Noninvasive urinary metabonomic diagnosis of human bladder cancer

Feline urine metabolomic signature: characterization of low-molecular-weight substances in urine from domestic cats

Objectives This aim of this study was to characterize the composition and content of the feline urine metabolome. Methods Eight healthy domestic cats were acclimated at least 10 days before starting the study. Urine samples (~2 ml) were collected by ultrasound-guided cystocentesis. Samples were centrifuged at 1000 × g for 8 mins, and the supernatant was analyzed by gas chromatography/time-of-flight mass spectrometery. The urine metabolome was characterized using an untargeted metabolomics approach. Results Three hundred and eighteen metabolites were detected in the urine of the eight cats. These molecules are key components of at least 100 metabolic pathways. Feline urine appears to be dominated by carbohydrates, carbohydrate conjugates, organic acid and derivatives, and amino acids and analogs. The five most abundant molecules were phenaceturic acid, hippuric acid, pseudouridine phosphate and 3-(4-hydroxyphenyl) propionic acid. Conclusions and relevance This study is the first to characterize the feline urine metabolome. The results of this study revealed the presence of multiple low-molecular-weight substances that were not known to be present in feline urine. As expected, the origin of the metabolites detected in urine was diverse, including endogenous compounds and molecules biosynthesized by microbes. Also, the diet seemed to have had a relevant role on the urine metabolome. Further exploration of the urine metabolic phenotype will open a window for discovering unknown, or poorly understood, metabolic pathways. In turn, this will advance our understanding of feline biology and lead to new insights in feline physiology, nutrition and medicine.

Plasma Metabolomics Analysis Based on GC-MS in Infertile Males with Kidney-Yang Deficiency Syndrome

Introduction

Chinese medicine syndrome diagnosis is the key requisite in the treatment of male infertility with traditional Chinese medicine (TCM). Kidney-Yang deficiency syndrome (KYDS) is the critical Chinese medicine syndrome of male infertility. To explore the modernized mechanisms of KYDS in male infertility, this study aims to investigate the metabolomics of males with KYDS.

Methods

The gas chromatography-mass spectrometry method was applied to analyze the plasma samples of 67 infertile males with KYDS compared with 55 age-matched healthy controls. The chemometric methods including principal component and partial least squares-discriminate analyses were employed to identify the potential biochemical patterns. With the help of the variable importance for the projection and receiver operating characteristic curve analyses, the potential biomarkers were extracted to define the clinical utility. Simultaneously the high-quality KEGG metabolic pathways database was used to identify the related metabolic pathways.

Results

The metabolomics profiles of infertile males with KYDS including 10 potential biomarkers and six metabolic pathways were identified. They precisely distinguished infertile males with KYDS from healthy controls.

Conclusions

These potential biomarkers and pathways suggest the substantial basis of infertile males with KYDS. The metabolomics profiles highlight the modernized mechanisms of infertile males with KYDS.

Unique and Novel Urinary Metabolomic Features in Malignant versus Benign Adrenal Neoplasms

Purpose: Adrenal incidentalomas must be differentiated from adrenocortical cancer (ACC). Currently, size, growth, and imaging characteristics determine the potential for malignancy but are imperfect. The aim was to evaluate whether urinary small molecules (<800 Da) are associated with ACC.Experimental Design: Preoperative fasting urine specimens from patients with ACC (n = 19) and benign adrenal tumors (n = 46) were analyzed by unbiased ultraperformance liquid chromatography/mass spectrometry. Creatinine-normalized features were analyzed by Progenesis, SIMCA, and unpaired t test adjusted by FDR. Features with an AUC >0.8 were identified through fragmentation patterns and database searches. All lead features were assessed in an independent set from patients with ACC (n = 11) and benign adrenal tumors (n = 46) and in a subset of tissue samples from patients with ACC (n = 15) and benign adrenal tumors (n = 15) in the training set.Results: Sixty-nine features were discovered and four known metabolites identified. Urinary creatine riboside was elevated 2.1-fold (P = 0.0001) in patients with ACC. L-tryptophan, Nε,Nε,Nε-trimethyl-L-lysine, and 3-methylhistidine were lower 0.33-fold (P < 0.0001), 0.56-fold (P < 0.0001), and 0.33-fold (P = 0.0003) in patients with ACC, respectively. Combined multivariate analysis of the four biomarkers showed an AUC of 0.89 [sensitivity 94.7% (confidence interval {CI}, 73.9%-99.1%), specificity 82.6% (CI, 68.6%-92.2%), PPV 69.2% (CI, 48.2%-85.6%), and NPV 97.4% (CI, 86.5%-99.6%)] for distinguishing ACC from benign tumors. Of the four, creatine riboside and four unknown features were validated. Creatine riboside, Nε,Nε,Nε-trimethyl-L-lysine, and two unknown features were elevated in ACC tumors.Conclusions: There are unique urinary metabolic features in patients with ACC with some metabolites present in patient tumor samples. Urinary creatine riboside can differentiate benign adrenal neoplasms from ACC. Clin Cancer Res; 23(17); 5302-10. ©2017 AACR.

Three serum metabolite signatures for diagnosing low-grade and high-grade bladder cancer

To address the shortcomings of cystoscopy and urine cytology for detecting and grading bladder cancer (BC), ultrahigh performance liquid chromatography (UHPLC) coupled with Q-TOF mass spectrometry in conjunction with univariate and multivariate statistical analyses was employed as an alternative method for the diagnosis of BC. A series of differential serum metabolites were further identified for low-grade(LG) and high-grade(HG) BC patients, suggesting metabolic dysfunction in malignant proliferation, immune escape, differentiation, apoptosis and invasion of cancer cells in BC patients. In total, three serum metabolites including inosine, acetyl-N-formyl-5-methoxykynurenamine and PS(O-18:0/0:0) were selected by binary logistic regression analysis, and receiver operating characteristic (ROC) test based on their combined use for HG BC showed that the area under the curve (AUC) was 0.961 in the discovery set and 0.950 in the validation set when compared to LG BC. Likewise, this composite biomarker panel can also differentiate LG BC from healthy controls with the AUC of 0.993 and 0.991 in the discovery and validation set, respectively. This finding suggested that this composite serum metabolite signature was a promising and less invasive classifier for probing and grading BC, which deserved to be further investigated in larger samples.

Mass spectrometric based approaches in urine metabolomics and biomarker discovery

Urine metabolomics has recently emerged as a prominent field for the discovery of non-invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non-biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid-liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4°C) and repetitive freeze-thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high-performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)-MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC-MS, other MS-based technologies have been utilized in urine metabolomics. These include direct injection (infusion)-MS, capillary electrophoresis-MS and gas chromatography-MS. In this article, the current progresses of different MS-based techniques in exploring the urine metabolome as well as the recent findings in providing potentially diagnostic urinary biomarkers are discussed. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:115-134, 2017.

Improving diagnostic molecular tests to monitor urothelial carcinoma recurrence

INTRODUCTION

The high recurrence rates associated with non-muscle invasive bladder cancer require close surveillance with cystoscopy, an invasive and expensive procedure with risk of missing cancer. Finding an accurate urinary biomarker that can detect recurrent disease would represent a significant advancement in management. Areas covered: This review summarizes the commercially-available urinary biomarkers including cytology, UroVysion, BTA, NMP22, uCyt+, and Cxbladder assays. Additionally, we review recent investigational urinary biomarkers that hold promise in bladder cancer surveillance. Expert commentary: The quest for a reliable urinary biomarker for bladder cancer is decades-old and seems intuitive given the direct contact of urine with malignant urothelium. Beyond urine cytology, there are many commercially-available products approved for surveillance. However, none of the assays are routinely used due to lack of sensitivity and/or specificity. As such, emerging technologies, in particular the '-omic' technologies have resulted in a proliferation of promising reports on novel biomarkers in recent literature.

Lowered circulating aspartate is a metabolic feature of human breast cancer

Distinct metabolic transformation is essential for cancer cells to sustain a high rate of proliferation and resist cell death signals. Such a metabolic transformation results in unique cellular metabolic phenotypes that are often reflected by distinct metabolite signatures in tumor tissues as well as circulating blood. Using a metabolomics platform, we find that breast cancer is associated with significantly (p = 6.27E-13) lowered plasma aspartate levels in a training group comprising 35 breast cancer patients and 35 controls. The result was validated with 103 plasma samples and 183 serum samples of two groups of primary breast cancer patients. Such a lowered aspartate level is specific to breast cancer as it has shown 0% sensitivity in serum from gastric (n = 114) and colorectal (n = 101) cancer patients. There was a significantly higher level of aspartate in breast cancer tissues (n = 20) than in adjacent non-tumor tissues, and in MCF-7 breast cancer cell line than in MCF-10A cell lines, suggesting that the depleted level of aspartate in blood of breast cancer patients is due to increased tumor aspartate utilization. Together, these findings suggest that lowed circulating aspartate is a key metabolic feature of human breast cancer.

Global Isotope Metabolomics Reveals Adaptive Strategies for Nitrogen Assimilation

Nitrogen cycling is a microbial metabolic process essential for global ecological/agricultural balance. To investigate the link between the well-established ammonium and the alternative nitrate assimilation metabolic pathways, global isotope metabolomics was employed to examine three nitrate reducing bacteria using (15)NO3 as a nitrogen source. In contrast to a control (Pseudomonas stutzeri RCH2), the results show that two of the isolates from Oak Ridge, Tennessee (Pseudomonas N2A2 and N2E2) utilize nitrate and ammonia for assimilation concurrently with differential labeling observed across multiple classes of metabolites including amino acids and nucleotides. The data reveal that the N2A2 and N2E2 strains conserve nitrogen-containing metabolites, indicating that the nitrate assimilation pathway is a conservation mechanism for the assimilation of nitrogen. Co-utilization of nitrate and ammonia is likely an adaption to manage higher levels of nitrite since the denitrification pathways utilized by the N2A2 and N2E2 strains from the Oak Ridge site are predisposed to the accumulation of the toxic nitrite. The use of global isotope metabolomics allowed for this adaptive strategy to be investigated, which would otherwise not have been possible to decipher.

Noninvasive metabolic profiling for painless diagnosis of human diseases and disorders

Metabolic profiling provides a powerful diagnostic tool complementary to genomics and proteomics. The pain, discomfort and probable iatrogenic injury associated with invasive or minimally invasive diagnostic methods, render them unsuitable in terms of patient compliance and participation. Metabolic profiling of biomatrices like urine, breath, saliva, sweat and feces, which can be collected in a painless manner, could be used for noninvasive diagnosis. This review article covers the noninvasive metabolic profiling studies that have exhibited diagnostic potential for diseases and disorders. Their potential applications are evident in different forms of cancer, metabolic disorders, infectious diseases, neurodegenerative disorders, rheumatic diseases and pulmonary diseases. Large scale clinical validation of such diagnostic methods is necessary in future.

Discovery of urine biomarkers for bladder cancer via global metabolomics

Bladder cancer (BC) is latent in its early stage and lethal in its late stage. Therefore, early diagnosis and intervention are essential for successful BC treatment. Considering the limitations of current diagnostic tools, noninvasive biomarkers that are both highly sensitive and specific are needed to improve the overall survival and quality of life of patients. With the advent of systems biology, "-omics" technologies have been developed over the past few decades. As a promising member, global metabolomics has increasingly been found to have clear potential for biomarker discovery. However, urinary metabolomics studies related to BC have lagged behind those of other urinary cancers, and major findings have not been systematically reported. The objective of this review is to comprehensively list the currently identified potential urinary metabolite biomarkers for BC.

Sensitive Electrochemical Immunosensor for Detection of Nuclear Matrix Protein-22 based on NH2-SAPO-34 Supported Pd/Co Nanoparticles

A novel sandwich-type electrochemical immunosensor using the new amino group functionalized silicoaluminophosphates molecular sieves (NH₂-SAPO-34) supported Pd/Co nanoparticles (NH₂-SAPO-34-Pd/Co NPs) as labels for the detection of bladder cancer biomarker nuclear matrix protein-22 (NMP-22) was developed in this work. The reduced graphene oxide-NH (rGO-NH) with good conductivity and large surface area was used to immobilize primary antibody (Ab₁). Due to the excellent catalytic activity toward hydrogen peroxide, NH₂-SAPO-34-Pd/Co NPs were used as labels and immobilized secondary antibody (Ab₂) through adsorption capacity of Pd/Co NPs to protein. The immunosensor displayed a wide linear range (0.001–20 ng/mL) and low detection limit (0.33 pg/mL). Good reproducibility and stability have showed satisfying results in the analysis of clinical urine samples. This novel and ultrasensitive immunosensor may have the potential application in the detection of different tumor markers.

Metabolic Profiling Regarding Pathogenesis of Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive, eventually fatal disease characterized by fibrosis of the lung parenchyma and loss of lung function. IPF is believed to be caused by repetitive alveolar epithelial cell injury and dysregulated repair process including uncontrolled proliferation of lung (myo) fibroblasts and excessive deposition of extracellular matrix proteins in the interstitial space; however, the pathogenic pathways involved in IPF have not been fully elucidated. In this study, we attempted to characterize metabolic changes of lung tissues involved in the pathogenesis of IPF using gas chromatography-mass spectrometry-based metabolic profiling. Partial least-squares discriminant analysis (PLS-DA) model generated from metabolite data was able to discriminate between the control subjects and IPF patients (R(2)X = 0.37, R(2)Y = 0.613 and Q(2) (cumulative) = 0.54, receiver operator characteristic AUC > 0.9). We discovered 25 metabolite signatures of IPF using both univariate and multivariate statistical analyses (FDR < 0.05 and VIP score of PLS-DA > 1). These metabolite signatures indicated alteration in metabolic pathways: adenosine triphosphate degradation pathway, glycolysis pathway, glutathione biosynthesis pathway, and ornithine aminotransferase pathway. The results could provide additional insight into understanding the disease and potential for developing biomarkers.

Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

Background

More accurate diagnostic methods are pressingly needed to diagnose breast cancer, the most common malignant cancer in women worldwide. Blood-based metabolomics is a promising diagnostic method for breast cancer. However, many metabolic biomarkers are difficult to replicate among studies.

Methods

We propose that higher-order functional representation of metabolomics data, such as pathway-based metabolomic features, can be used as robust biomarkers for breast cancer. Towards this, we have developed a new computational method that uses personalized pathway dysregulation scores for disease diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods.

Results

The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under the Curve, a receiver operating characteristic curve) of 0.968 and 0.934, sensitivities of 0.946 and 0.954, and specificities of 0.934 and 0.918. These two metabolomics-based pathway models are further validated by RNA-Seq-based TCGA (The Cancer Genome Atlas) breast cancer data, with AUCs of 0.995 and 0.993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer.

Conclusions

We have successfully developed a new type of pathway-based model to study metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease diagnosis.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0289-9) contains supplementary material, which is available to authorized users.

Metabolomics reveals positive acceleration(+Gz)-induced metabolic perturbations and the protective effect of Ginkgo biloba extract in a rat model based on ultra high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry

Positive acceleration (+Gz) in the head-to-foot direction generated by modern high-performance fighter jets during flight maneuvers is characterized by high G values and a rapid rate of acceleration, and is often long in duration and a repeated occurrence. The acceleration overload far exceeds the pilot's physiological tolerance limits and causes considerable strain on several organ systems. Despite the importance of monitoring pathophysiological alterations related to +Gz exposure, we lack a complete explanation of the pathophysiology of +Gz exposure. Ginkgo biloba extract (GBE) is a classic traditional Chinese medicine (TCM) that might exert a protective effect against +Gz exposure. However, its mechanism remains unclear. Here, a metabolomics approach based on ultra high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOFMS) was used to characterize +Gz-induced metabolic fluctuations in a rat model and to evaluate the protective effect of GBE. Using partial least-squares discriminant analysis for the classification and selection of biomarkers, eighteen serum metabolites related to +Gz exposure were identified, and were found to primarily involve the fatty acid β-oxidation pathway, glycerophospholipid metabolism, phospholipid metabolism, bile acid metabolism, purine metabolism and lysine metabolism. Taking these potential biomarkers as screening indexes, we found that GBE could reverse the pathological process of +Gz exposure by partially regulating the perturbed fatty acid β-oxidation pathway, glycerophospholipid metabolism, purine metabolism and lysine metabolism. This indicates that UHPLC-Q-TOFMS-based metabolomics provides a powerful tool to reveal serum metabolic fluctuations in response to +Gz exposure and to study the mechanism underlying TCM.

Biomarkers in bladder cancer: A metabolomic approach using in vitro and ex vivo model systems

Metabolomics has recently proved to be useful in the area of biomarker discovery for cancers in which early diagnostic and prognostic biomarkers are urgently needed, as is the case of bladder cancer (BC). This article presents a comprehensive review of the literature on the metabolomic studies on BC, highlighting metabolic pathways perturbed in this disease and the altered metabolites as potential biomarkers for BC detection. Current disease model systems used in the study of BC metabolome include in vitro-cultured cancer cells, ex vivo neoplastic bladder tissues and biological fluids, mainly urine but also blood serum/plasma, from BC patients. The major advantages and drawbacks of each model system are discussed. Based on available data, it seems that BC metabolic signature is mainly characterized by alterations in metabolites related to energy metabolic pathways, particularly glycolysis, amino acid and fatty acid metabolism, known to be crucial for cell proliferation, as well as glutathione metabolism, known to be determinant in maintaining cellular redox balance. In addition, purine and pyrimidine metabolism as well as carnitine species were found to be altered in BC. Finally, it is emphasized that, despite the progress made in respect to novel biomarkers for BC diagnosis, there are still some challenges and limitations that should be addressed in future metabolomic studies to ensure their translatability to clinical practice.

Three plasma metabolite signatures for diagnosing high altitude pulmonary edema

High-altitude pulmonary edema (HAPE) is a potentially fatal condition, occurring at altitudes greater than 3,000 m and affecting rapidly ascending, non-acclimatized healthy individuals. However, the lack of biomarkers for this disease still constitutes a bottleneck in the clinical diagnosis. Here, ultra-high performance liquid chromatography coupled with Q-TOF mass spectrometry was applied to study plasma metabolite profiling from 57 HAPE and 57 control subjects. 14 differential plasma metabolites responsible for the discrimination between the two groups from discovery set (35 HAPE subjects and 35 healthy controls) were identified. Furthermore, 3 of the 14 metabolites (C8-ceramide, sphingosine and glutamine) were selected as candidate diagnostic biomarkers for HAPE using metabolic pathway impact analysis. The feasibility of using the combination of these three biomarkers for HAPE was evaluated, where the area under the receiver operating characteristic curve (AUC) was 0.981 and 0.942 in the discovery set and the validation set (22 HAPE subjects and 22 healthy controls), respectively. Taken together, these results suggested that this composite plasma metabolite signature may be used in HAPE diagnosis, especially after further investigation and verification with larger samples.

Developing urinary metabolomic signatures as early bladder cancer diagnostic markers

Early detection is vital to improve the overall survival rate of bladder cancer (BCa) patients, yet there is a lack of a reliable urine-based assay for early detection of BCa. Urine metabolites represented a potential rich source of biomarkers for BCa. This study aimed to develop a metabolomics approach for high coverage discovery and identification of metabolites in urine samples. Urine samples from 23 early stage BCa patients and 21 healthy volunteers with minimum sample preparations were analyzed by a short 30 min UPLC-HRMS method. We detected and quantified over 9000 unique UPLC-HRMS features, which is more than four times than about 2000 features detected in previous urine metabolomic studies. Furthermore, multivariate OPLS-DA classification models were established to differentiate urine samples from bladder cancer cohort and normal health cohort. We identified three BCa-upregulated metabolites: nicotinuric acid, trehalose, AspAspGlyTrp, and three BCa-downregulated metabolites: inosinic acid, ureidosuccinic acid, GlyCysAlaLys. Finally, analysis of six post-surgery BCa urine samples showed that these BCa-metabolomic features reverted to normal state after tumor removal, suggesting that they reflected metabolomic features associated with BCa. ROC analyses using two linear regression models to combine the identified markers showed a high diagnostic performance for detecting BCa with AUC (area under the ROC curve) values of 0.919 to 0.934. In summary, we developed a high coverage metabolomic approach that has potential for biomarker discovery in cancers.

Use of Aleuria alantia Lectin Affinity Chromatography to Enrich Candidate Biomarkers from the Urine of Patients with Bladder Cancer

Developing a urine test to detect bladder tumours with high sensitivity and specificity is a key goal in bladder cancer research. We hypothesised that bladder cancer-specific glycoproteins might fulfill this role. Lectin-ELISAs were used to study the binding of 25 lectins to 10 bladder cell lines and serum and urine from bladder cancer patients and non-cancer controls. Selected lectins were then used to enrich glycoproteins from the urine of bladder cancer patients and control subjects for analysis by shotgun proteomics. None of the lectins showed a strong preference for bladder cancer cell lines over normal urothlelial cell lines or for urinary glycans from bladder cancer patients over those from non-cancer controls. However, several lectins showed a strong preference for bladder cell line glycans over serum glycans and are potentially useful for enriching glycoproteins originating from the urothelium in urine. Aleuria alantia lectin affinity chromatography and shotgun proteomics identified mucin-1 and golgi apparatus protein 1 as proteins warranting further investigation as urinary biomarkers for low-grade bladder cancer. Glycosylation changes in bladder cancer are not reliably detected by measuring lectin binding to unfractionated proteomes, but it is possible that more specific reagents and/or a focus on individual proteins may produce clinically useful biomarkers.

Investigation of Host-Gut Microbiota Modulation of Therapeutic Outcome

A broader understanding of factors underlying interindividual variation in pharmacotherapy is important for our pursuit of "personalized medicine." Based on knowledge gleaned from the investigation of human genetics, drug-metabolizing enzymes, and transporters, clinicians and pharmacists are able to tailor pharmacotherapies according to the genotype of patients. However, human host factors only form part of the equation that accounts for heterogeneity in therapeutic outcome. Notably, the gut microbiota possesses wide-ranging metabolic activities that expand the metabolic functions of the human host beyond that encoded by the human genome. In this review, we first illustrate the mechanisms in which gut microbes modulate pharmacokinetics and therapeutic outcome. Second, we discuss the application of metabonomics in deciphering the complex host-gut microbiota interaction in pharmacotherapy. Third, we highlight an integrative approach with particular mention of the investigation of gut microbiota using culture-based and culture-independent techniques to complement the investigation of the host-gut microbiota axes in pharmaceutical research.

The possibility of inventing new technologies in the detection of cancer by applying elements of the canine olfactory apparatus

In order to find better tools in the diagnosis of cancer in an earlier and more precise manner, researchers have explored the use of volatile organic compound (VOCs) as a way to detect this disease. Interestingly, the canine olfactory apparatus was observed to detect cancer in two anecdotal reports. After the description of these events, researchers began to study this phenomenon in a structured way in order to assess the ability of canines in detecting cancer-related VOCs. Due to the fact that some of these studies have shown that the canine olfactory apparatus is highly proficient in the detection of cancer-related VOCs, in this article we assess the possibility of constructing a bioelectronic-nose, based on canine olfactory receptors (ORs), for the purpose of diagnosing cancer in a more sensitive, specific, and cost effective manner than what is available nowadays. Furthermore, in order to prove the feasibility and the need of the proposed apparatus, we searched for the following type of articles: all of the studies that have examined, to our knowledge, the ability of dogs in detecting cancer; articles that assess the dog olfactory receptor (OR) gene repertoire, since a central part of the proposed bioelectronic nose is being able to recognize the odorant that emanates from the cancerous lesion, and for that purpose is necessary to express the canine ORs in heterologous cells; examples of articles that depict different devices that have been built for the purpose of detecting cancer-related VOCs, so as to assess if the construction of the proposed apparatus is needed; and articles that describe examples of already constructed bioelectronic noses, in order to demonstrate the existence of a technical precedent and thus the plausibility of the proposed device.

Diagnosis of bladder cancer and prediction of survival by urinary metabolomics

Bladder cancer (BC) is a common cancer but diagnostic modalities, such as cystoscopy and urinary cytology, have limitations. Here, high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (HPLC-QTOFMS) was used to profile urine metabolites of 138 patients with BC and 121 control subjects (69 healthy people and 52 patients with hematuria due to non-malignant diseases). Multivariate statistical analysis revealed that the cancer group could be clearly distinguished from the control groups on the basis of their metabolomic profiles, even when the hematuric control group was included. Patients with muscle-invasive BC could also be distinguished from patients with non-muscle-invasive BC on the basis of their metabolomic profiles. Successive analyses identified 12 differential metabolites that contributed to the distinction between the BC and control groups, and many of them turned out to be involved in glycolysis and betaoxidation. The association of these metabolites with cancer was corroborated by microarray results showing that carnitine transferase and pyruvate dehydrogenase complex expressions are significantly altered in cancer groups. In terms of clinical applicability, the differentiation model diagnosed BC with a sensitivity and specificity of 91.3% and 92.5%, respectively, and comparable results were obtained by receiver operating characteristic analysis (AUC = 0.937). Multivariate regression also suggested that the metabolomic profile correlates with cancer-specific survival time. The excellent performance and simplicity of this metabolomics-based approach suggests that it has the potential to augment or even replace the current modalities for BC diagnosis.

A novel method for the analysis of clinical biomarkers to investigate the effect of diet on health in a rat model

We demonstrate differentiation between two diets fed to rats across timeviainstrumentation combined with multivariate data analysis.

Analysis of urinary metabolomic profiling for unstable angina pectoris disease based on nuclear magnetic resonance spectroscopy

The NMR-based metabolomics approach showed good performance in identifying diagnostic urinary biomarkers, providing new insights into the metabolic process related to UAP.

Bladder cancer biomarker discovery using global metabolomic profiling of urine

Bladder cancer (BCa) is a common malignancy worldwide and has a high probability of recurrence after initial diagnosis and treatment. As a result, recurrent surveillance, primarily involving repeated cystoscopies, is a critical component of post diagnosis patient management. Since cystoscopy is invasive, expensive and a possible deterrent to patient compliance with regular follow-up screening, new non-invasive technologies to aid in the detection of recurrent and/or primary bladder cancer are strongly needed. In this study, mass spectrometry based metabolomics was employed to identify biochemical signatures in human urine that differentiate bladder cancer from non-cancer controls. Over 1000 distinct compounds were measured including 587 named compounds of known chemical identity. Initial biomarker identification was conducted using a 332 subject sample set of retrospective urine samples (cohort 1), which included 66 BCa positive samples. A set of 25 candidate biomarkers was selected based on statistical significance, fold difference and metabolic pathway coverage. The 25 candidate biomarkers were tested against an independent urine sample set (cohort 2) using random forest analysis, with palmitoyl sphingomyelin, lactate, adenosine and succinate providing the strongest predictive power for differentiating cohort 2 cancer from non-cancer urines. Cohort 2 metabolite profiling revealed additional metabolites, including arachidonate, that were higher in cohort 2 cancer vs. non-cancer controls, but were below quantitation limits in the cohort 1 profiling. Metabolites related to lipid metabolism may be especially interesting biomarkers. The results suggest that urine metabolites may provide a much needed non-invasive adjunct diagnostic to cystoscopy for detection of bladder cancer and recurrent disease management.

Metabonomic profiling of bladder cancer

Early diagnosis and life-long surveillance are clinically important to improve the long-term survival of bladder cancer patients. Currently, a noninvasive biomarker that is as sensitive and specific as cystoscopy in detecting bladder tumors is lacking. Metabonomics is a complementary approach for identifying perturbed metabolic pathways in bladder cancer. Significant progress has been made using modern metabonomic techniques to characterize and distinguish bladder cancer patients from control subjects, identify marker metabolites, and shed insights on the disease biology and potential therapeutic targets. With its rapid development, metabonomics has the potential to impact the clinical management of bladder cancer patients in the future by revolutionizing the diagnosis and life-long surveillance strategies and stratifying patients for diagnostic, surgical, and therapeutic clinical trials. An introduction to metabonomics, typical metabonomic workflow, and critical evaluation of metabonomic investigations in identifying biomarkers for the diagnosis of bladder cancer are presented.

Novel methodologies in analysis of small molecule biomarkers and living cells

Enzyme-linked immuno-sorbent assay (ELISA) is widely used for biomarker detection. A good biomarker can distinguish patients from healthy or benign diseases. However, the ELISA method is not suitable for small molecule or trace substance detection. Along with the development of new technologies, an increasing level of biomaterials, especially small molecules, will be identified as novel biomarkers. Quantitative immuno-PCR, chromatography-mass spectrometry, and nucleic acid aptamer are emerging methodologies for detection of small molecule biomarkers, even in living cells. In this review, we focus on these novel technologies and their potential for small molecule biomarkers and living cell analysis.

Noninvasive diagnosis and evaluation of curative surgery for gastric cancer by using NMR-based metabolomic profiling

BACKGROUND

Mass screening for gastric cancer (GC), particularly using endoscopy, may not be the most practical approach as a result of its high cost, lack of acceptance, and poor availability. Thus, novel markers that can be used in cost-effective diagnosis and noninvasive screening for GC are needed.

METHODS

A total of 154 urine samples from GC patients and healthy individuals and 30 pairs of matched tumor and normal stomach tissues were collected. Multivariate analysis was performed on urinary and tissue metabolic profiles acquired using (1)H nuclear magnetic resonance and (1)H high-resolution magic angle spinning spectroscopy, respectively. In addition, metabolic profiling of urine from GC patients after curative surgery was performed.

RESULTS

Multivariate statistical analysis showed significant separation in the urinary and tissue data of GC patients and healthy individuals. The metabolites altered in the urine of GC patients were related to amino acid and lipid metabolism, consistent with changes in GC tissue. In the external validation, the presence of GC (early or advanced) from the urine model was predicted with high accuracy, which showed much higher sensitivity than carbohydrate antigen 19-9 and carcinoembryonic antigen. Furthermore, 4-hydroxyphenylacetate, alanine, phenylacetylglycine, mannitol, glycolate, and arginine levels were significantly correlated with cancer T stage and, together with hypoxanthine level, showed a recovery tendency toward healthy controls in the postoperative samples compared to the preoperative samples.

CONCLUSIONS

An urinary metabolomics approach may be useful for the effective diagnosis of GC.

Non-invasive fecal metabonomic detection of colorectal cancer

Colorectal cancer (CRC) is a major cause of mortality in many developed countries. Effective screening strategies were called for to facilitate timely detection and to promote a better clinical outcome. In this study, the role of fecal metabonomics in the non-invasive detection of CRC was investigated. Gas chromatography/time-of-flight mass spectrometry (GC/TOFMS) was utilized for the metabolic profiling of feces obtained from 11 CRC patients and 10 healthy subjects. Concurrently, matched tumor and normal mucosae surgically excised from CRC patients were profiled. CRC patients were differentiated clearly from healthy subjects based on their fecal metabonomic profiles (orthogonal partial least squares discriminant analysis [OPLS-DA], 1 predictive and 3 Y-orthogonal components, R (2)X = 0.373, R (2)Y = 0.995, Q (2) [cumulative] = 0.215). The robustness of the OPLS-DA model was demonstrated by an area of 1 under the receiver operator characteristic curve. OPLS-DA revealed fecal marker metabolites (e.g., fructose, linoleic acid, and nicotinic acid) that provided novel insights into the tumorigenesis of CRC. Interestingly, a disparate set of CRC-related metabolic aberrations occurred at the tissue level, implying the contribution of processes beyond the direct shedding of tumor cells to the fecal metabotype. In summary, this work established proof-of-principle for GC/TOFMS-based fecal metabonomic detection of CRC and offered new perspectives on the underlying mechanisms.

Integrated technologies in the post-genomic era for discovery of bladder cancer urinary markers

The incidence of bladder cancer (BC) continues to rise with high recurrence and mortality rate, especially in the past three decades. The development of accurate and successful BC treatment relies mainly on early diagnosis. BC is a heterogeneous disease reflected by the presence of many potential biomarkers associated with different disease phenotypes. Nowadays, cystoscopy and urinary cytology are considered the gold standard diagnostic tools for BC. There are many limitations to cystoscopy including being invasive, labor-intensive and carcinoma in situ of the bladder may easily be missed. Urinary cytology is still a noninvasive technique with high accuracy in high-grade BC with a median sensitivity of 35%. Furthermore, the need for a sensitive, specific, non invasive, easily accessible BC biomarker is a major clinical need. The field of urinary BC biomarkers discovery is still a rapidly evolving discipline in which more recent technologies are evaluated and often optimized if they are not clinically significant to the urologists. Most of the current strategies for BC urinary biomarker detection depend on integration of information gleaned from the fields of genomics, transcriptomics, proteomics, epigenetics, metabolomics and bionanotechnology. Effort is currently being made to identify the most potentially beneficial urinary biomarkers. The purpose of this review is to summarize and explore the efficacy of gathering the information revealed from the cooperation of different omic strategies that paves the way towards various urinary markers discovery for screening, diagnosis and prognosis of human BC.

Low- and high-grade bladder cancer determination via human serum-based metabolomics approach

To address the shortcomings of urine cytology and cystoscopy for probing and grading urinary bladder cancer (BC), we applied (1)H nuclear magnetic resonance (NMR) spectroscopy as a surrogate method for the identification of BC. This study includes 99 serum samples comprising low-grade (LG; n = 36) and high-grade (HG; n = 31) BC as well as healthy controls (HC; n = 32). (1)H NMR-derived serum data were analyzed using orthogonal partial least-squares discriminant analysis (OPLS-DA). OPLS-DA-derived model validity was confirmed using an internal and external cross-validation. Internal validation was performed using the initial samples (n = 99) data set. External validation was performed on a new batch of suspected BC patients (n = 106) through a double-blind study. Receiver operating characteristic (ROC) curve analysis was also performed. OPLS-DA-derived serum metabolomics (six biomarkers, ROC; 0.99) were able to discriminate 95% of BC cases with 96% sensitivity and 94% specificity when compared to HC. Likewise (three biomarkers, ROC; 0.99), 98% of cases of LG were able to differentiate from HG with 97% sensitivity and 99% specificity. External validation reveals comparable results to the internal validation. (1)H NMR-based serum metabolic screening appears to be a promising and less invasive approach for probing and grading BC in contrast to the highly invasive and painful cystoscopic approach for BC detection.

Distinct metabolic profile of primary focal segmental glomerulosclerosis revealed by NMR-based metabolomics

Background

Primary focal segmental glomerulosclerosis (FSGS) is pathological entity which is characterized by idiopathic steroid-resistant nephrotic syndrome (SRNS) and progression to end-stage renal disease (ESRD) in the majority of affected individuals. Currently, there is no practical noninvasive technique to predict different pathological types of glomerulopathies. In this study, the role of urinary metabolomics in the diagnosis and pathogenesis of FSGS was investigated.

Methods

NMR-based metabolomics was applied for the urinary metabolic profile in the patients with FSGS (n = 25), membranous nephropathy (MN, n = 24), minimal change disease (MCD, n = 14) and IgA nephropathy (IgAN, n = 26), and healthy controls (CON, n = 35). The acquired data were analyzed using principal component analysis (PCA) followed by orthogonal projections to latent structure discriminant analysis (OPLS-DA). Model validity was verified using permutation tests.

Results

FSGS patients were clearly distinguished from healthy controls and other three types of glomerulopathies with good sensitivity and specificity based on their global urinary metabolic profiles. In FSGS patients, urinary levels of glucose, dimethylamine and trimethylamine increased compared with healthy controls, while pyruvate, valine, hippurate, isoleucine, phenylacetylglycine, citrate, tyrosine, 3-methylhistidine and β-hydroxyisovalerate decreased. Additionally, FSGS patients had lower urine N-methylnicotinamide levels compared with other glomerulopathies.

Conclusions

NMR-based metabonomic approach is amenable for the noninvasive diagnosis and differential diagnosis of FSGS as well as other glomerulopathies, and it could indicate the possible mechanisms of primary FSGS.

Blood volatile compounds as biomarkers for colorectal cancer

Many recent studies have focused on the connection between the composition of specific volatile organic compounds (VOCs) in exhaled breath and various forms of cancer. However, the composition of exhaled breath is affected by many factors, such as lung disease, smoking, and diet. VOCs are released into the bloodstream before they are exhaled; therefore, the analysis of VOCs in blood will provide more accurate results than the analysis of VOCs in exhaled breath. Blood were collected from 16 colorectal cancer patients and 20 healthy controls, then solid phase microextraction-chromatography-mass spectrometry (SPME-GC-MS) was used to analysis the exhaled volatile organic compounds (VOCs). The statistical methods principal component analysis (PCA) and partial least-squares discriminant analysis (PLSDA) were performed to deal with the final dates. Three metabolic biomarkers were found at significantly lower levels in the group of CRC patients than in the normal control group (P<0.01): phenyl methylcarbamate, ethylhexanol, and 6-t-butyl-2,2,9,9-tetramethyl-3,5-decadien-7-yne. In addition, significantly higher levels of 1,1,4,4-tetramethyl-2,5-dimethylene-cyclohexane were found in the group of CRC patients than in the normal control group (P<0.05). Compared with healthy individuals, patients with colorectal adenocarcinoma exhibited a distinct blood metabolic profile with respect to VOCs. The analysis of blood VOCs appears to have potential clinical applications for CRC screening.

Review of mass spectrometry-based metabolomics in cancer research

Metabolomics, the systematic investigation of all metabolites present within a biologic system, is used in biomarker development for many human diseases, including cancer. In this review, we investigate the current role of mass spectrometry-based metabolomics in cancer research. A literature review was carried out within the databases PubMed, Embase, and Web of Knowledge. We included 106 studies reporting on 21 different types of cancer in 7 different sample types. Metabolomics in cancer research is most often used for case-control comparisons. Secondary applications include translational areas, such as patient prognosis, therapy control and tumor classification, or grading. Metabolomics is at a developmental stage with respect to epidemiology, with the majority of studies including less than 100 patients. Standardization is required especially concerning sample preparation and data analysis. In the second part of this review, we reconstructed a metabolic network of patients with cancer by quantitatively extracting all reports of altered metabolites: Alterations in energy metabolism, membrane, and fatty acid synthesis emerged, with tryptophan levels changed most frequently in various cancers. Metabolomics has the potential to evolve into a standard tool for future applications in epidemiology and translational cancer research, but further, large-scale studies including prospective validation are needed.

Urinary biomarkers of bladder cancer: an update and future perspectives

Bladder cancer is one of the most prevalent cancers worldwide. Early detection of bladder tumors is critical for improved patient outcomes. The standard method for detection and surveillance of bladder tumors is cystoscopy with urinary cytology. Limitations of cystoscopy and urinary cytology have brought to light the need for more robust diagnostic assays. Ideally, such assays would be applicable to noninvasively obtained, voided urine, and be designed not only for diagnosis, but also for monitoring disease recurrence and response to therapy. Consequently, the development of a noninvasive urine-based assay would be of tremendous benefit to both patients and healthcare systems. This article reports some of the more prominent urine-based biomarkers reported in the literature. In addition, some new technologies that have been used to identify novel urinary biomarkers are highlighted.

Bladder cancer detection and monitoring: assessment of urine- and blood-based marker tests

Bladder cancer is one of the most prevalent cancers worldwide, but the treatment and management of this disease can be very successful if the disease is detected early. The development of molecular assays that could diagnose bladder cancer accurately, and at an early stage, would be a significant advance. Ideally, such molecular assays would be applicable to non-invasively obtained body fluids, and be designed not only for diagnosis but also for monitoring disease recurrence and response to treatment. In this article, we assess the performance of current diagnostic assays for bladder cancer and discuss some of the emerging biomarkers that could be developed to augment current bladder cancer detection strategies.