Endometriosis Is Associated with Functional Polymorphism in the Promoter of Heme Oxygenase 1 (HMOX1) Gene

Omics-based novel strategies in the diagnosis of endometriosis

Endometriosis, an enigmatic and chronic disorder, is considered a debilitating condition despite being benign. Globally, this gynecologic disorder affects up to 10% of females of reproductive age, impacting almost 190 million individuals. A variety of genetic and environmental factors are involved in endometriosis development, hence the pathophysiology and etiology of endometriosis remain unclear. The uncertainty of the etiology of the disease and its complexity along with nonspecific symptoms have led to misdiagnosis or lack of diagnosis of affected people. Biopsy and laparoscopy are referred to as the gold standard for endometriosis diagnosis. However, the invasiveness of the procedure, the unnecessary operation in disease-free women, and the dependence of the reliability of diagnosis on experience in this area are considered the most significant limitations. Therefore, continuous studies have attempted to offer a noninvasive and reliable approach. The recent advances in modern technologies have led to the generation of large-scale biological data sets, known as -omics data, resulting in the proceeding of the -omics century in biomedical sciences. Thereby, the present study critically reviews novel and noninvasive biomarkers that are based on -omics approaches from 2020 onward. The findings reveal that biomarkers identified based on genomics, epigenomics, transcriptomics, proteomics, and metabolomics are potentially able to diagnose endometriosis, predict prognosis, and stage patients, and potentially, in the near future, a multi-panel of these biomarkers will generate clinical benefits.

Homeobox regulator Wilms Tumour 1 is displaced by androgen receptor at cis-regulatory elements in the endometrium of PCOS patients

Decidualisation, the process whereby endometrial stromal cells undergo morphological and functional transformation in preparation for trophoblast invasion, is often disrupted in women with polycystic ovary syndrome (PCOS) resulting in complications with pregnancy and/or infertility. The transcription factor Wilms tumour suppressor 1 (WT1) is a key regulator of the decidualization process, which is reduced in patients with PCOS, a complex condition characterized by increased expression of androgen receptor in endometrial cells and high presence of circulating androgens. Using genome-wide chromatin immunoprecipitation approaches on primary human endometrial stromal cells, we identify key genes regulated by WT1 during decidualization, including homeobox transcription factors which are important for regulating cell differentiation. Furthermore, we found that AR in PCOS patients binds to the same DNA regions as WT1 in samples from healthy endometrium, suggesting dysregulation of genes important to decidualisation pathways in PCOS endometrium due to competitive binding between WT1 and AR. Integrating RNA-seq and H3K4me3 and H3K27ac ChIP-seq metadata with our WT1/AR data, we identified a number of key genes involved in immune response and angiogenesis pathways that are dysregulated in PCOS patients. This is likely due to epigenetic alterations at distal enhancer regions allowing AR to recruit cofactors such as MAGEA11, and demonstrates the consequences of AR disruption of WT1 in PCOS endometrium.

Identification and validation of an endoplasmic-reticulum-stress-related gene signature as an effective diagnostic marker of endometriosis

Background

Endometriosis is one of the most common benign gynecological diseases and is characterized by chronic pain and infertility. Endoplasmic reticulum (ER) stress is a cellular adaptive response that plays a pivotal role in many cellular processes, including malignant transformation. However, whether ER stress is involved in endometriosis remains largely unknown. Here, we aimed to explore the potential role of ER stress in endometriosis, as well as its diagnostic value.

Methods

We retrieved data from the Gene Expression Omnibus (GEO) database. Data from the GSE7305 and GSE23339 datasets were integrated into a merged dataset as the training cohort. Differentially expressed ER stress-related genes (DEG-ERs) were identified by integrating ER stress-related gene profiles downloaded from the GeneCards database with differentially expressed genes (DEGs) in the training cohort. Next, an ER stress-related gene signature was identified using LASSO regression analysis. The receiver operating characteristic curve was used to evaluate the discriminatory ability of the constructed model, which was further validated in the GSE51981 and GSE105764 datasets. Online databases were used to explore the possible regulatory mechanisms of the genes in the signature. Meanwhile, the CIBERSORT algorithm and Pearson correlation test were applied to analyze the association between the gene signature and immune infiltration. Finally, expression levels of the signature genes were further detected in clinical specimens using qRT-PCR and validated in the Turku endometriosis database.

Results

In total, 48 DEG-ERs were identified in the training cohort. Based on LASSO regression analysis, an eight-gene-based ER stress-related gene signature was constructed. This signature exhibited excellent diagnostic value in predicting endometriosis. Further analysis indicated that this signature was associated with a compromised ER stress state. In total, 12 miRNAs and 23 lncRNAs were identified that potentially regulate the expression of ESR1, PTGIS, HMOX1, and RSAD2. In addition, the ER stress-related gene signature indicated an immunosuppressive state in endometriosis. Finally, all eight genes showed consistent expression trends in both clinical samples and the Turku database compared with the training dataset.

Conclusions

Our work not only provides new insights into the impact of ER stress in endometriosis but also provides a novel biomarker with high clinical value.

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

BACKGROUND

Endometriosis 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.

METHODS

We 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.

RESULTS

Among 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.

CONCLUSIONS

Our proteomic analysis revealed distinct protein expression patterns induced by MQEO treatment in EESCs, highlighting the potential of MQEO for endometriosis treatment and biomarker discovery.

Screening of potential biomarkers for polycystic ovary syndrome and identification of expression and immune characteristics

BACKGROUND

Polycystic ovary syndrome (PCOS) seriously affects the fertility and health of women of childbearing age. We look forward to finding potential biomarkers for PCOS that can aid clinical diagnosis.

METHODS

We acquired PCOS and normal granulosa cell (GC) expression profiles from the Gene Expression Omnibus (GEO) database. After data preprocessing, differentially expressed genes (DEGs) were screened by limma package, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and Gene Set Enrichment Analysis (GSEA) were performed. Recursive feature elimination (RFE) algorithm and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis were used to acquire feature genes as potential biomarkers. Time-dependent receiver operator characteristic curve (ROC curve) and Confusion matrix were used to verify the classification performance of biomarkers. Then, the expression characteristics of biomarkers in PCOS and normal cells were analyzed, and the insulin resistance (IR) score of samples was computed by ssGSEA. Immune characterization of biomarkers was evaluated using MCP counter and single sample gene set enrichment analysis (ssGSEA). Finally, the correlation between biomarkers and the scores of each pathway was assessed.

RESULTS

We acquired 93 DEGs, and the enrichment results indicated that most of DEGs in PCOS group were significantly enriched in immune-related biological pathways. Further screening results indicated that JDP2 and HMOX1 were potential biomarkers. The area under ROC curve (AUC) value and Confusion matrix of the two biomarkers were ideal when separated and combined. In the combination, the training set AUC = 0.929 and the test set AUC = 0.917 indicated good diagnostic performance of the two biomarkers. Both biomarkers were highly expressed in the PCOS group, and both biomarkers, which should be suppressed in the preovulation phase, were elevated in PCOS tissues. The IR score of PCOS group was higher, and the expression of JDP2 and HMOX1 showed a significant positive correlation with IR score. Most immune cell scores and immune infiltration results were significantly higher in PCOS. Comprehensive analysis indicated that the two biomarkers had strong correlation with immune-related pathways.

CONCLUSION

We acquired two potential biomarkers, JDP2 and HMOX1. We found that they were highly expressed in the PCOS and had a strong positive correlation with immune-related pathways.

Identification of potential diagnostic biomarkers and therapeutic targets for endometriosis based on bioinformatics and machine learning analysis

PURPOSE

Endometriosis (EMs) is a major gynecological condition in women. Due to the absence of definitive symptoms, its early detection is very challenging; thus, it is crucial to find biomarkers to ease its diagnosis and therapy. Here, we aimed to identify potential diagnostic and therapeutic targets for EMs by constructing a regulatory network and using machine learning approaches.

METHODS

Three Gene Expression Omnibus (GEO) datasets were merged, and differentially expressed genes (DEGS) were identified after preprocessing steps. Using the DEGs, a transcription factor (TF)-mRNA-miRNA regulatory network was constructed, and hub genes were detected based on four different algorithms in CytoHubba. The hub genes were used to build a GaussianNB diagnostic model and also in docking analysis that were performed using Discovery Studio and AutoDock Vina software.

RESULTS

A total of 119 DEGs were identified between EMs and non-EMs samples. A regulatory network consisting of 52 mRNAs, 249 miRNAs, and 37 TFs was then constructed. The diagnostic model was introduced using the hub genes selected from the network (GATA6, HMOX1, HS3ST1, NFASC, and PTGIS) that its area under the curve (AUC) was 0.98 and 0.92 in the training and validation cohorts, respectively. Based on docking analysis, two chemical compounds, rofecoxib and retinoic acid, had potential therapeutic effects on EMs.

CONCLUSION

In conclusion, this study identified potential diagnostic and therapeutic targets for EMs which demand more experimental confirmations.

The role of iron in the pathogenesis of endometriosis: a systematic review

STUDY QUESTION

What is the role of iron in the pathophysiology of endometriosis?

SUMMARY ANSWER

Iron excess is demonstrated wherever endometriotic tissues are found and is associated with oxidative stress, an inflammatory micro-environment, and cell damage; the iron-mediated oxidative stress is independently linked to subfertility, symptom severity, and malignant transformation.

WHAT IS KNOWN ALREADY

Iron is found in excess in endometriotic tissues, and multiple mechanisms have been studied and posited to explain this. It is clear that iron excess plays a vital role in promoting oxidative stress and cell damage. The evidence base is large, but no comprehensive reviews exist to summarize our understanding and highlight the overarching themes to further our understanding and suggest future directions of study for the field.

STUDY DESIGN SIZE DURATION

This systematic review with a thematic analysis retrieved studies from the PubMed, Embase, Web of Science, and Cochrane Library databases and searches were conducted from inception through to August 2022. Human and animal studies published in the English language were included and identified using a combination of exploded MeSH terms ('Iron' and 'Endometriosis') and free-text search terms ('Iron', 'Ferric', 'Ferrous', 'Endometriosis', 'Endometrioma').

PARTICIPANTS/MATERIALS SETTING METHODS

This review was reported in accordance with the PRISMA guidelines. All studies reporting original data concerning the role of iron or iron complexes in the pathophysiology of endometriosis were included. Studies that did not report original data or provided a review of the field were excluded. Bias analysis was completed for each included study by using the Newcastle-Ottawa scoring system.

MAIN RESULTS AND THE ROLE OF CHANCE

There were 776 records identified and these were screened down to 53 studies which met the eligibility criteria, including 6 animal and 47 human studies, with 3556 individual participants. Iron excess is demonstrated in various tissues and fluids, including ovarian endometriomas, ovarian follicles, ectopic endometriotic lesions, and peritoneal fluid. Markers of oxidative stress are strongly associated with high iron levels, and aberrant expression of iron-transport proteins has been demonstrated. Abnormal resistance to ferroptosis is likely. Iron-mediated oxidative stress is responsible for a pro-inflammatory micro-environment and is linked to subfertility, symptom severity, and, possibly, malignant transformation.

LIMITATIONS REASONS FOR CAUTION

A minority of the included studies were of objectively low quality with a high risk of bias and may lead to misleading conclusions. Additionally, multiple studies failed to appropriately characterize the included patients by known confounding variables, such as menstrual cycle phase, which may introduce bias to the findings.

WIDER IMPLICATIONS OF THE FINDINGS

Current literature depicts a central role of aberrant iron mechanics and subsequent oxidative stress in endometriosis. It is likely that iron excess is at least partly responsible for the persistence and proliferation of ectopic endometriotic lesions. As such, iron mechanics represent an attractive target for novel therapeutics, including iron chelators or effectors of the iron-oxidative stress pathway. There are significant gaps in our current understanding, and this review highlights and recommends several topics for further research. These include the role of iron chelation, resistance to ferroptosis, the relationship between iron excess and localized hypoxia, systemic iron pathophysiology in endometriosis, and the role of oxidative stress in malignant transformation.

STUDY FUNDING/COMPETING INTERESTS

J.W. and S.G.P. are supported by clinical fellowships at Liverpool University Hospital NHS Foundation trust. No additional funding was requested or required for the completion of this work. C.J.H. is supported by a Wellbeing of Women project grant (RG2137). D.K.H. is supported by a Wellbeing of Women project grant (RG2137) and an MRC clinical research training fellowship (MR/V007238/1). The authors have no conflicts of interest to declare.

REGISTRATION NUMBER

A protocol was prospectively registered with the PROSPERO database in August 2021 (CRD42021272818).