Predicting ovarian cancer recurrence by plasma metabolic profiles before and after surgery

Background

Previous metabolomic studies have revealed that plasma metabolic signatures may predict epithelial ovarian cancer (EOC) recurrence. However, few studies have performed metabolic profiling of pre- and post-operative specimens to investigate EOC prognostic biomarkers.

Objective

The aims of our study were to compare the predictive performance of pre- and post-operative specimens and to create a better model for recurrence by combining biomarkers from both metabolic signatures.

Methods

Thirty-five paired plasma samples were collected from 35 EOC patients before and after surgery. The patients were followed-up until December, 2016 to obtain recurrence information. Metabolomics using rapid resolution liquid chromatography–mass spectrometry was performed to identify metabolic signatures related to EOC recurrence. The support vector machine model was employed to predict EOC recurrence using identified biomarkers.

Results

Global metabolomic profiles distinguished recurrent from non-recurrent EOC using both pre- and post-operative plasma. Ten common significant biomarkers, hydroxyphenyllactic acid, uric acid, creatinine, lysine, 3-(3,5-diiodo-4-hydroxyphenyl) lactate, phosphohydroxypyruvic acid, carnitine, coproporphyrinogen, l-beta-aspartyl-l-glutamic acid and 24,25-hydroxyvitamin D3, were identified as predictive biomarkers for EOC recurrence. The area under the receiver operating characteristic (AUC) values in pre- and post-operative plasma were 0.815 and 0.909, respectively; the AUC value after combining the two sets reached 0.964.

Conclusion

Plasma metabolomic analysis could be used to predict EOC recurrence. While post-operative biomarkers have a predictive advantage over pre-operative biomarkers, combining pre- and post-operative biomarkers showed the best predictive performance and has great potential for predicting recurrent EOC.

     

Variation of the microbiota and metabolome along the canine gastrointestinal tract

Introduction

The fecal microbiota are relevant to the health and disease of many species. The importance of the fecal metabolome has more recently been appreciated, but our knowledge of the microbiota and metabolome at other sites along the gastrointestinal tract remains deficient.

Objective

To analyze the gastrointestinal microbiota and metabolome of healthy domestic dogs at four anatomical sites.

Methods

Samples of the duodenal, ileal, colonic, and rectal contents were collected from six adult dogs after humane euthanasia for an unrelated study. The microbiota were characterized using Illumina sequencing of 16S rRNA genes. The metabolome was characterized by mass spectrometry-based methods.

Results

Prevalent phyla throughout the samples were Proteobacteria, Firmicutes, Fusobacteria, and Bacteroidetes, consistent with previous findings in dogs and other species. A total of 530 unique metabolites were detected; 199 of these were identified as previously named compounds, but 141 of them had at least one significantly different site-pair comparison. Noteworthy examples include relative concentrations of amino acids, which decreased from the small to large intestine; pyruvate, which peaked in the ileum; and several phenol-containing carboxylic acid compounds that increased in the large intestine.

Conclusion

The microbiota and metabolome vary significantly at different sites along the canine gastrointestinal tract.

     

Metabolomic profiling of maternal hair suggests rapid development of intrahepatic cholestasis of pregnancy

Introduction

Intrahepatic cholestasis of pregnancy (ICP) is a common maternal liver disease; development can result in devastating consequences, including sudden fetal death and stillbirth. Currently, recognition of ICP only occurs following onset of clinical symptoms.

Objective

Investigate the maternal hair metabolome for predictive biomarkers of ICP.

Methods

The maternal hair metabolome (gestational age of sampling between 17 and 41 weeks) of 38 Chinese women with ICP and 46 pregnant controls was analysed using gas chromatography–mass spectrometry.

Results

Of 105 metabolites detected in hair, none were significantly associated with ICP.

Conclusion

Hair samples represent accumulative environmental exposure over time. Samples collected at the onset of ICP did not reveal any metabolic shifts, suggesting rapid development of the disease.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

Characterization of ankylosing spondylitis and rheumatoid arthritis using <Superscript>1</Superscript>H NMR-based metabolomics of human fecal extracts

Introduction

The differences in fecal metabolome between ankylosing spondylitis (AS)/rheumatoid arthritis (RA) patients and healthy individuals could be the reason for an autoimmune disorder.

Objectives

The study explored the fecal metabolome difference between AS/RA patients and healthy controls to clarify human immune disturbance.

Methods

Fecal samples from 109 individuals (healthy controls 34, AS 40, and RA 35) were analyzed by ¹H NMR spectroscopy. Data were analyzed with principal component analysis (PCA) and orthogonal projection to latent structure discriminant (OPLS-DA) analysis.

Results

Significant differences in the fecal metabolic profiles could distinguish AS/RA patients from healthy controls but could not distinguish between AS and RA patients. The significantly decreased metabolites in AS/RA patients were butyrate, propionate, methionine, and hypoxanthine. Significantly increased metabolites in AS/RA patients were taurine, methanol, fumarate, and tryptophan.

Conclusion

The metabolome variations in feces indicated AS and RA were two homologous diseases that could not be distinguished by ¹H NMR metabolomics.

     

Characterization of trotter horses urine metabolome by means of proton nuclear magnetic resonance spectroscopy

Background

Metabolomics has been recognized as a powerful approach for disease screening. In order to highlight potential health issues in subjects, a key factor is the possibility to compare quantitatively the metabolome of their biofluids with reference values from healthy individuals. Such efforts towards the systematic characterization of the metabolome of biofluids in perfect health conditions, far from concluded for humans, have barely begun on horses.

Objectives

The present work attempts, for the first time, to give reference quantitative values for the molecules mostly represented in the urine metabolome of horses at rest and under light training, as observable by ¹H-NMR.

Methods

The metabolome of ten trotter horses, four male and six female, ranging from 3 to 8 years of age, has been observed by ¹H-NMR spectroscopy before and after three training sessions.

Results

We could characterize and quantify 54 molecules in trotter horse urine, originated from diet, protein digestion, energy generation or gut-microbial co-metabolism.

Conclusion

We were able to describe how gender, age and exercise affected their concentration, by means of a two steps protocol based on univariate and robust principal component analysis.

     

The metabolome 18 years on: a concept comes of age

Background

The term ‘metabolome’ was introduced to the scientific literature in September 1998.

Aim and key scientific concepts of the review

To mark its 18-year-old ‘coming of age’, two of the co-authors of that paper review the genesis of metabolomics, whence it has come and where it may be going.

     

Metabolomic biomarkers and novel dietary factors associated with gestational diabetes in China

Introduction

Gestational diabetes mellitus (GDM) is impaired glucose tolerance first recognised during pregnancy; its development is associated with many adverse outcomes. Mechanisms of GDM development are not fully elucidated and few studies have used Chinese participants.

Objectives

The aim of this study was to investigate the maternal metabolome associated with GDM in a Chinese population, and explore the relationship with maternal diet.

Methods

Ninety-three participants were recruited at 26–28 weeks’ gestation from Chongqing, China. Maternal urine, serum, and hair metabolomes were analysed using gas and liquid chromatography–mass spectrometry. Dietary intake was assessed using a 96-item food frequency questionnaire.

Results

Of the 1064 metabolites identified, 73 were significantly different between cases and controls (P?<?0.05), but only 2-aminobutyric acid had both a p- and q-value?<?0.05. A “snack-based-dietary-pattern” was associated with an increased likelihood of GDM (odds ratio 2·1; 95% confidence interval 1.1–3.9). The association remained significant after adjustment for calorie intake but not food volume.

Conclusion

This study provides a comprehensive characterization of the maternal metabolome. The snack-based dietary pattern associated with GDM suggests that timing and frequency of consumption are important factors in the relationship between maternal diet and GDM.

     

KIAA0101, a target gene of miR-429, enhances migration and chemoresistance of epithelial ovarian cancer cells

Background

Ovarian cancer is a common type of gynecological malignancies, and is the fifth leading cause of cancer-related death in women in the United States. MiR-429 and KIAA0101 have been found to be involved in several human malignancies, respectively. However, the role of miR-429 and KIAA0101, and the correlation between them during development of epithelial ovarian cancer (EOC) remain to be investigated.

Methods

The expression of KIAA0101 in EOC tissues and cells was measured by Quantitative real-time PCR, western blot, and immunochemistry. Cell proliferation assay, colony formation assay, and transwell assay was performed to assess the role of miR-429 and KIAA0101 in regulation of proliferation, migration, and chemoresistance of EOC cells. Luciferase assay was used to test the Wnt/β-catenin signaling activity in response to depletion of KIAA0101 and overexpression of miR-429.

Results

We found that KIAA0101 was upregulated in metastatic EOC tissues, compared to primary EOC tissues, and KIAA0101 was required for the migration activity and chemoresistance of EOC cells by enhancing Wnt/β-catenin signaling. Furthermore, we revealed KIAA0101 is direct target of miR-429. Similar to knockdown of KIAA0101, overexpression of miR-429 reduced invasion and chemoresistance of EOC cells. Co-transfection of KIAA0101 partially abrogates the inhibitory effects on invasion and chemoresistance in EOC cells.

Conclusions

KIAA0101, a target gene of miR-429, was upregulated in the metastatic EOC tissues, and enhanced the migration activity and chemoresistance of EOC cells. Both miR-429 and KIAA0101 may represent the potential therapeutic targets of EOC.

     

LC–MS-based metabolome analysis on steroid metabolites from the starfish <Emphasis Type="Italic">Patiria</Emphasis> (=<Emphasis Type="Italic">Asterina</Emphasis>) <Emphasis Type="Italic">pectinifera</Emphasis> in conditions of active feeding and stresses

Introduction

Starfish are recognized as interesting source of natural steroid products with pharmaceutical potential. Polar steroid metabolites of starfish have unique chemical structures and exhibit various biological activities but their biological functions are controversial.

Objectives

The objective of this study was to investigate the response of polar steroid metabolome of the starfish Patiria (=Asterina) pectinifera on various environmental factors and stresses.

Methods

Here we first have applied MS-based environmental metabolomics to elucidate the metabolic changes of polar steroid metabolome of starfish. Using HPLC–ESI–Q/TOF–MS approach followed by statistical analysis including principal component analysis and partial least squares discriminant analysis for data classification and potential biomarkers selection, we investigated the changes induced by feeding, injury, variations in water temperature and salinity, and oxygen deficiency.

Results

According to multivariate and univariate statistical analysis the responses to feeding, injury and water heating were better expressed than the others and have some similarity in their action on the steroid metabolome of the starfish P. pectinifera. Most constituents of asterosaponin pool were reduced and most constituents of polyhydroxysteroid and related glycoside pool were increased at that.

Conclusion

Our results indicate that various metabolic changes in polar steroid constituents of P. pectinifera are induced by feeding and stresses. We believe that these responses are connected with biological multifunctionality of these compounds.

     

Quantifying the cellular NAD+ metabolome using a tandem liquid chromatography mass spectrometry approach

Introduction

Nicotinamide adenine dinucleotide (NAD⁺) is an essential pyridine nucleotide that serves as a key hydride transfer coenzyme for several oxidoreductases. It is also the substrate for intracellular secondary messenger signalling by CD38 glycohydrolases, DNA repair by poly(adenosine diphosphate ribose) polymerase, and epigenetic regulation of gene expression by a class of histone deacetylase enzymes known as sirtuins. The measurement of NAD⁺ and its related metabolites (hereafter, the NAD⁺ metabolome) represents an important indicator of cellular function.

Objectives

A study was performed to develop a sensitive, selective, robust, reproducible, and rapid method for the concurrent quantitative determination of intracellular levels of the NAD⁺ metabolome in glial and oocyte cell extracts using liquid chromatography coupled to mass spectrometry (LC/MS/MS).

Methods

The metabolites were separated on a versatile amino column using a dual HILIC-RP gradient with heated electrospray (HESI) tandem mass spectrometry detection in mixed polarity multiple reaction monitoring mode.

Results

Quantification of 17 metabolites in the NAD⁺ metabolome in U251 human astroglioma cells could be achieved. Changes in NAD⁺ metabolism in U251 cell line, and murine oocytes under different culture conditions were also investigated.

Conclusion

This method can be used as a sensitive profiling tool, tailoring chromatography for metabolites that express significant pathophysiological changes in several disease conditions and is indispensable for targeted analysis.

     

Untargeted metabolomics reveals a mild impact of remote ischemic conditioning on the plasma metabolome and α-hydroxybutyrate as a possible cardioprotective factor and biomarker of tissue ischemia

Introduction

Remote ischemic conditioning (RIC) is a maneuver by which short non-lethal ischemic events are applied on distant organs or limbs to reduce ischemia and reperfusion injuries caused by e.g. myocardial infarct. Although intensively investigated, the specific mechanism of this protective phenomenon remains incompletely understood and in particular, knowledge on the role of small metabolites is scarce.

Objectives

In this study, we aimed to study perturbations in the plasma metabolome following RIC and gain insight into metabolic changes by the intervention as well as to identify potential novel cardio-protective metabolites.

Methods

Blood plasma samples from ten healthy males were collected prior to and after RIC and tested for bioactivity in a HL-1 based cellular model of ischemia–reperfusion damage. Following this, the plasma was analyzed using untargeted LC-qTOF-MS and regulated metabolites were identified using univariate and multivariate statistical analysis. Results were finally verified in a second plasma study from the same group of volunteers and by testing a metabolite ester in the HL-1 cell model.

Results

The analysis revealed a moderate impact on the plasma metabolome following RIC. One metabolite, α-hydroxybutyrate (AHB) however, stood out as highly significantly upregulated after RIC. AHB might be a novel and more sensitive plasma-biomarker of transient tissue ischemia than lactate. Importantly, it was also found that a cell permeable AHB precursor protects cardiomyocytes from ischemia–reperfusion damage.

Conclusion

Untargeted metabolomics analysis of plasma following RIC has led to insight into metabolism during RIC and revealed a possible novel metabolite of relevance to ischemic-reperfusion damage.

     

The urinary metabolome in female mink (<Emphasis Type="Italic">Mustela neovison</Emphasis>) shows distinct changes in protein and lipid metabolism during the transition from diapause to implantation

Introduction

The mink exhibit an obligatory diapause. The metabolic changes during the transition from diapause to implantation and established pregnancy are currently unknown.

Objectives

The study aimed to characterize changes in the urinary metabolome in mink during the period from mating to early gestation and to identify the metabolites involved.

Methods

Urine samples were collected from 56 female mink on March 24, April 8, and April 15, covering the period from mating to early pregnancy. The urine samples were subjected to non-targeted LC-MS metabolomics. Processed data were evaluated by principal component analysis (PCA) and the peak area of identified metabolites were subjected to ANOVA.

Results

The samples showed clear clustering according to sampling date in a PCA scores plot, and 35 metabolites differing significantly between sampling days were identified. The excretion of dicarboxylic acids and acylcarnitines of dicarboxylic acids exhibited a decline on April 8, and the same trend was observed for four unidentified metabolites, two of which were putatively identified as acids of the furan fatty acid type. The decreased excretion of lipid components was suggested to be a result of increased oxidation of these compounds. In contrast, the excretion of amino acid-related metabolites showed an increase on April 8 which was attributed to increased metabolism of amino acids at this time point.

Conclusion

The urinary metabolic profile of mink showed distinct changes during the period studied. The major changes were observed at the time of implantation where increases in the lipid and protein metabolism were evident.

     

Diagnosis of <Emphasis Type="Italic">Clostridium difficile</Emphasis> infection using an UPLC–MS based metabolomics method

Introduction

The fecal metabolome of Clostridium difficile (CD) infection is far from being understood, particularly its non-volatile organic compounds. The drawbacks of current tests used to diagnose CD infection hinder their application.

Objective

The aims of this study were to find new characteristic fecal metabolites of CD infection and develop a metabolomics model for the diagnosis of CD infection.

Methods

Ultra-performance liquid chromatography-mass spectrometry (UPLC–MS) was used to characterize the fecal metabolome of CD positive and negative diarrhea and healthy control stool samples.

Results

Diarrhea and healthy control samples showed distinct clusters in the principal components analysis score plot, and CD positive group and CD negative group demonstrated clearer separation in a partial least squares discriminate analysis model. The relative abundance of sphingosine, chenodeoxycholic acid, phenylalanine, lysophosphatidylcholine (C16:0), and propylene glycol stearate was higher, and the relative abundance of fatty amide, glycochenodeoxycholic acid, tyrosine, linoleyl carnitine, and sphingomyelin was lower in CD positive diarrhea groups, than in the CD negative group. A linear discriminant analysis model based on capsiamide, dihydrosphingosine, and glycochenodeoxycholic acid was further constructed to identify CD infection in diarrhea. The leave-one-out cross-validation accuracy and area under receiver operating characteristic curve for the training set/external validation set were 90.00/78.57%, and 0.900/0.7917 respectively.

Conclusions

Compared with other hospital-onset diarrhea, CD diarrhea has distinct fecal metabolome characteristics. Our UPLC–MS metabolomics model might be useful tool for diagnosing CD diarrhea.

     

Strategy for automated metabolic profiling of glioma subtypes from ex-vivo HRMAS spectra

Introduction

Infiltrating gliomas are primary brain tumors that express significant biological and clinical heterogeneity in adults, which complicates their treatment and prognosis. Characterization of tumor subtypes using spectroscopic analysis may assist in predicting malignant transformation and quantification of response to therapy.

Study objective

To implement an automated algorithm for classification of metabolomic profiles for the classification of glioma pathological grades and the prediction of malignant progression using spectra obtained by high-resolution magic angle spinning (HR-MAS) spectroscopy of patient-derived tissue samples.

Methods

237 image-guided tissue samples were obtained from 152 patients who underwent surgery for newly diagnosed or recurrent glioma and analyzed via HR-MAS spectroscopy. Orthogonal projection to latent structures discriminant analysis was used as a classifier and the variable-influence-on-projection values were evaluated to identify signature spectral regions.

Results

The accuracy of classifiers developed for discriminating glioma subtypes was 68% for newly diagnosed grade II versus III samples; 86 and 92% for new and recurrent grade III versus IV, respectively; 95% for newly diagnosed grade II versus IV; and 88% for recurrent grade II versus IV lesions. Classifiers distinguished between samples from newly diagnosed vs. recurrent lesions with an accuracy of 78% for grade III and 99% for grade IV glioma.

Conclusion

Classifying metabolomic profiles for new and recurrent glioma without prior assumptions regarding spectral components identified candidate in vivo biomarkers for use in assessing changes that are likely to impact treatment decisions.

     

Applications of metabolomics in the study and management of preeclampsia: a review of the literature

Introduction

Preeclampsia represents a major public health burden worldwide, but predictive and diagnostic biomarkers are lacking. Metabolomics is emerging as a valuable approach to generating novel biomarkers whilst increasing the mechanistic understanding of this complex condition.

Objectives

To summarize the published literature on the use of metabolomics as a tool to study preeclampsia.

Methods

PubMed and Web of Science were searched for articles that performed metabolomic profiling of human biosamples using either Mass-spectrometry or Nuclear Magnetic Resonance based approaches and which included preeclampsia as a primary endpoint.

Results

Twenty-eight studies investigating the metabolome of preeclampsia in a variety of biospecimens were identified. Individual metabolite and metabolite profiles were reported to have discriminatory ability to distinguish preeclamptic from normal pregnancies, both prior to and post diagnosis. Lipids and carnitines were among the most commonly reported metabolites. Further work and validation studies are required to demonstrate the utility of such metabolites as preeclampsia biomarkers.

Conclusion

Metabolomic-based biomarkers of preeclampsia have yet to be integrated into routine clinical practice. However, metabolomic profiling is becoming increasingly popular in the study of preeclampsia and is likely to be a valuable tool to better understand the pathophysiology of this disorder and to better classify its subtypes, particularly when integrated with other omic data.

     

Characterisation of the main drivers of intra- and inter- breed variability in the plasma metabolome of dogs

Introduction

Dog breeds are a consequence of artificial selection for specific attributes. These closed genetic populations have metabolic and physiological characteristics that may be revealed by metabolomic analysis.

Objectives

To identify and characterise the drivers of metabolic differences in the fasted plasma metabolome and then determine metabolites differentiating breeds.

Methods

Fasted plasma samples were collected from dogs maintained under two environmental conditions (controlled and client-owned at home). The former (n = 33) consisted of three breeds (Labrador Retriever, Cocker Spaniel and Miniature Schnauzer) fed a single diet batch, the latter (n = 96), client-owned dogs consisted of 9 breeds (Beagle, Chihuahua, Cocker Spaniel, Dachshund, Golden Retriever, Greyhound, German Shepherd, Labrador Retriever and Maltese) consuming various diets under differing feeding regimens. Triplicate samples were taken from Beagle (n = 10) and Labrador Retriever (n = 9) over 3 months. Non-targeted metabolite fingerprinting was performed using flow infusion electrospray-ionization mass spectrometry which was coupled with multivariate data analysis. Metadata factors including age, gender, sexual status, weight, diet and breed were investigated.

Results

Breed differences were identified in the plasma metabolome of dogs housed in a controlled environment. Triplicate samples from two breeds identified intra-individual variability, yet breed separation was still observed. The main drivers of variance in dogs maintained in the home environment were associated with breed and gender. Furthermore, metabolite signals were identified that discriminated between Labrador Retriever and Cocker Spaniels in both environments.

Conclusion

Metabolite fingerprinting of plasma samples can be used to investigate breed differences in client-owned dogs, despite added variance of diet, sexual status and environment.

     

LacaScore: a novel plasma sample quality control tool based on ascorbic acid and lactic acid levels

Introduction

Metabolome analysis is complicated by the continuous dynamic changes of metabolites in vivo and ex vivo. One of the main challenges in metabolomics is the robustness and reproducibility of results, partially driven by pre-analytical variations.

Objectives

The objective of this study was to analyse the impact of pre-centrifugation time and temperature, and to determine a quality control marker in plasma samples.

Methods

Plasma metabolites were measured by gas chromatography-mass spectrometry (GC–MS) and analysed with the MetaboliteDetector software. The metabolites, which were the most labile to pre-analytical variations, were further measured by enzymatic assays. A score was calculated for their use as quality control markers.

Results

The pre-centrifugation temperature was shown to be critical in the stability of plasma samples and had a significant impact on metabolite concentration profiles. In contrast, pre-centrifugation delay had only a minor impact. Based on the results of this study, whole blood should be kept on wet ice and centrifuged within maximum 3 h as a prerequisite for preparing EDTA plasma samples fit for the purpose of metabolome analysis.

Conclusions

We have established a novel blood sample quality control marker, the LacaScore, based on the ascorbic acid to lactic acid ratio in plasma, which can be used as an indicator of the blood pre-centrifugation conditions, and hence the suitability of the sample for metabolome analyses. This method can be applied in research institutes and biobanks, enabling assessment of the quality of their plasma sample collections.

     

Effect of experimental gingivitis induction and erythritol on the salivary metabolome and functional biochemistry of systemically healthy young adults

Introduction

Understanding the changes occurring in the oral ecosystem during development of gingivitis could help improve prevention and treatment strategies for oral health. Erythritol is a non-caloric polyol proposed to have beneficial effects on oral health.

Objectives

To examine the effect of experimental gingivitis and the effect of erythritol on the salivary metabolome and salivary functional biochemistry.

Methods

In a two-week experimental gingivitis challenge intervention study, non-targeted, mass spectrometry-based metabolomic profiling was performed on saliva samples from 61 healthy adults, collected at five time-points. The effect of erythritol was studied in a randomized, controlled trial setting. Fourteen salivary biochemistry variables were measured with antibody- or enzymatic activity-based assays.

Results

Bacterial amino acid catabolites (cadaverine, N-acetylcadaverine, and α-hydroxyisovalerate) and end-products of bacterial alkali-producing pathways (N-α-acetylornithine and γ-aminobutyrate) increased significantly during the experimental gingivitis. Significant changes were found in a set of 13 salivary metabolite ratios composed of host cell membrane lipids involved in cell signaling, host responses to bacteria, and defense against free radicals. An increase in mevalonate was also observed. There were no significant effects of erythritol. No significant changes were found in functional salivary biochemistry.

Conclusions

The findings underline a dynamic interaction between the host and the oral microbial biofilm during an experimental induction of gingivitis.