A Bioinformatics Approach to MicroRNA-Sequencing Analysis Based on Human Saliva Samples of Patients with Endometriosis

Endometriosis: recent advances that could accelerate diagnosis and improve care

Endometriosis is a common disorder associated with pain, gastrointestinal and urinary symptoms, infertility, and fatigue. It is defined by the presence of endometrial-like lesions found predominantly in the pelvis. Mechanisms that contribute to disease aetiology include changes in hormonal, inflammatory, and pain pathways. In this article, we focus on recent developments in imaging technologies, on our improved understanding of mechanisms contributing to infertility, on drug therapies that are in clinical trials, and on insights from studies on the gut that offer potential to support self-management strategies. We postulate that improvements in the quality of life of patients will be accelerated by reframing endometriosis as a multi-system disorder and learning from treatments targeting symptoms shared between endometriosis, neuroinflammatory, and gastrointestinal disorders.

Saliva, a molecular reflection of the human body? Implications for diagnosis and treatment

For many diseases, and cancer in particular, early diagnosis allows a wider range of therapies and a better disease management. This has led to improvements in diagnostic procedures, most often based on tissue biopsies or blood samples. Other biological fluids have been used to diagnose disease, and among them saliva offers a number of advantages because it can be collected non-invasively from large populations at relatively low cost. To what extent might saliva content reveal the presence of a tumour located at a distance from the oral cavity and the molecular information obtained from saliva be used to establish a diagnosis are current questions. This review focuses primarily on the content of saliva and shows how it potentially offers a source of diagnosis, possibly at an early stage, for pathologies such as cancers or endometriosis.

Gastrointestinal Myoelectrical Activity (GIMA) Biomarker for Noninvasive Diagnosis of Endometriosis

Background/Objectives: Endometriosis represents substantial direct and indirect healthcare costs impacted by an absence of uniformly accurate, non-invasive diagnostic tools. We endeavored to demonstrate gastrointestinal myoelectrical activity (GIMA) biomarkers, unique to endometriosis, will allow non-invasive, uniformly accurate diagnosis or exclusion of endometriosis. Methods: Prospective open-label comparative study of 154 patients, age ≥ 18, with or without diagnosed endometriosis. Population included 62 non-endometriosis controls (Cohort 1), 43 subjects with surgically/histologically confirmed endometriosis (Cohort 2), and 49 subjects with abdominal pain and negative imaging (Cohort 3). Non-invasive electroviscerography (EVG) recorded GIMA biomarkers from three abdominal electrodes before and 30 min post water load protocol. Cohort 2 had postoperative EVG and Cohort 3 had preoperative EVG. Calculated specificity, sensitivity, negative predictive value (NPV), positive predictive value (PPV), and predictive probability or C-statistic used univariate, multivariate, linear, and logistical regression analyses of the area under the curve (AUC) at all frequency and time points, including age and pain covariants. Results: The non-endometriosis cohort differed significantly from the endometriosis cohorts (p < 0.001) for median (IQR) and AUC percent frequency distribution of power at baseline, 10 min, 20 min, and 30 min post water load at all frequency ranges: 15-20 cpm, 30-40 cpm, and 40-50 cpm. The endometriosis cohorts were statistically similar (p > 0.05). GIMA biomarker threshold scoring demonstrated 95%/91% sensitivity and PPV, 96%/95% specificity and NPV, and a C-statistic of >99%/98%, respectively, for age subsets. GIMA biomarkers in Cohort 3 predicted 47/49 subjects positive and 2/49 negative for endometriosis, confirmed surgically. Hormonal therapy, surgical stage, nor pain score affected diagnostic accuracy. Conclusions: EVG with GIMA biomarker detection distinguished participants with and without endometriosis based upon endometriosis-specific GIMA biomarkers threshold scoring.

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.

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.

Crimson clues: advancing endometriosis detection and management with novel blood biomarkers

Endometriosis is an inflammatory condition affecting approximately 10% of the female-born population. Despite its prevalence, the lack of noninvasive biomarkers has contributed to an established global diagnostic delay. The intricate pathophysiology of this enigmatic disease may leave signatures in the blood, which, when detected, can be used as noninvasive biomarkers. This review provides an update on how investigators are utilizing the established disease pathways and innovative methodologies, including genome-wide association studies, next-generation sequencing, and machine learning, to unravel the clues left in the blood to develop blood biomarkers. Many blood biomarkers show promise in the discovery phase, but because of a lack of standardized and robust methodologies, they rarely progress to the development stages. However, we are now seeing biomarkers being validated with high diagnostic accuracy and improvements in standardization protocols, providing promise for the future of endometriosis blood biomarkers.

Prototype Salivary Assay for Quantification of Two Biomarkers for In Vitro Diagnosis of Endometriosis

Endometriosis, a very common disease in women, is characterized by endometrial structures outside the uterine cavity. The lack of a reliable noninvasive diagnostic test and the often nonspecific symptoms of this pathology are responsible for the delay in definitive diagnosis of this disease. Recently, through a proteomics approach, our research group has identified two potential diagnostic markers for endometriosis in serum (Zn-alpha2-glycoprotein and complement C3 precursor). In this article, we describe the experimental conditions of a simple ELISA for rapid quantification of these two biomarkers in the saliva of patients with endometriosis. Finally, preliminary experiments on a small cohort of patients and controls have confirmed the potential diagnostic value of this assay.

New class of RNA biomarker for endometriosis diagnosis: The potential of salivary piRNA expression

OBJECTIVES

In contrast to miRNA expression, little attention has been given to piwiRNA (piRNA) expression among endometriosis patients. The aim of the present study was to explore the human piRNAome and to investigate a potential piRNA saliva-based diagnostic signature for endometriosis.

METHODS

Data from the prospective "ENDOmiRNA" study (ClinicalTrials.gov Identifier: NCT04728152) were used. Saliva samples from 200 patients were analyzed in order to evaluate human piRNA expression using the piRNA bank. Next Generation Sequencing (NGS), barcoding of unique molecular identifiers and both Artificial Intelligence (AI) and machine learning (ML) were used. For each piRNA, sensitivity, specificity, and ROC AUC values were calculated for the diagnosis of endometriosis.

RESULTS

201 piRNAs were identified, none had an AUC ≥ 0.70, and only three piRNAs (piR-004153, piR001918, piR-020401) had an AUC between ≥ 0.6 and < 0.70. Seven were differentially expressed: piR-004153, piR-001918, piR-020401, piR-012864, piR-017716, piR-020326 and piR-016904. The respective correlation and accuracy to diagnose endometriosis according to the F1-score, sensitivity, specificity, and AUC ranged from 0 to 0.862 %, 0-0.961 %, 0.085-1, and 0.425-0.618. A correlation was observed between the patients' age (≥35 years) and piR-004153 (p = 0.002) and piR-017716 (p = 0.030). Among the 201 piRNAs, four were differentially expressed in patients with and without hormonal treatment: piR-004153 (p = 0.015), piR-020401 (p = 0.001), piR-012864 (p = 0.036) and piR-017716 (p = 0.009).

CONCLUSION

Our results support the link between piRNAs and endometriosis physiopathology and establish its utility as a potential diagnostic biomarker using saliva samples. Per se, piRNA expression should be analyzed along with the clinical status of a patient.

miRNA Studies in Glaucoma: A Comprehensive Review of Current Knowledge and Future Perspectives

Glaucoma, a neurodegenerative disorder that leads to irreversible blindness, remains a challenge because of its complex nature. MicroRNAs (miRNAs) are crucial regulators of gene expression and are associated with glaucoma and other diseases. We aimed to review and discuss the advantages and disadvantages of miRNA-focused molecular studies in glaucoma through discussing their potential as biomarkers for early detection and diagnosis; offering insights into molecular pathways and mechanisms; and discussing their potential utility with respect to personalized medicine, their therapeutic potential, and non-invasive monitoring. Limitations, such as variability, small sample sizes, sample specificity, and limited accessibility to ocular tissues, are also addressed, underscoring the need for robust protocols and collaboration. Reproducibility and validation are crucial to establish the credibility of miRNA research findings, and the integration of bioinformatics tools for miRNA database creation is a valuable component of a comprehensive approach to investigate miRNA aberrations in patients with glaucoma. Overall, miRNA research in glaucoma has provided significant insights into the molecular mechanisms of the disease, offering potential biomarkers, diagnostic tools, and therapeutic targets. However, addressing challenges such as variability and limited tissue accessibility is essential, and further investigations and validation will contribute to a deeper understanding of the functional significance of miRNAs in glaucoma.

Pathogenesis of Endometriosis: Focus on Adenogenesis-related Factors

Endometriosis can be defined as the presence of the endometrium outside the uterine cavity. It affects approximately 10% of women of reproductive age and causes infertility, chronic pain, and deterioration of the quality of life. Since the identification of the disease, various pathogenetic mechanisms have been proposed, such as retrograde menstruation, coelomic metaplasia, hormonal imbalance, stem cell involvement, and alterations in epigenetic regulation. However, the underlying pathogenesis of endometriosis remains inadequately understood. Elucidation of the precise mechanism of the development and progression of endometriosis is crucial for effective treatment. This review presents the major pathogenetic theories of endometriosis based on current research studies with a major focus on the potential role of uterine factors.

Value of non-coding RNAs to assess lymph node status in cervical cancer

Cervical cancer (CC) is the fourth cancer in women and is the leading cause of cancer death in 42 countries. Lymph node metastasis is a determinant prognostic factor, as underlined in the latest FIGO classification. However, assessment of lymph node status remains difficult, despite the progress of imaging such as PET-CT and MRI. In the specific setting of CC, all data underlined the need for new biomarkers easily available to assess lymph node status. Previous studies have underlined the potential value of ncRNA expression in gynecological cancers. In this review, we aimed to evaluate the contribution of ncRNAs in tissue and biofluid samples to determine lymph node status in CC with potential impact on both surgical and adjuvant therapies. In tissue samples, our analysis found that there are arguments to support the role of ncRNAs in physiopathology, differential diagnosis from normal tissue, preinvasive and invasive tumors. In biofluids, despite small studies especially concerning miRNAs expression, promising data opens up new avenue to establish a non-invasive signature for lymph node status as well as a tool to predict response to neo- and adjuvant therapies, thus improving management algorithm of patients with CC.

Insight on Non-Coding RNAs from Biofluids in Ovarian Tumors

Ovarian tumors are the most frequent adnexal mass, raising diagnostic and therapeutic issues linked to a large spectrum of tumors, with a continuum from benign to malignant. Thus far, none of the available diagnostic tools have proven efficient in deciding strategy, and no consensus exists on the best strategy between "single test", "dual testing", "sequential testing", "multiple testing options" and "no testing". In addition, there is a need for prognostic tools such as biological markers of recurrence and theragnostic tools to detect women not responding to chemotherapy in order to adapt therapies. Non-coding RNAs are classified as small or long based on their nucleotide count. Non-coding RNAs have multiple biological functions such as a role in tumorigenesis, gene regulation and genome protection. These ncRNAs emerge as new potential tools to differentiate benign from malignant tumors and to evaluate prognostic and theragnostic factors. In the specific setting of ovarian tumors, the goal of the present work is to offer an insight into the contribution of biofluid non-coding RNAs (ncRNA) expression.

Endometriosis-associated infertility diagnosis based on saliva microRNA signatures

RESEARCH QUESTION

Can a saliva-based miRNA signature for endometriosis-associated infertility be designed and validated by analysing the human miRNome?

DESIGN

The prospective ENDOmiARN study (NCT04728152) included 200 saliva samples obtained between January 2021 and June 2021 from women with pelvic pain suggestive of endometriosis. All patients underwent either laparoscopy, magnetic resonance imaging, or both. Patients diagnosed with endometriosis were allocated to one of two groups according to their fertility status. Data analysis consisted of identifying a set of miRNA biomarkers using next-generation sequencing, and development of a saliva-based miRNA signature of infertility among patients with endometriosis based on a random forest model.

RESULTS

Among the 153 patients diagnosed with endometriosis, 24% (n = 36) were infertile and 76% (n = 117) were fertile. Small RNA-sequencing of the 153 saliva samples yielded approximately 3712 M raw sequencing reads (from ∼13.7 M to ∼39.3 M reads/sample). Of the 2561 known miRNAs, the feature selection method generated a signature of 34 miRNAs linked to endometriosis-associated infertility. After validation, the most accurate signature model had a sensitivity, specificity and area under the curve of 100%.

CONCLUSION

A saliva-based miRNA signature for endometriosis-associated infertility is reported. Although the results still require external validation before using the signature in routine practice, this non-invasive tool is likely to have a major effect on care provided to women with endometriosis.