[Network Meta-analysis of peroral Chinese patent medicines for activating blood and resolving stasis in treatment of endometriosis].

Network Meta-analysis was performed to systematically compare the efficacy of different Chinese patent medicines for activating blood and resolving stasis in the treatment of endometriosis and to provide evidence-based references for clinical medication regimens. The relevant randomized controlled trials(RCTs) involving Chinese patent medicines combined with conventional treatment(experimental group) vs conventional treatment(control group) were retrieved from Chinese and English literature databases. The bias risk assessment tool recommended in Cochrane handbook 5.3 was used to evaluate the quality of the included studies. The result data of each outcome index was extracted for network Meta-analysis in Stata 15.0. A total of 44 RCTs were included in this study, involving 4 345 patients and 9 Chinese patent medicines. The network Meta-analysis revealed the following trends.(1)In terms of reducing the visual analogue scale(VAS) scores, Dan'e Fukang Plaster+conventional treatment>Xuefu Zhuyu Capsules+conventional treatment>Gongliuxiao Capsules+conventional treatment.(2)In terms of reducing cancer antigen CA125, Xiaojin Capsules+conventional treatment>Shaofu Zhuyu Granules+conventional treatment>Dan'e Fukang Plaster+conventional treatment.(3)In terms of reducing estradiol(E_2), Gongliuxiao Capsules+conventional treatment>Xiaojin Capsules+conventional treatment>Sanjie Zhentong Capsules+conventional treatment.(4) In terms of reducing recurrence rate, Guizhi Fuling Capsules+conventional treatment>Xuefu Zhuyu Capsules+conventional treatment>Dan'e Fukang Plaster+conventional treatment. The peroral Chinese patent medicines for activating blood and resolving stasis combined with conventional treatment have better efficacy in the treatment of endometriosis than conventional treatment. However, considering the low quality of the included literature, large-scale high-quality clinical trials are needed in the future research.

Potential mechanism of Luoshi Neiyi prescription in endometriosis based on serum pharmacochemistry and network pharmacology.

Introduction: Endometriosis (EMs) is characterized by ectopic growth of active endometrial tissue outside the uterus. The Luoshi Neiyi prescription (LSNYP) has been extensively used for treating EMs in China. However, data on the active chemical components of LSNYP are insufficient, and its pharmacological mechanism in EMs treatment remains unclear. This study aimed to explore the potential mechanism of LSNYP for EMs through network pharmacology based on the components absorbed into the blood. Methods: Ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry was used to analyze blood components, and a series of network pharmacology strategies were utilized to predict targets of these components and EMs. Protein-protein interaction (PPI) network analysis, component-target-disease network construction, gene ontology (GO) functional enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. Additionally, molecular docking, molecular dynamics simulations, and in vitro and in vivo experiments were conducted to validate the HIF1A/EZH2/ANTXR2 pathway associated with hypoxic pathology in EMs. Results: Thirty-four absorbed components suitable for network pharmacology analysis were identified, and core targets, such as interleukin 6, EGFR, HIF1A, and EZH2, were founded. Enrichment results indicated that treatment of EMs with LSNYP may involve the regulation of hypoxia and inflammatory-related signaling pathways and response to oxidative stress and transcription factor activity. Experimental results demonstrated that LSNYP could decrease the expression of HIF1A, ANTXR2, YAP1, CD44, and ß-catenin, and increased EZH2 expression in ectopic endometrial stromal cells and endometriotic tissues. Molecular docking and molecular dynamics simulations manifested that there was stable combinatorial activity between core components and key targets of the HIF1A/EZH2/ANTXR2 pathway. Conclusion: LSNYP may exert pharmacological effects on EMs via the HIF1A/EZH2/ANTXR2 pathway; hence, it is a natural herb-related therapy for EMs.

Luoshi Neiyi Prescription inhibits estradiol synthesis and inflammation in endometriosis through the HIF1A/EZH2/SF-1 pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Endometriosis (EMS) is a common gynecological disease that causes dysmenorrhea, chronic pelvic pain and infertility. Luoshi Neiyi Prescription (LSNYP), a traditional Chinese medicine (TCM) formula, is used to relieve EMS in the clinic. AIMS: This study aimed to examine the active components of LSNYP and the possible mechanism involved in its treatment of EMS. MATERIALS AND METHODS: Ultrahigh-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS) was used to identify the chemical components of LSNYP. Human primary ectopic endometrial stromal cells (ecESCs) and eutopic endometrial stromal cells (euESCs) were isolated, and the expression levels of hypoxia inducible factor 1A (HIF1A), enhancer of zeste homolog 2 (EZH2) and steroidogenic factor 1 (SF-1) were detected by immunofluorescence and qPCR. Cobalt chloride (CoCl2) was utilized to construct an in vitro hypoxic environment, and lentiviruses were engineered to downregulate HIF1A and EZH2 and upregulate EZH2. Subsequently, the expression levels of HIF1A, EZH2, and SF-1 were measured using qPCR or western blotting. The binding of EZH2 to the SF-1 locus in ESCs was examined via ChIP. Furthermore, the effects of LSNYP on the HIF1A/EZH2/SF-1 pathway were evaluated both in vitro and in vivo. RESULTS: A total of 185 components were identified in LSNYP. The protein and gene expression levels of HIF1A and SF-1 were increased, whereas those of EZH2 were decreased in ecESCs. After treating euESCs with 50 µmol L-1 CoCl2 for 24 h, cell viability and estradiol (E2) production were enhanced. Hypoxia decreased EZH2 protein expression, while si-HIF1A increased it. SF-1 was increased when EZH2 was downregulated in normal and hypoxic environments, whereas the overexpression of EZH2 led to a decrease in SF-1 expression. ChIP revealed that hypoxia reduced EZH2 binding to the SF-1 locus in euESCs. In vitro, LSNYP-containing serum decreased E2 and prostaglandin E2 (PGE2) production, inhibited cell proliferation and invasion, and reduced the expression of HIF1A, SF-1, steroidogenic acute regulatory protein (StAR), and aromatase cytochrome P450 (P450arom). In vivo, LSNYP suppressed inflammation and adhesion and inhibited the HIF1A/EZH2/SF-1 pathway in endometriotic tissues. CONCLUSIONS: LSNYP may exert pharmacological effects on EMS by inhibiting E2 synthesis and inflammation through regulation of the HIF1A/EZH2/SF-1 pathway. These results suggest that LSNYP may be a promising candidate for the treatment of EMS.

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

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