Screening and verifying endometrial carcinoma diagnostic biomarkers based on a urine metabolomic profiling study using UPLC-Q-TOF/MS

Urine and serum metabolomic analysis of endometrial cancer diagnosis and classification based on ultra-performance liquid chromatography mass spectrometry

OBJECTIVE

This study aimed to reveal the urinary and serum metabolic pattern of endometrial cancer (EC) and establish diagnostic models to identify EC from controls, high-risk from low-risk EC, and type II from type I EC.

METHOD

This study included 146 EC patients (comprising 79 low-risk and 67 high-risk patients, including 124 type I and 22 type II) and 59 controls. The serum and urine samples were analyzed using ultraperformance liquid chromatography mass spectrometry. Analysis was used to elucidate the distinct metabolites and altered metabolic pathways. Receiver operating characteristic (ROC) analyses were employed to discover and validate the potential biomarker models.

RESULTS

Serum and urine metabolomes displayed significant differences between EC and controls, with metabolites related to amino acid and nicotinamide metabolisms. The serum and urine panels distinguished these two groups with Area Under the Curve (AUC) of 0.821 and 0.902, respectively. The panel consisting of serum and urine metabolites demonstrated the best predictive ability (AUC = 0.953 and 0.976 in discovering and validation group). In comparing high-risk and low risk EC, differential metabolites were enriched in purine and glutamine metabolism. The AUC values for serum and urine panels were 0.818, and 0.843, respectively. The combined panel exhibited better predictive accuracy (0.881 in discovering group and 0.936 in external validation). In the comparison between type I and type II group, altered folic acid metabolism was identified. The serum, urine and combined panels discriminated these two groups with the AUC of 0.829, 0.913 and 0.922, respectively.

CONCLUSION

The combined urine and serum metabolome effectively revealed the metabolic patterns in EC patients, offering valuable diagnostic models for EC diagnosis and classification.

Modifications of Blood Molecular Components after Treatment with Low Ozone Concentrations

The ex vivo treatment of a limited volume of blood with gaseous oxygen-ozone (O2-O3) mixtures and its rapid reinfusion into the patient is a widespread medical procedure. O3 instantly reacts with the blood's antioxidant systems, disappearing before reinfusion, although the molecules formed act as messengers in the organism, inducing multiple antioxidant and anti-inflammatory responses. An appropriate dose of O3 is obviously essential to ensure both safety and therapeutic efficacy, and in recent years, the low-dose O3 concept has led to a significant reduction in the administered O3 concentrations. However, the molecular events triggered by such low concentrations in the blood still need to be fully elucidated. In this basic study, we analysed the molecular modifications induced ex vivo in sheep blood by 5 and 10 µg O3/mL O2 by means of a powerful metabolomics analysis in association with haemogas, light microscopy and bioanalytical assays. This combined approach revealed increased oxygenation and an increased antioxidant capacity in the O3-treated blood, which accorded with the literature. Moreover, original information was obtained on the impact of these low O3 concentrations on the metabolic pathways of amino acids, carbohydrates, lipids and nucleotides, with the modified metabolites being mostly involved in the preservation of the oxidant-antioxidant balance and in energy production.

Urine metabolomics for assessing fertility-sparing treatment efficacy in endometrial cancer: a non-invasive approach using ultra-performance liquid chromatography mass spectrometry

OBJECTIVE

This study aimed to reveal the urine metabolic change of endometrial cancer (EC) patients during fertility-sparing treatment and establish non-invasive predictive models to identify patients with complete remission (CR).

METHOD

This study enrolled 20 EC patients prior to treatment (PT) and 22 patients with CR, aged 25-40 years. Eligibility criteria consisted of stage IA high-grade EC, lesions confined to endometrium, normal hepatic and renal function, normal urine test, no contraindication for fertility-sparing treatment and no prior therapy. Urine samples were analyzed using ultraperformance liquid chromatography mass spectrometry (UPLC-MS), a technique chosen for its high sensitivity and resolution, allows for rapid, accurate identification and quantification of metabolites, providing a comprehensive metabolic profile and facilitating the discovery of potential biomarkers. Analytical techniques were employed to determine distinct metabolites and altered metabolic pathways. The statistical analyses were performed using univariate and multivariate analyses, logistic regression and receiver operating characteristic (ROC) curves to discover and validate the potential biomarker models.

RESULTS

A total of 108 different urine metabolomes were identified between CR and PT groups. These metabolites were enriched in ascorbate and aldarate metabolism, one carbon pool by folate, and some amino acid metabolisms pathways. A panel consisting of Baicalin, 5beta-1,3,7 (11)-Eudesmatrien-8-one, Indolylacryloylglycine, Edulitine, and Physapubenolide were selected as biomarkers, which demonstrated the best predictive ability with the AUC values of 0.982/0.851 in training/10-fold-cross-validation group, achieving a sensitivity of 0.975 and specificity of 0.967, respectively.

CONCLUSION

The urine metabolic analysis revealed the metabolic changes in EC patients during the fertility-sparing treatment. The predictive biomarkers present great potential diagnostic value in fertility-sparing treatments for EC patients, offering a less invasive means of monitoring treatment efficacy. Further research should explore the mechanistic underpinnings of these metabolic changes and validate the biomarker panel in larger, diverse populations due to the small sample size and single-institution nature of our study.

Endometrial cancer diagnostic and prognostic algorithms based on proteomics, metabolomics, and clinical data: a systematic review

Endometrial cancer is the most common gynaecological malignancy in developed countries. Over 382,000 new cases were diagnosed worldwide in 2018, and its incidence and mortality are constantly rising due to longer life expectancy and life style factors including obesity. Two major improvements are needed in the management of patients with endometrial cancer, i.e., the development of non/minimally invasive tools for diagnostics and prognostics, which are currently missing. Diagnostic tools are needed to manage the increasing number of women at risk of developing the disease. Prognostic tools are necessary to stratify patients according to their risk of recurrence pre-preoperatively, to advise and plan the most appropriate treatment and avoid over/under-treatment. Biomarkers derived from proteomics and metabolomics, especially when derived from non/minimally-invasively collected body fluids, can serve to develop such prognostic and diagnostic tools, and the purpose of the present review is to explore the current research in this topic. We first provide a brief description of the technologies, the computational pipelines for data analyses and then we provide a systematic review of all published studies using proteomics and/or metabolomics for diagnostic and prognostic biomarker discovery in endometrial cancer. Finally, conclusions and recommendations for future studies are also given.

Metabolic Changes and Their Associations with Selected Nutrients Intake in the Group of Workers Exposed to Arsenic

Arsenic (As) exposure causes numerous adverse health effects, which can be reduced by the nutrients involved in the metabolism of iAs (inorganic As). This study was carried out on two groups of copper-smelting workers: WN, workers with a urinary total arsenic (tAs) concentration within the norm (n = 75), and WH, workers with a urinary tAs concentration above the norm (n = 41). This study aimed to analyze the association between the intake level of the nutrients involved in iAs metabolism and the signal intensity of the metabolites that were affected by iAs exposure. An untargeted metabolomics analysis was carried out on urine samples using liquid chromatography-mass spectrometry, and the intake of the nutrients was analyzed based on 3-day dietary records. Compared with the WN group, five pathways (the metabolism of amino acids, carbohydrates, glycans, vitamins, and nucleotides) with twenty-five putatively annotated metabolites were found to be increased in the WH group. In the WN group, the intake of nutrients (methionine; vitamins B2, B6, and B12; folate; and zinc) was negatively associated with six metabolites (cytosine, D-glucuronic acid, N-acetyl-D-glucosamine, pyroglutamic acid, uridine, and urocanic acid), whereas in the WH group, it was associated with five metabolites (D-glucuronic acid, L-glutamic acid, N-acetyl-D-glucosamine, N-acetylneuraminic acid, and uridine). Furthermore, in the WH group, positive associations between methionine, folate, and zinc intake and the signal intensity of succinic acid and 3-mercaptolactic acid were observed. These results highlight the need to educate the participants about the intake level of the nutrients involved in iAs metabolism and may contribute to further considerations with respect to the formulation of dietary recommendations for people exposed to iAs.

Updates in gynecologic care for individuals with lynch syndrome

Lynch syndrome is an autosomal dominant hereditary cancer syndrome caused by germline pathogenic variants (PVs) in DNA mismatch repair genes (MLH1, MSH2, PMS2, MSH6) or the EPCAM gene. It is estimated to affect 1 in 300 individuals and confers a lifetime risk of cancer of 10-90%, depending on the specific variant and type of cancer. Lynch syndrome is the most common cause of inherited colorectal cancer, but for women, endometrial cancer is more likely to be the sentinel cancer. There is also evidence that certain PVs causing Lynch syndrome confer an increased risk of ovarian cancer, while the risk of ovarian cancer in others is not well defined. Given this, it is essential for the practicing gynecologist and gynecologic oncologist to remain up to date on the latest techniques in identification and diagnosis of individuals with Lynch syndrome as well as evidence-based screening and risk reduction recommendations for those impacted. Furthermore, as the landscape of gynecologic cancer treatment shifts towards treatment based on molecular classification of tumors, knowledge of targeted therapies well-suited for mismatch repair deficient Lynch tumors will be crucial. The objective of this review is to highlight recent updates in the literature regarding identification and management of individuals with Lynch syndrome as it pertains to endometrial and ovarian cancers to allow gynecologic providers the opportunity to both prevent and identify Lynch-associated cancers earlier, thereby reducing the morbidity and mortality of the syndrome.

Immunometabolic and potential tumor-promoting changes in 3D cervical cell models infected with bacterial vaginosis-associated bacteria

Specific bacteria of the human microbiome influence carcinogenesis at diverse anatomical sites. Bacterial vaginosis (BV) is the most common vaginal disorder in premenopausal women that is associated with gynecologic sequelae, including cervical cancer. BV-associated microorganisms, such as Fusobacterium, Lancefieldella, Peptoniphilus, and Porphyromonas have been associated with gynecologic and other cancers, though the pro-oncogenic mechanisms employed by these bacteria are poorly understood. Here, we integrated a multi-omics approach with our three-dimensional (3-D) cervical epithelial cell culture model to investigate how understudied BV-associated bacteria linked to gynecologic neoplasia influence hallmarks of cancer in vitro. Lancefieldella parvulum and Peptoniphilus lacrimalis elicited robust proinflammatory responses in 3-D cervical cells. Fusobacterium nucleatum and Fusobacterium gonidiaformans modulated metabolic hallmarks of cancer corresponding to accumulation of 2-hydroxyglutarate, pro-inflammatory lipids, and signs of oxidative stress and genotoxic hydrogen sulfide. This study provides mechanistic insights into how gynecologic cancer-associated bacteria might facilitate a tumor-promoting microenvironment in the human cervix.

Multi-Omic Profiling of Multi-Biosamples Reveals the Role of Amino Acid and Nucleotide Metabolism in Endometrial Cancer

Background

Endometrial cancer (EC) is one of the most common gynecological cancers. The traditional diagnosis of EC relies on histopathology, which, however, is invasive and may arouse tumor spread. There have been many studies aiming to find the metabolomic biomarkers of EC to improve the early diagnosis of cancer in a non-invasive or minimally invasive way, which can also provide valuable information for understanding the disease. However, most of these studies only analyze a single type of sample by metabolomics, and cannot provide a comprehensive view of the altered metabolism in EC patients. Our study tries to gain a pathway-based view of multiple types of samples for understanding metabolomic disorders in EC by combining metabolomics and proteomics.

Methods

Forty-four EC patients and forty-three controls were recruited for the research. We collected endometrial tissue, urine, and intrauterine brushing samples. Untargeted metabolomics and untargeted proteomics were both performed on the endometrial tissue samples, while only untargeted metabolomics was performed on the urine and intrauterine brushing samples.

Results

By integrating the differential metabolites and proteins between EC patients and controls detected in the endometrial tissue samples, we identified several EC-related significant pathways, such as amino acid metabolism and nucleotide metabolism. The significance of these pathways and the potential of metabolite biomarker-based diagnosis were then further verified by using urine and intrauterine brushing samples. It was found that the regulation of metabolites involved in the significant pathways showed similar trends in the intrauterine brushings and the endometrial tissue samples, while opposite trends in the urine and the endometrial tissue samples.

Conclusions

With multi-omics characterization of multi-biosamples, the metabolomic changes related to EC are illustrated in a pathway-based way. The network of altered metabolites and related proteins provides a comprehensive view of altered metabolism in the endometrial tissue samples. The verification of these critical pathways by using urine and intrauterine brushing samples provides evidence for the possible non-invasive or minimally invasive biopsy for EC diagnosis in the future.

Identification of novel diagnostic biomarkers in endometrial cancer using targeted metabolomic profiling

PURPOSE

Endometrial cancer (EC) is the most common gynecological malignancy with high disease burden especially in advanced stages of the disease. Our study investigated the metabolomic profile of EC patient's serum with the aim of identifying novel diagnostic biomarkers that could be used especially in early disease detection.

MATERIAL AND METHODS

Using targeted metabolomic serum profiling based on HPLC-TQ/MS, women with EC (n ​= ​15) and controls (n ​= ​21) were examined for 232 endogenous metabolites.

RESULTS

Top performing biomarkers included ceramides, acylcarnitines and 1-methyl adenosine. Top 4 biomarkers combined achieved 94% sensitivity with 75% specificity with AUC 92.5% (CI 90.5-94.5%). Individual markers also provided significant predictive values: C16-ceramide achieved sensitivity 73%, specificity 81%, AUC 0.83, C22-ceramide sensitivity 67%, specificity 81%, AUC 0.77, hydroxyhexadecenoylcarnitine sensitivity 60%, specificity 96%, AUC 0.76 and 1-methyladenosine sensitivity 67%, specificity 81%, AUC 0.75. The individual markers, however, did not reach the high sensitivity and specificity of the 4-biomarker combination.

CONCLUSIONS

Using mass spectrometry targeted metabolomic profiling, ceramides, acylcarnitines and 1-methyladenosine were identified as potential diagnostic biomarkers for EC. Additionally, these identified metabolites may provide additional insight into cancer cell metabolism.

Urinary Biomarkers and Their Potential for the Non-Invasive Detection of Endometrial Cancer

Endometrial cancer is the most common malignancy of the female genital tract and its incidence is rising in parallel with the mounting prevalence of obesity. Early diagnosis has great potential to improve outcomes as treatment can be curative, especially for early stage disease. Current tests and procedures for diagnosis are limited by insufficient accuracy in some and unacceptable levels of invasiveness and discomfort in others. There has, therefore, been a growing interest in the search for sensitive and specific biomarkers for endometrial cancer detection based on non-invasive sampling methodologies. Urine, the prototype non-invasive sample, is attractive for biomarker discovery as it is easily accessible and can be collected repeatedly and in quantity. Identification of urinary biomarkers for endometrial cancer detection relies on the excretion of systemic biomarkers by the kidneys or urinary contamination by biomarkers shed from the uterus. In this review, we present the current standing of the search for endometrial cancer urinary biomarkers based on cytology, genomic, transcriptomic, proteomic, and metabolomic platforms. We summarize the biomarker candidates and highlight the challenges inherent in urinary biomarker discovery. We review the various technologies with promise for biomarker detection and assess these novel approaches for endometrial cancer biomarker research.

Analytical tools for urocanic acid determination in human samples: A review

Urocanic acid is a chromophore found in the skin that has been identified as an important immunosuppressant and carcinogenesis mediator through its photoisomerization from trans to cis form induced by ultraviolet radiation. Research on analytical methods that explore urocanic acid isomerization is indispensable to fully understand the deleterious effects mediated by this biomarker. In this context, the current relevant analytical methods for determination of these isomers in human samples are summarized in this review. The methods presented here are applicable to human samples collected by noninvasive methods (or minimally invasive), encompassing an array of analytical techniques, including high-performance capillary electrophoresis, confocal Raman spectroscopy, gas chromatography, high-performance liquid chromatography, and mass spectrometry, among others. Developed high-performance liquid chromatography methods have proven to be advantageous, allowing noninvasive collections for in vivo analysis and the confocal Raman, specially, for real-time analysis. Among all these methods, high-performance liquid chromatography is the most investigated one with mass spectrometry or ultraviolet detector, and the mass spectrometry detector being the most studied in the last years, demonstrating high sensitivity, very low detection limits, and accurate identification, especially for clinical investigations.

Metabolomic Biomarkers for Detection, Prognosis and Identifying Recurrence in Endometrial Cancer

Metabolic reprogramming is increasingly recognised as one of the defining hallmarks of tumorigenesis. There is compelling evidence to suggest that endometrial cancer develops and progresses in the context of profound metabolic dysfunction. Whilst the incidence of endometrial cancer continues to rise in parallel with the global epidemic of obesity, there are, as yet, no validated biomarkers that can aid risk prediction, early detection, prognostic evaluation or surveillance. Advances in high-throughput technologies have, in recent times, shown promise for biomarker discovery based on genomic, transcriptomic, proteomic and metabolomic platforms. Metabolomics, the large-scale study of metabolites, deals with the downstream products of the other omics technologies and thus best reflects the human phenotype. This review aims to provide a summary and critical synthesis of the existing literature with the ultimate goal of identifying the most promising metabolite biomarkers that can augment current endometrial cancer diagnostic, prognostic and recurrence surveillance strategies. Identified metabolites and their biochemical pathways are discussed in the context of what we know about endometrial carcinogenesis and their potential clinical utility is evaluated. Finally, we underscore the challenges inherent in metabolomic biomarker discovery and validation and provide fresh perspectives and directions for future endometrial cancer biomarker research.

Urinary Metabolomic Profiling Analysis and Evaluation of the Effect of Ecklonia cava Extract Intake

Metabolomics is a powerful tool for the investigation of interactions between diet, nutrients, and human metabolism. Ecklonia cava is an edible brown alga that is abundantly found in Korea and Japan and contains unique polyphenols referred to as phlorotannins. However, there are few metabolomics studies related to the effects of polyphenols in humans. In this study, we performed a mass spectrometry-based metabolomics analysis of urine samples from participants with a body mass index (BMI) higher than 25 kg/m2 and lower than 30 kg/m2 to investigate the effects of the intake of seapolynol isolated from E. cava. Metabolomic profiling showed that the levels of riboflavin, urocanic acid, 5-hydroxy-6-methoxyindole glucuronide, and guanidino valeric acid were significantly increased in the seapolynol intake group compared with the placebo group. A correlation analysis was performed to identify the association between the metabolites' levels and clinical characteristics related to body fat. Among the metabolites whose concentrations changed in the seapolynol intake group, riboflavin was associated with BMI, body weight, fat mass, and percent body fat. These findings suggest that the decreased body fat induced by the intake of seapolynol is related to an increase in the antioxidant effect of riboflavin.

Cancer metabolomic markers in urine: evidence, techniques and recommendations

Urinary tests have been used as noninvasive, cost-effective tools for screening, diagnosis and monitoring of diseases since ancient times. As we progress through the 21st century, modern analytical platforms have enabled effective measurement of metabolites, with promising results for both a deeper understanding of cancer pathophysiology and, ultimately, clinical translation. The first study to measure metabolomic urinary cancer biomarkers using NMR and mass spectrometry (MS) was published in 2006 and, since then, these techniques have been used to detect cancers of the urological system (kidney, prostate and bladder) and nonurological tumours including those of the breast, ovary, lung, liver, gastrointestinal tract, pancreas, bone and blood. This growing field warrants an assessment of the current status of research developments and recommendations to help systematize future research.

Blood Metabolites Associate with Prognosis in Endometrial Cancer

Endometrial cancer has a high prevalence among post-menopausal women in developed countries. We aimed to explore whether certain metabolic patterns could be related to the characteristics of aggressive disease and poorer survival among endometrial cancer patients in Western Norway. Patients with endometrial cancer with short survival (n = 20) were matched according to FIGO (International Federation of Gynecology and Obstetrics, 2009 criteria) stage, histology, and grade, with patients with long survival (n = 20). Plasma metabolites were measured on a multiplex system including 183 metabolites, which were subsequently determined using liquid chromatography-mass spectrometry. Partial least square discriminant analysis, together with hierarchical clustering, was used to identify patterns which distinguished short from long survival. A proposed signature of metabolites related to survival was suggested, and a multivariate receiver operating characteristic (ROC) analysis yielded an area under the curve (AUC) of 0.820–0.965 (p ≤ 0.001). Methionine sulfoxide seems to be particularly strongly associated with poor survival rates in these patients. In a subgroup with preoperative contrast-enhanced computed tomography data, selected metabolites correlated with the estimated abdominal fat distribution parameters. Metabolic signatures may predict prognosis and be promising supplements when evaluating phenotypes and exploring metabolic pathways related to the progression of endometrial cancer. In the future, this may serve as a useful tool in cancer management.

Comparative Metabolomics Analysis of Cervicitis in Human Patients and a Phenol Mucilage-Induced Rat Model Using Liquid Chromatography Tandem Mass Spectrometry

Cervicitis is an exceedingly common gynecological disorder that puts women at high risk of sexually transmitted infections and induces a series of reproductive system diseases. This condition also has a significant impact on quality of life and is commonly misdiagnosed in clinical practice due to its complicated pathogenesis. In the present study, we performed non-targeted plasma metabolomics analysis of cervicitis in both plasma samples obtained from human patients and plasma samples from a phenol mucilage induced rat model of cervicitis, using ultra-performance liquid chromatography coupled to quadrupole time-of-flight tandem mass spectrometry. In addition to differences in histopathology, we identified differences in the metabolic profile between the cervicitis and control groups using unsupervised principal component analysis and orthogonal projections to latent structures discriminant analysis. These results demonstrated changes in plasma metabolites, with 27 and 22 potential endogenous markers identified in rat and human samples, respectively. The metabolic pathway analysis showed that linoleic acid, arachidonic acid, ether lipid, and glycerophospholipid metabolism are key metabolic pathways involved in cervicitis. This study showed the rat model was successfully created and applied to understand the pathogenesis of cervicitis.

Identification and functional analyses of differentially expressed metabolites in early stage endometrial carcinoma

Diagnosis of endometrial cancer is primarily based on symptoms and imaging, with early-stage disease being difficult to diagnose. Therefore, development of potential diagnostic biomarkers is required. Metabolomics, a quantitative measurement of the dynamic metabolism in living systems, can be applied to determine metabolite profiles in different disease states. Here, serum metabolomics was performed in 46 early stage endometrial cancer patients and 46 healthy volunteers. In addition, the effect of identified metabolites on tumor cell behavior (invasion, migration, proliferation, apoptosis and autophagy) was examined in endometrial cancer cell lines. Compared with controls, phenylalanine, indoleacrylic acid (IAA), phosphocholine and lyso-platelet-activating factor-16 (lyso-PAF) were differentially detected in patients. Functional analyses demonstrated that IAA, PAF and phenylalanine all dose-dependently inhibited tumor cell invasion and migration, and suppressed cell proliferation. PAF also induced tumor cell apoptosis and autophagy, while phenylalanine had no effect on apoptosis or autophagy. IAA triggered apoptosis and had a biphasic effect on autophagy: inhibiting autophagy with doses <1 mmol/L but inducing at 1 mmol/L. Interestingly, the alterations in proliferation, apoptosis and autophagy caused by 1 mmol/L IAA, were all reversed by the concomitant treatment of tryptophan (100 μmol/L). Phosphocholine inhibited tumor cell invasion and migration, and promoted cell proliferation and autophagy, all in a dose-dependent manner. Phosphocholine also protected cells from TNF-α-induced apoptosis. In conclusion, 4 serum metabolites were identified by serum metabolomics in endometrial cancer patients and functional analyses suggested that they may play roles in modulation of tumor cell behavior, although their exact mode of action still needs to be determined.

Identification of Metabolomic Biomarkers for Endometrial Cancer and Its Recurrence after Surgery in Postmenopausal Women

Endometrial cancer (EC) is the most frequent gynecological cancer in developed countries. Most EC occurs after menopause and is diagnosed as endometrioid (type I) carcinomas, which exhibit a favorable prognosis. In contrast, non-endometrioid (type II) carcinomas such as serous tumors have a poor prognosis. Our goal was to identify novel blood-based markers associated with EC subtypes and recurrence after surgery in postmenopausal women. Using mass spectrometry-based untargeted metabolomics, we examined preoperative serum metabolites among control women (n = 18) and those with non-recurrent (NR) and recurrent (R) cases of type I endometrioid (n = 24) and type II serous (n = 12) carcinomas. R and NR cases were similar with respect to pathological characteristics, body mass index, and age. A total of 1,592 compounds were analyzed including 14 different lipid classes. When we compared EC cases with controls, 137 metabolites were significantly different. A combination of spermine and isovalerate resulted in an age-adjusted area under the receiver-operating characteristic curve (AUC_adj) of 0.914 (P < 0.001) for EC detection. The combination of 2-oleoylglycerol and TAG42:2-FA12:0 allowed the distinction of R cases from NR cases with an AUC_adj of 0.901 (P < 0.001). Type I R cases were also characterized by much lower levels of bile acids and elevated concentrations of phosphorylated fibrinogen cleavage peptide, whereas type II R cases displayed higher levels of ceramides. The findings from our pilot study provide a detailed metabolomics study of EC and identify putative serum biomarkers for defining clinically relevant risk groups.

Metabolomic and Lipidomic Profiling Identifies The Role of the RNA Editing Pathway in Endometrial Carcinogenesis

Endometrial cancer (EC) remains the most common malignancy of the genital tract among women in developed countries. Although much research has been performed at genomic, transcriptomic and proteomic level, there is still a significant gap in the metabolomic studies of EC. In order to gain insights into altered metabolic pathways in the onset and progression of EC carcinogenesis, we used high resolution mass spectrometry to characterize the metabolomic and lipidomic profile of 39 human EC and 17 healthy endometrial tissue samples. Several pathways including lipids, Kynurenine pathway, endocannabinoids signaling pathway and the RNA editing pathway were found to be dysregulated in EC. The dysregulation of the RNA editing pathway was further investigated in an independent set of 183 human EC tissues and matched controls, using orthogonal approaches. We found that ADAR2 is overexpressed in EC and that the increase in expression positively correlates with the aggressiveness of the tumor. Furthermore, silencing of ADAR2 in three EC cell lines resulted in a decreased proliferation rate, increased apoptosis, and reduced migration capabilities in vitro. Taken together, our results suggest that ADAR2 functions as an oncogene in endometrial carcinogenesis and could be a potential target for improving EC treatment strategies.

Metabolomics for the masses: The future of metabolomics in a personalized world

Current clinical practices focus on a small number of biochemical directly related to the pathophysiology with patients and thus only describe a very limited metabolome of a patient and fail to consider the interations of these small molecules. This lack of extended information may prevent clinicians from making the best possible therapeutic interventions in sufficient time to improve patient care. Various post-genomics '('omic)' approaches have been used for therapeutic interventions previously. Metabolomics now a well-established'omics approach, has been widely adopted as a novel approach for biomarker discovery and in tandem with genomics (especially SNPs and GWAS) has the potential for providing systemic understanding of the underlying causes of pathology. In this review, we discuss the relevance of metabolomics approaches in clinical sciences and its potential for biomarker discovery which may help guide clinical interventions. Although a powerful and potentially high throughput approach for biomarker discovery at the molecular level, true translation of metabolomics into clinics is an extremely slow process. Quicker adaptation of biomarkers discovered using metabolomics can be possible with novel portable and wearable technologies aided by clever data mining, as well as deep learning and artificial intelligence; we shall also discuss this with an eye to the future of precision medicine where metabolomics can be delivered to the masses.