Direct Mass Spectrometry Differentiation of Ectopic and Eutopic Endometrium in Patients with Endometriosis

Follicular Fluid and Blood Monitorization of Infertility Biomarkers in Women with Endometriosis

Infertility is recognized globally as a social disease and a growing medical condition, posing a significant challenge to modern reproductive health. Endometriosis, the third-most frequent gynecologic disorder, is one of the most common and intricate conditions that can lead to female infertility. Despite extensive research, the etiology, malignant transformation, and biological therapy of endometriosis remain unknown. Blood and follicular fluid are two matrices that have been carefully studied and can provide insights into women's health. These matrices are clinically significant because they contain metabolites closely associated with women's illness stage and reproductive outcomes. Nowadays, the application of metabolomic analysis in biological matrices may be able to predict the outcome of assisted reproductive technologies with greater precision. From a molecular viewpoint on reproductive health, we evaluate and compare the utilization of human follicular fluid and blood as matrices in analysis for diagnostic and assisted reproductive technology (ART) predictors of success for endometriosis patients. In the follicular fluid (FF), plasma, and serum of endometriosis-affected women, researchers identified dysregulations of oxidative stress, upregulation of several immune factors, and aberrations in energy metabolic pathways. The altered signatures negatively correlate with the overall oocyte and embryo quality and fertilization rate.

Polygenic risk score phenome-wide association study reveals an association between endometriosis and testosterone

BACKGROUND

Endometriosis affects 1 in 9 women, yet it is poorly understood with long diagnostic delays, invasive diagnoses, and poor treatment outcomes. Characterised by the presence of endometrial-like tissue outside of the uterus, its main symptoms are pain and infertility. Endometriosis often co-occurs with other conditions, which may provide insights into the origins of endometriosis.

METHODS

Here a polygenic risk score phenome-wide association study of endometriosis was conducted in the UK Biobank to investigate the pleiotropic effects of a genetic liability to endometriosis. The relationship between the polygenic risk score for endometriosis and health conditions, blood and urine biomarkers and reproductive factors were investigated separately in females, males and females without an endometriosis diagnosis. The relationship between endometriosis and the blood and urine biomarkers was further investigated using genetic correlation and Mendelian randomisation approaches to identify causal relationships.

RESULTS

Multiple health conditions, blood and urine biomarkers and reproductive factors were associated with genetic liability to endometriosis in each group, indicating many endometriosis comorbidities are not dependent on the physical manifestation of endometriosis. Differences in the associated traits between males and females highlighted the importance of sex-specific pathways in the overlap of endometriosis with many other traits. Notably, an association of genetic liability to endometriosis with lower testosterone levels was identified. Follow-up analysis utilising Mendelian randomisation approaches suggested lower testosterone may be causal for both endometriosis and clear cell ovarian cancer.

CONCLUSIONS

This study highlights the diversity of the pleiotropic effects of genetic risk to endometriosis irrespective of a diagnosis of endometriosis. A key finding was the identification of a causal effect of the genetic liability to lower testosterone on endometriosis using Mendelian randomisation.

The 10 "Cardinal Sins" in the Clinical Diagnosis and Treatment of Endometriosis: A Bayesian Approach

Evidence-based data for endometriosis management are limited. Experiments are excluded without adequate animal models. Data are limited to symptomatic women and occasional observations. Hormonal medical therapy cannot be blinded if recognised by the patient. Randomised controlled trials are not realistic for surgery, since endometriosis is a variable disease with low numbers. Each diagnosis and treatment is an experiment with an outcome, and experience is the means by which Bayesian updating, according to the past, takes place. If the experiences of many are similar, this holds more value than an opinion. The combined experience of a group of endometriosis surgeons was used to discuss problems in managing endometriosis. Considering endometriosis as several genetically/epigenetically different diseases is important for medical therapy. Imaging cannot exclude endometriosis, and diagnostic accuracy is limited for superficial lesions, deep lesions, and cystic corpora lutea. Surgery should not be avoided for emotional reasons. Shifting infertility treatment to IVF without considering fertility surgery is questionable. The concept of complete excision should be reconsidered. Surgeons should introduce quality control, and teaching should move to explain why this occurs. The perception of information has a personal bias. These are the major problems involved in managing endometriosis, as identified by the combined experience of the authors, who are endometriosis surgeons.

Cell cycle, apoptosis, cell differentiation, and lipid metabolism gene expression in endometriotic tissue and exposure to parabens and benzophenones

AIM

To describe the expression profile in endometriotic tissue of genes involved in four signaling pathways related to the development and progression of endometriosis (cell cycle, apoptosis, cell differentiation and lipid metabolism) and to explore its relationship with the women exposure to chemicals with hormonal activity released from cosmetics and personal care products (PCPs).

METHODS

This cross-sectional study, encompassed within the EndEA study, comprised a subsample of 33 women with endometriosis. Expression levels of 13 genes (BMI1, CCNB1, CDK1, BAX, BCL2L1, FOXO3, SPP1, HOXA10, PDGFRA, SOX2, APOE, PLCG1 and PLCG2) in endometriotic tissue and urinary concentrations of 4 paraben (PB) and 3 benzophenone (BP) congeners were quantified. Bivariate linear and logistic regression analyses were performed to explore the associations between exposure and gene expression levels.

RESULTS

A total of 8 out 13 genes (61.5 %) were expressed in >75 % of the samples. Exposure to congeners of PBs and/or BPs was associated with the overexpression of CDK1 gene (whose protein drives cells through G2 phase and mitosis), HOXA10 and PDGFRA genes (whose proteins favor pluripotent cell differentiation to endometrial cells), and APOE (whose protein regulates the transport and metabolism of cholesterol, triglycerides and phospholipids in multiple tissues) and PLCG2 genes (whose protein creates 1D-myo-inositol 1,4,5-trisphosphate and diacylglycerol, two important second messengers).

CONCLUSIONS

Our findings suggest that women exposure to cosmetic and PCP-released chemicals might be associated with the promotion of cell cycle and cell differentiation as well as with lipid metabolism disruption in endometriotic tissue, three crucial signaling pathways in the development and progression of endometriosis. However, further studies should be accomplished to confirm these preliminary data.

Towards a Better Understanding of Endometriosis-Related Infertility: A Review on How Endometriosis Affects Endometrial Receptivity

Endometriosis is the most common cause of infertility. Endometrial receptivity has been suggested to contribute to infertility and poor reproductive outcomes in affected women. Even though experimental and clinical data suggest that the endometrium differs in women with endometriosis, the pathogenesis of impaired endometrial receptivity remains incomplete. Therefore, this review summarizes the potential mechanisms that affect endometrial function and contribute to implantation failure. Contemporary data regarding hormone imbalance, inflammation, and immunoregulatory dysfunction will be reviewed here. In addition, genetic, epigenetic, glycosylation, metabolism and microRNA in endometriosis-related infertility/subfertility will be summarized. We provide a brief discussion and perspectives on their future clinical implications in the diagnosis and therapy to improve endometrial function in affected women.

Current Role of Modern Chromatography with Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy in the Investigation of Biomarkers of Endometriosis

Endometriosis has a wide range of clinical manifestations, and the disease course is unpredictable, making the diagnosis a challenging task. Despite significant advances in the pathophysiology of endometriosis and various proposed theories, the exact etiology is not fully understood and is still unknown. The most commonly used biomarker of endometriosis is CA-125, however, it is nonspecific and is applied for cancers diagnosis. Therefore, the development of reliable noninvasive diagnostic tests for the early diagnosis of endometriosis remains one of the top priorities. Omics technologies are very promising approaches for constructing diagnostic models and biomarker discovery. Their use can greatly facilitate the study of such a complex disease as endometriosis. Nowadays, powerful analytical platforms commonly used in omics, such as gas and liquid chromatography with mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy, have proven to be a promising tools for biomarker discovery. The aim of this review is to summarize the various features of the analytical approaches, practical challenges and features of gas and liquid chromatography with MS and NMR spectroscopy (including sample processing protocols, technological advancements, and methodology) used for profiling of metabolites, lipids, peptides and proteins in physiological fluids and tissues from patients with endometriosis. In addition, this report devotes special attention to the issue of how comprehensive analyses of these profiles can effectively contribute to the study of endometriosis. The search query included reports published between 2012 and 2022 years in PubMed, Web-of-Science, SCOPUS, Science Direct.

Shotgun Lipidomics for Differential Diagnosis of HPV-Associated Cervix Transformation

A dramatic increase in cervical diseases associated with human papillomaviruses (HPV) in women of reproductive age has been observed over the past decades. An accurate differential diagnosis of the severity of cervical intraepithelial neoplasia and the choice of the optimal treatment requires the search for effective biomarkers with high diagnostic and prognostic value. The objective of this study was to introduce a method for rapid shotgun lipidomics to differentiate stages of HPV-associated cervix epithelium transformation. Tissue samples from 110 HPV-positive women with cervicitis (n = 30), low-grade squamous intraepithelial lesions (LSIL) (n = 30), high-grade squamous intraepithelial lesions (HSIL) (n = 30), and cervical cancers (n = 20) were obtained. The cervical epithelial tissue lipidome at different stages of cervix neoplastic transformation was studied by a shotgun label-free approach. It is based on electrospray ionization mass spectrometry (ESI-MS) data of a tissue extract. Lipidomic data were processed by the orthogonal projections to latent structures discriminant analysis (OPLS-DA) to build statistical models, differentiating stages of cervix transformation. Significant differences in the lipid profile between the lesion and surrounding tissues were revealed in chronic cervicitis, LSIL, HSIL, and cervical cancer. The lipids specific for HPV-induced cervical transformation mainly belong to glycerophospholipids: phosphatidylcholines, and phosphatidylethanolamines. The developed diagnostic OPLS-DA models were based on 23 marker lipids. More than 90% of these marker lipids positively correlated with the degree of cervix transformation. The algorithm was developed for the management of patients with HPV-associated diseases of the cervix, based on the panel of 23 lipids as a result. ESI-MS analysis of a lipid extract by direct injection through a loop, takes about 25 min (including preparation of the lipid extract), which is significantly less than the time required for the HPV test (several hours for hybrid capture and about an hour for PCR). This makes lipid mass spectrometric analysis a promising method for express diagnostics of HPV-associated neoplastic diseases of the cervix.

Is there a role for small molecule metabolite biomarkers in the development of a diagnostic test for endometriosis?

Endometriosis is a disease defined by the presence of benign lesions of endometrial-like glands and stroma outside the endometrial cavity. Affecting an estimated 11.4% of Australian women, symptoms include chronic pelvic pain, dysmenorrhea and infertility. The current gold standard of diagnosis requires an expensive and invasive laparoscopic surgery, resulting in delayed time to treatment. The identification of a non-invasive endometriosis biomarker - a measurable factor correlating with disease presence or activity - has therefore become a priority in endometriosis research, although no biomarker has yet been validated. As small molecule metabolites and lipids have emerged as a potential focus, this review with systematic approach, aims to summarize studies examining metabolomic biomarkers of endometriosis in order to guide future research. EMBASE, PubMed and Web of Science were searched using keywords: lipidomics OR metabolomics OR metabolome AND diagnostic tests OR biomarkers AND endometriosis, and only studies written in English from August 2000 to August 2020 were included. Twenty-nine studies met inclusion and exclusion criteria and were included. These studies identified potential biomarkers in serum, ectopic tissue, eutopic endometrium, peritoneal fluid, follicular fluid, urine, cervical swabs and endometrial fluid. Glycerophospholipids were identified as potential biomarkers in all specimens, except urine and cervical swab specimens. However, no individual molecule or metabolite combination has reached clinical diagnostic utility. Further research using large study populations with robust patient phenotype and specimen characterisation is required if we are to make progress in identifying and validating a non-invasive diagnostic test for endometriosis.

Lipidomic Alterations and PPARα Activation Induced by Resveratrol Lead to Reduction in Lesion Size in Endometriosis Models

Endometriosis is an estrogen-dependent chronic inflammatory disease that affects approximately 10% of women of reproductive age and up to 50% of women with infertility. The heterogeneity of the disease makes accurate diagnosis and treatment a clinical challenge. In this study, we generated two models of endometriosis: the first in rats and the second using human ectopic endometrial stromal cells (HEcESCs) derived from the lesion tissues of endometriosis patients. We then applied resveratrol to assess its therapeutic potential. Resveratrol intervention had significant efficacy to attenuate lesion size and to rectify aberrant lipid profiles of model rats. Lipidomic analysis revealed significant lipidomic alterations, including notable increases of sphingolipids and decreases of both glycerolipids and most phospholipids. Upon resveratrol application, both proliferation capacity and invasiveness parameters decreased, and the early apoptosis proportion increased for HEcESCs. The activation of PPARα was also noted as a factor potentially contributing to recovery from endometriosis in both models. Our study provides valuable insight into the mechanisms of resveratrol in endometriosis and therefore strengthens the potential for optimizing resveratrol treatment for this disease.

Alterations in lipid profile upon uterine fibroids and its recurrence

Uterine fibroids (UF) is the most common (about 70% cases) type of gynecological disease, with the recurrence rate varying from 11 to 40%. Because UF has no distinct symptomatology and is often asymptomatic, the specific and sensitive diagnosis of UF as well as the assessment for the probability of UF recurrence pose considerable challenge. The aim of this study was to characterize alterations in the lipid profile of tissues associated with the first-time diagnosed UF and recurrent uterine fibroids (RUF) and to explore the potential of mass spectrometry (MS) lipidomics analysis of blood plasma samples for the sensitive and specific determination of UF and RUF with low invasiveness of analysis. MS analysis of lipid levels in the myometrium tissues, fibroids tissues and blood plasma samples was carried out on 66 patients, including 35 patients with first-time diagnosed UF and 31 patients with RUF. The control group consisted of 15 patients who underwent surgical treatment for the intrauterine septum. Fibroids and myometrium tissue samples were analyzed using direct MS approach. Blood plasma samples were analyzed using high performance liquid chromatography hyphened with mass spectrometry (HPLC/MS). MS data were processed by discriminant analysis with projection into latent structures (OPLS-DA). Significant differences were found between the first-time UF, RUF and control group in the levels of lipids involved in the metabolism of glycerophospholipids, sphingolipids, lipids with an ether bond, triglycerides and fatty acids. Significant differences between the control group and the groups with UF and RUF were found in the blood plasma levels of cholesterol esters, triacylglycerols, (lyso) phosphatidylcholines and sphingomyelins. Significant differences between the UF and RUF groups were found in the blood plasma levels of cholesterol esters, phosphotidylcholines, sphingomyelins and triacylglycerols. Diagnostic models based on the selected differential lipids using logistic regression showed sensitivity and specificity of 88% and 86% for the diagnosis of first-time UF and 95% and 79% for RUF, accordingly. This study confirms the involvement of lipids in the pathogenesis of uterine fibroids. A diagnostically significant panel of differential lipid species has been identified for the diagnosis of UF and RUF by low-invasive blood plasma analysis. The developed diagnostic models demonstrated high potential for clinical use and further research in this direction.

Metabolomics in endometriosis: challenges and perspectives for future studies

Endometriosis is a complex disease characterized by inflammation and the growth of endometrial- like glands and stroma outside the uterine cavity. The pathophysiology of endometriosis is not entirely understood, however, with a prevalence of ~10% of women in their reproductive years, the disease symptoms significantly affect the quality of life of millions of women globally. Metabolomic studies have previously identified specific metabolites that could be a signature of endometriosis. This approach could potentially be used as a non-invasive tool for early diagnosis and provide a better understanding of endometriosis pathophysiology. This review aims to provide insight as to how endometriosis affects the metabolome by reviewing different studies that have used this approach to design follow-up studies. The search query included the term 'endometriosis' in combination with 'metabolomics', 'lipidomics', or 'sphingolipidomics' published between 2012 and 2020. We included studies in humans and animal models. Most studies reported differences in the metabolome of subjects with endometriosis in comparison to healthy controls and used samples taken from serum, endometrial tissue, follicular fluid, urine, peritoneal fluid, or endometrial fluid. Statistically significant metabolites contributed to group separation between patients and healthy controls. Reported metabolites included amino acids, lipids, organic acids, and other organic compounds. Differences in methods, analytical techniques, and the presence of confounding factors can interfere with results and interpretation of data. Metabolomics seems to be a promising tool for identifying significant metabolites in patients with endometriosis. Nonetheless, more investigation is needed in order to understand the significance of the study results.

Lay summary

Endometriosis is a chronic disease affecting the quality of life in one out of every ten women during their reproductive years, causing pain and infertility. It is characterized by inflammation and growth of tissue like the endometrium (uterus lining) outside the uterine cavity. Studies have searched for a predictor of endometriosis-associated changes by observing small molecules necessary for metabolism on a large scale (metabolomics). Metabolomics could serve to resolve one of the biggest challenges that patients with endometriosis face: a delay in diagnosis. In this review, the authors summarize identified potential biomarkers from various bodily fluids and tissues that are characteristic of metabolic processes observed in endometriosis. Biomarkers include cell growth, cell survival, high energy demand, oxidative stress, and fatty acid levels. A metabolomics approach offers promise as a non-invasive tool to identify significant metabolite changes in patients with endometriosis, potentially leading to earlier diagnoses and new opportunities for back-translational strategies.

Gene Expression Signature of Endometrial Samples from Women with and without Endometriosis

STUDY OBJECTIVE

To develop a prototype of a complex gene expression biomarker for the diagnosis of endometriosis on the basis of differences between the molecular signatures of the endometrium from women with and without endometriosis.

DESIGN

Prospective observational cohort study. Evidence obtained from a well-designed, controlled trial without randomization.

SETTING

Department of reproductive medicine and surgery, A.I. Evdokimov Moscow State University of Medicine and Dentistry.

PATIENTS

A total of 33 women (aged 32-38 years) were included in this study. Patients with and without endometriosis were divided into 2 separate groups. The group composed of patients with endometriosis included 19 living patients with endometriosis who underwent laparoscopic excision of endometriosis. The control group included 6 living patients who underwent laparoscopic excision of incompetent uterine scar after cesarean section, with both surgically and histologically confirmed absence of endometriosis and adenomyosis. An additional control/verification group included various previously RNA-sequencing-profiled tissue samples (endocervix, ovarian surface epithelium) of 8 randomly selected healthy female cadaveric donors aged 32 to 38 years. The exclusion criteria for all patients were hormone therapy and any intrauterine device use for more than 1 year preceding surgery, as well as absence of other diseases of the uterus, fallopian tubes, and ovaries.

INTERVENTIONS

Laparoscopic excision of endometriotic foci and hysteroscopy with endometrial sampling were performed. The cadaveric tissue samples included endocervix and ovarian surface epithelium. Endometrial sampling was obtained from the women in the control group. RNA sequencing was performed using Illumina HiSeq 3000 equipment (Illumina, Inc., San Diego, CA) for single-end sequencing. Unique bioinformatics algorithms were developed and validated using experimental and public gene expression datasets.

MEASUREMENTS AND MAIN RESULTS

We generated a characteristic signature of 5 genes downregulated in the endometrium and endometriotic tissue of the patients with endometriosis, selected after comparison with the endometrium of the women without endometriosis. This gene signature showed a capacity for nearly perfect separation of all 52 analyzed tissue samples of the patients with endometriosis (endometrial as well as endometriotic samples) from the 14 tissue samples of both living and cadaveric donors without endometriosis (area under the curve = 0.982, Matthews correlation coefficient = 0.832).

CONCLUSION

The gene signature of the endometrium identified in this study may potentially serve as a nonsurgical diagnostic method for endometriosis detection. Our data also suggest that the statistical method of 5-fold cross-validation of differential gene expression analysis can be used to generate robust gene signatures using real-world clinical data.

Lipidomic Alterations and PPARα Activation Induced by Resveratrol Lead to Reduction in Lesion Size in Endometriosis Models

Endometriosis is an estrogen‐dependent chronic inflammatory disease that affects approximately 10% of women of reproductive age and up to 50% of women with infertility. The heterogeneity of the disease makes accurate diagnosis and treatment a clinical challenge. In this study, we generated two models of endometriosis: the first in rats and the second using human ectopic endometrial stromal cells (HEcESCs) derived from the lesion tissues of endometriosis patients. We then applied resveratrol to assess its therapeutic potential. Resveratrol intervention had significant efficacy to attenuate lesion size and to rectify aberrant lipid profiles of model rats. Lipidomic analysis revealed significant lipidomic alterations, including notable increases of sphingolipids and decreases of both glycerolipids and most phospholipids. Upon resveratrol application, both proliferation capacity and invasiveness parameters decreased, and the early apoptosis proportion increased for HEcESCs. The activation of PPARα was also noted as a factor potentially contributing to recovery from endometriosis in both models. Our study provides valuable insight into the mechanisms of resveratrol in endometriosis and therefore strengthens the potential for optimizing resveratrol treatment for this disease.

Validation of Breast Cancer Margins by Tissue Spray Mass Spectrometry

Current methods for the intraoperative determination of breast cancer margins commonly suffer from the insufficient accuracy, specificity and/or low speed of analysis, increasing the time and cost of operation as well the risk of cancer recurrence. The purpose of this study is to develop a method for the rapid and accurate determination of breast cancer margins using direct molecular profiling by mass spectrometry (MS). Direct molecular fingerprinting of tiny pieces of breast tissue (approximately 1 × 1 × 1 mm) is performed using a home-built tissue spray ionization source installed on a Maxis Impact quadrupole time-of-flight mass spectrometer (qTOF MS) (Bruker Daltonics, Hamburg, Germany). Statistical analysis of MS data from 50 samples of both normal and cancer tissue (from 25 patients) was performed using orthogonal projections onto latent structures discriminant analysis (OPLS-DA). Additionally, the results of OPLS classification of new 19 pieces of two tissue samples were compared with the results of histological analysis performed on the same tissues samples. The average time of analysis for one sample was about 5 min. Positive and negative ionization modes are used to provide complementary information and to find out the most informative method for a breast tissue classification. The analysis provides information on 11 lipid classes. OPLS-DA models are created for the classification of normal and cancer tissue based on the various datasets: All mass spectrometric peaks over 300 counts; peaks with a statistically significant difference of intensity determined by the Mann–Whitney U-test (p < 0.05); peaks identified as lipids; both identified and significantly different peaks. The highest values of Q2 have models built on all MS peaks and on significantly different peaks. While such models are useful for classification itself, they are of less value for building explanatory mechanisms of pathophysiology and providing a pathway analysis. Models based on identified peaks are preferable from this point of view. Results obtained by OPLS-DA classification of the tissue spray MS data of a new sample set (n = 19) revealed 100% sensitivity and specificity when compared to histological analysis, the “gold” standard for tissue classification. “All peaks” and “significantly different peaks” datasets in the positive ion mode were ideal for breast cancer tissue classification. Our results indicate the potential of tissue spray mass spectrometry for rapid, accurate and intraoperative diagnostics of breast cancer tissue as a means to reduce surgical intervention.

Feature selection for OPLS discriminant analysis of cancer tissue lipidomics data

The mass spectrometry-based molecular profiling can be used for better differentiation between normal and cancer tissues and for the detection of neoplastic transformation, which is of great importance for diagnostics of a pathology, prognosis of its evolution trend, and development of a treatment strategy. The aim of the present study is the evaluation of tissue classification approaches based on various data sets derived from the molecular profile of the organic solvent extracts of a tissue. A set of possibilities are considered for the orthogonal projections to latent structures discriminant analysis: all mass spectrometric peaks over 300 counts threshold, subset of peaks selected by ranking with support vector machine algorithm, peaks selected by random forest algorithm, peaks with the statistically significant difference of the intensity determined by the Mann-Whitney U test, peaks identified as lipids, and both identified and significantly different peaks. The best predictive potential is obtained for OPLS-DA model built on nonpolar glycerolipids (Q² = 0.64, area under curve [AUC] = 0.95); the second one is OPLS-DA model with lipid peaks selected by random forest algorithm (Q² = 0.58, AUC = 0.87). Moreover, models based on particular molecular classes are more preferable from biological point of view, resulting in new explanatory mechanisms of pathophysiology and providing a pathway analysis. Another promising features for OPLS-DA modeling are phosphatidylethanolamines (Q² = 0.48, AUC = 0.86).

Molecular Imaging of Endometriosis Tissues using Desorption Electrospray Ionization Mass Spectrometry

Endometriosis is a pathologic condition affecting approximately 10% of women in their reproductive years. Characterized by abnormal growth of uterine endometrial tissue in other body areas, endometriosis can cause severe abdominal pain and/or infertility. Despite devastating consequences to patients' quality of life, the causes of endometriosis are not fully understood and validated diagnostic markers for endometriosis have not been identified. Molecular analyses of ectopic and eutopic endometrial tissues could lead to enhanced understanding of the disease. Here, we apply desorption electrospray ionization (DESI) mass spectrometry (MS) imaging to chemically and spatially characterize the molecular profiles of 231 eutopic and ectopic endometrial tissues from 89 endometriosis patients. DESI-MS imaging allowed clear visualization of endometrial glandular and stromal regions within tissue samples. Statistical models built from DESI-MS imaging data allowed classification of endometriosis lesions with overall accuracies of 89.4%, 98.4%, and 98.8% on training, validation, and test sample sets, respectively. Further, molecular markers that are significantly altered in ectopic endometrial tissues when compared to eutopic tissues were identified, including fatty acids and glycerophosphoserines. Our study showcases the value of MS imaging to investigate the molecular composition of endometriosis lesions and pinpoints metabolic markers that may provide new knowledge on disease pathogenesis.

Identification of potential endometriosis biomarkers in peritoneal fluid and blood plasma via shotgun lipidomics

Endometriosis is a recurrent and benign gynecological disorder, defined by the ectopic presence of endometrium. About 10% of reproductive-aged women suffer from endometriosis. There are no non-invasive or minimally invasive tests available in clinical practice to accurately diagnose endometriosis today. Here, we present our efforts to determine the diagnostic accuracy of biomarkers in peritoneal fluid and blood plasma using flow injection analysis with electrospray ionization tandem mass spectrometry (ESI-MS/MS) in 70 women with endometriosis and 20 women from a control group. The presence of endometriosis was confirmed by surgical findings and post-operative pathological examination. A qualitative and quantitative evaluation of the lipids in peritoneal fluids and blood plasma was carried out using electrospray ionization mass spectrometry (ESI-MS). The analysis revealed more than 140 molecular species of lipids, most of which pertained to five classes: phosphatidylcholines, phosphatidylethanolamines, sphingomyelins, di- and triglycerides. The data were analyzed using a statistical multifactorial method (i.e., PLS-DA). It was found that 9 potential biomarkers of endometriosis (LPC 16:0, PE O-20:0, PE O 34:1, PC 36:2, PC 36:4, PC 36:5, PC 38:4, PC 38:6 and SM 34:1) are common in blood plasma and peritoneal fluid, supporting connection with the pathological process. The sensitivity of the method developed for plasma was 93% with a specificity of 95%; for peritoneal fluid, the sensitivity was 90% and the specificity 95%. Accordingly, plasma is the most suitable biological fluid for clinical diagnostics of endometriosis. Further validation of these lipids as serologic biomarkers may enhance non-invasive diagnostic tools for patients with suspected endometriosis and reduce the frequency of diagnostic laparoscopy.

Lipidomic profile as a noninvasive tool to predict endometrial receptivity

For the present study we asked whether the endometrial fluid lipidomic may be a useful approach to predict endometrial receptivity in freeze-all cycles. For this case-control study, endometrial fluid samples were collected from 41 patients undergoing freeze-all cycles. Samples were split depending on the pregnancy outcome: positive group (n = 24) and negative group (n = 17). Data were acquired by the matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were applied. A list of potential biomarker ion ratios was obtained and the values were used to build a receiver operating characteristic (ROC) curve to predict pregnancy success. The lipid categories were attributed by LIPID MAPS database. Ion ratios were established according to their correlations and used for the analysis. The PCA showed a tendency of separation between the studied groups, whereas the PLS-DA was able to clearly distinguish them. Fifteen ratios (13 hyper-represented in the negative and two hyper-represented in the positive group) were selected according to their importance for model prediction. These ratios were used to build the ROC curve, which presented an area under curve of 84.0% (95%CI: 69.2-97.4%; p = 0.009). These findings suggest that lipidomic profiling of endometrial fluid may be a valuable tool for identifying the time interval comprising the window of implantation.