Biomarkers For Endometriosis Research Articles

Bioinformatic Analysis of m6A Regulator-Mediated RNA Methylation Modification Patterns and Immune Microenvironment Characterization in Endometriosis.

Epigenetic regulation plays an essential role in immunity and inflammation in endometriosis. In this study, we aimed to explore differences in m6A regulators between endometriosis patients and normal women and analyze the effect of m6A modification on immune and inflammatory microenvironment. The samples for analysis were downloaded from the Gene Expression Omnibus database, including ectopic endometrium (EC), eutopic endometrium (EU), and normal eutopic endometrium (NM) samples from non-endometriosis women. The validation process involved utilizing our previous RNA-sequencing data. Subsequently, a correlation analysis was performed to ascertain the relationship between m6A and the inflammatory microenvironment profile, encompassing infiltrating immunocytes, immune-inflammation reaction gene sets, and human leukocyte antigen genes. LASSO analyses were used to develop risk signature. The findings of this study indicate that the m6A regulators FTO were observed to be significantly up-regulated, while YTHDF2, CBLL1, and METTL3 were down-regulated in endometriosis tissues. The CIBERSORT analysis revealed that the local inflammatory microenvironment of ectopic lesions plays a crucial role in the development of endometriosis. Notably, M2 macrophages exhibited a significant difference between the EC and NM groups. Moreover, M2 macrophages demonstrated a positive correlation with FTO (0.39) and a negative correlation with CBLL1 (-0.35). Furthermore, consistent clustering of EC and EU samples resulted in the identification of three distinct cell subtypes. Among different cell subtypes, significant differences were in immunoinfiltrating cells, plasma cells, naive CD4 T cells, memory activated CD4 T cells, gamma delta T cells, resting NK cells and activated NK cells but not in macrophages. Furthermore, the identification of various compounds capable of targeting these m6A genes was achieved. In conclusions, our integrated bioinformatics analysis results demonstrated that m6A-related genes METTL3, CBLL1 and YTHDF2 may be useful biomarkers for endometriosis in ectopic endometrium. The potential therapeutic approach of targeting m6A regulators holds promise for the treatment of endometriosis.

Combined delta neutrophil index and red blood cell distribution width as a new biomarker to predict endometriosis

The aim of this study was to evaluate the use of delta neutrophil index (DNI) in predicting endometriosis. A retrospective, case-control study was performed in a tertiary care center. DNI, red cell distribution width (RDW), and other blood parameters obtained from complete blood counts of 267 patients, consisting of 122 (45.7%) endometriosis patients with proven pathology reports of stages 3-4, and a control group of 145 women who underwent laparoscopy for simple ovarian cyst and/or diagnostic purposes and had normal histopathology, were compared. Receiver operating characteristic and logistic regression analyses were performed. DNI and RDW were significantly higher in endometriosis patients than in the control group (p=0.034 and p=0.003, respectively). Other parameters obtained from complete blood counts (leukocyte, neutrophil, lymphocyte, monocytes, and platelet counts and neutrophil-to-lymphocyte ratio), did not differ (p>0.05). For DNI, at a cut-off value of 0.025, area under the curve (AUC) was 0.572 and it was statistically significant [p=0.042; 95% confidence interval (CI): 0.503-0.642, sensitivity: 45.9%, specificity: 67.6%, Youden’s index: 0.135]. For RDW, AUC: 0.601 for cut-off value of 13.65 was statistically significant (p=0.004, 95% CI: 0.553-0.669, sensitivity: 50.8%, specificity: 67.6%, Youden’s index: 0.184). The logistic regression model established with the combined marker obtained by multiplying the DNI and RDW was statistically significant (p<0.001, Nagelkerke R2=0.72, 95% CI: 2.58-47.26, B: 2.40, negative predictive value: 78.6%, positive predictive value: 37.7%). DNI, a new inflammatory marker, and RDW, known to be associated with inflammation, may be useful minimally invasive biomarkers of endometriosis.

Determination of Serum Arginase-1 Concentrations and Serum Arginase Activity for the Non-Invasive Diagnosis of Endometriosis.

Backgroud: Endometriosis remains a diagnostic challenge, both clinically and economically, affecting 6% to 15% of women of child-bearing potential. We have attempted to determine whether testing serum concentrations and activity of arginase isoenzymes could be useful for the non-invasive diagnosis of endometriosis. Methods: This study involved 180 women (105 endometriosis subjects-study group B; 22 subjects with other benign gynaecological conditions-control group 1-K1, both undergoing surgery; and 53 healthy subjects without features of endometriosis-control group 2-K2). Results: Preoperative and postoperative arginase-1 (Arg-1) concentrations were significantly higher in patients, as compared with the control groups K1 (p < 0.0001 and p = 0.0005, respectively) and K2 (both p < 0.0001). Similarly, arginase activity was significantly higher in patients than in the control group K1 before surgery and higher than in both control groups after surgery. No significant differences in either Arg-1 concentrations or arginase activity were noted between the operated control group K1 and the non-operated control group K2. A significant postoperative decrease in Arg-1 concentration was observed within both patient (p < 0.0001) and control group K1 (p = 0.0043). Diagnostic performance was assessed using the receiver operating characteristic (ROC) method. The threshold for differentiation between endometriosis patients and healthy non-operated controls was 42.3 ng/mL, with a sensitivity of 90% and specificity of 81%. For differentiation of patients and operated controls with benign gynaecological conditions, the threshold was 78.4 ng/mL, with a sensitivity of 61% and specificity of 95%. Conclusions: We, therefore, conclude that Arg-1 serum concentrations and arginase activity could be considered potential biomarkers for endometriosis but require further studies on larger cohorts of patients.

Metabolomics as a Candidate for Endometriosis Biomarker: A Systematic Review

Background: To date, diagnosis is still a challenge in managing endometriosis. There is a need to develop a less invasive yet accurate approach, such as a biomarker, to help diagnose endometriosis earlier and more precisely. Metabolomics, the study of metabolites, are thought to provide a more accurate relation to phenotype compared to other omics technology and may help develop endometriosis biomarkers. This review aims to systematically summarize evidence regarding the use of metabolomics studies in the diagnosis of endometriosis. Methods: This review was conducted according to PRISMA 2020 guidelines. Including studies on endometriosis and metabolomics in Medline, Embase, and Cochrane Library to May 2022. Inclusion: Women of reproductive age, laparoscopically diagnosed — exclusion criteria: no full-text, languages other than English, and animal studies. Papers were screened and extracted using Covidence, appraised using Newcastle-Ottawa Scale (NOS), by two independent reviewers. Results: A total of 33 studies are included in this review, and 24 showed positive results regarding the metabolites identified and their association with endometriosis. Twenty-four studies reported good area under curve (AUC), sensitivity, and specificity scores in diagnosing endometriosis using a prediction model from the attained metabolites. However, the summary of these scores is not feasible due to the lack of standardization in reporting metabolomics studies. Both serum and endometriotic lesion microenvironments, such as peritoneal fluid, endometrioma, follicular fluid, and tissue lesions, give essential information on which metabolites are altered in endometriosis. Phosphatidylcholine (PC), acylcarnitines (AC), and sphingomyelins (SM) are these studies’ most frequent significant metabolites, but their levels vary. Although all studies had an overall good appraisal score, regarding confounders included, the variation in their methods of analysis and prediction model approach should be interpreted with caution. These predictions are also mostly done without using two different data groups for test and validation. Conclusions: Metabolomics studies may become an alternative for a less invasive approach to diagnosing endometriosis. This review revealed how encouraging results from metabolomics studies are. However, the need for more standardization in the study report and preliminary design for making a prediction model is still in the way of fully trusting metabolomics studies to account for endometriosis diagnostic biomarkers. Registration: PROSPERO CRD42022334916

Identification of miR-30c-5p microRNA in Serum as a Candidate Biomarker to Diagnose Endometriosis.

The diagnosis of endometriosis by laparoscopy is delayed until advanced stages. In recent years, microRNAs have emerged as novel biomarkers for different diseases. These molecules are small non-coding RNA sequences involved in the regulation of gene expression and can be detected in peripheral blood. Our aim was to identify candidate serum microRNAs associated with endometriosis and their role as minimally invasive biomarkers. Serum samples were obtained from 159 women, of whom 77 were diagnosed with endometriosis by laparoscopy and 82 were healthy women. First, a preliminary study identified 29 differentially expressed microRNAs between the two study groups. Next, nine of the differentially expressed microRNAs in the preliminary analysis were evaluated in a new cohort of 67 women with endometriosis and 72 healthy women. Upon validation by quantitative real-time PCR technique, the circulating level of miR-30c-5p was significantly higher in the endometriosis group compared with the healthy women group. The area under the curve value of miR-30c-5p was 0.8437, demonstrating its diagnostic potential even when serum samples registered an acceptable limit of hemolysis. Dysregulation of this microRNA was associated with molecular pathways related to cancer and neuronal processes. We concluded that miR-30c-5p is a potential minimally invasive biomarker of endometriosis, with higher expression in the group of women with endometriosis diagnosed by laparoscopy.

Metabolome analysis as a potential source of biomarkers in endometriosis

Metabolome analysis as a potential source of biomarkers in endometriosis

Identification of programmed cell death-related genes and diagnostic biomarkers in endometriosis using a machine learning and Mendelian randomization approach.

Endometriosis (EM) is a prevalent gynecological disorder frequently associated with irregular menstruation and infertility. Programmed cell death (PCD) is pivotal in the pathophysiological mechanisms underlying EM. Despite this, the precise pathogenesis of EM remains poorly understood, leading to diagnostic delays. Consequently, identifying biomarkers associated with PCD is critical for advancing the diagnosis and treatment of EM. This study used datasets from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs) following preprocessing. By cross-referencing these DEGs with genes associated with PCD, differentially expressed PCD-related genes (DPGs) were identified. Enrichment analyses for KEGG and GO pathways were conducted on these DPGs. Additionally, Mendelian randomization and machine learning techniques were applied to identify biomarkers strongly associated with EM. The study identified three pivotal biomarkers: TNFSF12, AP3M1, and PDK2, and established a diagnostic model for EM based on these genes. The results revealed a marked upregulation of TNFSF12 and PDK2 in EM samples, coupled with a significant downregulation of AP3M1. Single-cell analysis further underscored the potential of TNFSF12, AP3M1, and PDK2 as biomarkers for EM. Additionally, molecular docking studies demonstrated that these genes exhibit significant binding affinities with drugs currently utilized in clinical practice. This study systematically elucidated the molecular characteristics of PCD in EM and identified TNFSF12, AP3M1, and PDK2 as key biomarkers. These findings provide new directions for the early diagnosis and personalized treatment of EM.

Diagnostic value of the combination of circulating serum miRNAs and CA125 in endometriosis.

Circulating microRNAs (miRNAs) can serve as noninvasive biomarkers for endometriosis, but their diagnostic and prognostic values require investigation. This study evaluated the potential of 6 miRNAs in diagnosing endometriosis and predicting fertility. The study included patients with endometriosis (stages I-IV) and controls admitted to Sun Yat-Sen Memorial Hospital between May 2013 and March 2014. The serum expression levels of 6 miRNAs (miR-199a, miR-145*, miR-122, miR-9*, miR-141*, and miR-542-3p) were determined using qRT-PCR. Receiver operating characteristics curves were used to determine the diagnostic accuracy. The study included 155 patients with endometriosis and 77 controls. The model combining miR-199a, miR-122, miR-145*, and miR-141* with the carbohydrate antigen 125 (CA125) exhibited 81.8% sensitivity and 92.6% specificity and an area under the curve of 0.939 for diagnosing endometriosis. When combining miR-199a, miR-122, miR-145*, miR-542-3p, and CA125, the receiver operating characteristics curve showed an area under the curve of 0.759 and 79.6% sensitivity and 73.5% specificity for stage I/II versus III/IV endometriosis. Circulating miRNA levels were associated with pelvic adhesions (miR-199a, P < .05), lesion distribution (miR-9*, miR-145*, and miR-141*; all P < .05), and the presence of deep infiltrating endometriosis (miR-199a and miR-122; both P < .001). The expression levels of miR-199a, miR-122, and miR-542-3p decreased with an increasing endometriosis fertility index. The model combining circulating miRNAs (miR-199a, miR-122, miR-145*, and miR-141*) and CA125 is promising for diagnosing endometriosis and its severity. miR-199a, miR-122, and miR-542-3p were associated with the endometriosis fertility index and might be used to predict fertility preoperatively, but these results require confirmation.

Standardized protocol for quantification of nerve bundle density as a biomarker for endometriosis

IntroductionWe propose a standardized protocol for measurement of nerve bundle density in endometriosis as a potential biomarker, including in deep endometriosis (DE), ovarian endometriomas (OMA) and superficial peritoneal endometriosis (SUP).MethodsThis was a prospective cohort of surgically excised endometriosis samples from Dec 1st 2013 and Dec 31st 2017 at a tertiary referral center for endometriosis in Vancouver, BC, Canada. Surgical data were available from linked patient registry. Protein gene product 9.5 (PGP9.5) was used to identify nerve bundles on immunohistochemistry. PGP9.5 nerve bundles were counted visually. To calculate nerve bundle density, PGP9.5 nerve bundle count was divided by the tissue surface area (total on the slide). All samples were assessed using NHS Elements software for semi-automated measurement of the tissue surface area. For a subset of samples, high power fields (HPFs) were also counted as manual measurement of the tissue surface area. Intraclass correlation was used to assess intra observer and inter observer reliability. Generalized linear mixed model (GLMM) with random intercepts only was conducted to assess differences in PGP9.5 nerve bundle density by endometriosis type (DE, OMA, SUP).ResultsIn total, 236 tissue samples out of 121 participants were available for analysis in the current study. Semi-automated surface area measurement could be performed in 94.5% of the samples and showed good correlation with manually counted HPFs (Spearman's rho = 0.781, p &amp;lt; 0.001). To assess intra observer reliability, 11 samples were assessed twice by the same observer; to assess inter observer reliability, 11 random samples were blindly assessed by two observers. Intra observer reliability and inter observer reliability for nerve bundle density were excellent: 0.979 and 0.985, respectively. PGP9.5 nerve bundle density varied among samples and no nerve bundles could be found in 24.6% of the samples. GLMM showed a significant difference in PGP9.5 nerve bundle density between the different endometriosis types (X2 = 87.6, P &amp;lt; 0.001 after adjusting for hormonal therapy, with higher density in DE and SUP in comparison to OMA).ConclusionA standardized protocol is presented to measure PGP9.5 nerve bundle density in endometriosis, which may serve as a biomarker reflecting local neurogenesis in the endometriosis microenvironment.

Machine learning-based integrated identification of predictive combined diagnostic biomarkers for endometriosis

Background: Endometriosis (EM) is a common gynecological condition in women of reproductive age, with diverse causes and a not yet fully understood pathogenesis. Traditional diagnostics rely on single diagnostic biomarkers and does not integrate a variety of different biomarkers. This study introduces multiple machine learning techniques, enhancing the accuracy of predictive models. A novel diagnostic approach that combines various biomarkers provides a new clinical perspective for improving the diagnostic efficiency of endometriosis, holding significant potential for clinical application.Methods: In this study, GSE51981 was used as a test set, and 11 machine learning algorithms (Lasso, Stepglm, glmBoost, Support Vector Machine, Ridge, Enet, plsRglm, Random Forest, LDA, XGBoost, and NaiveBayes) were employed to construct 113 predictive models for endometriosis. The optimal model was determined based on the AUC values derived from various algorithms. These genes were then evaluated using nine machine learning algorithms (Random Forest, SVM, Gradient Boosting Machine, LASSO, XGB, NNET, Generalized Linear Model, KNN, and Decision Tree) to assess significance scores and identify diagnostic genes for each algorithm. The diagnostic value of these genes was further validated in external datasets from GSE7305, GSE11691, and GSE120103.Results: Analysis of the GSE51981 dataset revealed 62 DEGs. The Stepglm [Both] and plsRglm algorithms identified 30 genes with the most potential using the AUC evaluation. Subsequently, nine machine learning algorithms were applied to select diagnostic genes, leading to the identification of five key diagnostic genes using the LASSO algorithm. The ADAT1 gene exhibited the best single-gene predictive performance, with an AUC of 0.785. A combination of genes (FOS, EPHX1, DLGAP5, PCSK5, and ADAT1) achieves an AUC of 0.836 in the test dataset. Moreover, these genes consistently exhibited an AUC exceeding 0.78 in all validation datasets, demonstrating superior predictive performance. Furthermore, correlation analysis with immune infiltration strengthened their predictive value by demonstrating the close relationship of the diagnostic genes with immune infiltrating cells.Conclusion: A combination of biomarkers consisting of FOS, EPHX1, DLGAP5, PCSK5, and ADAT1 can serve as a diagnostic tool for endometriosis, enhancing diagnostic efficiency. The association of these genes with immune infiltrating cells reveals their potential role in the pathogenesis of endometriosis, providing new insights for early detection and treatment.

ITRAQ-based proteomics analysis of human ectopic endometrial stromal cells treated by Maqian essential oil

BackgroundEndometriosis is a common and complex syndrome characterized by the presence of endometrial-like tissue outside the uterus. Chinese medicine has been recently found to show good efficacy in treating endometriosis. Our previous results revealed that Maqian fruit essential oil (MQEO) could inhibit the proliferation and induce apoptosis of ectopic endometrial stromal cells (EESCs), but the mechanisms remain unclear. In this study, we aim to explore the molecular mechanism of MQEO’s specific effects in EESCs.MethodsWe conducted a quantitative proteomics analysis by iTRAQ on EESCs treated with MQEO or DMSO. Then deep analysis was performed based on differentially expressed proteins, including Gene Ontology enrichment analysis, pathway enrichment analysis and protein interaction analysis. Candidate protein targets were subsequently verified by western blotting.ResultsAmong 6575 identified proteins, 435 proteins exhibited altered expression levels in MQEO-treated EESCs. Of these proteins, most were distributed in signal transduction as well as immune system and the most significantly altered pathway was complement and coagulation cascades. Moreover, two differentially expressed proteins (Heme oxygenase 1 and Acyl-CoA 6-desaturase) were verified and they can be potential biomarkers for endometriosis treatment.ConclusionsOur proteomic analysis revealed distinct protein expression patterns induced by MQEO treatment in EESCs, highlighting the potential of MQEO for endometriosis treatment and biomarker discovery.

Leukocyte telomere length is associated with increased risk of endometriosis: a bidirectional two-sample Mendelian randomization study.

Endometriosis (EMs) is a common gynecological disorder. Observational studies on the relationship between leukocyte telomere length (LTL) and EMs have shown conflicting results. The purpose of this study was to evaluate the precise causal relationship between LTL and EMs using Mendelian randomization (MR) methodology. We employed MR to assess the causal relationship between LTL and EMs. Summary data from several large-scale genome-wide association studies (GWAS) were used for bidirectional two-sample MR analysis. Sensitivity analyses were conducted to ensure the robustness of our results. All analyses were also replicated in another completely independent EMs dataset. Our MR analysis indicated that genetically predicted longer LTL increased the risk of EMs (IVW: discovery, OR=1.169, 95%CI: 1.059-1.290, p=0.002; validation, OR=1.302, 95%CI: 1.140-1.487, p=0.000), while EMs had no causal impact on LTL (IVW: discovery, OR=1.013, 95%CI: 1.000-1.027, p=0.056; IVW: validation, OR=1.005, 95%CI: 0.995-1.015, p=0.363). Causal estimates were supported by various calculation models (including MR-Egger, Weighted median, MR-PRESSO, and MR-RAPS). Heterogeneity and pleiotropy analyses also indicated robustness of the results. Our findings substantiate the idea that a genetically predicted longer LTL elevates the risk of EMs, with no influence of EMs on LTL risk. This research bolsters the causal link between LTL and EMs, overcoming the constraints of earlier observational studies. It implies that LTL may potentially function as a biomarker for EMs, opening up novel possibilities for EMs prevention and treatment.

The Holy Grail of endometriosis biomarkers in the diagnostic process – How much would it be worth and what does it look like?

Previously, the gold standard for the diagnosis of endometriosis involved the performance of laparoscopic surgery, which allows the visualization and histological examination of the endometrial tissue. According to the latest guidelines published by the European Society of Human Reproduction and Embryology (ESHRE) in 2022, surgery is recommended only in patients with diagnostic difficulties associated with the use of non-invasive methods or in case of inappropriate or unsuccessful empirical treatment. At the same time, it is not recommended to use the measurement of biomarkers in the endometrial tissue, blood, menstrual or uterine fluids to diagnose endometriosis as the ESHRE guideline development group indicated the need of larger, multi-center prospective studies on this matter. The aim of this narrative review is to present advances in knowledge on non-invasive endometriosis diagnostic opportunities with emphasis on proteomics, the use of endometrial aspiration biopsy, iron metabolism, vitamin D-binding protein, extracellular matrix signaling pathways, epithelial−mesenchymal transformation, and other molecular pathways, together with a critical analysis of studies cited in the recent ESHRE guidelines.

Non-invasive tests for endometriosis are here; how reliable are they, and what should we do with the results?

A reliable non-invasive biomarker for endometriosis is highly likely in the coming years. In the lead-up to this, clinicians need to be aware of commercially available tests as they become accessible, be aware of the level of evidence to support them and be prepared to counsel and manage patients who present with the results of such tests. One such test gaining popularity in Europe was developed using a machine-based learning algorithm to analyse thousands of microRNAs based on a 200-patient cohort with suspected endometriosis in France. We explore the background science for this commercially available test; outline the questions that remain to be answered; and caution against its use outside of a research setting.

ПОТЕНЦИАЛЬНЫЕ БИОМАРКЕРЫ ЭНДОМЕТРИОЗА: ПОИСК ПРОДОЛЖАЕТСЯ

Abstract. Introduction. Endometriosis is a chronic estrogen-dependent disease characterized by the presence of endometrial-like tissue outside the uterine cavity and most often manifested by pelvic pain and infertility. It affects up to 10% of women of reproductive age, which is about 190 million women worldwide, and it is a serious medical and social issue. In the clinical context, it is advisable to search for biomarkers of the disease to ensure early noninvasive diagnosis. Current literature on potential biomarkers of endometriosis is already quite extensive. However, despite many publications, there is no consensus on and no similar approaches to defining such markers. Therefore, the search for potential biomarkers of endometriosis is still relevant. Aim: To summarize the information of contemporary literature on possible biomarkers of endometriosis that can be used in its early diagnosis and treatment. Materials and Methods. This is a review of publications based on search results in electronic resources in Russian and international systems, such as eLibrary, PubMed, MedLine, Crossref, etc., over the past 8 years (2015-2023). Results and Discussion. A constantly improving palette of the latest technologies that include and combine metabolomics, genomics, and proteomics, can be the key to success in finding reliable biomarkers. For such a complex and heterogeneous disease as endometriosis, a panel of biomarkers is likely to be more accurate than a single marker, both for the diagnosis and probably for helping classify subtypes of the disease. Conclusion. Current literature on potential biomarkers is quite extensive, but the desired result has not been achieved yet. Further research is needed.

Identification and validation of M2 macrophage-related genes in endometriosis

AimsM2 macrophage is believed to play an important role in the development of endometriosis. This study aimed to identify several key genes related to the M2 macrophage in endometriosis. MethodDifferential expressed genes between endometriosis and non-endometriosis were identified based on three microarray datasets from the Gene Expression Omnibus database. Gene modules significantly associated with M2 macrophage were identified from the weighted gene co-expression network analysis. Furthermore, by intersecting the differential expressed genes and M2 macrophage-associated module genes, M2 macrophage-related genes in endometriosis were identified. Functional analyses of the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes for these genes were then performed. Following, the least absolute shrinkage and selection operator, random forest, and receiver operating characteristic curves were further conducted to identify the key M2 macrophage-related genes in endometriosis. Finally, the expressions of key genes in endometriosis, as well as their correlations with M2 macrophages were verified in an independent validation cohort. ResultsTotally, 185 M2 macrophage-related genes were identified, and they were mainly enriched in functions associated with the cell cycle, oocyte maturation, and immune response. Following machine learning algorithms, eight key genes were selected in the endometriosis: PGR, OLFM4, PIP5K1B, CCNA1, BRIP1, CADM1, PRAME, and GCNT1. The eight key genes were confirmed to be negative with M2 macrophage infiltration levels. Furthermore, the expression levels of these genes were significantly lower in the middle secretory stage while relevantly higher in the proliferative stage. The validation analysis also showed similar outcomes with the above results. ConclusionEight M2 macrophage-related genes were identified as potential biomarkers of endometriosis, providing novel understanding of immune cells in the endometriosis.

MiRNA Expression Profiles in an Ectopic Endometrium of Patients at Different Stage of Endometriosis

Endometriosis is a debilitating disease that affects up to 15% of women worldwide. Delayed diagnosis, lack of noninvasive biomarker and unexplained pathogenesis are key problems for specialists and patients alike. MiRNAs are a class of noncoding RNAs that regulate myriad of cellular functions. These gene expression regulators may prove to be attractive biomarkers with diagnostic and prognostic value for endometriosis.&#x0D; Tissue samples were collected from the participants enrolled in the study during laparoscopy (patients) and hysteroscopy (control group). After RNA isolation (miRNeasy MiniKit, Qiagen) based on the disease stage, three pools – each containing 15 RNA samples, were constructed: 1) early stage endometriosis, 2) late stage endometriosis, and 3) healthy controls. Each pool sample was subjected to reverse transcription via miScript II RT Kit, Qiagen to obtain cDNA. SYBR Green based Real-time PCR assay was used to determine the expression profile of 84 miRNAs (Human miFinder miRNA PCR Array, Qiagen).&#x0D; We detected 32 differently expressed miRNAs between early stage endometriosis and control group, and 51 differently expressed miRNAs between advanced stage endometriosis and control group. Three miRNAs were differentially expressed with more than 10-fold change in the early stage group and thn miRNAs showed more than 10-fold change in the advanced stages group. The three miRNAs with the highest fold change in the expression levels in both case groups were nominated as potential biomarkers for endometriosis. The results of the analysis of their target genes supports the role of deregulation of apoptosis, angiogenesis, epithelial-mesenchymal transition, and various other cellular signalling pathways in endometriosis development.

Microvesicles released from ectopic endometrial foci as a potential biomarker of endometriosis.

Angiogenesis is engaged in endometriosis. It is regulated by regulatory factors and cytokines, transported in microvesicles. The purpose was to investigate the presence of MVs with vascular endothelial growth factor (VEGF) and metalloproteinase-9 (MMP-9) in peripheral blood and peritoneal fluid of women operated on for endometrioma or teratoma Material and methods:Microvesicles (MVs) were determined in blood samples and peritoneal fluid samples collected from women aged 20-60 years operated on for endometriosis (test group) and teratoma (control group). The final investigations were performed on 47 patients, who qualified for the study based on the meticulous inclusion criteria. MVs were analyzed by flow cytometry (FACS) using annexin V, antibodies for molecules characteristic of cells from endometriosis foci (keratin 18 (K18), CD105, CD146), and antibodies for intraepithelial vascular growth factor VEGF and metalloproteinase-9 (MMP-9). The sample was double "reading" using flow cytometry (FACSCantoII). Cytometry analysis confirmed MVs' presence in plasma and peritoneal fluid collected from patients with both endometriosis and teratomas. A statistically significant higher level of AnnexinV (+) MVs were observed in plasma samples of endometriosis patients. In the control group, there was a higher percentage of double-positive VEGF (+)/MMP-9 (+) and single MMP-9 (+) positive MVs in the serum. In the peritoneal fluid higher frequency of double-positive VEGF (+)/MMP-9 (+) MVs were found in the control group. However, the amount of VEGF (+) / MMP-9 (+) MVs object did not enable to differentiate between the test and control groups. The study was the first, in which MVs were confirmed in plasma and peritoneal fluid in benign adnexa tumors. Microvesicles are present in peripheral blood and peritoneal fluid samples collected from patients with endometriosis and teratomas. Microvesicles with proangiogenic factors (VEGF and MMP-9) are more abundant in blood and peritoneal fluid samples from patients with teratomas.

Assessment of MMP14, CAV2, CLU and SPARCL1 expression profiles in endometriosis

Endometriotic cells exhibit a notable degree of invasiveness and some characteristics of tissue remodeling underlying lesion formation. In this regard, do matrix metalloproteinases 14 (MMP14) and other related genes such as SPARC-like protein 1 (SPARCL1), caveolin 2 (CAV2), and clusterin (CLU) exert any significant influence in the processes of endometriosis development and pathophysiology is not apparent. We aim to assess whether these genes could serve as potential diagnostic biomarkers in endometriosis. Microarray-based gene expression analysis was performed on total RNA extracted from endometriotic tissue samples treated with and without gonadotropin-releasing hormone agonist (GnRHa). The GnRHa untreated patients were considered the control group. The validation of genes was performed using quantitative real-time polymerase chain reaction (qRT-PCR). qRT-PCR analysis showed significant downregulation in the expression of MMP14 (p = 0.024), CAV2 (p = 0.017), and upregulation of CLU (p = 0.005) in endometriosis patients treated with GnRHa. SPARCL1 did not show any significant (p = 0.30) change in the expression compared to the control group. These data have the potential to contribute to the comprehension of the molecular pathways implicated in the remodeling of the extracellular matrix, which is a vital step for the physiology of the endometrium. Based on the result, it is concluded that changes in the expression of MMP14, CAV2, and CLU post-treatment imply their role in the pathophysiology of endometriosis and may serve as a potential diagnostic biomarker of endometriosis in response to GnRHa treatment in patients with ovarian endometrioma.

FZD7: A potential biomarker for endometriosis.

Endometriosis is a chronic inflammatory, benign disorder that often co-occurs with adenomyosis and/or leiomyoma. The overall incidence of endometriosis in reproductive period women was nearly 10%. However, the exact mechanisms of endometriosis-associated pathogenesis are still unknown. In this study, we aimed to investigate whether Frizzled-7 (FZD7) would effectively promote the development of endometriosis. The microarray-based data analysis was performed to screen endometriosis-related differentially expressed genes. This process uncovered specific hub genes, and the nexus of vital genes and ferroptosis-related genes were pinpointed. Then, we collected human endometrial and endometriotic tissues from patients with endometriosis of the ovary (n = 39) and control patients without endometriosis (n = 10, who underwent hysterectomy for uterine fibroids) to compare the expression of FZD7. These findings indicated that the expression of FZD7 was high compared with normal endometrium, and FZD7 may promote the progression of endometriosis. FZD7 may serve as a potential therapeutic target for endometriosis treatment.