miRNAs and lncRNAs: Potential Non-Invasive Biomarkers for Endometriosis

Elsayed A, López-Berestein G, Amero P, Rodríguez-Aguayo C. An Overview of the Immune Modulatory Properties of Long Non-Coding RNAs and Their Potential Use as Therapeutic Targets in Cancer

Long non-coding RNAs (lncRNAs) play pivotal roles in regulating immune responses, immune cell differentiation, activation, and inflammatory processes. In cancer, they are gaining prominence as potential therapeutic targets due to their ability to regulate immune checkpoint molecules and immune-related factors, suggesting avenues for bolstering anti-tumor immune responses. Here, we explore the mechanistic insights into lncRNA-mediated immune modulation, highlighting their impact on immunity. Additionally, we discuss their potential to enhance cancer immunotherapy, augmenting the effectiveness of immune checkpoint inhibitors and adoptive T cell therapies. LncRNAs as therapeutic targets hold the promise of revolutionizing cancer treatments, inspiring further research in this field with substantial clinical implications.

Exosomal microRNAs and long noncoding RNAs: as novel biomarkers for endometriosis

Endometriosis is a gynecological inflammatory disorder characterized by the development of endometrial-like cells outside the uterine cavity. This disease is associated with a wide range of clinical presentations, such as debilitating pelvic pain and infertility issues. Endometriosis diagnosis is not easily discovered by ultrasound or clinical examination. Indeed, difficulties in noninvasive endometriosis diagnosis delay the confirmation and management of the disorder, increase symptoms, and place a significant medical and financial burden on patients. So, identifying specific and sensitive biomarkers for this disease should therefore be a top goal. Exosomes are extracellular vesicles secreted by most cell types. They transport between cells' bioactive molecules such as noncoding RNAs and proteins. MicroRNAs and long noncoding RNAs which are key molecules transferred by exosomes have recently been identified to have a significant role in endometriosis by modulating different proteins and their related genes. As a result, the current review focuses on exosomal micro-and-long noncoding RNAs that are involved in endometriosis disease. Furthermore, major molecular mechanisms linking corresponding RNA molecules to endometriosis development will be briefly discussed to better clarify the potential functions of exosomal noncoding RNAs in the therapy and diagnosis of endometriosis.

TGFBI as a candidate biomarker for non-invasive diagnosis of early-stage endometriosis

STUDY QUESTION

Can cartilage oligomeric matrix protein (COMP) and transforming growth factor-β-induced protein ig-h3 (TGFBI) alone or in combination with cancer antigen 125 (CA-125) be considered as potential blood biomarkers of endometriosis?

SUMMARY ANSWER

The results of this study indicate that COMP has no diagnostic value. TGFBI has potential as a non-invasive biomarker of the early stages of endometriosis, while TGFBI together with CA-125 has similar diagnostic characteristics as CA-125 alone for all stages of endometriosis.

WHAT IS KNOWN ALREADY

Endometriosis is a common, chronic gynecological disease that significantly affects patient quality of life by causing pain and infertility. The gold standard for diagnosis is visual inspection of pelvic organs by laparoscopy, therefore there is an urgent need for discovery of non-invasive biomarkers for endometriosis to reduce diagnostic delays and allow earlier treatment of patients. The potential biomarkers for endometriosis evaluated in this study (COMP and TGFBI) were previously identified by our proteomic analysis of peritoneal fluid samples.

STUDY DESIGN, SIZE, DURATION

This is a case-control study divided into a discovery (n = 56 patients) and a validation phase (n = 237 patients). All patients were treated between 2008 and 2019 in a tertiary medical center.

PARTICIPANTS/MATERIALS, SETTING, METHOD

Patients were stratified based on the laparoscopic findings. The discovery phase included 32 endometriosis patients (cases) and 24 patients with confirmed absence of endometriosis (controls). The validation phase included 166 endometriosis and 71 control patients. Concentrations of COMP and TGFBI were measured by ELISA in plasma samples, whereas concentration of CA-125 was measured using a clinically validated assay for serum samples. Statistical and receiver operating characteristic (ROC) curve analyses were performed. The classification models were built using the linear support vector machine (SVM) method with the SVM built-in feature ranking method.

MAIN RESULTS AND THE ROLE OF CHANCE

The discovery phase revealed significantly increased concentration of TGFBI, but not COMP, in plasma samples of patients with endometriosis compared to controls. In this smaller cohort, univariate ROC analysis showed fair diagnostic potential of TGFBI, with an AUC value of 0.77, sensitivity of 58%, and specificity of 84%. The classification model built using linear SVM and combining TGFBI and CA-125 showed an AUC value of 0.91, sensitivity of 88% and specificity of 75% in distinguishing patients with endometriosis from controls. The validation phase results revealed similar diagnostic characteristics of the SVM model combining TGFBI and CA-125, with an AUC value of 0.83, sensitivity of 83% and specificity of 67% and CA-125 alone with AUC value of 0.83, sensitivity of 73% and specificity of 80%. TGFBI exhibited good diagnostic potential for early-stage endometriosis (revised American Society for Reproductive Medicine stage I-II), with an AUC value of 0.74, sensitivity of 61% and specificity of 83% compared to CA-125, which had an AUC value of 0.63, sensitivity of 60% and specificity of 67%. An SVM model combining TGFBI and CA-125 showed a high AUC value of 0.94 and sensitivity of 95% for diagnosing moderate-to-severe endometriosis.

LIMITATIONS, REASONS FOR CAUTION

The diagnostic models were built and validated from a single endometriosis center, and thus further validation and technical verification in a multicenter study with a larger cohort is needed. Additional limitation was lack of histological confirmation of disease for some patients in the validation phase.

WIDER IMPLICATIONS OF THE FINDINGS

This study revealed for the first time increased concentration of TGFBI in plasma samples of patients with endometriosis, particularly those with minimal-to-mild endometriosis, compared to controls. This is the first step in considering TGFBI as a potential non-invasive biomarker for the early stages of endometriosis. It also opens a path for new basic research to investigate the importance of TGFBI in the pathophysiology of endometriosis. Further studies are needed to confirm the diagnostic potential of a model based on TGFBI and CA-125 for the non-invasive diagnosis of endometriosis.

STUDY FUNDING/COMPETING INTEREST(S)

The preparation of this manuscript was supported by grant J3-1755 from the Slovenian Research Agency to T.L.R and EU H2020-MSCA-RISE project TRENDO (grant 101008193). All authors declare that they have no conflicts of interest.

TRIAL REGISTRATION NUMBER

NCT0459154.

How to Improve Non-Invasive Diagnosis of Endometriosis with Advanced Statistical Methods

Background and Objectives: Endometriosis is one of the most common gynecological disorders in women of reproductive age. Causing pelvic pain and infertility, it is considered one of the most serious health problems, being responsible for work absences or productivity loss. Its diagnosis is often delayed because of the need for an invasive laparoscopic approach. Despite years of studies, no single marker for endometriosis has been discovered. The aim of this research was to find an algorithm based on symptoms and laboratory tests that could diagnose endometriosis in a non-invasive way. Materials and Methods: The research group consisted of 101 women hospitalized for diagnostic laparoscopy, among which 71 had confirmed endometriosis. Data on reproductive history were collected in detail. CA125 (cancer antigen-125) level and VEGF1(vascular endothelial growth factor 1) were tested in blood samples. Among the used statistical methods, the LASSO regression—a new important statistical tool eliminating the least useful features—was the only method to have significant results. Results: Out of 19 features based on results of LASSO, 7 variables were chosen: body mass index, age of menarche, cycle length, painful periods, information about using contraception, CA125, and VEGF1. After multivariate logistic regression with a backward strategy, the three most significant features were evaluated. The strongest impact on endometriosis prediction had information about painful periods, CA125 over 15 u/mL, and the lowest BMI, with a sensitivity of 0.8800 and a specificity of 0.8000, respectively. Conclusions: Advanced statistical methods are crucial when creating non-invasive tests for endometriosis. An algorithm based on three easy features, including painful menses, BMI level, and CA125 concentration could have an important place in the non-invasive diagnosis of endometriosis. If confirmed in a prospective study, implementing such an algorithm in populations with a high risk of endometriosis will allow us to cover patients suspected of endometriosis with proper treatment.

Long Non-Coding RNA SNHG4 Expression in Women with Endometriosis: A Pilot Study

BACKGROUND

Endometriosis is a chronic disease of the genital organs that mainly affects women of reproductive age. The analysis of long non-coding RNA (lncRNA) in endometriosis is a novel field of science. Recently, attention has been drawn to SNHG4, which is incorrectly expressed in various human diseases, including endometriosis.

AIM

The aim of this pilot study was to analyze the expression of lncRNA small nucleolar RNA host gene 4 (SNHG4) and to investigate its significance in endometriosis.

MATERIAL AND METHODS

LncRNA SNHG4 expression was investigated in paraffin blocks in endometriosis patients (n = 100) and in endometriosis-free controls (n = 100) using a real-time PCR assay.

RESULTS

This study revealed a higher expression of SNHG4 in endometriosis patients than in controls. A statistically significant relationship between expression level and SNHG4 was found in relation to The Revised American Society for Reproductive Medicine classification of endometriosis, 1996, in the group of patients with endometriosis.

CONCLUSION

This pilot study has revealed that gene expression in SNHG4 plays an important role in the pathogenesis of endometriosis.

Non-Coding RNAs in Health and Disease: Editorial

Non-coding RNAs (ncRNAs) represent the largest part of the transcriptional production of the human genome and play key roles in health and disease processes [...].

Analysis of Long Non-Coding RNA (lncRNA) UCA1, MALAT1, TC0101441, and H19 Expression in Endometriosis

Endometriosis is a disease of complex etiology. Hormonal, immunological, and environmental factors are involved in its formation. In recent years, special attention has been paid to genetic mechanisms that can have a significant impact on the increased incidence of endometriosis. The study aimed to analyze the expression of four long non-coding RNA (lncRNA) genes, UCA1, MALAT1, TC0101441, and H19, in the context of the risk of developing endometriosis. The material for genetic testing for the expression of lncRNA genes were tissue slices embedded in paraffin blocks from patients with endometriosis (n = 100) and the control group (n = 100). Gene expression was determined by the RT-PCR technique. The expression of the H19 gene in endometriosis patients was statistically significantly lower than in the control group. A statistically significant association was found between H19 gene expression in relation to The Revised American Society for Reproductive Medicine classification of endometriosis (rASRM) in the group of patients with endometriosis. Research suggests that H19 expression plays an important role in the pathogenesis of endometriosis.

Identification of functional TF-miRNA-hub gene regulatory network associated with ovarian endometriosis

Endometriosis (EMs), one of the most common gynecological diseases, seriously affects the health and wellness of women; however, the underlying pathogenesis remains unclear. This study focused on dysregulated genes and their predicted transcription factors (TFs) and miRNAs, which may provide ideas for further mechanistic research. The microarray expression dataset GSE58178, which included six ovarian endometriosis (OE) samples and six control samples, was downloaded from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to study the cellular and organism-level functions of DEGs. The protein-protein interaction (PPI) network was built and visualized using Cytoscape, and modules and hub genes were explored using various algorithms. Furthermore, we predicted miRNAs and TFs of hub genes using online databases, and constructed the TF-miRNA-hub gene network. There were 124 upregulated genes and 66 downregulated genes in EMs tissues. GO enrichment analysis showed that DEGs were concentrated in reproductive structure development and collagen-containing extracellular matrix, while KEGG pathway analysis showed that glycolysis/gluconeogenesis and central carbon metabolism in cancer require further exploration. Subsequently, HIF1A, LDHA, PGK1, TFRC, and CD9 were identified as hub genes, 22 miRNAs and 34 TFs were predicted to be upstream regulators of hub genes, and these molecules were pooled together. In addition, we found three key feedback loops in the network, MYC-miR-34a-5p-LDHA, YY1-miR-155-5p-HIF1A, and RELA-miR-93-5p-HIF1A, which may be closely related to OE development. Taken together, our study structured a TF-miRNA-hub gene network to decipher the molecular mechanism of OE, which may provide novel insights for clinical diagnosis and treatment.

Function of the Long Noncoding RNAs in Hepatocellular Carcinoma: Classification, Molecular Mechanisms, and Significant Therapeutic Potentials

Hepatocellular carcinoma (HCC) is the most common and serious type of primary liver cancer. HCC patients have a high death rate and poor prognosis due to the lack of clear signs and inadequate treatment interventions. However, the molecular pathways that underpin HCC pathogenesis remain unclear. Long non-coding RNAs (lncRNAs), a new type of RNAs, have been found to play important roles in HCC. LncRNAs have the ability to influence gene expression and protein activity. Dysregulation of lncRNAs has been linked to a growing number of liver disorders, including HCC. As a result, improved understanding of lncRNAs could lead to new insights into HCC etiology, as well as new approaches for the early detection and treatment of HCC. The latest results with respect to the role of lncRNAs in controlling multiple pathways of HCC were summarized in this study. The processes by which lncRNAs influence HCC advancement by interacting with chromatin, RNAs, and proteins at the epigenetic, transcriptional, and post-transcriptional levels were examined. This critical review also highlights recent breakthroughs in lncRNA signaling pathways in HCC progression, shedding light on the potential applications of lncRNAs for HCC diagnosis and therapy.

Identification of potential repurposed drugs for treating endometriosis-associated infertility among women

Endometriosis is the most common gynecological abnormality seen in 10-15% of women of reproductive age, causing infertility in ∼25% of cases, which calls for treatment. Thus, in this study, we have identified miRNAs and genes involved in endometriosis progression, leading to infertility, by performing gene expression analysis followed by pathway analysis and protein-protein networks study. Further, we have predicted repurposed small molecule drugs that will neutralize the regulatory effect of targeting miRNAs that induce sterility in endometriosis. This study predicted two transcription factors, FOXO1, and CREB1, targeted by miRNAs that can be modulated by the repurposed drugs, BRD-K55473186, and methylstat, respectively, for the treatment of infertility due to endometriosis. The former drug seems better and more effective than the other as it showed stronger binding at the active site of FOXO1. These findings provide the rationale for targeting miRNA-regulated transcriptional regulators controlling several biological processes to treat endometriosis and prevent the recurrence of implantation failure or infertility.

Molecular Mechanisms Underlying the Association between Endometriosis and Ectopic Pregnancy

Endometriosis is a common inflammatory disease characterized by the presence of endometrial cells outside the uterine cavity. It is estimated that it affects 10% of women of reproductive age. Its pathogenesis covers a wide range of abnormalities, including adhesion, proliferation, and cell signaling disturbances. It is associated with a significant deterioration in quality of life as a result of chronic pelvic pain and may also lead to infertility. One of the most serious complications of endometriosis is an ectopic pregnancy (EP). Currently, the exact mechanism explaining this phenomenon is unknown; therefore, there are no effective methods of prevention. It is assumed that the pathogenesis of EP is influenced by abnormalities in the contraction of the fallopian tube muscles, the mobility of the cilia, and in the fallopian microenvironment. Endometriosis can disrupt function on all three levels and thus contribute to the implantation of the embryo beyond the physiological site. This review takes into account aspects of the molecular mechanisms involved in the pathophysiology of endometriosis and EP, with particular emphasis on the similarities between them.