Metabolomics by proton nuclear magnetic resonance spectroscopy of the response to chloroethylnitrosourea reveals drug efficacy and tumor adaptive metabolic pathways

Genetic correlation between circulating metabolites and chalazion: a two-sample Mendelian randomization study

Background: Lipid metabolism disorders were observationally associated with chalazion, but the causality of the related circulating metabolites on chalazion remained unknown. Here, we investigated the potential causal relationship between circulating metabolites and chalazion using two-sample Mendelian randomization (MR) analysis. Methods: For the primary analysis, 249 metabolic biomarkers were obtained from the UK Biobank, and 123 circulating metabolites were obtained from the publication by Kuttunen et al. for the secondary analysis. Chalazion summary data were obtained from the FinnGen database. Inverse variance weighted (IVW) is the main MR analysis method, and the MR assumptions were evaluated in sensitivity and colocalization analyses. Results: Two MR analyses results showed that the common metabolite, alanine, exhibited a genetic protective effect against chalazion (primary analysis: odds ratio [OR] = 0.680; 95% confidence interval [CI], 0.507-0.912; p = 0.010; secondary analysis: OR = 0.578; 95% CI, 0.439-0.759; p = 0.00008). The robustness of the findings was supported by heterogeneity and horizontal pleiotropy analysis. Two colocalization analyses showed that alanine did not share a region of genetic variation with chalazion (primary analysis: PPH4 = 1.95%; secondary analysis: PPH4 = 25.3%). Moreover, previous studies have suggested that an increase in the degree of unsaturation is associated with an elevated risk of chalazion (OR = 1.216; 95% CI, 1.055-1.401; p = 0.007), with omega-3 fatty acids (OR = 1.204; 95% CI, 1.054-1.377; p = 0.006) appearing to be the major contributing factor, as opposed to omega-6 fatty acids (OR = 0.850; 95% CI, 0.735-0.982; p = 0.027). Conclusion: This study suggests that alanine and several unsaturated fatty acids are candidate molecules for mechanistic exploration and drug target selection in chalazion.

Metabolomics Analysis as a Tool to Measure Cobalt Neurotoxicity: An In Vitro Validation

In this study, cobalt neurotoxicity was investigated in human astrocytoma and neuroblastoma (SH-SY5Y) cells using proliferation assays coupled with LC-MS-based metabolomics and transcriptomics techniques. Cells were treated with a range of cobalt concentrations between 0 and 200 µM. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay revealed cobalt cytotoxicity and decreased cell metabolism in a dose and time-dependent manner was observed by metabolomics analysis, in both cell lines. Metabolomic analysis also revealed several altered metabolites particularly those related to DNA deamination and methylation pathways. One of the increased metabolites was uracil which can be generated from DNA deamination or fragmentation of RNA. To investigate the origin of uracil, genomic DNA was isolated and analyzed by LC-MS. Interestingly, the source of uracil, which is uridine, increased significantly in the DNA of both cell lines. Additionally, the results of the qRT-PCR showed an increase in the expression of five genes Mlh1, Sirt2, MeCP2, UNG, and TDG in both cell lines. These genes are related to DNA strand breakage, hypoxia, methylation, and base excision repair. Overall, metabolomic analysis helped reveal the changes induced by cobalt in human neuronal-derived cell lines. These findings could unravel the effect of cobalt on the human brain.

Bayesian kinetic modeling for tracer-based metabolomic data

BACKGROUND

Stable Isotope Resolved Metabolomics (SIRM) is a new biological approach that uses stable isotope tracers such as uniformly [Formula: see text]-enriched glucose ([Formula: see text]-Glc) to trace metabolic pathways or networks at the atomic level in complex biological systems. Non-steady-state kinetic modeling based on SIRM data uses sets of simultaneous ordinary differential equations (ODEs) to quantitatively characterize the dynamic behavior of metabolic networks. It has been increasingly used to understand the regulation of normal metabolism and dysregulation in the development of diseases. However, fitting a kinetic model is challenging because there are usually multiple sets of parameter values that fit the data equally well, especially for large-scale kinetic models. In addition, there is a lack of statistically rigorous methods to compare kinetic model parameters between different experimental groups.

RESULTS

We propose a new Bayesian statistical framework to enhance parameter estimation and hypothesis testing for non-steady-state kinetic modeling of SIRM data. For estimating kinetic model parameters, we leverage the prior distribution not only to allow incorporation of experts' knowledge but also to provide robust parameter estimation. We also introduce a shrinkage approach for borrowing information across the ensemble of metabolites to stably estimate the variance of an individual isotopomer. In addition, we use a component-wise adaptive Metropolis algorithm with delayed rejection to perform efficient Monte Carlo sampling of the posterior distribution over high-dimensional parameter space. For comparing kinetic model parameters between experimental groups, we propose a new reparameterization method that converts the complex hypothesis testing problem into a more tractable parameter estimation problem. We also propose an inference procedure based on credible interval and credible value. Our method is freely available for academic use at https://github.com/xuzhang0131/MCMCFlux .

CONCLUSIONS

Our new Bayesian framework provides robust estimation of kinetic model parameters and enables rigorous comparison of model parameters between experimental groups. Simulation studies and application to a lung cancer study demonstrate that our framework performs well for non-steady-state kinetic modeling of SIRM data.

BRCA1 overexpression attenuates breast cancer cell growth and migration by regulating the pyruvate kinase M2-mediated Warburg effect via the PI3K/AKT signaling pathway

This work explored the mechanism of the effect of breast-cancer susceptibility gene 1 (BRCA1) on the metabolic characteristics of breast cancer cells, including the Warburg effect and its specific signaling. We transfected MCF-7 cells with a BRCA1-encoding LXSN plasmid or PKM2 siRNA and examined cancer cell metabolism using annexin V staining, inhibitory concentration determination, Western blotting, glucose uptake and lactic acid content measurements, and Transwell assays to assess glycolytic activity, cell apoptosis, and migration, and sensitivity to anti-cancer treatment. The BRCA1-expressing MCF-7 cells demonstrated low PKM2 expression and decreased glycolytic activity (downregulated hexokinase 2 (HK2) expression, upregulated isocitrate dehydrogenase 1 (IDH1) expression, and reduced O₂ and glucose consumption and lactate production) via regulation of PI3K/AKT pathway compared with the empty LXSN group. BRCA1 transfection slightly increased apoptotic activity, decreased cell migration, and increased the IC₅₀ index for doxorubicin, paclitaxel, and cisplatin. Inhibiting PKM2 using siRNA attenuated the IC₅₀ index for doxorubicin, paclitaxel, and cisplatin compared with the control. Inhibiting PKM2 activated PI3K/AKT signaling, increased apoptosis, and decreased MCF-7 cell migration. Our data suggest that BRCA1 overexpression reverses the Warburg effect, inhibits cancer cell growth and migration, and enhances the sensitivity to anti-cancer treatment by decreasing PKM2 expression regulated by PI3K/AKT signaling. These novel metabolic findings represent a potential mechanism by which BRCA1 exerts its inhibitory effect on breast cancer.

Early detection of treatment futility in patients with metastatic colorectal cancer

PURPOSE

Chemotherapy options for treating CRC have rapidly expanded in recent years, and few have predictive biomarkers. Oncologists are challenged with evidence-based selection of treatments, and response is evaluated retrospectively based on serial imaging beginning after 2-3 months. As a result, cumulative toxicities may appear in patients who will not benefit. Early recognition of non-benefit would reduce cumulative toxicities. Our objective was to determine treatment-related changes in the circulating metabolome corresponding to treatment futility.

METHODS

Metabolomic studies were performed on serial plasma samples from patients with CRC in a randomized controlled trial of cetuximab vs. cetuximab + brivanib (N = 188). GC-MS quantified named 94 metabolites and concentrations were evaluated at baseline, Weeks 1, 4 and 12 after treatment initiation. In a discovery cohort (N = 68), a model distinguishing changes in metabolites associated with radiographic disease progression and response was generated using OPLS-DA. A cohort of 120 patients was used for validation of the model.

RESULTS

By one week after treatment, a stable model of 21 metabolites could distinguish between progression and partial response (R2Y = 0.859; Q2Y = 0.605; P = 5e-4). In the validation cohort, patients with the biomarker had a significantly shorter OS (P < 0.0001). In a separate cohort of patients with HCC on axitinib, appearance of the biomarker also signified a shorter PFS (1.7 months vs. 9.2 months, P = 0.001).

CONCLUSION

We have identified changes in the metabolome that appear within 1 week of starting treatment associated with treatment futility. The novel approach described is applicable to future efforts in developing a biomarker for early assessment of treatment efficacy.

One extraction tool for in vitro-in vivo extrapolation? SPME-based metabolomics of in vitro 2D, 3D, and in vivo mouse melanoma models

Solid phase microextraction (SPME) in combination with high-resolution mass spectrometry was employed for the determination of metabolomic profile of mouse melanoma growth within in vitro 2D, in vitro 3D, and in vivo models. Such multi-model approach had never been investigated before. Due to the low-invasiveness of SPME, it was possible to perform time-course analysis, which allowed building time profile of biochemical reactions in the studied material. Such approach does not require the multiplication of samples as subsequent analyses are performed from the very same cell culture or from the same individual. SPME already reduces the number of animals required for experiment; therefore, it is with good concordance with the 3Rs rule (replacement, reduction, and refinement). Among tested models, the largest number of compounds was found within the in vitro 2D cell culture model, while in vivo and in vitro 3D models had the lowest number of detected compounds. These results may be connected with a higher metabolic rate, as well as lower integrity of the in vitro 2D model compared to the in vitro 3D model resulting in a lower number of compounds released into medium in the latter model. In terms of in vitro-in vivo extrapolation, the in vitro 2D model performed more similar to in vivo model compared to in vitro 3D model; however, it might have been due to the fact that only compounds secreted to medium were investigated. Thus, in further experiments to obtain full metabolome information, the intraspheroidal assessment or spheroid dissociation would be necessary.

Canine metabolomics advances

INTRODUCTION

Canis lupus familiaris is a domestic dog and many owners consider their pets as a family member. Medical bills with dogs are overcame only by the health care received by humans. Medical care is constantly progressing, and so is veterinary care. Metabolomics is the ''omic" technique aimed to the study of metabolome, low-molecular weight molecules, through biofluids or tissue samples. And it also allows to evaluate disease diagnosis and prognosis, therapeutic evaluation and toxicological studies.

OBJECTIVES

The goal of this paper is to review the current and potential applications of metabolomics in domestic dogs.

METHOD

ScienceDirect, Scopus, Reaxys and PubMed were searched for papers that performed canine metabolomics in any research area.

RESULTS

We analysed 38 papers, published until April 2019 in canine metabolomics approach. Metabolomic research in dogs so far can be divided into three areas: (a) Metabolomics studies in veterinary science, such as improving pet dogs health and welfare. (b) Diet, breeds and species discrimination. (c) Use of dogs as animal model in different diseases and drug development (evaluation toxicity and effect).

CONCLUSIONS

The results of this review showed that interest in metabolomics is growing in veterinary research. Several canine diseases have been evaluated with some promise for potential biomarker and/or disease mechanism discovery. Because canine metabolomics is a relatively new area, the researches spread across different research areas and with few studies in each area.

LC/MS-Based Polar Metabolite Profiling Identified Unique Biomarker Signatures for Cervical Cancer and Cervical Intraepithelial Neoplasia Using Global and Targeted Metabolomics

Cervical cancer remains one of the most prevalent cancers among females worldwide. Therefore, it is important to discover new biomarkers for early diagnosis of cervical intraepithelial neoplasia (CIN) and cervical cancer, preferably non-invasive ones. In the present study, we aimed to identify unique metabolic signatures for CINs and cervical cancers using global and targeted metabolomic profiling. Plasma samples (69 normal, 55 CIN1, 42 CIN2/3, and 60 cervical cancer) were examined by ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UPLC-QTOF-MS) coupled with multivariate statistical analysis. Metabolic pathways were analyzed using the integrated web-based tool MetaboAnalyst. A multivariate logistic regression analysis was conducted to evaluate the combined association of metabolites and human papillomavirus (HPV) status with the risk of cervical carcinogenesis. A total of 28 metabolites exhibiting discriminating levels among normal, CIN, and cervical cancer patients (Kruskal–Wallis test p < 0.05) were identified in the global profiling analysis. The pathway analysis showed significantly altered alanine, aspartate, and glutamate metabolic pathways (FDR p-value < 0.05) in both the discovery and validation phases. Seven metabolites (AMP, aspartate, glutamate, hypoxanthine, lactate, proline, and pyroglutamate) were discriminated between CINs and cervical cancer versus normal (area under the curve (AUC) value > 0.8). The levels of these metabolites were significantly high in patients versus normal (p < 0.0001) and were associated with increased risk of developing CIN2/3 and cervical cancer. Additionally, elevated levels of the seven metabolites combined with positive HPV status were correlated with substantial risk of cancer progression. These results demonstrated that metabolomics profiling is capable of distinguishing CINs and cervical cancers from normal and highlighted potential biomarkers for the early detection of cervical carcinogenesis.

A strategy for early detection of response to chemotherapy drugs based on treatment-related changes in the metabolome

We describe a biomarker-based approach to delivering chemotherapy that entails monitoring treatment changes in the circulating metabolome that reflect efficacy. In-vitro, multiple tumor cell lines were exposed to numerous chemotherapeutics. Supernatants were collected at baseline and 72 hours post treatment. MTT assays were used to quantify growth inhibition. Clinical samples were derived from a phase II clinical trial of second-line axitinib in patients with advanced hepatocellular carcinoma. Sera were collected at baseline and 2–4 weeks after treatment initiation. Response to therapy was estimated by CT scan at 8 weeks. Samples were analyzed by gas chromatography-mass spectrometry to identify metabolomic changes associated with response. In vitro, we found drug-specific and generalizable patterns of change in the extracellular metabolome accompany growth inhibition. A cell death signature was also identified. This approach was also applied to clinical samples. While the in vitro signatures were detectable in vivo, a more robust signal was identified clinically that appeared within 4 weeks of administering drug that distinguished individuals with a treatment response. These changes were extinguished as tumor growth resumed. Serial monitoring of the metabolome during chemotherapy is a means to follow treatment efficacy and emergence of resistance, informing the oncologist whether to modify treatment.

Reflection of treatment proficiency of hydroxyurea treated β-thalassemia serum samples through nuclear magnetic resonance based metabonomics

β-Thalassemia is a widespread autosomal recessive blood disorder found in most parts of the world. Fetal hemoglobin (HbF), a form of hemoglobin is found in infants, replaced by adult hemoglobin (HbA) after birth. Hydroxyurea (HU) is one of the most effective HbF inducer used for the treatment of anemic diseases. We aimed to improve the understanding of HU therapy in β-thalassemia by metabonomics approach using ¹H NMR spectroscopy. This study includes 40 cases of β-thalassemia before and after HU therapy along with 40 healthy as controls. Carr-Purcell-Meiboom-Gill (CPMG) sequence was used to identify forty-one putative metabolites. Generation of models like partial least square discriminant analysis (PLS-DA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA) based on different metabolites including lipids, amino acids, glucose, fucose, isobutyrate, and glycerol revealed satisfactory outcomes with 85.2% and 91.1% classification rates, respectively. The concentration of these metabolites was altered in β-thalassemia samples. However, after HU treatment metabolic profile of same patients showed closeness towards healthy. Deviant metabolic pathways counting lipoprotein changes, glycolysis, TCA cycle, fatty acid and choline metabolisms were identified as having significant differences among study groups. Findings of this study may open a better way to monitor HU treatment effectiveness in β-thalassemia patients, as the results suggested that metabolic profile of β-thalassemia patients shows similarity towards normal profile after this therapy.

Plasma metabolite profiling and chemometric analyses of tobacco snuff dippers and patients with oral cancer: Relationship between metabolic signatures

BACKGROUND

Cancer of oral cavity is a seriously growing problem in many parts of the world. In Indian subcontinent, most of these cases have been attributed to the use of tobacco-related products. This study is focused on the identification of distinguishing metabolites of oral cancer in comparison with tobacco snuff dippers and healthy controls.

METHODS

A total of 234 plasma samples including 62 healthy controls, 81 tobacco snuff dippers, and 91 oral cancer samples were analyzed using mass spectrometry.

RESULTS

Twenty-nine of 3326 metabolites were found to distinguish among oral cancer, tobacco snuff dippers, and healthy controls using P-value ≤.001 and fold change ≥3. Prediction model was generated with an overall accuracy of 89.3%. Two metabolites, that is, stearyl alcohol and sucrose, can be used as predictive biomarkers showing progression of tobacco snuff dippers toward oral cancer.

CONCLUSION

The unique metabolite profile gives evidence of a strong correlation between tobacco snuff dipping and oral cancer.

Response of Cisplatin Resistant Skov-3 Cells to [Pt(O,O'-Acac)(γ-Acac)(DMS)] Treatment Revealed by a Metabolomic ¹H-NMR Study

The novel [Pt(O,O′-acac)(γ-acac)(DMS)], Ptac2S, Pt(II) complex has recently gained increasing attention as a potential anticancer agent for its pharmacological activity shown in different tumor cell lines, studied both in vitro and in vivo. The mechanism of action of Ptac2S, operating on non-genomic targets, is known to be very different from that of cis-[PtCl₂(NH₃)₂], cisplatin, targeting nucleic acids. In this work, we evaluated the cytotoxicity of Ptac2S on the cisplatin resistant Epithelial Ovarian Carcinoma (EOC), SKOV-3 cells, by the MTT assay. A ¹H-NMR metabolomic approach coupled with multivariate statistical analysis was used for the first time for Ptac2S to figure out the biological mechanisms of action of the complex. The metabolic variations of intracellular metabolites and the composition of the corresponding extracellular culture media were compared to those of cisplatin (cells were treated at the IC₅₀ doses of both drugs). The reported comparative metabolomic analysis revealed a very different metabolic profile between Ptac2S and cisplatin treated samples, thus confirming the different mechanism of action of Ptac2S also in the Epithelial Ovarian Carcinoma (EOC), SKOV-3 cells line. In particular, higher levels of pyruvate were observed in Ptac2S treated, with respect to cisplatin treated, cells (in both aqueous and culture media). In addition, a very different lipid expression resulted after the exposure to the two drugs (Ptac2S and cisplatin). These results suggest a possible explanation for the Ptac2S ability to circumvent cisplatin resistance in SKOV-3 cells.

NMR-based Metabolomic Techniques Identify the Toxicity of Emodin in HepG2 Cells

Emodin is a natural anthraquinone derivative that is present in various herbal preparations. The pharmacological effects of emodin include anticancer, hepatoprotective, anti-inflammatory, antioxidant and even antimicrobial activities. However, emodin also has been reported to induce hepatotoxicity, nephrotoxicity, genotoxicity and reproductive toxicity. The mechanism of emodin's adverse effects is complicated and currently not well understood. This study aimed to establish a cell metabonomic method to investigate the toxicity of emodin and explore its potential mechanism and relevant targets. In the present study, metabonomic profiles of cell extracts and cell culture media obtained using the ¹H NMR technique were used to assess emodin toxicity in HepG2 cells. Multivariate statistical analyses such as partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were used to characterize the metabolites that differed between the control and emodin groups. The results indicated that emodin resulted in differences in 33 metabolites, including acetate, arginine, aspartate, creatine, isoleucine, leucine and histidine in the cell extract samples and 23 metabolites, including alanine, formate, glutamate, succinate and isoleucine, in the cell culture media samples. Approximately 8 pathways associated with these metabolites were disrupted in the emodin groups. These results demonstrated the potential for using cell metabonomics approaches to clarify the toxicological effects of emodin, the underlying mechanisms and potential biomarkers. Our findings may help with the development of novel strategies to discover targets for drug toxicity, elucidate the changes in regulatory signal networks and explore its potential mechanism of action.

Monitoring for Response to Antineoplastic Drugs: The Potential of a Metabolomic Approach

For most cancers, chemotherapeutic options are rapidly expanding, providing the oncologist with substantial choices. Therefore, there is a growing need to select the best systemic therapy, for any individual, that effectively halts tumor progression with minimal toxicity. Having the capability to predict benefit and to anticipate toxicity would be ideal, but remains elusive at this time. An alternative approach is an adaptive approach that involves close observation for treatment response and emergence of resistance. Currently, response to systemic therapy is estimated using radiographic tests. Unfortunately, radiographic estimates of response are imperfect and radiographic signs of response can be delayed. This is particularly problematic for targeted agents, as tumor shrinkage is often not apparent with these drugs. As a result, patients are exposed to prolonged courses of toxic drugs that may ultimately be found to be ineffective. A biomarker-based adaptive strategy that involves the serial analysis of the metabolome is attractive. The metabolome changes rapidly with changes in physiology. Changes in the circulating metabolome associated with various antineoplastic agents have been described, but further work will be required to understand what changes signify clinical benefit. We present an investigative approach for the discovery and validation of metabolomic response biomarkers, which consists of serial analysis of the metabolome and linkage of changes in the metabolome to measurable therapeutic benefit. Potential pitfalls in the development of metabolomic biomarkers of response and loss of response are reviewed.

Specificities of Human Hepatocellular Carcinoma Developed on Non-Alcoholic Fatty Liver Disease in Absence of Cirrhosis Revealed by Tissue Extracts ¹H-NMR Spectroscopy

There is a rising incidence of non-alcoholic fatty liver disease (NAFLD) as well as of the frequency of Hepato-Cellular Carcinoma (HCC) associated with NAFLD. To seek for putative metabolic pathways specific of the NAFLD etiology, we performed comparative metabolomics between HCC associated with NAFLD and HCC associated with cirrhosis. The study included 28 pairs of HCC tissue versus distant Non-Tumoral Tissue (NTT) collected from patients undergoing hepatectomy. HCC was associated with cirrhosis (n = 9), normal liver (n = 6) and NAFLD (n = 13). Metabolomics was performed using 1H-NMR Spectroscopy on tissue extracts and combined to multivariate statistical analysis. In HCC compared to NTT, statistical models showed high levels of lactate and phosphocholine, and low level of glucose. Shared and Unique Structures (SUS) plots were performed to remove the impact of underlying disease on the metabolic profile of HCC. HCC-cirrhosis was characterized by high levels of β-hydroxybutyrate, tyrosine, phenylalanine and histidine whereas HCC-NAFLD was characterized by high levels of glutamine/glutamate. In addition, the overexpression glutamine/glutamate on HCC-NAFLD was confirmed by both Glutamine Synthetase (GS) immuno-staining and NMR-spectroscopy glutamine quantification. This study provides evidence of metabolic specificities of HCC associated with non-cirrhotic NAFLD versus HCC associated with cirrhosis. These alterations could suggest activation of glutamine synthetase pathway in HCC-NAFLD and mitochondrial dysfunction in HCC-cirrhosis, that may be part of specific carcinogenic processes.

Applications of high-resolution magic angle spinning MRS in biomedical studies I-cell line and animal models

High-resolution magic angle spinning (HRMAS) MRS allows for direct measurements of non-liquid tissue and cell specimens to present valuable insights into the cellular metabolisms of physiological and pathological processes. HRMAS produces high-resolution spectra comparable to those obtained from solutions of specimen extracts but without complex metabolite extraction processes, and preserves the tissue cellular structure in a form suitable for pathological examinations following spectroscopic analysis. The technique has been applied in a wide variety of biomedical and biochemical studies and become one of the major platforms of metabolomic studies. By quantifying single metabolites, metabolite ratios, or metabolic profiles in their entirety, HRMAS presents promising possibilities for diagnosis and prediction of clinical outcomes for various diseases, as well as deciphering of metabolic changes resulting from drug therapies or xenobiotic interactions. In this review, we evaluate HRMAS MRS results on animal models and cell lines reported in the literature, and present the diverse applications of the method for the understanding of pathological processes and the effectiveness of therapies, development of disease animal models, and new progress in HRMAS methodology.

Distinguishing Benign from Malignant Pancreatic and Periampullary Lesions Using Combined Use of ¹H-NMR Spectroscopy and Gas Chromatography-Mass Spectrometry

Previous work demonstrated that serum metabolomics can distinguish pancreatic cancer from benign disease. However, in the clinic, non-pancreatic periampullary cancers are difficult to distinguish from pancreatic cancer. Therefore, to test the clinical utility of this technology, we determined whether any pancreatic and periampullary adenocarcinoma could be distinguished from benign masses and biliary strictures. Sera from 157 patients with malignant and benign pancreatic and periampullary lesions were analyzed using proton nuclear magnetic resonance (¹H-NMR) spectroscopy and gas chromatography–mass spectrometry (GC-MS). Multivariate projection modeling using SIMCA-P+ software in training datasets (n = 80) was used to generate the best models to differentiate disease states. Models were validated in test datasets (n = 77). The final ¹H-NMR spectroscopy and GC-MS metabolomic profiles consisted of 14 and 18 compounds, with AUROC values of 0.74 (SE 0.06) and 0.62 (SE 0.08), respectively. The combination of ¹H-NMR spectroscopy and GC-MS metabolites did not substantially improve this performance (AUROC 0.66, SE 0.08). In patients with adenocarcinoma, glutamate levels were consistently higher, while glutamine and alanine levels were consistently lower. Pancreatic and periampullary adenocarcinomas can be distinguished from benign lesions. To further enhance the discriminatory power of metabolomics in this setting, it will be important to identify the metabolomic changes that characterize each of the subclasses of this heterogeneous group of cancers.

(1)H NMR studies distinguish the water soluble metabolomic profiles of untransformed and RAS-transformed cells

Metabolomic profiling is an increasingly important method for identifying potential biomarkers in cancer cells with a view towards improved diagnosis and treatment. Nuclear magnetic resonance (NMR) provides a potentially noninvasive means to accurately characterize differences in the metabolomic profiles of cells. In this work, we use (1)H NMR to measure the metabolomic profiles of water soluble metabolites extracted from isogenic control and oncogenic HRAS-, KRAS-, and NRAS-transduced BEAS2B lung epithelial cells to determine the robustness of NMR metabolomic profiling in detecting differences between the transformed cells and their untransformed counterparts as well as differences among the RAS-transformed cells. Unique metabolomic signatures between control and RAS-transformed cell lines as well as among the three RAS isoform-transformed lines were found by applying principal component analysis to the NMR data. This study provides a proof of principle demonstration that NMR-based metabolomic profiling can robustly distinguish untransformed and RAS-transformed cells as well as cells transformed with different RAS oncogenic isoforms. Thus, our data may potentially provide new diagnostic signatures for RAS-transformed cells.

Oesophageal squamous cell carcinoma (ESCC): Advances through omics technologies, towards ESCC salivaomics

Oesophageal Squamous Cell Carcinoma (ESCC) is one of the two main subtypes of oesophageal cancer, affecting mainly populations in Asia. Though there have been great efforts to develop methods for a better prognosis, there is still a limitation in the staging of this affection. As a result, ESCC is detected at advances stages, when the interventions on the patient do not have such a positive outcome, leading in many cases to recurrence and to a very low 5-year survival rate, causing high mortality. A way to decrease the number of deaths is the use of biomarkers that can trace the advance of the disease at early stages, when surgical or chemotherapeutic methodologies would have a greater effect on the evolution of the subject. The new high throughput omics technologies offer an unprecedented chance to screen for thousands of molecules at the same time, from which a new set of biomarkers could be developed. One of the most convenient types of samples is saliva, an accessible body fluid that has the advantage of being non-invasive for the patient, being easy to store or to process. This review will focus on the current status of the new omics technologies regarding salivaomics in ESCC, or when not evaluated yet, the achievements in related diseases.

Temporal characterization of serum metabolite signatures in lung cancer patients undergoing treatment

Lung cancer causes more deaths in men and women than any other cancer related disease. Currently, few effective strategies exist to predict how patients will respond to treatment. We evaluated the serum metabolomic profiles of 25 lung cancer patients undergoing chemotherapy ± radiation to evaluate the feasibility of metabolites as temporal biomarkers of clinical outcomes. Serial serum specimens collected prospectively from lung cancer patients were analyzed using both nuclear magnetic resonance (¹H-NMR) spectroscopy and gas chromatography mass spectrometry (GC-MS). Multivariate statistical analysis consisted of unsupervised principal component analysis or orthogonal partial least squares discriminant analysis with significance assessed using a cross-validated ANOVA. The metabolite profiles were reflective of the temporal distinction between patient samples before during and after receiving therapy (¹H-NMR, p < 0.001: and GC-MS p < 0.01). Disease progression and survival were strongly correlative with the GC-MS metabolite data whereas stage and cancer type were associated with ¹H-NMR data. Metabolites such as hydroxylamine, tridecan-1-ol, octadecan-1-ol, were indicative of survival (GC-MS p < 0.05) and metabolites such as tagatose, hydroxylamine, glucopyranose, and threonine that were reflective of progression (GC-MS p < 0.05). Metabolite profiles have the potential to act as prognostic markers of clinical outcomes for lung cancer patients. Serial ¹H-NMR measurements appear to detect metabolites diagnostic of tumor pathology, while GC-MS provided data better related to prognostic clinical outcomes, possibility due to physiochemical bias related to specific biochemical pathways. These results warrant further study in a larger cohort and with various treatment options.

Metabolic responses induced by DNA damage and poly (ADP-ribose) polymerase (PARP) inhibition in MCF-7 cells

Genomic instability is one of the hallmarks of cancer. Several chemotherapeutic drugs and radiotherapy induce DNA damage to prevent cancer cell replication. Cells in turn activate different DNA damage response (DDR) pathways to either repair the damage or induce cell death. These DDR pathways also elicit metabolic alterations which can play a significant role in the proper functioning of the cells. The understanding of these metabolic effects resulting from different types of DNA damage and repair mechanisms is currently lacking. In this study, we used NMR metabolomics to identify metabolic pathways which are altered in response to different DNA damaging agents. By comparing the metabolic responses in MCF-7 cells, we identified the activation of poly (ADP-ribose) polymerase (PARP) in methyl methanesulfonate (MMS)-induced DNA damage. PARP activation led to a significant depletion of NAD+. PARP inhibition using veliparib (ABT-888) was able to successfully restore the NAD+ levels in MMS-treated cells. In addition, double strand break induction by MMS and veliparib exhibited similar metabolic responses as zeocin, suggesting an application of metabolomics to classify the types of DNA damage responses. This prediction was validated by studying the metabolic responses elicited by radiation. Our findings indicate that cancer cell metabolic responses depend on the type of DNA damage responses and can also be used to classify the type of DNA damage.

Metabolic differentiation and classification of abnormal Savda Munziq's pharmacodynamic role on rat models with different diseases by nuclear magnetic resonance-based metabonomics

Background:

Abnormal Savda Munziq (ASMq) is a traditional Uyghur herbal preparation used as a therapy for abnormal Savda-related diseases. In this study, we investigate ASMq's dynamic effects on abnormal Savda rat models under different disease conditions.

Materials and Methods:

Abnormal Savda rat models with hepatocellular carcinoma (HCC), type 2 diabetes mellitus (T2DM), and asthma dosed of ASMq. Serum samples of each animal tested by nuclear magnetic resonance spectroscopy and analyzed by orthogonal projection to latent structure with discriminant analysis.

Results:

Compared with healthy controls, HCC rats had higher concentrations of amino acids, fat-related metabolites, lactate, myoinositol, and citrate, but lower concentrations of α-glucose, β-glucose, and glutamine. Following ASMq treatment, the serum acetone very low-density lipoprotein (VLDL), LDL, unsaturated lipids, acetylcysteine, and pyruvate concentration decreased, but α-glucose, β-glucose, and glutamine concentration increased (P < 0.05). T2DM rats had higher concentrations of α- and β-glucose, but lower concentrations of isoleucine, leucine, valine, glutamine, glycoprotein, lactate, tyrosine, creatine, alanine, carnitine, and phenylalanine. After ASMq treated T2DM groups showed reduced α- and β-glucose and increased creatine levels (P < 0.05). Asthma rats had higher acetate, carnitine, formate, and phenylalanine levels, but lower concentrations of glutamine, glycoprotein, lactate, VLDL, LDL, and unsaturated lipids. ASMq treatment showed increased glutamine and reduced carnitine, glycoprotein, formate, and phenylalanine levels (P < 0.05).

Conclusion:

Low immune function, decreased oxidative defense, liver function abnormalities, amino acid deficiencies, and energy metabolism disorders are common characteristics of abnormal Savda-related diseases. ASMq may improve the abnormal metabolism and immune function of rat models with different diseases combined abnormal Savda.

Metabolomic study of Chinese medicine Huang Qin decoction as an effective treatment for irinotecan-induced gastrointestinal toxicity

Metabolomic study revealed Chinese medicine HQD reducing irinotecan-induced gastrointestinal toxicity by regulating glutamine, tryptophan and lipid metabolisms.

An effective assessment of valproate sodium-induced hepatotoxicity with UPLC-MS and (1)HNMR-based metabonomics approach

Valproate sodium is one of the most prescribed antiepileptic drugs. However, valproate sodium has various side effects, especially its toxicity on liver. Current markers for toxicity reflect mostly the late stages of tissue damage; thus, more efficient methods for toxicity evaluation are desired. To evaluate the toxicity of valproate sodium on liver, we performed both UPLC-MS and (1)HNMR-based metabonomics analysis of serum samples from 34 epileptic patients (age: 42.0±18.6, 18 male/16 female) after valproate sodium treatment. Compared to conventional markers, the serum metabolic profiles provided clear distinction of the valproate sodium induced normal liver function and abnormal liver function in epileptic patients. Through multivariate statistical analysis, we identified marker metabolites associated with the hepatotoxicity induced by valproate sodium, such as glucose, lactate, acetoacetate, VLDL/LDL, lysophosphatidylcholines, phosphatidylcholines, choline, creatine, amino acids, N-acetyl glycoprotein, pyruvate and uric acid. This metabonomics approach may provide effective way to evaluate the valproate sodium-induced toxicity in a manner that can complement current measures. This approach is expected to find broader application in other drug-induced toxicity assessment.

BRCA1 induces major energetic metabolism reprogramming in breast cancer cells

The hypermetabolic nature of cancer cells and their increased reliance on “aerobic glycolysis”, as originally described by Otto Warburg and colleagues, are considered metabolic hallmarks of cancer cells. BRCA1 is a major tumor suppressor in breast cancer and it was implicated in numerous pathways resulting in anticarcinogenic functions. The objective of our study was to address specific contributions of BRCA1 to the metabolic features of cancer cells, including the so-called “Warburg effect”. To get a comprehensive approach of the role of BRCA1 in tumor cell metabolism, we performed a global transcriptional and metabolite profiling in a BRCA1-mutated breast cancer cell line transfected or not by wild-type BRCA1. This study revealed that BRCA1 induced numerous modifications of metabolism, including strong inhibition of glycolysis while TCA cycle and oxidative phosphorylation tended to be activated. Regulation of AKT by BRCA1 in both our cell model and BRCA1-mutated breast tumors was suggested to participate in the effect of BRCA1 on glycolysis. We could also show that BRCA1 induced a decrease of ketone bodies and free fatty acids, maybe consumed to supply Acetyl-CoA for TCA cycle. Finally increased activity of antioxidation pathways was observed in BRCA1-transfected cells, that could be a consequence of ROS production by activated oxidative phosphorylation. Our study suggests a new function for BRCA1 in cell metabolic regulation, globally resulting in reversion of the Warburg effect. This could represent a new mechanism by which BRCA1 may exert tumor suppressor function.

Potential of metabolomics in preclinical and clinical drug development

Metabolomics is an upcoming technology system which involves detailed experimental analysis of metabolic profiles. Due to its diverse applications in preclinical and clinical research, it became an useful tool for the drug discovery and drug development process. This review covers the brief outline about the instrumentation and interpretation of metabolic profiles. The applications of metabolomics have a considerable scope in the pharmaceutical industry, almost at each step from drug discovery to clinical development. These include finding drug target, potential safety and efficacy biomarkers and mechanisms of drug action, the validation of preclinical experimental models against human disease profiles, and the discovery of clinical safety and efficacy biomarkers. As we all know, nowadays the drug discovery and development process is a very expensive, and risky business. Failures at any stage of drug discovery and development process cost millions of dollars to the companies. Some of these failures or the associated risks could be prevented or minimized if there were better ways of drug screening, drug toxicity profiling and monitoring adverse drug reactions. Metabolomics potentially offers an effective route to address all the issues associated with the drug discovery and development.

Metabolomics and transcriptomics demonstrate severe oxidative stress in both localized chemotherapy-treated and bystander tumors

BACKGROUND

Localized radiotherapy is long known to cause damages to not only targeted but also non-targeted cells, the so-called bystander (BS) effect. Recently, BS effect was demonstrated in response to chemotherapy. To get further insight into the mechanism of chemotherapy-induced BS effect in vivo, we investigated the response of normal tissues and untreated BS melanomas, at distance from localized chemotherapy-treated melanomas.

METHODS

B16 melanoma cells were inoculated sc in one flank, in mice. Chemotherapy was administered intratumorally. After 3 weeks, untreated melanomas were implanted into the other flank. Tumors were analyzed morphologically, and using metabolomics and transcriptomics.

RESULTS

Locally-treated melanomas showed growth inhibition and pleiotropic metabolic and transcriptional alterations. Tumors recovered slow proliferation while exhibiting prominent oxidative stress response (decreased glutathione level, and increased expression of genes including Mt1, Gpx3, Sod3, and Hmox1). Plasma contained increased levels of oxidative stress products. However, liver and soleus muscle displayed unaltered morphological characteristics. In contrast, untreated BS melanomas induced from naive B16 cells showed reduced growth, marked oxidative stress response (decreased glutathione level, and increased expression of genes including Sod2, Gpx1 and Gsr), and ras oncogene expression alterations. Furthermore, metabolomics and transcriptomics enabled to estimate the proportion of cells undergoing the BS effect within treated tumors.

CONCLUSION

Treatment of tumors with chemotherapy induces BS effects, underpinned by oxidative stress, in abnormal proliferating tissues in vivo, not in normal tissue, that significantly contribute to overall tumor response. General significance BS effect significantly contributes to response to chemotherapy, and may be exploited to improve overall response to cancer treatment.

Studies of Secondary Melanoma on C57BL/6J Mouse Liver Using 1H NMR Metabolomics

NMR metabolomics, consisting of solid state high resolution magic angle spinning (HR-MAS) ¹H-NMR, liquid state high resolution ¹H-NMR, and principal components analysis (PCA) has been used to study secondary metastatic B16-F10 melanoma in C57BL/6J mouse liver. The melanoma group can be differentiated from its control group by PCA analysis of the estimates of absolute concentrations from liquid state ¹H-NMR spectra on liver tissue extracts or by the estimates of absolute peak intensities of metabolites from ¹H HR-MAS-NMR data on intact liver tissues. In particular, we found that the estimates of absolute concentrations of glutamate, creatine, fumarate and cholesterol are elevated in the melanoma group as compared to controls, while the estimates of absolute concentrations of succinate, glycine, glucose, and the family of linear lipids including long chain fatty acids, total choline and acyl glycerol are decreased. The ratio of glycerophosphocholine (GPC) to phosphocholine (PCho) is increased by about 1.5 fold in the melanoma group, while the estimate of absolute concentration of total choline is actually lower in melanoma mice. These results suggest the following picture in secondary melanoma metastasis: Linear lipid levels are decreased by beta oxidation in the melanoma group, which contributes to an increase in the synthesis of cholesterol, and also provides an energy source input for TCA cycle. These findings suggest a link between lipid oxidation, the TCA cycle and the hypoxia-inducible factors (HIF) signal pathway in tumor metastases. Thus, this study indicates that the metabolic profile derived from NMR analysis can provide a valuable bio-signature of malignancy and cell hypoxia in metastatic melanoma.

Functional metabolomics uncovers metabolic alterations associated to severe oxidative stress in MCF7 breast cancer cells exposed to ascididemin

Marine natural products are a source of promising agents for cancer treatment. However, there is a need to improve the evaluation of their mechanism of action in tumors. Metabolomics of the response to anti-tumor agents is a tool to reveal candidate biomarkers and metabolic targets. We used two-dimensional high-resolution magic angle spinning proton-NMR spectroscopy-based metabolomics to investigate the response of MCF7 breast cancer cells to ascididemin, a marine alkaloid and lead molecule for anti-cancer treatment. Ascididemin induced severe oxidative stress and apoptosis within 48 h of exposure. Thirty-three metabolites were quantified. Metabolic response involved downregulation of glycolysis and the tricarboxylic acid cycle, and phospholipid metabolism alterations. Candidate metabolic biomarkers of the response of breast cancer cells to ascididemin were proposed including citrate, gluconate, polyunsaturated fatty acids, glycerophospho-choline and -ethanolamine. In addition, candidate metabolic targets were identified. Overall, the response to Asc could be related to severe oxidative stress and anti-inflammatory effects.

(1)H NMR-based metabonomics study on the toxicity alleviation effect of other traditional Chinese medicines in Niuhuang Jiedu tablet to realgar (As2S2)

ETHNOPHARMACOLOGICAL RELEVANCE

Niuhuang Jiedu Tablet (NJT) is an effective prescription of traditional Chinese medicine (TCM) used in treating acute tonsillitis, pharyngitis, periodontitis and mouth ulcer. NJT is prepared from Xionghuang (Realgar, As2S2), Rengong Niuhuang (Bovis Calculus Artificialis), Bingpian (Borneolum Synthcticum), Shigao (Gypsum Fibrosum), Dahuang (Rhei Radix et Rhizoma), Huangqin (Scutellariae Radix), Jiegeng (Platycodonis Radix) and Gancao (Glycyrrhizae Radix et Rhizoma). In the prescription, significant level of realgar (As2S2) as a potentially toxic element is contained.

AIM OF THE STUDY

In this study, (1)H NMR-based metabonomics approach has been used to investigate the toxicity of realgar (As2S2) after being counterbalanced by other TCMs in NJT.

MATERIALS AND METHODS

Male Wistar rats were divided into five groups: control, group I (treated with Realgar), group II (treated with Realgar, Bovis Calculus Artificialis, Borneolum Synthcticum, Gypsum Fibrosum, Rhei Radix et Rhizoma, Scutellariae Radix, Platycodonis Radix and Glycyrrhizae Radix et Rhizoma), group III (treated with Realgar, Bovis Calculus Artificialis, Borneolum Synthcticum and Gypsum Fibrosum) and group IV (treated with Realgar, Rhei Radix et Rhizoma, Scutellariae Radix, Platycodonis Radix and Glycyrrhizae Radix et Rhizoma). Based on (1)H-NMR spectra of urine and serum from rats, PCA and PLS-DA were performed to identify different metabolic profiles. Liver and kidney histopathology examinations and serum clinical chemistry analysis were also performed.

RESULTS

PLS-DA scores plots demonstrated that the cluster of group I was separated from that of control rats, while group II was located close to control rats, indicating that metabolic profiles of group II were restored toward those of control rats. The metabolic profiles of group III were similar to those of group I, while the metabolic profiles of group II were almost in line with those of group II. Statistics results were confirmed by the histopathological examination and biochemical assay.

CONCLUSION

Our results indicated that it was more secure and much less toxic for counterbalanced realgar (As2S2) in NJT. The effective material bases of toxicity alleviation to realgar (As2S2) were Dahuang (Rhei Radix et Rhizoma), Huangqin (Scutellariae Radix), Jiegeng (Platycodonis Radix) and Gancao (Glycyrrhizae Radix et Rhizoma), which regulated energy metabolism, choline metabolism, amino acid metabolism and gut flora disorder affected by realgar (As2S2) exposure.

In vivo efficacy of melanoma internal radionuclide therapy with a 131I-labelled melanin-targeting heteroarylcarboxamide molecule

The development of alternative therapies for melanoma treatment is of great interest as long-term tumour regression is not achieved with new targeted chemotherapies on selected patients. We previously demonstrated that radioiodinated heteroarylcarboxamide ([131I]ICF01012) induced a strong anti-tumoural effect by inhibiting both primary tumour growth and dissemination process in a B16BL6 melanoma model. In our study, we show that a single injection of [131I]ICF01012 (ranging from 14.8 to 22.2 MBq) was effective and associated with low and transient haematological toxicity. Concerning pigmented organs, cutaneous melanocytes and skin were undamaged. In 30% of treated animals, no histological alteration of retina was observed, and in the remaining 70%, damages were restricted to the optic nerve area. Using the Medical Internal Radiation Dose methodology, we determined that the absorbed dose in major organs is very low (<4 Gy) and that a delivery of 30 Gy to the tumour is sufficient for an effective anti-tumoural response. Molecular analyses of treated tumours showed a strong radiobiological effect with a decrease in proliferation, survival and pro-angiogenic-related markers and an increase in tumour suppressor gene expression, melanogenesis and anti-angiogenic markers. All these features are in accordance with a tumour cell death mechanism that mainly occurs by mitotic catastrophe and provide a better understanding of in vivo anti-tumoural effects of [131I] radionuclide. Our findings raise [131I]ICF01012 a good candidate for disseminated melanoma treatment and strongly support transfer of [131I]ICF01012 to clinical trial.

Metabolomics reveals metabolic targets and biphasic responses in breast cancer cells treated by curcumin alone and in association with docetaxel

BACKGROUND

Curcumin (CUR) has deserved extensive research due to its anti-inflammatory properties, of interest in human diseases including cancer. However, pleiotropic even paradoxical responses of tumor cells have been reported, and the mechanisms of action of CUR remain uncompletely elucidated.

METHODOLOGY/PRINCIPAL FINDINGS

(1)H-NMR spectroscopy-based metabolomics was applied to get novel insight into responses of MCF7 and MDA-MB-231 breast cancer cells to CUR alone, and MCF7 cells to CUR in cotreatment with docetaxel (DTX). In both cell types, a major target of CUR was glutathione metabolism. Total glutathione (GSx) increased at low dose CUR (≤ 10 mg.l(-1)-28 µM-) (up to +121% in MCF7 cells, P<0.01, and +138% in MDA-MB-231 cells, P<0.01), but decreased at high dose (≥ 25 mg.l(-1) -70 µM-) (-49%, in MCF7 cells, P<0.02, and -56% in MDA-MB-231 cells, P<0.025). At high dose, in both cell types, GSx-related metabolites decreased, including homocystein, creatine and taurine (-60 to -80%, all, P<0.05). Together with glutathione-S-transferase actvity, data established that GSx biosynthesis was upregulated at low dose, and GSx consumption activated at high dose. Another major target, in both cell types, was lipid metabolism involving, at high doses, accumulation of polyunsaturated and total free fatty acids (between ×4.5 and ×11, P<0.025), and decrease of glycerophospho-ethanolamine and -choline (about -60%, P<0.025). Multivariate statistical analyses showed a metabolic transition, even a biphasic behavior of some metabolites including GSx, between low and high doses. In addition, CUR at 10 mg.l(-1) in cotreatment with DTX induced modifications in glutathione metabolism, lipid metabolism, and glucose utilization. Some of these changes were biphasic depending on the duration of exposure to CUR.

CONCLUSIONS/SIGNIFICANCE

Metabolomics reveals major metabolic targets of CUR in breast cancer cells, and biphasic responses that challenge the widely accepted beneficial effects of the phytochemical.

Metabolomic analysis of dynamic response and drug resistance of gastric cancer cells to 5-fluorouracil

Metabolomics has developed as an important new tool in cancer research. It is expected to lead to the discovery of biomarker candidates for cancer diagnosis and treatment. The current study aimed to perform a comprehensive metabolomic analysis of the intracellular dynamic responses of human gastric cancer cells to 5-fluorouracil (5-FU), referencing the mechanisms of drug action and drug resistance. Small metabolites in gastric cancer cells and 5-FU-resistant cells were measured by liquid chromatography-mass spectrometry. Candidates for drug targets were selected according to the presence or absence of resistance, before and after 5-FU treatment. In addition, the gene expression of each candidate was assessed by reverse transcription-polymerase chain reaction. The number of metabolites in cancer cells dramatically changed during short-term treatment with 5-FU. Particularly, proline was reduced to one-third of its original level and glutamate was increased by a factor of 3 after 3 h of treatment. The metabolic production of glutamate from proline proceeds by proline dehydrogenase (PRODH), producing superoxide. After 5-FU treatment, PRODH mRNA expression was upregulated 2-fold and production of superoxide was increased by a factor of 3. In 5-FU-resistant cells, proline and glutamate levels were less affected than in non-resistant cells, and PRODH mRNA expression and superoxide generation were not increased following treatment. In conclusion, the authors identified a candidate biomarker, PRODH, for drug effects using a meta-bolomic approach, a result that was confirmed by conventional methods. In the future, metabolomics will play an important role in the field of cancer research.

Characterization of temporary metabolic changes following Cantonese herbal tea intervention

Cantonese herbal tea (CHT) has been consumed in South China to alleviate feelings of discomfort due to the heat and humidity in the body according to the theory of traditional Chinese medicine (TCM). To understand the in vivo mechanism of CHT, a ¹H-NMR-based metabonomic approach was used to investigate the global biological characterization of rat serum following the intake of CHT and to understand the mechanisms of action of CHT. Serum samples from rats with consecutive CHT intake after 10, 20 and 30 days and corresponding control rats were analysed by high-resolution ¹H-NMR spectroscopy. Principal component analysis (PCA) and orthogonal projection on latent structures discriminant analysis (OPLS-DA) were utilized for ¹H-NMR spectra analysis and temporal metabolic changes identification. For the 10-day CHT intake group, no significant metabolic response was detected, whereas the 20-day group showed elevation of glucogeneogenesis and a shift in energy metabolism from carbohydrate metabolism to lipid metabolism. In addition, a notable decrease in pyruvate content with a consistent increase in lactate content, and significant decrease in both lipoprotein and glucose contents was observed for the 30-day group, indicating potential metabolic dysfunction. The metabonomics technique combining metabolic profiles with multivariate analysis enhanced our current understanding of the host's metabolic response to CHT intake.

Normal human melanocytes exposed to chronic insulin and glucose supplementation undergo oncogenic changes and methyl group metabolism cellular redistribution

Recent epidemiological studies have suggested a link between cancer and pathophysiological conditions associated with hyperinsulinemia. In this report, we address the possible role of insulin exposure in melanocyte transformation. To this aim, normal melanocytes were exposed to chronic insulin and glucose supplementation (twice the standard medium concentration) for at least 3 wk. After 3-wk treatment, melanocytes increased proliferation (doubling time: 2.7 vs. 5.6 days, P < 0.01). After 3-wk treatment or after 3-wk treatment followed by 4-wk reculture in standard medium, melanocytes were able to grow in soft agar colonies. Treated melanocytes had increased DNA content (+8%, P < 0.05), chromosomal aberrations, and modified oncoprotein profile: p-Akt expression increased (+32%, P < 0.01), Akt decreased, and c-Myc increased (+40%, P < 0.05). PP2A protein expression increased (+42, P < 0.05), while PP2A methylation decreased (-42%, P < 0.05), and PP2A activity was reduced (-27%, P < 0.05). PP2A transcription level was increased (ppp2r1a, PP2A subunit A, +44%, P < 0.05). Also, transcriptomic data revealed modifications in insr (insulin receptors, +10%, P < 0.05) and Il8 (inflammation protein, +99%, P < 0.01). Glycolysis was modified with increased transcription of Pgk1 and Hif1a (P < 0.05), decreased transcription of Pfkfb3 (P < 0.05), decreased activity of pyruvate kinase (P < 0.01), and decreased pyruvate cell content as assessed by (1)H-NMR spectroscopy. In addition, methyl group metabolism was altered with decreased global DNA methylation (-51%, P < 0.01), increased cytosolic protein methylation (+18%, P < 0.05), and consistent changes in methylated species on (1)H-NMR spectra. In conclusion, exposure to chronic insulin and glucose supplementation induces oncogenic changes and methyl group metabolism redistribution, which may be a biomarker of transformation.

Metabonomic signature analysis of cervical carcinoma and precancerous lesions in women by (1)H NMR spectroscopy

(1)H nuclear magnetic resonance (NMR)-based metabonomics has been used to characterize the metabolic profiles of cervical intraepithelial neoplasia (CIN) and cervical squamous cell carcinoma (CSCC). Principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) were used to model the systematic variation related to patients with CIN or CSCC with healthy controls. Potential metabolic biomarkers were identified using database comparisons, and the one-way analysis of variance (ANOVA) test was used to examine the significance of the metabolites. Compared with plasma obtained from the healthy controls, plasma from patients with CIN had higher levels of very-low density lipoprotein (VLDL), acetone, unsaturated lipid and carnitine, together with lower levels of creatine, lactate, isoleucine, leucine, valine, alanine, glutamine, histidine, glycine, acetylcysteine, myo-inositol, choline and glycoprotein. Plasma from patients with CSCC had higher levels of acetate and formate, together with lower levels of creatine, lactate, isoleucine, leucine, valine, alanine, glutamine, histidine and tyrosine compared with the plasma of the healthy controls. In addition, compared with the plasma of patients with CIN, the plasma of CSCC patients had higher levels of acetate, formate, lactate, isoleucine, leucine, valine, alanine, glutamine, histidine, tyrosine, acetylcysteine, myo-inositol, glycoprotein, α-glucose and β-glucose, together with lower levels of acetone, unsaturated lipid and carnitine. Moreover, the profiles showed high feasibility and specificity by statistical analysis with OPLS-DA compared to the Thinprep cytology test (TCT) by setting the histopathological outcome as standard. The metabolic profile obtained for cervical cancer is significant, even for the precancerous disease. This suggests a systemic metabolic response to cancer, which may be used to identify potential early diagnostic biomarkers of the cancer and to establish clinical diagnostic methods.

Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer

Earlier detection of patients with metastatic colorectal cancer (mCRC) might improve their treatment and survival outcomes. In this study, we used proton nuclear magnetic resonance ((1)H-NMR) to profile the serum metabolome in patients with mCRC and determine whether a disease signature may exist that is strong enough to predict overall survival (OS). In 153 patients with mCRC and 139 healthy subjects from three Danish hospitals, we profiled two independent sets of serum samples in a prospective phase II study. In the training set, (1)H-NMR metabolomic profiling could discriminate patients with mCRC from healthy subjects with a cross-validated accuracy of 100%. In the validation set, 96.7% of subjects were correctly classified. Patients from the training set with maximally divergent OS were chosen to construct an OS predictor. After validation, patients predicted to have short OS had significantly reduced survival (HR, 3.4; 95% confidence interval, 2.06-5.50; P = 1.33 × 10(-6)). A number of metabolites concurred with the (1)H-NMR fingerprint of mCRC, offering insights into mCRC metabolic pathways. Our findings establish that (1)H-NMR profiling of patient serum can provide a strong metabolomic signature of mCRC and that analysis of this signature may offer an independent tool to predict OS.

The emerging field of quantitative blood metabolomics for biomarker discovery in critical illnesses

Metabolomics, a science of systems biology, is the global assessment of endogenous metabolites within a biologic system and represents a "snapshot" reading of gene function, enzyme activity, and the physiological landscape. Metabolite detection, either individual or grouped as a metabolomic profile, is usually performed in cells, tissues, or biofluids by either nuclear magnetic resonance spectroscopy or mass spectrometry followed by sophisticated multivariate data analysis. Because loss of metabolic homeostasis is common in critical illness, the metabolome could have many applications, including biomarker and drug target identification. Metabolomics could also significantly advance our understanding of the complex pathophysiology of acute illnesses, such as sepsis and acute lung injury/acute respiratory distress syndrome. Despite this potential, the clinical community is largely unfamiliar with the field of metabolomics, including the methodologies involved, technical challenges, and, most importantly, clinical uses. Although there is evidence of successful preclinical applications, the clinical usefulness and application of metabolomics in critical illness is just beginning to emerge, the advancement of which hinges on linking metabolite data to known and validated clinically relevant indices. In addition, other important aspects, such as patient selection, sample collection, and processing, as well as the needed multivariate data analysis, have to be taken into consideration before this innovative approach to biomarker discovery can become a reliable tool in the intensive care unit. The purpose of this review is to begin to familiarize clinicians with the field of metabolomics and its application for biomarker discovery in critical illnesses such as sepsis.

Characterisation of human embryonic stem cells conditioning media by 1H-nuclear magnetic resonance spectroscopy

Background

Cell culture media conditioned by human foreskin fibroblasts (HFFs) provide a complex supplement of protein and metabolic factors that support in vitro proliferation of human embryonic stem cells (hESCs). However, the conditioning process is variable with different media batches often exhibiting differing capacities to maintain hESCs in culture. While recent studies have examined the protein complement of conditioned culture media, detailed information regarding the metabolic component of this media is lacking.

Methodology/Principal Findings

Using a ¹H-Nuclear Magnetic Resonance (¹H-NMR) metabonomics approach, 32 metabolites and small compounds were identified and quantified in media conditioned by passage 11 HFFs (CMp11). A number of metabolites were secreted by HFFs with significantly higher concentration of lactate, alanine, and formate detected in CMp11 compared to non-conditioned media. In contrast, levels of tryptophan, folate and niacinamide were depleted in CMp11 indicating the utilisation of these metabolites by HFFs. Multivariate statistical analysis of the ¹H-NMR data revealed marked age-related differences in the metabolic profile of CMp11 collected from HFFs every 24 h over 72 h. Additionally, the metabolic profile of CMp11 was altered following freezing at −20°C for 2 weeks. CM derived from passage 18 HFFs (CMp18) was found to be ineffective at supporting hESCs in an undifferentiated state beyond 5 days culture. Multivariate statistical comparison of CMp11 and CMp18 metabolic profiles enabled rapid and clear discrimination between the two media with CMp18 containing lower concentrations of lactate and alanine as well as higher concentrations of glucose and glutamine.

Conclusions/Significance

¹H-NMR-based metabonomics offers a rapid and accurate method of characterising hESC conditioning media and is a valuable tool for monitoring, controlling and optimising hESC culture media preparation.

Toxicological characterization of N-methyl-N-nitrosourea-induced cataract in rats by LC/MS-based metabonomic analysis

Cataract is one of the most serious drug-induced side effects that can terminate the development of drug candidates, and pharmaceutical companies consider it important to evaluate cataract-inducing potential in the early phases. Metabonomics is expected to be a powerful approach for the safety evaluation of drug candidates. In this study, we conducted a toxicological characterization of N-methyl-N-nitrosourea (MNU)-induced cataract in rats by LC/MS-based metabonomic analysis. MNU was intraperitoneally administered once to 15-day old rats at 70 mg kg(-1) . After that, animals were kept for 3 weeks waiting for cataract formation. Lens samples for metabonomic analysis were collected on 7, 14 and 21 days after MNU administration. Comprehensive analyses of lens metabolites were conducted using an LC/MS system, and multivariate data for each sample were compared by principal component analysis (PCA) to find any changes in lens metabolites. Lens opacity was confirmed by ophthalmoscopy 14 days after dosing, and even by gross observation 21 days after dosing. PCA of the lens samples for the control and MNU-treated groups revealed that the metabolite profiles of lens differed from each other, and several lens metabolites, such as lots of α-amino acids and gluthathione, decreased after MNU treatment. In conclusion, metabonomic analysis enabled us to identify new marker candidates for cataract and provided a better understanding of the mechanism related to MNU-induced cataract. It was considered that metabonomics is a useful approach for the characterization of drug-induced toxicity.

¹H NMR-based metabolic profiling of naproxen-induced toxicity in rats

The dose-dependent perturbations in urinary metabolite concentrations caused by naproxen toxicity were investigated using ¹H NMR spectroscopy coupled with multivariate statistical analysis. Histopathologic evaluation of naproxen-induced acute gastrointestinal damage in rats demonstrated a significant dose-dependent effect. Furthermore, principal component analysis (PCA) of ¹H NMR from rat urine revealed a dose-dependent metabolic shift between the vehicle-treated control rats and rats treated with low-dose (10 mg/kg body weight), moderate-dose (50 mg/kg), and high-dose (100 mg/kg) naproxen, coinciding with their gastric damage scores after naproxen administration. The resultant metabolic profiles demonstrate that the naproxen-induced gastric damage exhibited energy metabolism perturbations that elevated their urinary levels of citrate, cis-aconitate, creatine, and creatine phosphate. In addition, naproxen administration decreased choline level and increased betaine level, indicating that it depleted the main protective constituent of the gastric mucosa. Moreover, naproxen stimulated the decomposition of tryptophan into kynurenate, which inhibits fibroblast growth factor-1 and delays ulcer healing. These findings demonstrate that ¹H NMR-based urinary metabolic profiling can facilitate noninvasive and rapid diagnosis of drug side effects and is suitable for elucidating possible biological pathways perturbed by drug toxicity.

Chronic myeloid leukemia patients sensitive and resistant to imatinib treatment show different metabolic responses

The BCR-ABL tyrosine kinase inhibitor imatinib is highly effective for chronic myeloid leukemia (CML). However, some patients gradually develop resistance to imatinib, resulting in therapeutic failure. Metabonomic and genomic profiling of patients' responses to drug interventions can provide novel information about the in vivo metabolism of low-molecular-weight compounds and extend our insight into the mechanism of drug resistance. Based on a multi-platform of high-throughput metabonomics, SNP array analysis, karyotype and mutation, the metabolic phenotypes and genomic polymorphisms of CML patients and their diverse responses to imatinib were characterized. The untreated CML patients (UCML) showed different metabolic patterns from those of healthy controls, and the discriminatory metabolites suggested the perturbed metabolism of the urea cycle, tricarboxylic acid cycle, lipid metabolism, and amino acid turnover in UCML. After imatinib treatment, patients sensitive to imatinib (SCML) and patients resistant to imatinib (RCML) had similar metabolic phenotypes to those of healthy controls and UCML, respectively. SCML showed a significant metabolic response to imatinib, with marked restoration of the perturbed metabolism. Most of the metabolites characterizing CML were adjusted to normal levels, including the intermediates of the urea cycle and tricarboxylic acid cycle (TCA). In contrast, neither cytogenetic nor metabonomic analysis indicated any positive response to imatinib in RCML. We report for the first time the associated genetic and metabonomic responses of CML patients to imatinib and show that the perturbed in vivo metabolism of UCML is independent of imatinib treatment in resistant patients. Thus, metabonomics can potentially characterize patients' sensitivity or resistance to drug intervention.

Navigating the human metabolome for biomarker identification and design of pharmaceutical molecules

Metabolomics is a rapidly evolving discipline that involves the systematic study of endogenous small molecules that characterize the metabolic pathways of biological systems. The study of metabolism at a global level has the potential to contribute significantly to biomedical research, clinical medical practice, as well as drug discovery. In this paper, we present the most up-to-date metabolite and metabolic pathway resources, and we summarize the statistical, and machine-learning tools used for the analysis of data from clinical metabolomics. Through specific applications on cancer, diabetes, neurological and other diseases, we demonstrate how these tools can facilitate diagnosis and identification of potential biomarkers for use within disease diagnosis. Additionally, we discuss the increasing importance of the integration of metabolomics data in drug discovery. On a case-study based on the Human Metabolome Database (HMDB) and the Chinese Natural Product Database (CNPD), we demonstrate the close relatedness of the two data sets of compounds, and we further illustrate how structural similarity with human metabolites could assist in the design of novel pharmaceuticals and the elucidation of the molecular mechanisms of medicinal plants.

Quantitative two-dimensional HRMAS 1H-NMR spectroscopy-based metabolite profiling of human cancer cell lines and response to chemotherapy

NMR spectroscopy-based metabolomics still needs development in quantification procedures. A method was designed for quantitative two-dimensional high resolution magic angle spinning (HRMAS) proton-NMR spectroscopy-based metabolite profiling of intact cells. It uses referencing of metabolite-related NMR signals to protein-related NMR signals and yields straightforward and automatable metabolite profiling. The method enables exploitation of only two-dimensionally visible metabolites and combination of one- and two-dimensional spectra, thus providing an appreciable number of screened metabolites. With this procedure, 32 intracellular metabolites were attributed and quantified in human normal fibroblasts and tumor cells. The phenotype of several tumor cell lines (MCF7, PC3, 143B, and HepG2) was characterized by high levels of glutathione in cell lines with the higher proliferation rate, high levels of creatine, low levels of free amino acids, increased levels of phospholipid derivatives (mostly phosphocholine), and lower lactate content in cell lines with the higher proliferation rate. Other metabolites such as fatty acids differed widely among tumor cell lines. The response of tumor cell lines to chemotherapy also was evaluated by differential metabolite profiling, bringing insights into drug cytotoxicity and tumor cell adaptive mechanisms. The method may prove widely applicable to tumor cell phenotyping.

Biochemical disorders induced by cytotoxic marine natural products in breast cancer cells as revealed by proton NMR spectroscopy-based metabolomics

Marine plants and animals are sources of a huge number of pharmacologically active compounds, some of which exhibit antineoplastic activity of clinical relevance. However the mechanism of action of marine natural products (MNPs) is poorly understood. In this study, proton NMR spectroscopy-based metabolomics was applied to unravel biochemical disorders induced in human MCF7 breast cancer cells by 3 lead candidate anticancer MNPs: ascididemin (Asc), lamellarin-D (Lam-D), and kahalalide F (KF). Asc, Lam-D, and KF provoked a severe decrease in DNA content in MCF7 cells after 24-h treatment. Asc and Lam-D provoked apoptosis, whereas KF induced non-apoptotic cell death. Metabolite profiling revealed major biochemical disorders following treatment. The response of MCF7 tumor cells to Asc involved the accumulation of citrate (x17 the control level, P<0.001), testifying enzyme blockade in citrate metabolism, and the accumulation of gluconate (x9.8, P<0.005), a metabolite never reported at such concentration in tumor cells, probably testifying glycolysis shutdown. The response to Lam-D involved the accumulation of aspartate (x7.2, P<0.05), glutamate (x14.7, P<0.05), and lactate (x2.3, P<0.05), probably in relation with the targeting of the malate-aspartate shuttle, as discussed. The response to KF involved increased lipid accumulation (polyunsaturated fatty acids x9.8, P<0.05), and phospholipid and acetate derivative alterations. Altogether, this study demonstrates the potential of proton NMR spectroscopy-based metabolomics to help uncover metabolic targets and elucidate the mechanism of cytotoxicity of candidate antineoplastic MNPs.