Metabolomic profiling of lung and prostate tumor tissues by capillary electrophoresis time-of-flight mass spectrometry

A critical appraisal of the role of metabolomics in breast cancer research and diagnostics

Breast cancer (BC) remains the most prevalent cancer among women worldwide, despite significant advancements in its prevention and treatment. The escalating incidence of BC globally necessitates continued research into novel diagnostic and therapeutic strategies. Metabolomics, a burgeoning field, offers a comprehensive analysis of all metabolites within a cell, tissue, system, or organism, providing crucial insights into the dynamic changes occurring during cancer development and progression. This review focuses on the metabolic alterations associated with BC, highlighting the potential of metabolomics in identifying biomarkers for early detection, diagnosis, treatment and prognosis. Metabolomics studies have revealed distinct metabolic signatures in BC, including alterations in lipid metabolism, amino acid metabolism, and energy metabolism. These metabolic changes not only support the rapid proliferation of cancer cells but also influence the tumour microenvironment and therapeutic response. Furthermore, metabolomics holds great promise in personalized medicine, facilitating the development of tailored treatment strategies based on an individual's metabolic profile. By providing a holistic view of the metabolic changes in BC, metabolomics has the potential to revolutionize our understanding of the disease and improve patient outcomes.

Primordial aqueous alteration recorded in water-soluble organic molecules from the carbonaceous asteroid (162173) Ryugu

We report primordial aqueous alteration signatures in water-soluble organic molecules from the carbonaceous asteroid (162173) Ryugu by the Hayabusa2 spacecraft of JAXA. Newly identified low-molecular-weight hydroxy acids (HO-R-COOH) and dicarboxylic acids (HOOC-R-COOH), such as glycolic acid, lactic acid, glyceric acid, oxalic acid, and succinic acid, are predominant in samples from the two touchdown locations at Ryugu. The quantitative and qualitative profiles for the hydrophilic molecules between the two sampling locations shows similar trends within the order of ppb (parts per billion) to ppm (parts per million). A wide variety of structural isomers, including α- and β-hydroxy acids, are observed among the hydrophilic molecules. We also identify pyruvic acid and dihydroxy and tricarboxylic acids, which are biochemically important intermediates relevant to molecular evolution, such as the primordial TCA (tricarboxylic acid) cycle. Here, we find evidence that the asteroid Ryugu samples underwent substantial aqueous alteration, as revealed by the presence of malonic acid during keto-enol tautomerism in the dicarboxylic acid profile. The comprehensive data suggest the presence of a series for water-soluble organic molecules in the regolith of Ryugu and evidence of signatures in coevolutionary aqueous alteration between water and organics in this carbonaceous asteroid.

Unveiling the altered metabolic pathways induced by nivolumab in non-small cell lung cancer via GC-MS metabolomics approach coupled with multivariate analysis

This research investigates the effects of the immunotherapeutic agent nivolumab on the metabolism of lung cancer cells (NCI-H1975) using GC-MS metabolomic profiling. Multivariate analysis such as unsupervised PCA and supervised OPLS-DA along with univariate analysis and pathway analysis were employed to explore the metabolomic data and identify altered metabolic pathways induced by nivolumab treatment. The study revealed distinct metabolic alterations in cancer cells, linked to proliferative and survival advantages, such as enhanced glycolysis, increased glutaminolysis, and modified amino acid metabolism. Key findings indicate elevated levels of glycolysis-related metabolites (glycine, alanine, pyruvate, and lactate) and TCA cycle intermediates (succinate, fumarate, malate) in cancer cells, with a significant decrease following nivolumab treatment. Additionally, lower levels of aspartic acid and citrate in cancer cells imply altered nucleotide synthesis and fatty acid production essential for tumor growth. Treatment with nivolumab also reduced oleic acid levels, indicative of its effect on disrupted lipid metabolism. Our research shows nivolumab's potential to modify metabolic pathways involved in lung cancer progression, suggesting its dual role in cancer therapy: as an immune response modulator and a metabolic pathway disruptor.

The gluconeogenesis enzyme PCK2 has a non-enzymatic role in proteostasis in endothelial cells

Endothelial cells (ECs) are highly glycolytic, but whether they generate glycolytic intermediates via gluconeogenesis (GNG) in glucose-deprived conditions remains unknown. Here, we report that glucose-deprived ECs upregulate the GNG enzyme PCK2 and rely on a PCK2-dependent truncated GNG, whereby lactate and glutamine are used for the synthesis of lower glycolytic intermediates that enter the serine and glycerophospholipid biosynthesis pathways, which can play key roles in redox homeostasis and phospholipid synthesis, respectively. Unexpectedly, however, even in normal glucose conditions, and independent of its enzymatic activity, PCK2 silencing perturbs proteostasis, beyond its traditional GNG role. Indeed, PCK2-silenced ECs have an impaired unfolded protein response, leading to accumulation of misfolded proteins, which due to defective proteasomes and impaired autophagy, results in the accumulation of protein aggregates in lysosomes and EC demise. Ultimately, loss of PCK2 in ECs impaired vessel sprouting. This study identifies a role for PCK2 in proteostasis beyond GNG.

Salivary metabolomic biomarkers for non-invasive lung cancer detection

Identifying novel biomarkers for early detection of lung cancer is crucial. Non-invasively available saliva is an ideal biofluid for biomarker exploration; however, the rationale underlying biomarker detection from organs distal to the oral cavity in saliva requires clarification. Therefore, we analyzed metabolomic profiles of cancer tissues compared with those of adjacent non-cancerous tissues, as well as plasma and saliva samples collected from patients with lung cancer (n = 109 pairs). Additionally, we analyzed plasma and saliva samples collected from control participants (n = 83 and 71, respectively). Capillary electrophoresis-mass spectrometry and liquid chromatography-mass spectrometry were performed to comprehensively quantify hydrophilic metabolites. Paired tissues were compared, revealing 53 significantly different metabolites. Plasma and saliva showed 44 and 40 significantly different metabolites, respectively, between patients and controls. Of these, 12 metabolites exhibited significant differences in all three comparisons and primarily belonged to the polyamine and amino acid pathways; N1-acetylspermidine exhibited the highest discrimination ability. A combination of 12 salivary metabolites was evaluated using a machine learning method to differentiate patients with lung cancer from controls. Salivary data were randomly split into training and validation datasets. Areas under the receiver operating characteristic curve were 0.744 for cross-validation using training data and 0.792 for validation data. This model exhibited a higher discrimination ability for N1-acetylspermidine than that for other metabolites. The probability of lung cancer calculated using this model was independent of most patient characteristics. These results suggest that consistently different salivary biomarkers in both plasma and lung tissues might facilitate non-invasive lung cancer screening.

Metabolomics Analysis and Diagnosis of Lung Cancer: Insights from Diverse Sample Types

Lung cancer is a highly fatal disease that poses a significant global health burden. The absence of characteristic clinical symptoms frequently results in the diagnosis of most patients at advanced stages of lung cancer. Although low-dose computed tomography (LDCT) screening has become increasingly prevalent in clinical practice, its high rate of false positives continues to present a significant challenge. In addition to LDCT screening, tumor biomarker detection represents a critical approach for early diagnosis of lung cancer; unfortunately, no tumor marker with optimal sensitivity and specificity is currently available. Metabolomics has recently emerged as a promising field for developing novel tumor biomarkers. In this paper, we introduce metabolic pathways, instrument platforms, and a wide variety of sample types for lung cancer metabolomics. Specifically, we explore the strengths, limitations, and distinguishing features of various sample types employed in lung cancer metabolomics research. Additionally, we present the latest advances in lung cancer metabolomics research that utilize diverse sample types. We summarize and enumerate research studies that have investigated lung cancer metabolomics using different metabolomic sample types. Finally, we provide a perspective on the future of metabolomics research in lung cancer. Our discussion of the potential of metabolomics in developing new tumor biomarkers may inspire further study and innovation in this dynamic field.

Association of plasma branched-chain amino acid with multiple cancers: A mendelian randomization analysis

BACKGROUND

Studies have suggested a possible relevance between branched-chain amino acid (BCAA) catabolic enzymes and cancers. However, few studies have explored the variation in circulating concentrations of BCAAs. Our study used bi-directional, two-sample Mendelian randomization (MR) analysis for predicting the causality between the BCAA levels and 9 types of cancers.

METHODS

The largest genome-wide association studies (GWAS) provided data for total BCAAs, valine, leucine, and isoleucine from the UK Biobank. Data on multiple cancer endpoints were collected from various sources, such as the International Lung Cancer Consortium (ILCCO), the Pancreatic Cancer Cohort Consortium 1 (PanScan1), the Breast Cancer Association Consortium (BCAC), the FinnGen Biobank, and the Ovarian Cancer National Alliance (OCAC). The mainly analysis method was the inverse-variance-weighted (IVW). For assessing horizontal pleiotropy, the researchers performed MR-Egger regression and MR-PRESSO global test. Finally, the Cochran's Q test served for evaluating the heterogeneity.

RESULTS

Circulating total BCAAs levels (OR 1.708, 95%CI 1.168, 2.498; p = 0.006), valine levels (OR 1.747, 95%CI 1.217, 2.402; p < 0.001), leucine levels (OR 1.923, 95%CI 1.279, 2.890; p = 0.002) as well as isoleucine levels (OR 1.898, 95%CI 1.164, 3.094; p = 0.010) positively correlated with the squamous cell lung cancer risk. Nevertheless, no compelling evidence was found to support a causal link between BCAAs and any other examined cancers.

CONCLUSIONS

Increased circulating total-BCAAs levels, leucine levels, isoleucine levels and valine levels had higher hazard of squamous cell lung cancer. No such associations were found for BCAAs with other cancers.

Impact of Different Treatment Regimens and Timeframes in the Plasmatic Metabolic Profiling of Patients with Lung Adenocarcinoma

In recent years, the treatment of advanced non-small cell lung cancer (NSCLC) has suffered a variety of alterations. Chemotherapy (CTX), immunotherapy (IT) and tyrosine kinase inhibitors (TKI) have shown remarkable results. However, not all patients with NSCLC respond to these drug treatments or receive durable benefits. In this framework, metabolomics has been applied to improve the diagnosis, treatment, and prognosis of lung cancer and particularly lung adenocarcinoma (AdC). In our study, metabolomics was used to analyze plasma samples from 18 patients with AdC treated with CTX or IT via 1H-NMR spectroscopy. Relevant clinical information was gathered, and several biochemical parameters were also evaluated throughout the treatments. During the follow-up of patients undergoing CTX or IT, imaging control is recommended in order to assess the effectiveness of the therapy. This evaluation is usually performed every three treatments. Based on this procedure, all the samples were collected before the beginning of the treatment and after three and six treatments. The identified and quantified metabolites in the analyzed plasma samples were the following: isoleucine, valine, alanine, acetate, lactate, glucose, tyrosine, and formate. Multivariate/univariate statistical analyses were performed. Our data are in accordance with previous published results, suggesting that the plasma glucose levels of patients under CTX become higher throughout the course of treatment, which we hypothesize could be related to the tumor response to the therapy. It was also found that alanine levels become lower during treatment with CTX regimens, a fact that could be associated with frailty. NMR spectra of long responders' profiles also showed similar results. Based on the results of the study, metabolomics can represent a potential option for future studies, in order to facilitate patient selection and the monitoring of therapy efficacy in treated patients with AdC. Further studies are needed to improve the prospective identification of predictive markers, particularly glucose and alanine levels, as well as confer guidance to NSCLC treatment and patient stratification, thus avoiding ineffective therapeutic strategies.

Emerging Biosensing Methods to Monitor Lung Cancer Biomarkers in Biological Samples: A Comprehensive Review

Lung cancer is the most commonly diagnosed of all cancers and one of the leading causes of cancer deaths among men and women worldwide, causing 1.5 million deaths every year. Despite developments in cancer treatment technologies and new pharmaceutical products, high mortality and morbidity remain major challenges for researchers. More than 75% of lung cancer patients are diagnosed in advanced stages, leading to poor prognosis. Lung cancer is a multistep process associated with genetic and epigenetic abnormalities. Rapid, accurate, precise, and reliable detection of lung cancer biomarkers in biological fluids is essential for risk assessment for a given individual and mortality reduction. Traditional diagnostic tools are not sensitive enough to detect and diagnose lung cancer in the early stages. Therefore, the development of novel bioanalytical methods for early-stage screening and diagnosis is extremely important. Recently, biosensors have gained tremendous attention as an alternative to conventional methods because of their robustness, high sensitivity, inexpensiveness, and easy handling and deployment in point-of-care testing. This review provides an overview of the conventional methods currently used for lung cancer screening, classification, diagnosis, and prognosis, providing updates on research and developments in biosensor technology for the detection of lung cancer biomarkers in biological samples. Finally, it comments on recent advances and potential future challenges in the field of biosensors in the context of lung cancer diagnosis and point-of-care applications.

Increased ENT2 expression and its association with altered purine metabolism in cell lines derived from different stages of colorectal cancer

Colorectal cancer (CRC) is one of the most prevalent malignant cancer types worldwide. Although the purine metabolism pathway is vital for cancer cell survival, little is known about the role of equilibrative nucleoside transporter 2 (ENT2) in CRC development and its association with purine metabolites. The aim of the present study was to evaluate the levels of hypoxanthine phosphoribosyl transferase (HPRT), hypoxanthine and uric acid (UA), as well as xanthine oxidase (XO) activity, and investigate their association with ENT2 expression levels in a normal human colon cell line and CRC cell lines derived from different stages of CRC. These analyses were performed using the normal colon CCD-841CoN cell line and a panel of human CRC cell lines comprising SW480, HCT15 and HCT116, which represent Dukes' B, C and D stages, respectively. Reverse transcription-quantitative PCR was performed to determine the level of ENT2 mRNA expression. In cells of all CRC stages, the levels of HPRT and hypoxanthine were significantly higher (P<0.05), while XO activity and UA levels were significantly decreased (P<0.05), compared with those in the CCD-841CoN cell line. ENT2 expression was found to be elevated in cells derived from all stages of CRC. The Dukes' D stage cell line had higher levels of HPRT and hypoxanthine, although its ENT2 level was not significantly lower than that of the Dukes' B and C stage cell lines. Increased levels of HPRT and hypoxanthine in various stages of CRC may indicate an increase in the activity of the salvage pathway. The increased expression of ENT2 implies the importance of the ENT2 protein in facilitating hypoxanthine transport, which is required for enhanced DNA synthesis via hypoxanthine recycling. In conclusion, ENT2 may have potential as a target in the development of CRC therapeutics.

Characteristic Metabolic Changes in Skeletal Muscle Due to Vibrio vulnificus Infection in a Wound Infection Model

Vibrio vulnificus is a bacterium that inhabits warm seawater or brackish water environments and causes foodborne diseases and wound infections. In severe cases, V. vulnificus invades the skeletal muscle tissue, where bacterial proliferation leads to septicemia and necrotizing fasciitis with high mortality. Despite this characteristic, information on metabolic changes in tissue infected with V. vulnificus is not available. Here, we elucidated the metabolic changes in V. vulnificus-infected mouse skeletal muscle using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS). Metabolome analysis revealed changes in muscle catabolites and energy metabolites during V. vulnificus infection. In particular, succinic acid accumulated but fumaric acid decreased in the infected muscle. However, the virulence factor deletion mutant revealed that changes in metabolites and bacterial proliferation were abolished in skeletal muscle infected with a multifunctional-autoprocessing repeats-in-toxin (MARTX) mutant. On the other hand, mice that were immunosuppressed via cyclophosphamide (CPA) treatment exhibited a similar level of bacterial counts and metabolites between the wild type and MARTX mutant. Therefore, our data indicate that V. vulnificus induces metabolic changes in mouse skeletal muscle and proliferates by using the MARTX toxin to evade the host immune system. This study indicates a new correlation between V. vulnificus infections and metabolic changes that lead to severe reactions or damage to host skeletal muscle. IMPORTANCE V. vulnificus causes necrotizing skin and soft tissue infections (NSSTIs) in severe cases, with high mortality and sign of rapid deterioration. Despite the severity of the infection, the dysfunction of the host metabolism in skeletal muscle triggered by V. vulnificus is poorly understood. In this study, by using a mouse wound infection model, we revealed characteristic changes in muscle catabolism and energy metabolism in skeletal muscle associated with bacterial proliferation in the infected tissues. Understanding such metabolic changes in V. vulnificus-infected tissue may provide crucial information to identify the mechanism via which V. vulnificus induces severe infections. Moreover, our metabolite data may be useful for the recognition, identification, or detection of V. vulnificus infections in clinical studies.

Lung cancer metabolomic data from tumor core biopsies enables risk-score calculation for progression-free and overall survival

INTRODUCTION

Metabolomics has emerged as a powerful method to provide insight into cancer progression, including separating patients into low- and high-risk groups for overall (OS) and progression-free survival (PFS). However, survival prediction based mainly on metabolites obtained from biofluids remains elusive.

OBJECTIVES

This proof-of-concept study evaluates metabolites as biomarkers obtained directly from tumor core biopsies along with covariates age, sex, pathological stage at diagnosis (I/II vs. III/VI), histological subtype, and treatment vs. no treatment to risk stratify lung cancer patients in terms of OS and PFS.

METHODS

Tumor core biopsy samples obtained during routine lung cancer patient care at the University of Louisville Hospital and Norton Hospital were evaluated with high-resolution 2DLC-MS/MS, and the data were analyzed by Kaplan-Meier survival analysis and Cox proportional hazards regression. A linear equation was developed to stratify patients into low and high risk groups based on log-transformed intensities of key metabolites. Sparse partial least squares discriminant analysis (SPLS-DA) was performed to predict OS and PFS events.

RESULTS

Univariable Cox proportional hazards regression model coefficients divided by the standard errors were used as weight coefficients multiplied by log-transformed metabolite intensity, then summed to generate a risk score for each patient. Risk scores based on 10 metabolites for OS and 5 metabolites for PFS were significant predictors of survival. Risk scores were validated with SPLS-DA classification model (AUROC 0.868 for OS and AUROC 0.755 for PFS, when combined with covariates).

CONCLUSION

Metabolomic analysis of lung tumor core biopsies has the potential to differentiate patients into low- and high-risk groups based on OS and PFS events and probability.

Metabolic Phenotyping in Prostate Cancer Using Multi-Omics Approaches

Prostate cancer (PCa), one of the most frequently diagnosed cancers among men worldwide, is characterized by a diverse biological heterogeneity. It is well known that PCa cells rewire their cellular metabolism to meet the higher demands required for survival, proliferation, and invasion. In this context, a deeper understanding of metabolic reprogramming, an emerging hallmark of cancer, could provide novel opportunities for cancer diagnosis, prognosis, and treatment. In this setting, multi-omics data integration approaches, including genomics, epigenomics, transcriptomics, proteomics, lipidomics, and metabolomics, could offer unprecedented opportunities for uncovering the molecular changes underlying metabolic rewiring in complex diseases, such as PCa. Recent studies, focused on the integrated analysis of multi-omics data derived from PCa patients, have in fact revealed new insights into specific metabolic reprogramming events and vulnerabilities that have the potential to better guide therapy and improve outcomes for patients. This review aims to provide an up-to-date summary of multi-omics studies focused on the characterization of the metabolomic phenotype of PCa, as well as an in-depth analysis of the correlation between changes identified in the multi-omics studies and the metabolic profile of PCa tumors.

Branched-chain amino acids govern the high learning ability phenotype in Tokai high avoider (THA) rats

To fully understand the mechanisms governing learning and memory, animal models with minor interindividual variability and higher cognitive function are required. THA rats established by crossing those with high learning capacity exhibit excellent learning and memory abilities, but the factors underlying their phenotype are completely unknown. In the current study, we compare the hippocampi of parental strain Wistar rats to those of THA rats via metabolomic analysis in order to identify molecules specific to the THA rat hippocampus. Higher branched-chain amino acid (BCAA) levels and enhanced activation of BCAA metabolism-associated enzymes were observed in THA rats, suggesting that acetyl-CoA and acetylcholine are synthesized through BCAA catabolism. THA rats maintained high blood BCAA levels via uptake of BCAAs in the small intestine and suppression of BCAA catabolism in the liver. Feeding THA rats with a BCAA-reduced diet decreased acetylcholine levels and learning ability, thus, maintaining high BCAA levels while their proper metabolism in the hippocampus is the mechanisms underlying the high learning ability in THA rats. Identifying appropriate BCAA nutritional supplements and activation methods may thus hold potential for the prevention and amelioration of higher brain dysfunction, including learning disabilities and dementia.

Detection and verification of coexisting diagnostic markers in plasma and serum of patients with non-small-cell lung cancer

Aim: To screen and identify the potential biomarkers co-existing in plasma and serum of patients with non-small-cell lung cancer (NSCLC), and establish appropriate diagnostic models. Methods: A cohort of 195 plasma samples and 180 serum samples were obtained from healthy controls (HCs), adenocarcinoma (AdC) and squamous cell carcinoma (SqCC) patients enrolled from the First Affiliated Hospital of Nanjing Medical University. Metabolites in plasma and serum were analyzed by GC-MS. Results: Hypoxanthine was found to have good performance in the differential diagnosis of NSCLC (including AdC and SqCC) and HC (area under the receiver operating characteristic [AUROC] ≥0.85). Combinations of metabolites could be used for differential diagnosis of NSCLC and HC (AUROC >0.93), AdC and HC (AUROC >0.91), SqCC and HC (AUROC >0.95), AdC and SqCC (AUROC >0.72). Conclusions: Metabolomics based on GC-MS can screen and identify the differential metabolites coexisting in plasma and serum of patients with NSCLC, and prediction models established by this method can be used for the differential diagnosis of patients with NSCLC.

Metabolomic Profiling in Lung Cancer: A Systematic Review

Lung cancer continues to be a significant burden worldwide and remains the leading cause of cancer-associated mortality. Two considerable challenges posed by this disease are the diagnosis of 61% of patients in advanced stages and the reduced five-year survival rate of around 4%. Noninvasively collected samples are gaining significant interest as new areas of knowledge are being sought and opened up. Metabolomics is one of these growing areas. In recent years, the use of metabolomics as a resource for the study of lung cancer has been growing. We conducted a systematic review of the literature from the past 10 years in order to identify some metabolites associated with lung cancer. More than 150 metabolites have been associated with lung cancer-altered metabolism. These were detected in different biological samples by different metabolomic analytical platforms. Some of the published results have been consistent, showing the presence/alteration of specific metabolites. However, there is a clear variability due to lack of a full clinical characterization of patients or standardized patients selection. In addition, few published studies have focused on the added value of the metabolomic profile as a means of predicting treatment response for lung cancer. This review reinforces the need for consistent and systematized studies, which will help make it possible to identify metabolic biomarkers and metabolic pathways responsible for the mechanisms that promote tumor progression, relapse and eventually resistance to therapy.

Salubrinal Enhances Cancer Cell Death during Glucose Deprivation through the Upregulation of xCT and Mitochondrial Oxidative Stress

Cancer cells have the metabolic flexibility to adapt to heterogeneous tumor microenvironments. The integrated stress response (ISR) regulates the cellular adaptation response during nutrient stress. However, the issue of how the ISR regulates metabolic flexibility is still poorly understood. In this study, we activated the ISR using salubrinal in cancer cells and found that salubrinal repressed cell growth, colony formation, and migration but did not induce cell death in a glucose-containing condition. Under a glucose-deprivation condition, salubrinal induced cell death and increased the levels of mitochondrial reactive oxygen species (ROS). We found that these effects of salubrinal and glucose deprivation were associated with the upregulation of xCT (SLC7A11), which functions as an antiporter of cystine and glutamate and maintains the level of glutathione to maintain redox homeostasis. The upregulation of xCT did not protect cells from oxidative stress-mediated cell death but promoted it during glucose deprivation. In addition, the supplementation of ROS scavenger N-acetylcysteine and the maintenance of intracellular levels of amino acids via sulfasalazine (xCT inhibitor) or dimethyl-α-ketoglutarate decreased the levels of mitochondrial ROS and protected cells from death. Our results suggested that salubrinal enhances cancer cell death during glucose deprivation through the upregulation of xCT and mitochondrial oxidative stress.

Integrative Metabolomic and Lipidomic Profiling of Lung Squamous Cell Carcinoma for Characterization of Metabolites and Intact Lipid Species Related to the Metastatic Potential

SQCC is a major type of NSCLC, which is a major cause of cancer-related deaths, and there were no reports regarding the prediction of metastatic potential of lung SQCC by metabolomic and lipidomic profiling. In this study, metabolomic and lipidomic profiling of lung SQCC were performed to predict its metastatic potential and to suggest potential therapeutic targets for the inhibition of lung SQCC metastasis. Human bronchial epithelial cells and four lung SQCC cell lines with different metastatic potentials were analyzed using gas chromatography-mass spectrometry and direct infusion-mass spectrometry. Based on the obtained metabolic and lipidomic profiles, we constructed models to predict the metastatic potential of lung SQCC; glycerol, putrescine, β-alanine, hypoxanthine, inosine, myo-inositol, phosphatidylinositol (PI) 18:1/18:1, and PI 18:1/20:4 were suggested as characteristic metabolites and intact lipid species associated with lung SQCC metastatic potential. In this study, we established predictive models for the metastatic potential of lung SQCC; furthermore, we identified metabolites and intact lipid species relevant to lung SQCC metastatic potential that may serve as potential therapeutic targets for the inhibition of lung SQCC metastasis.

The Ability of Metabolomics to Discriminate Non-Small-Cell Lung Cancer Subtypes Depends on the Stage of the Disease and the Type of Material Studied

Identification of the NSCLC subtype at an early stage is still quite sophisticated. Metabolomics analysis of tissue and plasma of NSCLC patients may indicate new, and yet unknown, metabolic pathways active in the NSCLC. Our research characterized the metabolomics profile of tissue and plasma of patients with early and advanced NSCLC stage. Samples were subjected to thorough metabolomics analyses using liquid chromatography-mass spectrometry (LC-MS) technique. Tissue and/or plasma samples from 137 NSCLC patients were analyzed. Based on the early stage tissue analysis, more than 200 metabolites differentiating adenocarcinoma (ADC) and squamous cell lung carcinoma (SCC) subtypes as well as normal tissue, were identified. Most of the identified metabolites were amino acids, fatty acids, carnitines, lysoglycerophospholipids, sphingomyelins, plasmalogens and glycerophospholipids. Moreover, metabolites related to N-acyl ethanolamine (NAE) biosynthesis, namely glycerophospho (N-acyl) ethanolamines (GP-NAE), which discriminated early-stage SCC from ADC, have also been identified. On the other hand, the analysis of plasma of chronic obstructive pulmonary disease (COPD) and NSCLC patients allowed exclusion of the metabolites related to the inflammatory state in lungs and the identification of compounds (lysoglycerophospholipids, glycerophospholipids and sphingomyelins) truly characteristic to cancer. Our results, among already known, showed novel, thus far not described, metabolites discriminating NSCLC subtypes, especially in the early stage of cancer. Moreover, the presented results also indicated the activity of new metabolic pathways in NSCLC. Further investigations on the role of NAE biosynthesis pathways in the early stage of NSCLC may reveal new prognostic and diagnostic targets.

Metabolomics in cancer research and emerging applications in clinical oncology

Cancer has myriad effects on metabolism that include both rewiring of intracellular metabolism to enable cancer cells to proliferate inappropriately and adapt to the tumor microenvironment, and changes in normal tissue metabolism. With the recognition that fluorodeoxyglucose-positron emission tomography imaging is an important tool for the management of many cancers, other metabolites in biological samples have been in the spotlight for cancer diagnosis, monitoring, and therapy. Metabolomics is the global analysis of small molecule metabolites that like other -omics technologies can provide critical information about the cancer state that are otherwise not apparent. Here, the authors review how cancer and cancer therapies interact with metabolism at the cellular and systemic levels. An overview of metabolomics is provided with a focus on currently available technologies and how they have been applied in the clinical and translational research setting. The authors also discuss how metabolomics could be further leveraged in the future to improve the management of patients with cancer.

Comparative metabolomics studies of blood collected in streck and heparin tubes from lung cancer patients

Metabolomics analysis of blood from patients (n = 42) undergoing surgery for suspected lung cancer was performed in this study. Venous and arterial blood was collected in both Streck and Heparin tubes. A total of 96 metabolites were detected, affected by sex (n = 56), collection tube (n = 33), and blood location (n = 8). These metabolites belonged to a wide array of compound classes including lipids, acids, pharmaceutical agents, signalling molecules, vitamins, among others. Phospholipids and carboxylic acids accounted for 28% of all detected compounds. Out of the 33 compounds significantly affected by collection tube, 18 compounds were higher in the Streck tubes, including allantoin and ketoleucine, and 15 were higher in the Heparin tubes, including LysoPC(P-16:0), PS 40:6, and chenodeoxycholic acid glycine conjugate. Based on our results, it is recommended that replicate blood samples from each patient should be collected in different types of blood collection tubes for a broader range of the metabolome. Several metabolites were found at higher concentrations in cancer patients such as lactic acid in Squamous Cell Carcinoma, and lysoPCs in Adenocarcinoma and Acinar Cell Carcinoma, which may be used to detect early onset and/or to monitor the progress of the cancer patients.

Metabolomics bridging proteomics along metabolites/oncometabolites and protein modifications: Paving the way toward integrative multiomics

Systems biology adopted functional and integrative multiomics approaches enable to discover the whole set of interacting regulatory components such as genes, transcripts, proteins, metabolites, and metabolite dependent protein modifications. This interactome build up the midpoint of protein-protein/PTM, protein-DNA/RNA, and protein-metabolite network in a cell. As the key drivers in cellular metabolism, metabolites are precursors and regulators of protein post-translational modifications [PTMs] that affect protein diversity and functionality. The precisely orchestrated core pattern of metabolic networks refer to paradigm 'metabolites regulate PTMs, PTMs regulate enzymes, and enzymes modulate metabolites' through a multitude of feedback and feed-forward pathway loops. The concept represents a flawless PTM-metabolite-enzyme(protein) regulomics underlined in reprogramming cancer metabolism. Immense interconnectivity of those biomolecules in their spectacular network of intertwined metabolic pathways makes integrated proteomics and metabolomics an excellent opportunity, and the central component of integrative multiomics framework. It will therefore be of significant interest to integrate global proteome and PTM-based proteomics with metabolomics to achieve disease related altered levels of those molecules. Thereby, present update aims to highlight role and analysis of interacting metabolites/oncometabolites, and metabolite-regulated PTMs loop which may function as translational monitoring biomarkers along the reprogramming continuum of oncometabolism.

Cancers in Agreement? Exploring the Cross-Talk of Cancer Metabolomic and Transcriptomic Landscapes Using Publicly Available Data

One of the major hallmarks of cancer is the derailment of a cell's metabolism. The multifaceted nature of cancer and different cancer types is transduced by both its transcriptomic and metabolomic landscapes. In this study, we re-purposed the publicly available transcriptomic and metabolomics data of eight cancer types (breast, lung, gastric, renal, liver, colorectal, prostate, and multiple myeloma) to find and investigate differences and commonalities on a pathway level among different cancer types. Topological analysis of inferred graphical Gaussian association networks showed that cancer was strongly defined in genetic networks, but not in metabolic networks. Using different statistical approaches to find significant differences between cancer and control cases, we highlighted the difficulties of high-level data-merging and in using statistical association networks. Cancer transcriptomics and metabolomics and landscapes were characterized by changed macro-molecule production, however, only major metabolic deregulations with highly impacted pathways were found in liver cancer. Cell cycle was enriched in breast, liver, and colorectal cancer, while breast and lung cancer were distinguished by highly enriched oncogene signaling pathways. A strong inflammatory response was observed in lung cancer and, to some extent, renal cancer. This study highlights the necessity of combining different omics levels to obtain a better description of cancer characteristics.

Comprehensive Dipeptide Analysis Revealed Cancer-Specific Profile in the Liver of Patients with Hepatocellular Carcinoma and Hepatitis

As the physical properties and functionality of dipeptides differ from those of amino acids, they have attracted attention in metabolomics; however, their functions in vivo have not been clarified in detail. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, and its major cause is chronic hepatitis. This study was conducted to explore tumor-specific dipeptide characteristics by performing comprehensive dipeptide analysis in the tumor and surrounding nontumor tissue of patients with HCC. Dipeptides were analyzed by liquid chromatography tandem mass spectrometry and capillary electrophoresis tandem mass spectrometry. Principal component analysis using 236 detected dipeptides showed differences in the dipeptide profiles between nontumor and tumor tissues; however, no clear difference was observed in etiological comparison. In addition, the N- and C-terminal amino acid compositions of the detected dipeptides significantly differed, suggesting the substrate specificity of enzyme proteins, such as peptidase. Furthermore, hepatitis-derived HCC may show a characteristic dipeptide profile even before tumor formation. These results provide insight into HCC pathogenesis and may help identify novel biomarkers for diagnosis.

Comparison of the ischemic and non-ischemic lung cancer metabolome reveals hyper activity of the TCA cycle and autophagy

Recent advances in cancer biology reveal the importance of metabolic changes in cancer; however, less is known about how metabolic pathways in tumors are regulated in vivo. Here, we report analysis of the lung cancer metabolism based on different surgical procedures, namely lobectomy and partial resection. In lobectomy, but not in partial resection, pulmonary arteries and veins are ligated prior to removal of tissues, rendering tissues ischemic. We show that tumors indeed undergo ischemia upon lobectomy and that the tumor metabolome differs markedly from that of tumors removed by partial resection. Comparison of the responses to ischemia in tumor and normal lung tissues revealed that lung cancer tissue exhibits greater TCA cycle and autophagic activity than do normal lung tissues in vivo in patients. Finally, we report that deleting ATG7, which encodes a protein essential for autophagy, antagonizes growth of tumors derived from lung cancer cell lines, suggesting that autophagy confers metabolic advantages to lung cancer. Our findings shed light on divergent metabolic responses to ischemia seen in tumors and normal tissues.

Association between Metabolites and the Risk of Lung Cancer: A Systematic Literature Review and Meta-Analysis of Observational Studies

Globally, lung cancer is the most prevalent cancer type. However, screening and early detection is challenging. Previous studies have identified metabolites as promising lung cancer biomarkers. This systematic literature review and meta-analysis aimed to identify metabolites associated with lung cancer risk in observational studies. The literature search was performed in PubMed and EMBASE databases, up to 31 December 2019, for observational studies on the association between metabolites and lung cancer risk. Heterogeneity was assessed using the I2 statistic and Cochran's Q test. Meta-analyses were performed using either a fixed-effects or random-effects model, depending on study heterogeneity. Fifty-three studies with 297 metabolites were included. Most identified metabolites (252 metabolites) were reported in individual studies. Meta-analyses were conducted on 45 metabolites. Five metabolites (cotinine, creatinine riboside, N-acetylneuraminic acid, proline and r-1,t-2,3,c-4-tetrahydroxy-1,2,3,4-tetrahydrophenanthrene) and five metabolite groups (total 3-hydroxycotinine, total cotinine, total nicotine, total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (sum of concentrations of the metabolite and its glucuronides), and total nicotine equivalent (sum of total 3-hydroxycotinine, total cotinine and total nicotine)) were associated with higher lung cancer risk, while three others (folate, methionine and tryptophan) were associated with lower lung cancer risk. Significant heterogeneity was detected across most studies. These significant metabolites should be further evaluated as potential biomarkers for lung cancer.

Global metabolomics profiling of colorectal cancer in Malaysian patients

Introduction: The serum metabolomics approach has been used to identify metabolite biomarkers that can diagnose colorectal cancer (CRC) accurately and specifically. However, the biomarkers identified differ between studies suggesting that more studies need to be performed to understand the influence of genetic and environmental factors. Therefore, this study aimed to identify biomarkers and affected metabolic pathways in Malaysian CRC patients. Methods: Serum from 50 healthy controls and 50 CRC patients were collected at UKM Medical Centre. The samples were deproteinized with acetonitrile and untargeted metabolomics profile determined using liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOFMS, Agilent USA). The data were analysed using Mass Profiler Professional (Agilent, USA) software. The panel of biomarkers determined were then used to identify CRC from a new set of 20 matched samples. Results: Eleven differential metabolites were identified whose levels were significantly different between CRC patients compared to normal controls. Based on the analysis of the area under the curve, 7 of these metabolites showed high sensitivity and specificity as biomarkers. The use of the 11 metabolites on a new set of samples was able to differentiate CRC from normal samples with 80% accuracy. These metabolites were hypoxanthine, acetylcarnitine, xanthine, uric acid, tyrosine, methionine, lysoPC, lysoPE, citric acid, 5-oxoproline, and pipercolic acid. The data also showed that the most perturbed pathways in CRC were purine, catecholamine, and amino acid metabolisms. Conclusion: Serum metabolomics profiling can be used to identify distinguishing biomarkers for CRC as well as to further our knowledge of its pathophysiological mechanisms.

A transgenic mouse expressing miR-210 in proximal tubule cells shows mitochondrial alteration: possible association of miR-210 with a shift in energy metabolism

Previously we reported that the microRNA miR-210 is aberrantly upregulated in clear cell renal cell carcinoma (ccRCC) via deregulation of the VHL-HIF pathway. In the present study, to investigate the biological impact of miR-210 in ccRCC tumorigenesis, we developed a transgenic mouse line expressing miR-210 in proximal tubule cells under control of the mouse SGLT2/Slc5a2 promoter. Light microscopy revealed desquamation of the tubule cells and regeneration of the proximal tubule, suggesting that miR-210 expression led to damage of the proximal tubule cells. Electron microscopy revealed alterations to the mitochondria in proximal tubule cells, with marked reduction of the mitochondrial inner membrane, which is the main site of ATP production via oxidative phosphorylation (OxPhos). An additional in vitro study revealed that this loss of the inner membrane was associated with downregulation of Iscu and Ndufa4, the target genes of miR-210, suggesting that the miR-210-ISCU/NDUFA4 axis may affect mitochondrial energy metabolism. Furthermore, metabolome analysis revealed activation of anaerobic glycolysis in miR-210-transfected cells, and consistent with this the secretion of lactate, the final metabolite of anaerobic glycolysis, was significantly increased. Lactate concentration was higher in the kidney cortex of transgenic mice relative to wild-type mice, although the difference was not significant (p = 0.070). On the basis of these findings, we propose that miR-210 may induce a shift of energy metabolism from OxPhos to glycolysis by acting on the mitochondrial inner membrane. In addition to activation of glycolysis, we observed activation of the pentose phosphate pathway (PPP) and an increase in the total amount of amino acids in miR-210-transfected cells. This may help cells synthesize nucleotides and proteins for building new cells. These results suggest that miR-210 may be involved in the metabolic changes in the early stage of ccRCC development, helping the cancer cells to acquire growth and survival advantages. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Type III Secretion Effector VopQ of Vibrio parahaemolyticus Modulates Central Carbon Metabolism in Epithelial Cells

The metabolic response of host cells upon infection is pathogen specific, and infection-induced host metabolic reprogramming may have beneficial effects on the proliferation of pathogens. V. parahaemolyticus contains a range of virulence factors to manipulate host signaling pathways and metabolic processes. In this study, we identified that the T3SS1 VopQ effector rewrites host metabolism in conjunction with the inflammation and cell death processes. Understanding how VopQ reprograms host cell metabolism during the infection could help us to identify novel therapeutic strategies to enhance the survival of host cells during V. parahaemolyticus infection.

Vibrio parahaemolyticus is a Gram-negative halophilic pathogen that frequently causes acute gastroenteritis and occasional wound infection. V. parahaemolyticus contains several virulence factors, including type III secretion systems (T3SSs) and thermostable direct hemolysin (TDH). In particular, T3SS1 is a potent cytotoxic inducer, and T3SS2 is essential for causing acute gastroenteritis. Although much is known about manipulation of host signaling transductions by the V. parahaemolyticus effector, little is known about the host metabolomic changes modulated by V. parahaemolyticus. To address this knowledge gap, we performed a metabolomic analysis of the epithelial cells during V. parahaemolyticus infection using capillary electrophoresis-time of flight mass spectrometry (CE-TOF/MS). Our results revealed significant metabolomic perturbations upon V. parahaemolyticus infection. Moreover, we identified that T3SS1’s VopQ effector was responsible for inducing the significant metabolic changes in the infected cells. The VopQ effector dramatically altered the host cell’s glycolytic, tricarboxylic acid cycle (TCA), and amino acid metabolisms. VopQ effector disrupted host cell redox homeostasis by depleting cellular glutathione and subsequently increasing the level of reactive oxygen species (ROS) production.

IMPORTANCE The metabolic response of host cells upon infection is pathogen specific, and infection-induced host metabolic reprogramming may have beneficial effects on the proliferation of pathogens. V. parahaemolyticus contains a range of virulence factors to manipulate host signaling pathways and metabolic processes. In this study, we identified that the T3SS1 VopQ effector rewrites host metabolism in conjunction with the inflammation and cell death processes. Understanding how VopQ reprograms host cell metabolism during the infection could help us to identify novel therapeutic strategies to enhance the survival of host cells during V. parahaemolyticus infection.

Glycolate is a Novel Marker of Vitamin B2 Deficiency Involved in Gut Microbe Metabolism in Mice

Microbes in the human gut play a role in the production of bioactive compounds, including some vitamins. Although several studies attempted to identify definitive markers for certain vitamin deficiencies, the role of gut microbiota in these deficiencies is unclear. To investigate the role of gut microbiota in deficiencies of four vitamins, B₂, B₆, folate, and B₁₂, we conducted a comprehensive analysis of metabolites in mice treated and untreated with antibiotics. We identified glycolate (GA) as a novel marker of vitamin B₂ (VB2) deficiency, and show that gut microbiota sense dietary VB2 deficiency and accumulate GA in response. The plasma GA concentration responded to reduced VB2 supply from both the gut microbiota and the diet. These results suggest that GA is a novel marker that can be used to assess whether or not the net supply of VB2 from dietary sources and gut microbiota is sufficient. We also found that gut microbiota can provide short-term compensation for host VB2 deficiency when dietary VB2 is withheld.

Metabolic and lipidomic characterization of malignant pleural effusion in human lung cancer

Malignant pleural effusion (MPE) is an important hallmark for late-stage lung cancer with metastasis. Current clinical diagnosis methods require tedious work to distinguish MPE from benign pleural effusion (BPE). The objective of this study was to characterize the metabolic signatures in MPE of lung cancer, and identify potential metabolite biomarkers for diagnosis of MPE. MPE from lung cancer (n = 46) and BPE from tuberculosis patients (n = 32) were investigated by liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based global metabolomic and lipidomic profiling. Multivariate partial least-square discriminative analysis models exhibited distinct metabolic profiles between MPE and BPE. A total of 25 ether lipids, including phosphatidylcholines (PC), lysophosphatidylcholines (LPC) and phosphatidylethanolamines (PE), were observed to be significantly downregulated in MPE with excellent diagnostic potential. Plasmalogen PC(40:3p) showed highest AUC value of 0.953 in receiver operating characteristic (ROC) model. Oxidized polyunsaturated fatty acids (PUFA) were upregulated in MPE. The obtained results implied a high oxidative stress and peroxisome disorder in lung cancer patients. Combined metabolomic and lipidomic profiling have discovered potential biomarkers in MPE with excellent clinical diagnostic capability. Dysregulated ether lipids and oxidized PUFAs have implied an aberrant redox metabolism, which provides novel insights into the pathology of MPE in lung cancer.

A New Era of Prostate Cancer Precision Medicine

Prostate cancer is the second most common male cancer affecting Western society. Despite substantial advances in the exploration of prostate cancer biomarkers and treatment strategies, men are over diagnosed with inert prostate cancer, while there is also a substantial mortality from the invasive disease. Precision medicine is the management of treatment profiles across different cancers predicting therapies for individual cancer patients. With strategies including individual genomic profiling and targeting specific cancer pathways, precision medicine for prostate cancer has the potential to impose changes in clinical practices. Some of the recent advances in prostate cancer precision medicine comprise targeting gene fusions, genome editing tools, non-coding RNA biomarkers, and the promise of liquid tumor profiling. In this review, we will discuss these recent scientific advances to scale up these approaches and endeavors to overcome clinical barriers for prostate cancer precision medicine.

A metabolic profile of routine needle biopsies identified tumor type specific metabolic signatures for breast cancer stratification: a pilot study

INTRODUCTION

Metabolomics has recently emerged as a tool for understanding comprehensive tumor-associated metabolic dysregulation. However, only limited application of this technology has been introduced into the clinical setting of breast cancer.

OBJECTIVES

The aim of this study was to determine the feasibility of metabolome analysis using routine CNB/VAB samples from breast cancer patients and to elucidate metabolic signatures using metabolic profiling.

METHODS

After breast cancer screenings, 20 consecutive patients underwent CNB/VAB, and diagnosed with benign, DCIS and IDC by histology. Metabolome analysis was performed using CE-MS. Differential metabolites were then analyzed and evaluated with MetaboAnalyst 4.0.

RESULTS

We measured 116-targeted metabolites involved in energy metabolism. Principal component analysis and unsupervised hierarchical analysis revealed a distinct metabolic signature unique to namely "pure" IDC samples, whereas that of DCIS was similar to benign samples. Pathway analysis unveiled the most affected pathways of the "pure" IDC metabotype, including "pyrimidine," "alanine, aspartate, and glutamate" and "arginine and proline" pathways.

CONCLUSIONS

Our proof-of-concept study demonstrated that CE-MS-based CNB/VAB metabolome analysis is feasible for implementation in routine clinical settings. The most affected pathways in this study may contribute to improved breast cancer stratification and precision medicine.

MITF controls the TCA cycle to modulate the melanoma hypoxia response

In response to the dynamic intra-tumor microenvironment, melanoma cells adopt distinct phenotypic states associated with differential expression of the microphthalmia-associated transcription factor (MITF). The response to hypoxia is driven by hypoxia-inducible transcription factors (HIFs) that reprogram metabolism and promote angiogenesis. HIF1α indirectly represses MITF that can activate HIF1α expression. Although HIF and MITF share a highly related DNA-binding specificity, it is unclear whether they co-regulate subset of target genes. Moreover, the genomewide impact of hypoxia on melanoma and whether melanoma cell lines representing different phenotypic states exhibit distinct hypoxic responses is unknown. Here we show that three different melanoma cell lines exhibit widely different hypoxia responses with only a core 23 genes regulated in common after 12 hr in hypoxia. Surprisingly, under hypoxia MITF is transiently up-regulated by HIF1α and co-regulates a subset of HIF targets including VEGFA. Significantly, we also show that MITF represses itself and also regulates SDHB to control the TCA cycle and suppress pseudo-hypoxia. Our results reveal a previously unsuspected role for MITF in metabolism and the network of factors underpinning the hypoxic response in melanoma.

Analytical strategies for the determination of amino acids: Past, present and future trends

This review describes the analytical methods that have been developed over the years to tackle the high polarity and non-chromophoric nature of amino acids (AAs). First, the historical methods are briefly presented, with a strong focus on the use of derivatization reagents to make AAs detectable with spectroscopic techniques (ultraviolet and fluorescence) and/or sufficiently retained in reversed phase liquid chromatography. Then, an overview of the current analytical strategies for achiral separation of AAs is provided, in which mass spectrometry (MS) becomes the most widely used detection mode in combination with innovative liquid chromatography or capillary electrophoresis conditions to detect AAs at very low concentration in complex matrixes. Finally, some future trends of AA analysis are provided in the last section of the review, including the use of supercritical fluid chromatography (SFC), multidimensional liquid chromatography and electrophoretic separations, hyphenation of ion exchange chromatography to mass spectrometry, and use of ion mobility spectrometry mass spectrometry (IM-MS). Various application examples will also be presented throughout the review to highlight the benefits and limitations of these different analytical approaches for AAs determination.

Mitochondrial supercomplex assembly promotes breast and endometrial tumorigenesis by metabolic alterations and enhanced hypoxia tolerance

Recent advance in cancer research sheds light on the contribution of mitochondrial respiration in tumorigenesis, as they efficiently produce ATP and oncogenic metabolites that will facilitate cancer cell growth. Here we show that a stabilizing factor for mitochondrial supercomplex assembly, COX7RP/COX7A2L/SCAF1, is abundantly expressed in clinical breast and endometrial cancers. Moreover, COX7RP overexpression associates with prognosis of breast cancer patients. We demonstrate that COX7RP overexpression in breast and endometrial cancer cells promotes in vitro and in vivo growth, stabilizes mitochondrial supercomplex assembly even in hypoxic states, and increases hypoxia tolerance. Metabolomic analyses reveal that COX7RP overexpression modulates the metabolic profile of cancer cells, particularly the steady-state levels of tricarboxylic acid cycle intermediates. Notably, silencing of each subunit of the 2-oxoglutarate dehydrogenase complex decreases the COX7RP-stimulated cancer cell growth. Our results indicate that COX7RP is a growth-regulatory factor for breast and endometrial cancer cells by regulating metabolic pathways and energy production.

CE-MS for anionic metabolic profiling: An overview of methodological developments

The efficient profiling of highly polar and charged metabolites in biological samples remains a huge analytical challenge in metabolomics. Over the last decade, new analytical techniques have been developed for the selective and sensitive analysis of polar ionogenic compounds in various matrices. Still, the analysis of such compounds, notably for acidic ionogenic metabolites, remains a challenging endeavor, even more when the available sample size becomes an issue for the total analytical workflow. In this paper, we give an overview of the possibilities of capillary electrophoresis-mass spectrometry (CE-MS) for anionic metabolic profiling by focusing on main methodological developments. Attention is paid to the development of improved separation conditions and new interfacing designs in CE-MS for anionic metabolic profiling. A complete overview of all CE-MS-based methods developed for this purpose is provided in table format (Table 1) which includes information on sample type, separation conditions, mass analyzer and limits of detection (LODs). Selected applications are discussed to show the utility of CE-MS for anionic metabolic profiling, especially for small-volume biological samples. On the basis of the examination of the reported literature in this specific field, we conclude that there is still room for the design of a highly sensitive and reliable CE-MS method for anionic metabolic profiling. A rigorous validation and the availability of standard operating procedures would be highly favorable in order to make CE-MS an alternative, viable analytical technique for metabolomics.

Liquid Biopsy in Lung Cancer Screening: The Contribution of Metabolomics. Results of A Pilot Study

Background: Lung cancer is the most common cause of cancer-related deaths worldwide. Early diagnosis is crucial to increase the curability chance of the patients. Low dose CT screening can reduce lung cancer mortality, but it is associated with several limitations. Metabolomics is a promising technique for cancer diagnosis due to its ability to provide chemical phenotyping data. The intent of our study was to explore metabolomic effects and profiles of lung cancer patients to determine if metabolic perturbations in the SSAT-1/polyamine pathway can distinguish between healthy participants and lung cancer patients as a diagnostic and treatment monitoring tool. Patients and Methods: Plasma samples were collected as part of the SSAT1 Amantadine Cancer Study. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to identify and quantify metabolite concentrations in lung cancer patient and control samples. Standard statistical analyses were performed to determine whether metabolite concentrations could differentiate between healthy subjects and lung cancer patients, as well as risk prediction modeling applied to determine whether metabolic profiles could provide an indication of cancer progression in later stage patients. Results: A panel consisting of 14 metabolites, which included 6 metabolites in the polyamine pathway, was identified that correctly discriminated lung cancer patients from controls with an area under the curve of 0.97 (95% CI: 0.875-1.0). Conclusion: When used in conjunction with the SSAT-1/polyamine pathway, these metabolites may provide the specificity required for diagnosing lung cancer from other cancer types and could be used as a diagnostic and treatment monitoring tool.

Metabolomic approach to the exploration of biomarkers associated with disease activity in rheumatoid arthritis

We aimed to investigate metabolites associated with the 28-joint disease activity score based on erythrocyte sedimentation rate (DAS28-ESR) in patients with rheumatoid arthritis (RA) using capillary electrophoresis quadrupole time-of-flight mass spectrometry. Plasma and urine samples were collected from 32 patients with active RA (DAS28-ESR≥3.2) and 17 with inactive RA (DAS28-ESR<3.2). We found 15 metabolites in plasma and 20 metabolites in urine which showed a significant but weak positive or negative correlation with DAS28-ESR. When metabolites between active and inactive patients were compared, 9 metabolites in plasma and 15 in urine were found to be significantly different. Consequently, we selected 11 metabolites in plasma and urine as biomarker candidates which significantly correlated positively or negatively with DAS28-ESR, and significantly differed between active and inactive patients. When a multiple logistic regression model was built to discriminate active and inactive cohorts, three variables-histidine and guanidoacetic acid from plasma and hypotaurine from urine-generated a high area under the receiver operating characteristic (ROC) curve value (AUC = 0.8934). Thus, this metabolomics approach appeared to be useful for investigating biomarkers of RA. Combination of plasma and urine analysis may lead to more precise and reliable understanding of the disease condition. We also considered the pathophysiological significance of the found biomarker candidates.

[Study on the Metabolic Reprogramming of Lung Cancer Cells Regulated by Docetaxel Based on Metabolomics]

背景与目的

多西他赛是一种临床常用的抗肿瘤药物，是晚期非小细胞肺癌（non-small cell lung cancer, NSCLC）的一线用药。然而，多西他赛抗NSCLC作用的分子机制尚不明确。研究表明肿瘤细胞的代谢重编程在肿瘤发生发展过程中发挥重要作用。本研究旨在通过结合代谢组学分析及生物学手段来探讨多西他赛所影响的NSCLC细胞代谢通路。

方法

首先，通过CCK-8实验分析多西他赛对NSCLC细胞活力的影响，筛选合适药物浓度。接下来，通过基于气相色谱质谱联用（gas chromatography-mass spectrometry, GC-MS）的代谢组学技术分析多西他赛处理和未处理的A549和H1299细胞。并通过统计学计算得到处理组和未处理组间的差异代谢物。最后，通过蛋白质免疫印迹分析（Western blot）多西他赛对其所调控的相关代谢途径中关键酶蛋白质表达水平的影响。

结果

多西他赛可时间依赖和浓度依赖地抑制A549和H1299细胞活力。随着多西他赛处理时间延长，凋亡敏感蛋白质多聚二磷酸腺苷核糖聚合酶[Poly(ADP-)Polymerase, PARP]逐渐被激活裂解形成P89片段。代谢组学分析发现，药物处理后的A549和H1299细胞内，8种代谢物均发生显著变化，主要集中于三羧酸（tricarboxylic acid, TCA）循环代谢通路。同时，药物处理后，TCA循环关键调控酶异柠檬酸脱氢酶蛋白质表达水平显著下降。

结论

多西他赛诱导NSCLC增殖抑制及凋亡的效应可能与下调异柠檬酸脱氢酶，进而抑制三羧酸循环代谢途径有关。

Metabolomics Contributions to the Discovery of Prostate Cancer Biomarkers

Prostate cancer (PCa) is one of the most frequently diagnosed cancers and a leading cause of death among men worldwide. Despite extensive efforts in biomarker discovery during the last years, currently used clinical biomarkers are still lacking enough specificity and sensitivity for PCa early detection, patient prognosis, and monitoring. Therefore, more precise biomarkers are required to improve the clinical management of PCa patients. In this context, metabolomics has shown to be a promising and powerful tool to identify novel PCa biomarkers in biofluids. Thus, changes in polyamines, tricarboxylic acid (TCA) cycle, amino acids, and fatty acids metabolism have been reported in different studies analyzing PCa patients' biofluids. The review provides an up-to-date summary of the main metabolic alterations that have been described in biofluid-based studies of PCa patients, as well as a discussion regarding their potential to improve clinical PCa diagnosis and prognosis. Furthermore, a summary of the most significant findings reported in these studies and the connections and interactions between the different metabolic changes described has also been included, aiming to better describe the specific metabolic signature associated to PCa.

GLUT6 is a lysosomal transporter that is regulated by inflammatory stimuli and modulates glycolysis in macrophages

The solute carrier family is an important protein class governing compound transport across membranes. However, some of its members remain functionally unidentified. We analyzed ChIP-seq data for the NF-κB family transcription factor RelA and identified GLUT6 as a functionally uncharacterized transporter that putatively works in inflammatory responses. Inflammatory stimuli increase GLUT6 expression level, although GLUT6-knockout mice exhibit a subtle phenotype to lipopolysaccharide administration. Metabolomics and in vitro analyses show that GLUT6 functions as a glycolysis modulator in inflammatory macrophages. GLUT6 does not mediate glucose uptake and is localized on lysosomal membranes. We conclude that GLUT6 is a lysosomal transporter that is regulated by inflammatory stimuli and modulates inflammatory responses by affecting the metabolic shift in macrophages.

Interplay between hypoxia and androgen controls a metabolic switch conferring resistance to androgen/AR-targeted therapy

Despite recent advances, the efficacy of androgen/androgen receptor (AR)-targeted therapy remains  limited for many patients with metastatic prostate cancer. This is in part because prostate cancers adaptively switch to the androgen/AR-independent pathway for survival and growth, thereby conferring therapy resistance. Tumor hypoxia is considered as a major cause of treatment resistance. However, the exact mechanism is largely unclear. Here we report that chronic-androgen deprivation therapy (ADT) in the condition of hypoxia induces adaptive androgen/AR-independence, and therefore confers resistance to androgen/AR-targeted therapy, e.g., enzalutamide. Mechanistically, this is mediated by glucose-6-phosphate isomerase (GPI), which is transcriptionally repressed by AR in hypoxia, but restored and increased by AR inhibition. In turn, GPI maintains glucose metabolism and energy homeostasis in hypoxia by redirecting the glucose flux from androgen/AR-dependent pentose phosphate pathway (PPP) to hypoxia-induced glycolysis pathway, thereby reducing the growth inhibitory effect of enzalutamide. Inhibiting GPI overcomes the therapy resistance in hypoxia in vitro and increases enzalutamide efficacy in vivo.

CE-MS for metabolomics: Developments and applications in the period 2016-2018

In the field of metabolomics, CE-MS is now recognized as a strong analytical technique for the analysis of (highly) polar and charged metabolites in a wide range of biological samples. Over the past few years, significant attention has been paid to the design and improvement of CE-MS approaches for (large-scale) metabolic profiling studies and for establishing protocols in order to further expand the role of CE-MS in metabolomics. In this paper, which is a follow-up of a previous review paper covering the years 2014-2016 (Electrophoresis 2017, 38, 190-202), main advances in CE-MS approaches for metabolomics studies are outlined covering the literature from July 2016 to June 2018. Aspects like developments in interfacing designs and data analysis tools for improving the performance of CE-MS for metabolomics are discussed. Representative examples highlight the utility of CE-MS in the fields of biomedical, clinical, microbial, and plant metabolomics. A complete overview of recent CE-MS-based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings and MS detection mode. Finally, some general conclusions and perspectives are given.

Metabolomic profiling of human lung tumor tissues - nucleotide metabolism as a candidate for therapeutic interventions and biomarkers

Although metabolomics has attracted considerable attention in the field of lung cancer (LC) detection and management, only a very limited number of works have applied it to tissues. As such, the aim of this study was the thorough analysis of metabolic profiles of relevant LC tissues, including the most important histological subtypes (adenocarcinoma and squamous cell lung carcinoma). Mass spectrometry‐based metabolomics, along with genetic expression and histological analyses, were performed as part of this study, the widest to date, to identify metabolic alterations in tumors of the most relevant histological subtypes in lung. A total of 136 lung tissue samples were analyzed and 851 metabolites were identified through metabolomic analysis. Our data show the existence of a clear metabolic alteration not only between tumor vs. nonmalignant tissue in each patient, but also inherently intrinsic changes in both AC and SCC. Significant changes were observed in the most relevant biochemical pathways, and nucleotide metabolism showed an important number of metabolites with high predictive capability values. The present study provides a detailed analysis of the metabolomic changes taking place in relevant biochemical pathways of the most important histological subtypes of LC, which can be used as biomarkers and also to identify novel targets.

A review of metabolism-associated biomarkers in lung cancer diagnosis and treatment

INTRODUCTION

Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection has proven essential to extend survival. Genomic and proteomic advances have provided impetus to the effort dedicated to detect and diagnose the disease at an earlier stage. Recently, the study of metabolites associated with tumor formation and progression has inaugurated the era of cancer metabolomics to aid in this effort.

OBJECTIVES

This review summarizes recent work regarding novel metabolites with the potential to serve as biomarkers for early lung tumor detection, evaluation of disease progression, and prediction of patient outcomes.

METHOD

We compare the metabolite profiling of cancer patients with that of healthy individuals, and the metabolites identified in tissue and biofluid samples and their usefulness as lung cancer biomarkers. We discuss metabolite alterations in tumor versus paired non-tumor lung tissues, as well as metabolite alterations in different stages of lung cancers and their usefulness as indicators of disease progression and overall survival. We evaluate metabolite dysregulation in different types of lung cancers, and those associated with lung cancer versus other lung diseases. We also examine metabolite differences between lung cancer patients and smokers/risk-factor individuals.

RESULT

Although an extensive list of metabolites has been evaluated to distinguish between these cases, refinement of methods is further required for adequate patient diagnosis.

CONCLUSION

We conclude that with technological advancement, metabolomics may be able to replace more invasive and costly diagnostic procedures while also providing the means to more effectively tailor treatment to patient-specific tumors.