutgrass Galingale Rhizome. Lishizhen Medicine and Materia Medica Research 2017, 28: 3. Tsai PJ, Lin YH, Chen JL et al. Identifying Chinese Herbal Medicine Network for Endometriosis: Implications from a Population-Based Database in Taiwan. Evid Based Complement Alternat Med 2017, 2017:7501015. Jinlong R, Peng L, Jinan W et al. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. J Cheminform 2014, 6:13. Xu X, Zhang W, Huang C et al. A Novel Chemometric Method for the Prediction of Human Oral Bioavailability. International Journal of Molecular Sciences 2012, 13(6):6964. Tian S, Wang J, Li Y et al. The application of in silico drug-likeness predictions in pharmaceutical research. Advanced Drug Delivery Reviews 2015, 86:2-10. Kim S, Thiessen PA, Bolton EE et al. PubChem Substance and Compound databases. Nucleic Acids Res 2016, 44: D1202-13. Zhao L, Gu C, Ye M, Zhang Z et al. Integration analysis of microRNA and mRNA paired expression profiling identifies deregulated microRNA-transcription factor-gene regulatory networks in ovarian endometriosis. Reprod Biol Endocrinol 2018, 16(1):4. Stelzer G, Rosen N, Plaschkes I et al. The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses. Current Protocols in Bioinformatics 2016, 54:1.30.1-1.30.33. Janet P, Josep S, Ferran S et al. The DisGeNET cytoscape app: Exploring and visualizing disease genomics data. Computational and Structural Biotechnology Journal 2021, 19:2960-2967. Shannon P, Markiel A, Ozier O et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003, 13(11):2498-504. Tang Y, Li M, Wang J et al. CytoNCA: a cytoscape plugin for centrality analysis and evaluation of protein interaction networks. Biosystems 2015, 127:67-72. Chin CH, Chen SH, Wu HH et al. cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Syst Biol 2014, 8 Suppl 4(Suppl 4):S11. Yu G, Wang LG, Han Y et al. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 2012, 16(5):284-7. Subramanian A, Tamayo P, Mootha VK et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 2005, 102(43):15545-50. Han SJ, Jung SY, Wu SP et al. Estrogen Receptor β Modulates Apoptosis Complexes and the Inflammasome to Drive the Pathogenesis of Endometriosis. Cell 2015, 163(4):960-974. Heard ME, Melnyk SB, Simmen FA et al. High-Fat Diet Promotion of Endometriosis in an Immunocompetent Mouse Model is Associated With Altered Peripheral and Ectopic Lesion Redox and Inflammatory Status. Endocrinology 2016, 157(7):2870-82. Symons LK, Miller JE, Kay VR et al. The Immunopathophysiology of Endometriosis. Trends Mol Med 2018 , 24(9):748-762 . Mantovani A, Allavena P, Sica A et al. Cancer-related inflammation. Nature Publishing Group 2008, 454(7203):436-44. Zheng W, Wu J, Gu J et al. Modular Characteristics and Mechanism of Action of Herbs for Endometriosis Treatment in Chinese Medicine: A Data Mining and Network Pharmacology–Based Identification. Frontiers in Pharmacology 2020, 11:147. Zhou J, Qu F. Treating gynaecological disorders with traditional Chinese medicine: a review. African Networks on Ethnomedicines 2009, 6(4):494-517. Hung YC, Kao CW, Lin CC et al. Chinese Herbal Products for Female Infertility in Taiwan: A Population-Based Cohort Study. Medicine 2016, 95:e3075. Soumaya KJ, Dhekra M, Fadwa C et al. Pharmacological, antioxidant, genotoxic studies and modulation of rat splenocyte functions by Cyperus rotundus extracts. BMC Complement Altern Med 2013, 13:28. Barrington RD, Needs PW, Williamson G et al. MK571 inhibits phase-2 conjugation of flavonols by Caco-2/TC7 cells, but does not specifically inhibit their apical efflux. Biochem Pharmacol 2015, 95(3):193-200. Kandikattu HK, Rachitha P, Krupashree K et al. LC–ESI-MS/MS analysis of total oligomeric flavonoid fraction of Cyperus rotundus and its antioxidant, macromolecule damage protective and antihemolytic effects. Pathophysiology 2015, 22(4):165-173. Park S, Lim W, Bazer FW et al. Quercetin inhibits proliferation of endometriosis regulating cyclin D1 and its target microRNAs in vitro and in vivo. The Journal of nutritional biochemistry 2019, 63:87–100. Jamali N, Zal F, Mostafavi-Pour Z et al. Ameliorative Effects of Quercetin and Metformin and Their Combination Against Experimental Endometriosis in Rats. Reprod Sci 2021, 28(3):683-692. Ruiz A, Ruiz L, Colón-Caraballo M et al. Pharmacological blockage of the CXCR4-CXCL12 axis in endometriosis leads to contrasting effects in proliferation, migration, and invasion. Biol Reprod 2018, 98(1):4-14. Szymanowski K, Mikołajczyk M, Wirstlein P et al. Matrix metalloproteinase-2 (MMP-2), MMP-9, tissue inhibitor of matrix metalloproteinases (TIMP-1) and transforming growth factor-β2 (TGF-β2) expression in eutopic endometrium of women with peritoneal endometriosis. Ann Agric Environ Med 2016, 23(4):649-653.. Afzali MF, Popichak KA, Burton LH et al. A novel diindolylmethane analog, 1,1-bis(3'-indolyl)-1-(p-chlorophenyl) methane, inhibits the tumor necrosis factor-induced inflammatory response in primary murine synovial fibroblasts through a Nurr1-dependent mechanism. Mol Immunol 2018, 101:46-54. Kuessel L, Wenzl R, Proestling K et al. Soluble VCAM-1/soluble ICAM-1 ratio is a promising biomarker for diagnosing endometriosis. Hum Reprod 2017, 32(4):770-779. Liu Y, Wang J, Zhang X. An Update on the Multifaceted Role of NF-kappaB in Endometriosis. Int J Biol Sci 2022, 18(11):4400-4413. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 29 Mar, 2023 Editor assigned by journal 15 Mar, 2023 First submitted to journal 09 Mar, 2023 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-2667223","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":187593417,"identity":"ae5e367d-dcbe-4d77-a95e-32bcbf4983d2","order_by":0,"name":"Xingyi Fang","email":"","orcid":"","institution":"Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xingyi","middleName":"","lastName":"Fang","suffix":""},{"id":187593418,"identity":"7250688f-c154-407e-a77a-9c9ba3c3e45b","order_by":1,"name":"Yi Gong","email":"","orcid":"","institution":"Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Gong","suffix":""},{"id":187593419,"identity":"bedebbf0-180a-4696-a2dc-61541db6ecb6","order_by":2,"name":"Jinjing Li","email":"","orcid":"","institution":"Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jinjing","middleName":"","lastName":"Li","suffix":""},{"id":187593420,"identity":"16ba349d-2c97-4521-bfa5-32da84ce4aac","order_by":3,"name":"Yanbin Jin","email":"","orcid":"","institution":"Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yanbin","middleName":"","lastName":"Jin","suffix":""},{"id":187593421,"identity":"68323dda-1aa3-4253-a2d4-32f66fab676e","order_by":4,"name":"Yongwei Limeng","email":"","orcid":"","institution":"Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yongwei","middleName":"","lastName":"Limeng","suffix":""},{"id":187593422,"identity":"7fa377ab-cb21-4783-9c80-81b286ebd863","order_by":5,"name":"Yanlin Ma","email":"","orcid":"","institution":"Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yanlin","middleName":"","lastName":"Ma","suffix":""},{"id":187593423,"identity":"b92fb42b-9f9d-4082-bb5d-2a9e38d42e03","order_by":6,"name":"Yuanhua Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIiWNgGAWjYBACAwh1gJmNvbHxMQODBITPQ4QWdj6ew4eNSdLCLyeRliYNF8anxVwi+dnDr213pNl4zphVF9RY5Om2H2B88LaNQd4chxbLGWnmxrJtz4zZ2HvMbs84JlFsdiaB2XBuG4PhzgYcDruRYCYt2XY4GWTLbR42icRtNxjYpHnbGBIMDuDSkv4NpKW+TSLHrJjnH1gL+2/8WnLMJD+2HWZmA3qfmbcNYgszXi1n3pRJM5wDagEGsjRvH1DLmcRmyTnnJAw34NJyPH2b5I+yw8zy7Y2Nn3m+1SVuO3744Ic3ZTbyuGwBAWZeNhQ+YwMDPE5xAMYff/DKj4JRMApGwUgHAAnfXPm7hFL7AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-6923-6968","institution":"Hainan Medical University","correspondingAuthor":true,"prefix":"","firstName":"Yuanhua","middleName":"","lastName":"Huang","suffix":""}],"badges":[],"createdAt":"2023-03-07 23:44:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2667223/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2667223/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":35109472,"identity":"0f1a87b3-ef8d-4775-8d9b-fdb8a038c8fb","added_by":"auto","created_at":"2023-03-31 15:18:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":447220,"visible":true,"origin":"","legend":"\u003cp\u003eOverall design of the study.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2667223/v1/ffecc8181cc86213e3baf247.png"},{"id":35107557,"identity":"2b19d69f-ca2f-43de-b9aa-afaa315f6f8a","added_by":"auto","created_at":"2023-03-31 14:54:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":180344,"visible":true,"origin":"","legend":"\u003cp\u003eVenny analysis of targets for Cyperi Rhizoma effective compounds and Endometriosis.\u003c/p\u003e\n\u003cp\u003e(A)Identification of DEGs in GSE105764. (B)Overlapping genes of Cyperi Rhizoma and endometriosis. (C) Heatmaps showed the expression patterns of these 34 DEGs.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-2667223/v1/82c1f609560483fa87475436.png"},{"id":35107561,"identity":"a743472a-287f-4b50-a5d3-6f58670b57e3","added_by":"auto","created_at":"2023-03-31 14:54:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1082208,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork diagram of “CR Compound-Interactive Target”. Brown represents active compounds of CR, and red is the EMS targets.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-2667223/v1/911881b50ed827e963ef69a9.png"},{"id":35106993,"identity":"e5c5aaaf-731b-4b10-93e3-6ec5c754b552","added_by":"auto","created_at":"2023-03-31 14:46:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":142542,"visible":true,"origin":"","legend":"\u003cp\u003eThe interaction network of CR and EMS targets and hub genes. (A) The network of CR and EMS targets, and the line indicates the type of interaction; (B) The hub genes in the interaction network.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-2667223/v1/22efe2a44e0ed438b2908962.png"},{"id":35107558,"identity":"46fa9d68-9636-4914-858b-fc8f0da3b9ea","added_by":"auto","created_at":"2023-03-31 14:54:15","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":354273,"visible":true,"origin":"","legend":"\u003cp\u003eEnrichment analyses.(A)Go analysis; (B)Kegg analysis; (C)GSEA analysis;\u003c/p\u003e\n\u003cp\u003e(D)Sankey diagram of the enrichment analyses of the therapeutic targets of CR in EMS treatment.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-2667223/v1/719cd01c36f788c14628a726.png"},{"id":35108303,"identity":"62b3c3ff-7df9-4393-831a-b7df206021b1","added_by":"auto","created_at":"2023-03-31 15:02:15","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":47780,"visible":true,"origin":"","legend":"\u003cp\u003eExpression of ICAM1 and VCAM1 in GSE7305dataset.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-2667223/v1/cc377c4bfc4530e2d62d2a47.png"},{"id":35106995,"identity":"6bf368ca-6288-4d49-864d-bf0fe3fb8f05","added_by":"auto","created_at":"2023-03-31 14:46:15","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":403790,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular Docking Analysis of Key Target Protein and Active Components Interactions. (A) For quercetin with ICAM1 and VCAM1. \u0026nbsp;(B) For kaempferol with ICAM1 and VCAM1.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-2667223/v1/70b17f8fbcd455e7bc2ea69d.png"},{"id":35108458,"identity":"c268cd4b-407e-406e-bf1a-8f6211aee68e","added_by":"auto","created_at":"2023-03-31 15:10:15","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":55729,"visible":true,"origin":"","legend":"\u003cp\u003eRT-qPCR and Western blot analyses of the effect of CR on adhesion molecule gene expression in TNF-α-activated HESCs. (A) RT-qPCR analysis. \u0026nbsp;(B) Western blot analysis.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-2667223/v1/184f31b16b04dcf8d1f37d60.png"},{"id":35109492,"identity":"e6c76877-d14a-4a92-91a5-3d392afd761b","added_by":"auto","created_at":"2023-03-31 15:18:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2793041,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2667223/v1/94f9b36a-1fed-44f7-9d2c-cb2d776d414a.pdf"}],"financialInterests":"","formattedTitle":"Exploration of the mechanisms of Cyperi Rhizoma in the treatment of endometriosis through GEO datasets, network pharmacology, and molecular docking studies","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eEndometriosis (EMS) is an estrogen-dependent, chronic inflammatory gynaecological disorder characterised by the growth of endometrial-like tissue outside the uterine cavity[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Endometriosis, which affects over 10% of women of reproductive age, is a significant contributor to infertility, but its aetiology remains unclear. The conventional approach to treating endometriosis is surgical removal of the lesions and hormonal suppression, but these treatments are often associated with side effects and a high rate of recurrence[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Against this backdrop, complementary and alternative medicine (CAM) has recently gained popularity due to its low side effects and high efficacy[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCyperi Rhizoma (CR), the dried rhizome of Cyperus rotundus L. of the plant family Cyperaceae, has a long history of clinical use and is referred to as the 'holy medicine' in gynaecology[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Pharmacological studies have shown that CR has multiple properties, including antioxidant, anti-inflammatory, antidepressant, antipyretic, analgesic, antitumour, hypoglycaemic and antibacterial effects. These properties make CR a widely used therapeutic option for the treatment of a variety of diseases in the nervous system, cardiovascular system, digestive system, uterus and other systems in the clinical setting[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e][\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e][\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. According to a recent analysis of 12,986 herbal prescriptions for the treatment of endometriosis in China, CR was the most commonly used single herb, appearing in 18.8% of all prescriptions[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].CR's therapeutic impact and mechanism for EMS, however, are yet unknown. In order to investigate the underlying mechanisms of the potential benefits of CR in alleviating the symptoms of EMS, a multidisciplinary approach was used, incorporating GEO datasets, network pharmacology, molecular docking, and in vitro experiments(see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These findings provide a novel theoretical basis for the clinical use of CR in the treatment of EMS.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2 Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Active ingredients of Cyperi Rhizoma and CR-related target screening\u003c/h2\u003e \u003cp\u003eInformation on the components of CR was obtained from the Traditional Chinese Medicine Systems Pharmacology database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://tcmsp-e.com/\u003c/span\u003e\u003cspan address=\"https://tcmsp-e.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). TCMSP is one of the world's biggest databases of Chinese herbal medicine, including information on the links between herbs, natural chemicals, target proteins, and disorders[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The TCMSP used oral bioavailability (OB) of ≥ 30 percent and drug likeness (DL) of ≥ 0.18 to screen possible active components of CR. When evaluating the efficacy of a drug, one of the key parameters assessed is its oral bioavailability (OB), which represents the fraction of an orally administered drug that reaches the systemic circulation[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In drug design, the word \"druglikeness\" (DL) is used to define a substance's druglikeness in terms of factors such as bioavailability, and it assists in optimizing pharmacokinetic and pharmacological aspects[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. To identify potential targets, the active ingredients were searched in the TCMSP and PubChem databases (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). PubChem is a public chemical database that is used by both scientists and the general public. This database compiles chemical data from a variety of sources and arranges it into several data sets[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. EMS-related target screening\u003c/h2\u003e \u003cp\u003eThe identification of EMS-relevant targets was performed using the Gene Expression Omnibus (GEO) database, the GeneCards database and the DisGeNET database. RNA-sequencing dataset GSE105764 from the GEO database, which contained 8 paired eutopic (EU) and ectopic (EC) endometrium samples based on GPL20301 (Illumina HiSeq 4000)[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Identification of differentially expressed genes (DEGs) between EC and EU samples was performed using the 'edgeR' package. Genes meeting specific cutoff criteria of FDR \u0026lt; 0.05 and |logFC|\u0026gt;2.0 were defined as DEGs. GeneCards is a comprehensive library of functions in the fields of proteomics, genomics, and transcriptomics[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. DisGeNET is a public-access database of genes and variants linked to human illnesses[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. A Venn diagram was then constructed using the genes obtained. The genes that overlapped were grouped together as candidate targets.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Construction of the “Compound-Target” Network\u003c/h2\u003e \u003cp\u003eThe compounds and associated genes were fed into the Cytoscap 3.7.2 software, resulting in the generation of a compound target interaction network. Cytoscape 3.7.2 is a freely available open source network visualisation software[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The most critical compound in the network was discovered using the CytoNCA plug-in for Cytoscape[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Protein-Protein Interaction Network\u003c/h2\u003e \u003cp\u003eTo facilitate further research, protein-protein interaction (PPI) information was obtained by importing potential targets into String, with the species set to Homo sapiens and the medium confidence level set to 0.4. The MCC algorithm has been used in the 'cytoHubba' program of Cytoscape 3.7.2 to discover the 10 most prominent hub genes[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Enrichment analyses\u003c/h2\u003e \u003cp\u003eGO and KEGG enrichment analysis was performed using the R package \"clusterProfiler\" [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. A p-value of less than 0.05 was used as the criterion for significance. The GO enrichment analysis focused primarily on identifying the biological processes (BP), cellular components (CC), and molecular functions (MF) associated with genes. The KEGG pathway analysis was performed to discover the biological pathways that are associated with the genes. To gain a deeper understanding of the underlying molecular mechanisms of our target candidates, Gene Set Enrichment Analyses (GSEA) were performed using the R package \"gsva\"[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. External dataset verifies the expression of characteristic genes\u003c/h2\u003e \u003cp\u003eGSE7305 was an EMS-related chip dataset comprising 10 healthy subjects, and 10 patients with endometriosis. Based on the relative gene expression data derived from the GSE7305 dataset, we further validated the expression levels of the hub genes previously identified in the GSE105764 dataset.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Molecular docking validation\u003c/h2\u003e \u003cp\u003eBased on the insights gained from the Compound-Target network analysis, high priority compounds and biological targets were selected for molecular docking studies using AutoDock Vina. The 2D molecular structures of the active compounds and critical proteins were obtained using the TCMSP databases and the RCSB PDB (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.rcsb.org/\u003c/span\u003e\u003cspan address=\"http://www.rcsb.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The energy minimization of the molecular structures and the conversion to the mol2 format were performed using ChemBio3D. Docking validation was then performed using both Autodock 1.5.6 and AutoDock Vina. The molecular docking patterns were visualized using Pymol (version 2.2.0) and further analyzed using the Discovery Studio Client software (version 19.1.0).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Preparation of plant material extract\u003c/h2\u003e \u003cp\u003eCyperus rotundus rhizomes were obtained from a local market in Haikou, China. The dried and ground plant material was extracted with ethanol. Cyperi rhizoma extract (CRE) powder was dissolved in dimethyl sulfoxide (DMSO) and filtered through a 0.22 µm filter.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9. Cell Culture\u003c/h2\u003e \u003cp\u003eHuman endometrial stromal cells (HESCs) were obtained from the college of Life Science of Xiamen University (Xiamen, China). HESCs were cultured in DMEM/F-12 supplemented with 10% (v/v) fetal bovine serum and 1% penicillin-streptomycin (100 U/mL, Gibco) at 37°C and 5% CO2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.10. Western blotting analysis\u003c/h2\u003e \u003cp\u003eThe cells were rinsed with PBS. Protein lysis buffer was used for extraction. Protein concentration was determined by the BCA assay. Cell lysates were combined with 5X SDS sample buffer, boiled for 4 minutes, and separated by 10% SDS-PAGE analysis. Proteins were transferred to polyvinylidene difluoride membranes after electrophoresis. The polyvinylidene difluoride membranes were blocked with 2% bovine serum albumin (BSA) for 30 minutes. The membranes were then washed and incubated overnight at 4°C in a solution containing specific primary antibodies, Tris-buffered saline, 2% BSA, and 0.1% Tween-20 (TBS-T). The polyvinylidene difluoride membranes were washed three times in a row to remove any residual primary antibody and then incubated for two hours with horseradish peroxidase-conjugated secondary antibody (at dilutions ranging from 1:1000 to 1:2000). After a careful washing protocol of three times with TBS-T, the presence of immunopositive bands was detected using the ECL chemiluminescent detection system. The acquired data were then analyzed using the ImageQuant Las-4000 imaging platform.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.11. Quantitative real-time RT-PCR\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe qPCR Eastep® Super Total RNA Extraction Kit (Promega, Fitchburg, WI, USA) was used to extract total RNA from the cells. Complementary DNA was then synthesized from total RNA using ChamQ Universal SYBR™ qPCR Master Mix (Vazyme Biotechnology, Nanjing, China) according to the manufacturer's protocol. The polymerase chain reaction (PCR) was performed using ChamQ Universal SYBR qPCR Master Mix in the presence of SYBR Green I fluorescent dye. The amount of product was determined by the comparative threshold cycle (CT) value. The data were quantitatively analyzed using the \u003csup\u003e2−∆∆\u003c/sup\u003eCT method. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) amplification was performed using the following qRT-PCR primer sets: ICAM-1_S (5′-CCG TGA ATG TGC TCT CCC-3′) and ICAM-1_AS (5′-ATT TCT TGA TCT TCC GCT GG-3′); VCAM-1_S (5′-CAG GTG GAG CTC TAC TCA TTC C-3′) and VCAM-1_AS (5′-GAA TAG TCT CCC CCT TAA GTA ATT C-3′). The amplification of the GAPDH gene for normalisation purposes was performed using a set of primers designated GAPDH_S (5′-GAA GAT GGT GAT GGG ATT TC-3′) and GAPDH_AS (5′-GAA GGT GAA GGT CGG AGT-3′).\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.12. Statistical analyses\u003c/b\u003e \u003c/p\u003e \u003cp\u003eBioinformatic analysis was performed using the R programming language, with comparisons between groups performed using the Wilcoxon test. A p-value of less than 0.05 was considered indicative of statistical significance unless otherwise stated.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003ch2\u003e3.1 Active ingredients of Cyperi Rhizoma and CR-related target screening\u003c/h2\u003e\u003cp\u003eA screening of the TCMSP database using OB ≥ 30% and DL ≥ 0.18 as criteria revealed the presence of 18 active compounds in Cyperi Rhizoma that met the established standards(see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A comprehensive search of the TCMSP and PubChem databases identified 467 targets in Cyperi Rhizoma.\u003c/p\u003e\u003cdiv class=\"gridtable\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\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\u003eInformation on 18 effective compounds of Cyperi Rhizoma\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMolecule ID\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMolecule Name\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOB (%)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDL\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL003044\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChryseriol\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.85\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL000354\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eisorhamnetin\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49.60\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL003542\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8-Isopentenyl-kaempferol\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.04\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL000358\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ebeta-sitosterol\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.91\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL000359\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esitosterol\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.91\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL004027\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,4-Epoxy-16-hydroxyheneicos-1,3,12,14,18-pentaene\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL004053\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIsodalbergin\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.45\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL004058\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKhell\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.19\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL004059\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ekhellol glucoside\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74.96\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL010489\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResivit\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.84\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL004068\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003erosenonolactone\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79.84\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL004071\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHyndarin\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73.94\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL004074\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003estigmasterol glucoside_qt\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.83\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL004077\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esugeonyl acetate\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL000422\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ekaempferol\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.88\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL000449\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStigmasterol\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.83\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL000006\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eluteolin\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL000098\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equercetin\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.43\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eOB: oral bioavailability, DL:drug likeness\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003e3.2 EMS-related target screening and Venn analysis\u003c/h2\u003e\u003cp\u003eUsing the criteria of |log2 FC| \u0026gt; 2 and adjusting P-value \u0026lt; 0.05, 1975 differentially expressed genes (DEGs, 1053 upregulated and 922 downregulated) were obtained from the GSE105764 sequencing dataset(see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). A search of the DisGeNET and GeneCards databases using the keyword \"endometriosis\" resulted in the identification of 1188 and 2750 EMS-related targets, respectively.\u003c/p\u003e\u003cp\u003eThe Venny tool was used to analyze the overlap between phytomedicine targets and disease-related genes, resulting in the identification of 34 genes that could potentially serve as targets for Cyperi Rhizoma therapy in endometriosis. These genes included 26 that were shown to be upregulated and 8 that were downregulated in EMS (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB,Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The expression levels of the 34 differentially expressed genes (DEGs) are shown in a heatmap format in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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\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\u003eDifferential gene expression analysis of GSE105764.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene symbol\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLogFC\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFDR\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eChange\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD163\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.360768041\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.15E-28\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.39E-26\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICAM1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.91363036\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.58E-23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.91E-21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVCAM1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.793684837\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.39E-21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.22E-19\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.305851467\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.13E-17\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.53E-15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCL2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.447944366\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.41E-16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14E-14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKR1B1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.021567977\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.07E-15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.77E-13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTIMP1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.31034405\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.16E-15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.78E-13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCYP19A1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.647443725\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.42E-12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.76E-11\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSELE\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.060620414\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.66E-12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.11E-10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBDNF\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.052340528\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.79E-11\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.44E-10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNFRSF1B\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.048841521\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.67E-10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.04E-09\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMP9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.857544356\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.23E-08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.28E-07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNOS2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.684821621\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.27E-08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.81E-07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCXCL12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.450653688\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.04E-07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.40E-06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCYP1B1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.368375739\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.25E-07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.15E-06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePRKCB\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.002892676\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.87E-07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.71E-06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLAU\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.371894372\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.29E-06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.59E-06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD40LG\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.263178217\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.38E-06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.12E-05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPOE\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.043017016\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.86E-06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.33E-05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMPO\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.733416304\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.52E-05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.11E-05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL18\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.08313355\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.59E-05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000268371\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLC2A4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.041949264\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000128062\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000487682\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCXCL8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.346397603\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000412842\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001387641\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMP1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.289169724\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000575944\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001878686\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.124402372\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00087151\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002720124\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMP3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.283576581\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001939556\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00551061\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESR1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.566021217\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.19E-14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.54E-13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003edown\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCLDN4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-5.925801462\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.17E-14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.45E-13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003edown\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMET\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.992218865\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.77E-14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.44E-13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003edown\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePGR\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.366958516\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.12E-07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.68E-06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003edown\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIRC5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.390144421\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.60E-05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000194662\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003edown\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCDK1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.244934986\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.69E-05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000235401\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003edown\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLPI\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.26481389\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000328801\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001137384\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003edown\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDPP4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.343411098\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002334849\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006464018\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003edown\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003e3.3 The “Compound-Target” Network\u003c/h2\u003e\u003cp\u003eA \"Compound-Target\" network was constructed by integrating the active compounds and potential targets in Cytoscape 3.7.2(see Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The network illustrates the multiple effects of the active ingredients in Cyperi Rhizoma on endometriosis. CytoNCA analysis revealed that the top two active compounds were quercetin and kaempferol(see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The results of the analysis suggest that quercetin and kaempferol may play a critical role in mediating the anti-endometriosis effects of Cyperi Rhizoma.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe top 10 compounds and hub genes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMolecule Name\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDegree\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNode name\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMCC Score\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003equercetin\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIL6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.05E + 09\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ekaempferol\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMMP9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.05E + 09\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eluteolin\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCCL2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.05E + 09\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eisorhamnetin\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCXCL8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.05E + 09\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebeta-sitosterol\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eICAM1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.05E + 09\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStigmasterol\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIL10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.05E + 09\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChryseriol\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVCAM1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.05E + 09\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyndarin\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIL18\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.05E + 09\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8-Isopentenyl-kaempferol\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSELE\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.04E + 09\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esitosterol\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTIMP1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.96E + 09\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003e3.4 Protein-Protein Interaction Network\u003c/h2\u003e\u003cp\u003eTo construct the PPI network, 34 potential targets were imported into the STRING database(see Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). The protein-protein interaction data showed a total of 34 nodes and 228 edges with an average degree of 13.4, reflecting a well-connected network structure. Analysis using the Cytoscape plugin cytoHubba and the Maximum Correlation Coefficient (MCC) algorithm revealed the top ten most significant genes in the network, including IL6, MMP9, CCL2, CXCL8, ICAM1, IL10, VCAM1, IL18, SELE, and TIMP1(see Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003ch2\u003e3.5 Enrichment analyses\u003c/h2\u003e\u003cp\u003eWe performed a functional and pathway enrichment analysis of 34 genes using the clusterProfiler R package to gain insight into the molecular mechanisms involved. The GO biological process (GO-BP) category was mainly involved in “regulation of inflammatory response”, “positive regulation of cell adhesion”, etc(see Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA,Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The GO cellular component (GO-CC) category was mainly involved in “external side of plasma membrane”, “collagen-containing extracellular matrix”, etc. The GO molecular function (GO-MF) category was mainly involved in “receptor ligand activity”, “integrin binding”, etc. The results of the KEGG pathway analysis revealed significant associations with pathways such as the TNF pathway and the NF-kappa B pathway, among others(see Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB,Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Gene set enrichment analysis (GSEA) across the MSigDB.v7.0 revealed significant enrichment in “GO_LEUKOCYTE_MIGRATION” and “GO_INFLAMMATORY_RESPONSE” (see Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC,Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). A Sankey diagram was used to directly illustrate the relationships between the enrichment analyses results and the genes involved(see Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD).\u003c/p\u003e\u003cdiv class=\"gridtable\"\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\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEnrichment analyses.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eID\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTerm\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdj_pval\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGenes\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBP\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGO:0050727\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eregulation of inflammatory response\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.88E-07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIL10, CYP19A1, SELE, TNFRSF1B, MMP9, APOE, IL18, IL6, MMP3, ESR1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGO:0045785\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003epositive regulation of cell adhesion\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.83E-06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVCAM1, IL10, CCL2, SELE, CXCL12, CD40LG, IL18, IL6, DPP4\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCC\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGO:0009897\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eexternal side of plasma membrane\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001510618\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCD163, ICAM1, VCAM1, SELE, CXCL12, CD40LG, SLC2A4\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGO:0062023\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecollagen-containing extracellular matrix\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.005911366\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eICAM1, TIMP1, MMP9, CXCL12, APOE, SLPI\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMF\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGO:0048018\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ereceptor ligand activity\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.06E-07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIL10, CCL2, TIMP1, BDNF, CXCL12, CD40LG, IL18, CXCL8, IL6, DPP4\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGO:0005178\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eintegrin binding\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002815111\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eICAM1, VCAM1, CXCL12, CD40LG\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKEGG\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehsa04668\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTNF signaling pathway\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.78E-07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eICAM1, VCAM1, CCL2, SELE, TNFRSF1B,\u003c/p\u003e \u003cp\u003eMMP9, IL6, MMP3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehsa04064\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNF-kappa B signaling pathway\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.57E-06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eICAM1, VCAM1, CXCL12, PRKCB, PLAU,\u003c/p\u003e \u003cp\u003eCD40LG, CXCL8\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGSEA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003emsigdb.v7.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGO_LEUKOCYTE_MIGRATION\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04728902\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCYP19A1,MMP9,IL10,MMP1,SELE,VCAM1,CCL2,CXCL8\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGO_INFLAMMATORY_RESPONSE\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04728902\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCYP19A1,MMP3,MMP9,CD163,IL10,SELE,VCAM1,CCL2,CXCL8,TIMP1,CD40LG\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003ch3\u003e3.6. External dataset verifies \u0026nbsp;the expression of characteristic genes\u003c/h3\u003e\u003cp\u003eUsing the Chip dataset (GSE7305), we conducted a validation study. Our results show that the expression levels of ICAM1 and VCAM1 are increased in endometriosis, which is consistent with the results obtained from the sequencing dataset(GSE105764)(see Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003ch2\u003e3.6 Molecular docking validation\u003c/h2\u003e\u003cp\u003eThe \"Compound-Target\" network's top two active components (quercetin and kaempferol) bind adhesion molecules (ICAM1 and VCAM1) to various degrees (see Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). According to Pymol 2.2.0. (3D structure) and Discovery Studio 2019 Client (2D structure) results, quercetin stably bound to the active site of ICAM1 through GLU-284, LYS-305, and LYS-287 on the ICAM1 target protein, and stably bound to the active site of VCAM1 through SER-41, TRP-35, and VAL-47 on the VCAM1 target protein. Kaempferol stably bound to the active site of ICAM1 through LYS-305 and GLU-301 on the ICAM1 target protein, and stably bound to the active site of VCAM1 through LYS-46, VAL-47, and VAL-190 on the VCAM1 target protein(see Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1680269393.png\"\u003e\u003c/p\u003e\u003ch2\u003e3.7 CR suppressed ICAM1 and VCAM1 expression\u003c/h2\u003e\u003cp\u003eTo investigate the effect of CR on the adhesion capacity of ectopic endometrial cells, we performed RT-qPCR and Western blot analyses to assess the mRNA and protein expression of adhesion molecules (VCAM1 and ICAM1) in endometrial cells in different groups. Exposure of endometriotic stromal cells to TNF-α(10 ng/ml) for 16 hours significantly increased total cellular ICAM1 and VCAM1 protein levels. Pretreatment with CR (50 µg/ml) for 1 hour significantly attenuated the TNF-α-induced upregulation of ICAM1 and VCAM1 protein expression in total cellular content.\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eEndometriosis is a pathological condition characterised by the presence and growth of endometrial cells outside the uterine cavity[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The complexity of the pathophysiology of endometriosis is due to the interaction of genetic, hormonal, inflammatory and immune factors[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The presence of diverse immune cells in the peritoneal cavity environment enhances the invasive and adhesive properties of endometrial cells[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Stimulation of the inflammatory response results in the secretion of cytokines and chemokines into the peritoneal cavity, leading to the creation of a microenvironment that facilitates the growth of ectopic endometrial tissue by promoting local angiogenesis and inhibiting the process of endometrial apoptosis[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Adhesion, invasion and angiogenesis are integral components of the pathogenesis of endometriosis and form the basis of our TCM-based therapeutic approach[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. According to traditional medicine in Vietnam and Taiwan, the use of a decoction made from the CR plant is known to have therapeutic benefits for women suffering from infertility and dysmenorrhoea as a result of endometriosis[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e][\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The CR plant contains biologically active compounds, including flavonoids, with potential immunomodulatory, analgesic, anti-inflammatory and antioxidant properties[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, the exact mechanism of CR's therapeutic effect on endometriosis-related symptoms remains to be elucidated.\u003c/p\u003e \u003cp\u003eIn this study, a systematic network pharmacology analysis was conducted to explore the mechanism of CR in the treatment of symptoms of endometriosis. Components with oral bioavailability (OB) values\u0026thinsp;\u0026ge;\u0026thinsp;30% and drug-likelihood (DL) values\u0026thinsp;\u0026ge;\u0026thinsp;0.18 in CR demonstrated high absorption in the body. As a result, 18 bioactive compounds and 34 potential targets for the treatment of endometriosis with Cyperi Rhizoma were predicted, providing the possibility to elucidate the pharmacological processes of CR.\u003c/p\u003e \u003cp\u003eQuercetin and kaempferol have been identified as the predominant bioactive compounds in CR. Quercetin and kaempferol, two members of the flavonoid family of polyphenolic compounds, have been classified in the subclass of flavonols[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The flavonoids present in CR have been shown to exhibit a number of biologically significant activities, including scavenging the stable radical DPPH, chelating metal ions, scavenging the reactive nitrogen species NO and hydroxyl radicals, and demonstrating antioxidant activity[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In addition, quercetin has been shown to inhibit proliferation and induce cell cycle arrest in endometriotic cells[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In a rat model of endometriosis, combination treatment with quercetin and metformin was found to induce regression of endometrial implants, likely due to its anti-estrogenic and anti-inflammatory properties[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe top ten core nodes identified in the PPI network analysis were IL6, MMP9, CCL2, CXCL8, ICAM1, IL10, VCAM1, IL18, SELE and TIMP1. The inflammatory cytokines IL-6, CCL2, CXCL8, IL10 and IL18 were associated with endometriosis. In the context of endometriosis, it has been proposed that the shed endometrial tissue migrating into the peritoneal cavity may trigger an inflammatory response, with factors released by inflammatory cells (as well as the stromal component of the refluxed endometrium) potentially inducing proliferation of endometrial epithelial cells[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The role of matrix metalloproteinase (MMP) activity is thought to be important in the early stages of endometriosis progression. Disturbances in the balance between matrix metalloproteinases (MMPs), such as MMP9, and their tissue inhibitors (TIMPs), such as TIMP1, could be detrimental and potentially promote the progression of endometriosis[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. VCAM1 and ICAM1 have been shown to play a role in the inflammatory process by facilitating the adhesion of monocytes to endothelial cells[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The ratio of soluble VCAM1 to soluble ICAM1 is a promising biomarker for the diagnosis of endometriosis[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGO enrichment analysis highlighted \"regulation of inflammatory response\" and \"positive regulation of cell adhesion\". The results of the KEGG and GSEA enrichment analyses support the results of the GO analysis, indicating a relationship between the inflammatory response and the activation of the TNF signalling pathway, as well as the GO_INFLAMMATORY_RESPONSE. Our analysis showed that ICAM1 and VCAM1 are involved in the \"positive regulation of cell adhesion\", the TNF signalling pathway, the NF-kappa B signalling pathway and the \"GO_INFLAMMATORY_RESPONSE\". Analysis of the chip datasets (GSE7305) showed that ICAM1 and VCAM1 were significantly upregulated in endometriosis, which was consistent with the findings from the sequencing datasets (GSE105764). Molecular docking results showed efficient binding of ICAM1 and VCAM1 to the flavonoids quercetin and kaempferol. Additionally, our in vitro experiments showed that CR significantly suppressed the expression of ICAM1 and VCAM1 in HESCs induced by TNF-α stimulation. In conclusion, CR has been shown to have anti-inflammatory and anti-adhesive properties in EMS, resulting in a significant reduction in the expression levels of VCAM1 and ICAM1.\u003c/p\u003e \u003cp\u003eHowever, our study had some limitations. Previous studies have shown that NF-κB signaling induces the high expression of key adhesion molecules in the ectopic endometrium, including ICAM1, and vascular VCAM1[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. CR maybe reduce the inflammatory response and adhesive ability of endometriotic cells, possibly via the NF-κB signaling pathway. So, further experiments and analysis are needed to validate our predicted results.\u003c/p\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003eOur study showed that CR contains 18 bioactive components and 34 potential therapeutic targets. Quercetin and kaempferol were the main active compounds in CR that produced therapeutic effects against EMS. IL6, MMP9, CCL2, CXCL8, ICAM1, IL10, VCAM1, IL18, SELE and TIMP1 emerged as key hub genes. GO, KEGG and GSEA analysis showed that ICAM1 and VCAM1 are involved in \"positive regulation of cell adhesion\", TNF signalling pathway, NF-kappa B signalling pathway and \"GO_INFLAMMATORY_RESPONSE\". GEO chip and sequencing data revealed significant upregulation of ICAM1 and VCAM1 in ectopic endometrial tissue from EMS. In addition, both quercetin and kaempferol were shown to have strong binding affinities for ICAM1 and VCAM1 in molecular docking. The results of RT-qPCR and Western blotting experiments showed that CR effectively reduced TNF-α-induced expression of ICAM1 and VCAM1 in human endometriotic stromal cells. Our results provide a novel basis for exploring the potential of CR as a preventive and therapeutic approach to EMS in humans.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe data used to support the results of the study are included in the published paper.\u003c/p\u003e\n\u003ch2\u003eConflicts of Interest\u003c/h2\u003e\n\u003cp\u003eThe authors of this paper have no potential conflicts of interest.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026rsquo; Contributions and Consent to participate\u003c/h2\u003e\n\u003cp\u003eYuanhua Huang and Yanlin Ma were responsible for the conception and design of the study and the experiments, while data collection was performed by Jinjing Li, Yanbin Jin and Yongwei Limeng. Xingyi Fang and Yi Gong designed the experiments and drafted the manuscript. The final version of the manuscript was approved by all authors.\u003c/p\u003e\n\u003ch2\u003eFunding Statement\u003c/h2\u003e\n\u003cp\u003eThis study was financially supported by the Hainan Provincial Natural Science Foundation (No. ZDKJ2021037), the China Postdoctoral Science Foundation (No. 2021M691466) and the National Natural Science Foundation of China (No. 8220061871).\u003c/p\u003e\n\u003ch2\u003eEthics approval\u003c/h2\u003e\n\u003cp\u003eThe Medical Ethics Committee of the First Affiliated Hospital of Hainan Medical University reviewed and approved our project for implementation, confirming its compliance with all relevant laws and regulations.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eAll authors have consented to the publication of this article.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and material\u003c/h2\u003e\n\u003cp\u003eThe data is transparent and can be made publicly available for publication.\u003c/p\u003e\n\u003ch2\u003eCode availability\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNirgianakis K, Egger K, Kalaitzopoulos DR et al. 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An Update on the Multifaceted Role of NF-kappaB in Endometriosis. \u003cem\u003eInt J Biol Sci\u003c/em\u003e 2022, 18(11):4400-4413.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"reproductive-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resc","sideBox":"Learn more about [Reproductive Sciences](https://rd.springer.com/journal/43032)","snPcode":"43032","submissionUrl":"https://www.editorialmanager.com/resc/default2.aspx","title":"Reproductive Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"endometriosis, Cyperi Rhizoma, GEO datasets, network pharmacology, molecular docking, ICAM1, VCAM1","lastPublishedDoi":"10.21203/rs.3.rs-2667223/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2667223/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCyperi rhizoma (CR) has traditionally been used to treat endometriosis (EMS), but its molecular mechanism remains unclear. To address this, we used a multi-faceted approach that included analysis of GEO datasets, network pharmacology, molecular docking and in vitro experiments.CR components and their potential targets were identified using TCMSP and PubChem, while GEO datasets, GeneCards, and DisGeNET were used to retrieve EMS-related targets. Compound-target and protein-protein interaction networks were constructed using Cytoscape and STRING, respectively, and hub genes were identified using CytoHubba. Enrichment analysis and molecular docking were performed, and RT-qPCR and Western blotting were used to assess protein expression levels. According to our research, there are 18 active CR components and 34 possible anti-EMS targets. Network analysis identified quercetin and kaempferol as potential key chemicals and revealed IL6, MMP9, CCL2, CXCL8, ICAM1, L10, VCAM1, IL18, SELE and TIMP1 as central hub genes in the network. GO, KEGG and GSEA analyses showed that ICAM1 and VCAM1 are involved in \"positive regulation of cell adhesion\", TNF signalling pathway, NF-kappa B signalling pathway and \"GO_INFLAMMATORY_RESPONSE\". Analysis of the GEO datasets revealed that ICAM1 and VCAM1 were upregulated in endometriosis compared to controls. Molecular docking showed that quercetin and kaempferol have strong binding affinities for these proteins. RT-qPCR and Western blotting analyses showed that CR treatment suppressed ICAM1 and VCAM1 expression, leading to reduced inflammation and adhesion in endometriosis-associated symptoms. Thus, these results provide a novel rationale for the potential of CR in the treatment of EMS.\u003c/p\u003e","manuscriptTitle":"Exploration of the mechanisms of Cyperi Rhizoma in the treatment of endometriosis through GEO datasets, network pharmacology, and molecular docking studies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-03-31 14:46:10","doi":"10.21203/rs.3.rs-2667223/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2023-03-29T18:09:48+00:00","index":0,"fulltext":""},{"type":"editorAssigned","content":"","date":"2023-03-15T11:45:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Reproductive Sciences","date":"2023-03-09T08:34:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"reproductive-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resc","sideBox":"Learn more about [Reproductive Sciences](https://rd.springer.com/journal/43032)","snPcode":"43032","submissionUrl":"https://www.editorialmanager.com/resc/default2.aspx","title":"Reproductive Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"0b48b79d-6df5-4090-ae51-6507e2b84f60","owner":[],"postedDate":"March 31st, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-06-03T05:06:05+00:00","versionOfRecord":[],"versionCreatedAt":"2023-03-31 14:46:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2667223","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2667223","identity":"rs-2667223","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}