1H-NMR based metabonomic profiling of human esophageal cancer tissue

Metabolomic profiling of upper GI malignancies in blood and tissue: a systematic review and meta-analysis

OBJECTIVE

To conduct a systematic review and meta-analysis of case-control and cohort human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on esophageal cancer (EC), cancer of the gastroesophageal junction (GEJ), and gastric cancer (GC) in blood and tissue.

BACKGROUND

Upper gastrointestinal cancers (UGC), predominantly EC, GEJ, and GC, are malignant tumour types with high morbidity and mortality rates. Numerous studies have focused on metabolomic profiling of UGC in recent years. In this systematic review and meta-analysis, we have provided a collective summary of previous findings on metabolites and metabolomic profiling associated with EC, GEJ and GC.

METHODS

Following the PRISMA procedure, a systematic search of four databases (Embase, PubMed, MEDLINE, and Web of Science) for molecular epidemiologic studies on the metabolomic profiles of EC, GEJ and GC was conducted and registered at PROSPERO (CRD42023486631). The Newcastle-Ottawa Scale (NOS) was used to benchmark the risk of bias for case-controlled and cohort studies. QUADOMICS, an adaptation of the QUADAS-2 (Quality Assessment of Diagnostic Accuracy) tool, was used to rate diagnostic accuracy studies. Original articles comparing metabolite patterns between patients with and without UGC were included. Two investigators independently completed title and abstract screening, data extraction, and quality evaluation. Meta-analysis was conducted whenever possible. We used a random effects model to investigate the association between metabolite levels and UGC.

RESULTS

A total of 66 original studies involving 7267 patients that met the required criteria were included for review. 169 metabolites were differentially distributed in patients with UGC compared to healthy patients among 44 GC, 9 GEJ, and 25 EC studies including metabolites involved in glycolysis, anaerobic respiration, tricarboxylic acid cycle, and lipid metabolism. Phosphatidylcholines, eicosanoids, and adenosine triphosphate were among the most frequently reported lipids and metabolites of cellular respiration, while BCAA, lysine, and asparagine were among the most commonly reported amino acids. Previously identified lipid metabolites included saturated and unsaturated free fatty acids and ketones. However, the key findings across studies have been inconsistent, possibly due to limited sample sizes and the majority being hospital-based case-control analyses lacking an independent replication group.

CONCLUSION

Thus far, metabolomic studies have provided new opportunities for screening, etiological factors, and biomarkers for UGC, supporting the potential of applying metabolomic profiling in early cancer diagnosis. According to the results of our meta-analysis especially BCAA and TMAO as well as certain phosphatidylcholines should be implicated into the diagnostic procedure of patients with UGC. We envision that metabolomics will significantly enhance our understanding of the carcinogenesis and progression process of UGC and may eventually facilitate precise oncological and patient-tailored management of UGC.

Metabolites, Healthy Lifestyle, and Polygenic Risk Score Associated with Upper Gastrointestinal Cancer: Findings from the UK Biobank Study

Previous metabolomics studies have highlighted the predictive value of metabolites on upper gastrointestinal (UGI) cancer, while most of them ignored the potential effects of lifestyle and genetic risk on plasma metabolites. This study aimed to evaluate the role of lifestyle and genetic risk in the metabolic mechanism of UGI cancer. Differential metabolites of UGI cancer were identified using partial least-squares discriminant analysis and the Wilcoxon test. Then, we calculated the healthy lifestyle index (HLI) score and polygenic risk score (PRS) and divided them into three groups, respectively. A total of 15 metabolites were identified as UGI-cancer-related differential metabolites. The metabolite model (AUC = 0.699) exhibited superior discrimination ability compared to those of the HLI model (AUC = 0.615) and the PRS model (AUC = 0.593). Moreover, subgroup analysis revealed that the metabolite model showed higher discrimination ability for individuals with unhealthy lifestyles compared to that with healthy individuals (AUC = 0.783 vs 0.684). Furthermore, in the genetic risk subgroup analysis, individuals with a genetic predisposition to UGI cancer exhibited the best discriminative performance in the metabolite model (AUC = 0.770). These findings demonstrated the clinical significance of metabolic biomarkers in UGI cancer discrimination, especially in individuals with unhealthy lifestyles and a high genetic risk.

A Transfer Hydrogenation Approach to Activity-Based Sensing of Formate in Living Cells

Formate is a major reactive carbon species in one-carbon metabolism, where it serves as an endogenous precursor for amino acid and nucleic acid biosynthesis and a cellular source of NAD(P)H. On the other hand, aberrant elevations in cellular formate are connected to progression of serious diseases, including cancer and Alzheimer's disease. Traditional methods for formate detection in biological environments often rely on sample destruction or extensive processing, resulting in a loss of spatiotemporal information. To help address these limitations, here we present the design, synthesis, and biological evaluation of a first-generation activity-based sensing system for live-cell formate imaging that relies on iridium-mediated transfer hydrogenation chemistry. Formate facilitates an aldehyde-to-alcohol conversion on various fluorophore scaffolds to enable fluorescence detection of this one-carbon unit, including through a two-color ratiometric response with internal calibration. The resulting two-component probe system can detect changes in formate levels in living cells with a high selectivity over potentially competing biological analytes. Moreover, this activity-based sensing system can visualize changes in endogenous formate fluxes through alterations of one-carbon pathways in cell-based models of human colon cancer, presaging the potential utility of this chemical approach to probe the continuum between one-carbon metabolism and signaling in cancer and other diseases.

Serine synthesis and catabolism in starved lung cancer and primary bronchial epithelial cells

Serine and glycine give rise to important building blocks in proliferating cells. Both amino acids are either synthesized de novo or taken up from the extracellular space. In lung cancer, serine synthesis gene expression is variable, yet, expression of the initial enzyme, phosphoglycerate dehydrogenase (PHGDH), was found to be associated with poor prognosis. While the contribution of de novo synthesis to serine pools has been shown to be enhanced by serine starvation, the impact of glucose deprivation, a commonly found condition in solid cancers is poorly understood. Here, we utilized a stable isotopic tracing approach to assess serine and glycine de novo synthesis and uptake in different lung cancer cell lines and normal bronchial epithelial cells in variable serine, glycine, and glucose conditions. Under low glucose supplementation (0.2 mM, 3-5% of normal plasma levels), serine de novo synthesis was maintained or even activated. As previously reported, also gluconeogenesis supplied carbons from glutamine to serine and glycine under these conditions. Unexpectedly, low glucose treatment consistently enhanced serine to glycine conversion, along with an up-regulation of the mitochondrial one-carbon metabolism enzymes, serine hydroxymethyltransferase (SHMT2) and methylenetetrahydrofolate dehydrogenase (MTHFD2). The relative contribution of de novo synthesis greatly increased in low serine/glycine conditions. In bronchial epithelial cells, adaptations occurred in a similar fashion as in cancer cells, but serine synthesis and serine to glycine conversion, as assessed by label enrichments and gene expression levels, were generally lower than in (PHGDH positive) cancer cells. In summary, we found a variable contribution of glucose or non-glucose carbon sources to serine and glycine and a high adaptability of the downstream one-carbon metabolism pathway to variable glucose supply.

SHMT2 regulates esophageal cancer cell progression and immune Escape by mediating m6A modification of c-myc

BACKGROUND

In recent years, the role of altered cellular metabolism in tumor progression has attracted widespread attention. Related metabolic enzymes have also been considered as potential cancer therapeutic targets. Serine hydroxymethyltransferase 2 (SHMT2) has been reported to be upregulated in several cancers and associated with poor prognosis. However, there are few studies of SHMT2 in esophageal cancer (EC), and the related functions and mechanisms also need to be further explored.

METHODS

In this study, we first analyzed SHMT2 expression in EC by online database and clinical samples. Then, the biological functions of SHMT2 in EC were investigated by cell and animal experiments. The intracellular m6A methylation modification levels were also evaluated by MeRIP. Linked genes and mechanisms of SHMT2 were analyzed by bioinformatics and rescue experiments.

RESULTS

We found that SHMT2 expression was abnormally upregulated in EC and associated with poor prognosis. Functionally, SHMT2 silencing suppressed c-myc expression in an m6A-dependent manner, thereby blocking the proliferation, migration, invasion and immune escape abilities of EC cells. Mechanistically, SHMT2 encouraged the accumulation of methyl donor SAM through a one-carbon metabolic network, thereby regulating the m6A modification and stability of c-myc mRNA in a METTL3/FTO/ALKBH5/IGF2BP2-dependent way. In vivo animal experiments also demonstrated that SHMT2 mediated MYC expression by m6A-methylation modification, thus boosting EC tumorigenesis.

CONCLUSION

In conclusion, our data illustrated that SHMT2 regulated malignant progression and immune escape of EC cell through c-myc m6A modification. These revealed mechanisms related to SHMT2 in EC and maybe offer promise for the development of new therapeutic approaches.

1H NMR-based metabolomics of paired tissue, serum and urine samples reveals an optimized panel of biofluids metabolic biomarkers for esophageal cancer

INTRODUCTION

The goal of this study was to establish an optimized metabolic panel by combining serum and urine biomarkers that could reflect the malignancy of cancer tissues to improve the non-invasive diagnosis of esophageal squamous cell cancer (ESCC).

METHODS

Urine and serum specimens representing the healthy and ESCC individuals, together with the paralleled ESCC cancer tissues and corresponding distant non-cancerous tissues were investigated in this study using the high-resolution 600 MHz 1H-NMR technique.

RESULTS

We identified distinct 1H NMR-based serum and urine metabolic signatures respectively, which were linked to the metabolic profiles of esophageal-cancerous tissues. Creatine and glycine in both serum and urine were selected as the optimal biofluids biomarker panel for ESCC detection, as they were the overlapping discriminative metabolites across serum, urine and cancer tissues in ESCC patients. Also, the were the major metabolites involved in the perturbation of "glycine, serine, and threonine metabolism", the significant pathway alteration associated with ESCC progression. Then a visual predictive nomogram was constructed by combining creatine and glycine in both serum and urine, which exhibited superior diagnostic efficiency (with an AUC of 0.930) than any diagnostic model constructed by a single urine or serum metabolic biomarkers.

DISCUSSION

Overall, this study highlighted that NMR-based biofluids metabolomics fingerprinting, as a non-invasive predictor, has the potential utility for ESCC detection. Further studies based on a lager number size and in combination with other omics or molecular biological approaches are needed to validate the metabolic pathway disturbances in ESCC patients.

Metabolomics of Esophageal Squamous Cell Carcinoma Tissues: Potential Biomarkers for Diagnosis and Promising Targets for Therapy

Background

The incidence of esophageal squamous cell carcinoma in China ranks first in the world. The early diagnosis technology is underdeveloped, and the prognosis is poor, which seriously threatens the quality of life of the Chinese people. Epidemiological findings are related to factors such as diet, living habits, and age. The specific mechanism is not clear yet. Metabolomics is a kind of omics that simultaneously and quantitatively analyzes the comprehensive profile of metabolites in living systems. It has unique advantages in the study of the diagnosis and pathogenesis of tumor-related diseases, especially in the search for biomarkers. Therefore, it is desirable to perform metabolic profiling analysis of cancer tissues through metabolomics to find potential biomarkers for the diagnosis and treatment of esophageal squamous cell carcinoma.

Methods

HPLC-TOF-MS/MS technology and Illumina Hiseq Xten Sequencing was used for the analysis of 210 pairs of matched esophageal squamous cell carcinoma tissues and normal tissues in Zhenjiang City, Jiangsu Province, a high-incidence area of esophageal cancer in China. Bioinformatics analysis was also performed.

Results

Through metabolomic and transcriptomic analysis, this study found that a total of 269 differential metabolites were obtained in esophageal squamous cell carcinoma and normal tissues, and 48 differential metabolic pathways were obtained through KEGG enrichment analysis. After further screening and identification, 12 metabolites with potential biomarkers to differentiate esophageal squamous cell carcinoma from normal tissues were obtained.

Conclusions

From the metabolomic data, 4 unknown compounds were found to be abnormally expressed in esophageal squamous cell carcinoma for the first time, such as 9,10-epoxy-12,15-octadecadienoate; 3 metabolites were found in multiple abnormal expression in another tumor, but upregulation or downregulation was found for the first time in esophageal cancer, such as oleoyl glycine; at the same time, it was further confirmed that five metabolites were abnormally expressed in esophageal squamous cell carcinoma, which was similar to the results of other studies, such as PE.

Unraveling the Rewired Metabolism in Lung Cancer Using Quantitative NMR Metabolomics

Lung cancer cells are well documented to rewire their metabolism and energy production networks to enable proliferation and survival in a nutrient-poor and hypoxic environment. Although metabolite profiling of blood plasma and tissue is still emerging in omics approaches, several techniques have shown potential in cancer diagnosis. In this paper, the authors describe the alterations in the metabolic phenotype of lung cancer patients. In addition, we focus on the metabolic cooperation between tumor cells and healthy tissue. Furthermore, the authors discuss how metabolomics could improve the management of lung cancer patients.

1H-NMR based metabolic study of MMTV-PyMT mice along with pathological progress to screen biomarkers for the early diagnosis of breast cancer

This study showed the common metabolic changes between BC patients and mice, which were related to pathological processes.

Oncogenic Ras expression increases cellular formate production

One-carbon units, critical intermediates for cell growth, may be produced by a variety of means, one of which is via the production of formate. Excessive formate accumulation, known as formate overflow and a characteristic of oxidative cancer, has been observed in cancer cells. However, the basis for this high rate of formate production is unknown. We examined the effect of elevated expression of oncogenic Ras (RasV12), on formate production in NIH-3T3 cells (mouse fibroblasts) cultured with either labelled ¹³C-serine or ¹³C-glycine. Formate accumulation by the fibroblasts transformed by RasV12 was increased two-threefold over those by vector control (Babe) cells. The production of formate exceeded the rate of utilization in both cell types. ¹³C-formate was produced almost exclusively from the #3 carbon of ¹³C-serine. Virtually no labelled formate was produced from either the #2 carbon of serine or the #2 carbon of glycine. The increased formate production by RasV12 cells was associated with increased mRNA abundances for enzymes of formate production in both the mitochondria and the cytosol. Thus, we find the oncogenic RasV12 significantly increases formate overflow and may be one way for tumor cells to produce one-carbon units required for enhanced proliferation of these cells and/or for other processes which have not been identified.

Plasma-metabolite-based machine learning is a promising diagnostic approach for esophageal squamous cell carcinoma investigation

The aim of this study was to develop a diagnostic strategy for esophageal squamous cell carcinoma (ESCC) that combines plasma metabolomics with machine learning algorithms. Plasma-based untargeted metabolomics analysis was performed with samples derived from 88 ESCC patients and 52 healthy controls. The dataset was split into a training set and a test set. After identification of differential metabolites in training set, single-metabolite-based receiver operating characteristic (ROC) curves and multiple-metabolite-based machine learning models were used to distinguish between ESCC patients and healthy controls. Kaplan-Meier survival analysis and Cox proportional hazards regression analysis were performed to investigate the prognostic significance of the plasma metabolites. Finally, twelve differential plasma metabolites (six up-regulated and six down-regulated) were annotated. The predictive performance of the six most prevalent diagnostic metabolites through the diagnostic models in the test set were as follows: arachidonic acid (accuracy: 0.887), sebacic acid (accuracy: 0.867), indoxyl sulfate (accuracy: 0.850), phosphatidylcholine (PC) (14:0/0:0) (accuracy: 0.825), deoxycholic acid (accuracy: 0.773), and trimethylamine N-oxide (accuracy: 0.653). The prediction accuracies of the machine learning models in the test set were partial least-square (accuracy: 0.947), random forest (accuracy: 0.947), gradient boosting machine (accuracy: 0.960), and support vector machine (accuracy: 0.980). Additionally, survival analysis demonstrated that acetoacetic acid was an unfavorable prognostic factor (hazard ratio (HR): 1.752), while PC (14:0/0:0) (HR: 0.577) was a favorable prognostic factor for ESCC. This study devised an innovative strategy for ESCC diagnosis by combining plasma metabolomics with machine learning algorithms and revealed its potential to become a novel screening test for ESCC.

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Six most prevalent diagnostic plasma metabolites were identified in ESCC.

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Plasma-metabolite-based machine learning models (PLS, RF, GBM, and SVM) for ESCC diagnosis.

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Acetoacetic acid was an unfavorable prognostic factor, while PC (14:0/0:0) was a favorable prognostic factor for ESCC.

A systematic review of metabolomic profiling of gastric cancer and esophageal cancer

Objective: Upper gastrointestinal (UGI) cancers, predominantly gastric cancer (GC) and esophageal cancer (EC), are malignant tumor types with high morbidity and mortality rates. Accumulating studies have focused on metabolomic profiling of UGI cancers in recent years. In this systematic review, we have provided a collective summary of previous findings on metabolites and metabolomic profiling associated with GC and EC.

Methods: A systematic search of three databases (Embase, PubMed, and Web of Science) for molecular epidemiologic studies on the metabolomic profiles of GC and EC was conducted. The Newcastle–Ottawa Scale (NOS) was used to assess the quality of the included articles.

Results: A total of 52 original studies were included for review. A number of metabolites were differentially distributed between GC and EC cases and non-cases, including those involved in glycolysis, anaerobic respiration, tricarboxylic acid cycle, and protein and lipid metabolism. Lactic acid, glucose, citrate, and fumaric acid were among the most frequently reported metabolites of cellular respiration while glutamine, glutamate, and valine were among the most commonly reported amino acids. The lipid metabolites identified previously included saturated and unsaturated free fatty acids, aldehydes, and ketones. However, the key findings across studies to date have been inconsistent, potentially due to limited sample sizes and the majority being hospital-based case-control analyses lacking an independent replication group.

Conclusions: Studies on metabolomics have thus far provided insights into etiological factors and biomarkers for UGI cancers, supporting the potential of applying metabolomic profiling in cancer prevention and management efforts.

Parotid saliva 1 H-NMR analysis for colon cancer metabolomics: A case report

BACKGROUND

A key priority in colon cancer research is the identification of molecular biomarkers to improve early diagnosis, guide prognosis, and the design of new therapeutic approaches. Saliva is a powerful diagnostic biofluid that can be used to detect systemic alterations. This study aimed to investigate the parotid saliva (PS) metabolic Proton Nuclear Magnetic Resonance (¹ H-NMR) profile of a patient diagnosed with colon cancer, and the subsequent changes 1 year after the end of chemotherapy.

CASE REPORT

We describe the ¹ H-NMR PS spectrum of a 65-year-old woman diagnosed with colon cancer (G3 pT3 pN1c) (T0), and the changes in the spectrum from PS collected 1 year after the end of chemotherapy (XELOX: capecitabine plus oxaliplatin) (T1). The data was co-analyzed with blood test cancer antigens (S-CEA; S-CA19-9) and thyroid peroxidase antibody (TPOAb) measurements obtained simultaneously in order to identify peaks and interpret the spectra. The blood cancer antigens (S-CEA; S-CA19-9) and the PS ¹ H-NMR peaks for fatty acids, lactate, acetate, N-acetyl sugars, citrate, tyrosine, saccharides, and formate decreased at T1 compared to T0. Whereas, the thyroid peroxidase antibody (TPOAb) blood values increased at T1 compared to T0 reflecting the changes in the ¹ H-NMR spectral window of 1-3.5 ppm.

CONCLUSION

PS ¹ H-NMR profiling identified modified metabolites that revealed cancer cells metabolism disturbances that subsequently decreased with time throughout treatment. These altered metabolites are potential biomarkers, providing a molecular diagnostic approach for clinical diagnosis, and prognosis of human colon cancer.

Serum metabolomics analysis for the progression of esophageal squamous cell carcinoma

BACKGROUND: Previous metabolomics studies have found differences in metabolic characteristics between the healthy and ESCC patients. However, few of these studies concerned the whole process of the progression of ESCC. This study aims to explore serum metabolites associated with the progression of ESCC.

METHODS: Serum samples from 653 participants (305 normal, 77 esophagitis, 228 LGD, and 43 HGD/ESCC) were examined by ultra-high performance liquid chromatography quadruple time-of-flight mass spectrometry (UHPLC-QTOF/MS). Principal component analysis (PCA) was first applied to obtain an overview of the clustering trend for the multidimensional data. Fuzzy c-means (FCM) clustering was then used to screen metabolites with a changing tendency in the progression of ESCC. Univariate ordinal logistic regression analysis and multiple ordinal logistic regression analysis were applied to evaluate the association of metabolites with the risk of ESCC progression, and adjusted for age, gender, BMI, tobacco smoking, and alcohol drinking status.

RESULTS: After FCM clustering analysis, a total of 38 metabolites exhibiting changing tendency among normal, esophagitis, LGD, and HGD/ESCC patients. Final results showed 15 metabolites associated with the progression of ESCC. Ten metabolites (dopamine, L-histidine, 5-hydroxyindoleacetate, L-tryptophan, 2'-O-methylcytidine, PC (14:0/0:0), PC (O-16:1/0:0), PE (18:0/0:0), PC (16:1/0:0), PC (18:2/0:0)) were associated with decreased risk of developing ESCC. Five metabolites (hypoxanthine, inosine, carnitine (14:1), glycochenodeoxycholate, PC (P-18:0/18:3)) were associated with increased risk of developing ESCC.

CONCLUSIONS: These results demonstrated that serum metabolites are associated with the progression of ESCC. These metabolites are capable of potential biomarkers for the risk prediction and early detection of ESCC.

Efficacy of Analytical Technologies in Metabolomics Studies of the Gastrointestinal Cancers

According to the reports of the World Health Organization and the International Agency for Research on Cancer, cancer is the second leading cause of human death worldwide. However, early-stage detection of cancers can efficiently enhance the chance of therapy and saving lives. Metabolomics strategies apply a variety of approaches to discover new potential diagnoses, prognoses, and/or therapeutic biomarkers of various diseases. Metabolomics aims to identify and measure different low-molecular-weight biomolecules in physiological environments. In these studies, special metabolites are extracted from biological samples and identified using analytical techniques. Afterward, using data processing programs discovering significantly associated biomarkers is pursued. In the present review, we aimed to discuss recently reported analytical approaches on the metabolomics studies of gastrointestinal cancers including gastric, colorectal, and esophageal cancers. The gas- and liquid-chromatography with different detectors have been shown that are the main analytical techniques and for metabolites quantification, nuclear magnetic resonance has been utilized as a master method.

One-Carbon Metabolism and Development of the Conceptus During Pregnancy: Lessons from Studies with Sheep and Pigs

The pregnancy recognition signal from the conceptus (embryo/fetus and associated membranes) to the mother is interferon tau (IFNT) in ruminants and estradiol, possibly in concert with interferons gamma and delta in pigs. Those pregnancy recognition signals silence expression of interferon stimulated genes (ISG) in uterine luminal (LE) and superficial glandular (sGE) epithelia while inducing expression of genes for transport of nutrients, including glucose and amino acids, into the uterine lumen to support growth and development of the conceptus. In sheep and pigs, glucose not utilized immediately by the conceptus is converted to fructose. Glucose, fructose, serine and glycine in uterine histotroph can contribute to one carbon (1C) metabolism that provides one-carbon groups for the synthesis of purines and thymidylate, as well as S-adenosylmethionine for epigenetic methylation reactions. Serine and glycine are transported into the mitochondria of cells and metabolized to formate that is transported into the cytoplasm for the synthesis of purines, thymidine and S-adenosylmethionine. The unique aspects of one-carbon metabolism are discussed in the context of the hypoxic uterine environment, aerobic glycolysis, and similarities in metabolism between cancer cells and cells of the rapidly developing fetal-placental tissues during pregnancy. Further, the evolution of anatomical and functional aspects of the placentae of sheep and pigs versus primates is discussed in the context of mechanisms to efficiently obtain, store and utilize nutrients required for rapid fetal growth in the last one-half of gestation.

Nerve input to tumours: Pathophysiological consequences of a dynamic relationship

It is well known that tumours arising in different organs are innervated and that 'perineural invasion' (cancer cells escaping from the tumour by following the nerve trunk) is a negative prognostic factor. More surprisingly, increasing evidence suggests that the nerves can provide active inputs to tumours and there is two-way communication between nerves and cancer cells within the tumour microenvironment. Cells of the immune system also interact with the nerves and cancer cells. Thus, the nerve connections can exert significant control over cancer progression and modulating these (physically or chemically) can affect significantly the cancer process. Nerve inputs to tumours are derived mainly from the sympathetic (adrenergic) and the parasympathetic (cholinergic) systems, which are interactive. An important component of the latter is the vagus nerve, the largest of the cranial nerves. Here, we present a two-part review of the nerve inputs to tumours and their effects on tumorigenesis. First, we review briefly some relevant general issues including ultrastructural aspects, stemness, interactions between neurones and primary tumours, and communication between neurones and metastasizing tumour cells. Ultrastructural characteristics include synaptic vesicles, tumour microtubes and gap junctions enabling formation of cellular networks. Second, we evaluate the pathophysiology of the nerve input to five major carcinomas: cancers of prostate, stomach, colon, lung and pancreas. For each cancer, we present (i) the nerve inputs normally present in the cancer organ and (ii) how these interact and influence the cancer process. The best clinical evidence for the role of nerves in promoting tumorigenesis comes from prostate cancer patients where metastatic progression has been shown to be suppressed significantly in cases of spinal cord injury. The balance of the sympathetic and parasympathetic contributions to early versus late tumorigenesis varies amongst the different cancers. Different branches of the vagus provide functional inputs to several of the carcinomas and, in two-way interaction with the sympathetic nervous system, affect different stages of the cancer process. Overall, the impact of the vagus nerve can be 'direct' or 'indirect'. Directly, the effect of the vagus is primarily to promote tumorigenesis and this is mediated through cholinergic receptor mechanisms. Indirectly, pro- and anti-tumour effects can occur by stimulation or inhibition of the sympathetic nervous system, respectively. Less well understood are the 'indirect' anti-tumour effect of the vagus nerve via immunomodulation/inflammation, and the role of sensory innervation. A frequent occurrence in the nerve-tumour interactions is the presence of positive feedback driven by agents like nerve growth factor. We conclude that the nerve inputs to tumours can actively and dynamically impact upon cancer progression and are open to clinical exploitation.

L-Arginine/NO Pathway Metabolites in Colorectal Cancer: Relevance as Disease Biomarkers and Predictors of Adverse Clinical Outcomes Following Surgery

The L-Arginine/NO pathway is involved in carcinogenesis and immunity. Its diagnostic and prognostic value in colorectal cancer (CRC) was determined using tandem mass spectrometry in 199 individuals (137 with CRC) and, during a three-day follow up, in 60 patients undergoing colorectal surgery. Citrulline was decreased and asymmetric (ADMA) and symmetric (SDMA) dimethylarginines and dimethylamine (DMA) were increased in CRC. The DMA increase corresponded with CRC advancement while arginine, ADMA, and SDMA levels were higher in left-sided cancers. Arginine, citrulline, ADMA, and DMA dropped and SDMA increased post incision. Females experienced a more substantial drop in arginine. The arginine and ADMA dynamics depended on blood loss. The initial SDMA increase was higher in patients requiring transfusions. Postoperative dynamics in arginine and dimethylarginines differed in robot-assisted and open surgery. Concomitant SDMA, citrulline, and DMA quantification displayed a 92% accuracy in detecting CRC. Monitoring changes in arginine, ADMA, and SDMA in the early postoperative period predicted postoperative ileus with 84% and surgical site infections with 90% accuracy. Changes in ADMA predicted operative morbidity with 90% and anastomotic leakage with 77% accuracy. If positively validated, L-arginine/NO pathway metabolites may facilitate CRC screening and surveillance, support differential diagnosis, and assist in clinical decision-making regarding patients recovering from colorectal surgery.

Mitochondrial apoptosis and curtailment of hypoxia-inducible factor-1α/fatty acid synthase: A dual edge perspective of gamma linolenic acid in ER+ mammary gland cancer

Gamma linolenic acid is a polyunsaturated fatty acid having selective anti-tumour properties with negligible systemic toxicity. In the present study, the anti-cancer potential of gamma linolenic acid and its effects on mitochondrial as well as hypoxia-associated marker was evaluated. The effect of gamma linolenic acid was scrutinised against ER + MCF-7 cells by using fluorescence microscopy, JC-1 staining, dot plot assay and cell cycle analysis. The in vitro results were also confirmed using carcinogen (n-methyl-n-nitrosourea) induced in vivo model. The early and late apoptotic signals in the conjugation with mitochondrial depolarisation were found once scrutinised through mitochondrial membrane potential and life death staining after gamma linolenic acid treatment. Gamma linolenic acid arrested the cell cycle in G0/G1 phase with the majority of cell populations in the early apoptotic stage. The translocation of phosphatidylserine was studied through annexin-V FITC dot plot assay. The markers of cellular proliferation (decreased alveolar bud count, histopathological architecture restoration and loss of tumour micro-vessels) were diminished after gamma linolenic acid treatment. Gamma linolenic acid ameliorates the biological effects of n-methyl-n-nitrosourea persuading the mitochondrial mediated death pathway and impeding the hypoxic microenvironment to make a halt in palmitic acid synthesis. SIGNIFICANCE: The present study elaborates the effect of gamma linolenic acid on mammary gland cancer by following mitochondrial-mediated death apoptosis pathway. Gamma linolenic acid also inhibits cell-wall synthesis by the curtailment of HIF-1α and FASN level in mammary gland cancer.

Metabolic Biomarkers of Squamous Cell Carcinoma of the Aerodigestive Tract: A Systematic Review and Quality Assessment

Introduction. Aerodigestive squamous cell carcinomas (ASCC) constitute a major source of global cancer deaths. Patients typically present with advanced, incurable disease, so new means of detecting early disease are a research priority. Metabolite quantitation is amenable to point-of-care analysis and can be performed in ASCC surrogates such as breath and saliva. The purpose of this systematic review is to summarise progress of ASCC metabolomic studies, with an emphasis on the critical appraisal of methodological quality and reporting.

METHOD

A systematic online literature search was performed to identify studies reporting metabolic biomarkers of ASCC. This review was conducted in accordance with the recommendations of the Cochrane Library and MOOSE guidelines.

RESULTS

Thirty studies comprising 2117 patients were included in the review. All publications represented phase-I biomarker discovery studies, and none validated their findings in an independent cohort. There was heterogeneity in study design and methodological and reporting quality. Sensitivities and specificities were higher in oesophageal and head and neck squamous cell carcinomas compared to those in lung squamous cell carcinoma. The metabolic phenotypes of these cancers were similar, as was the kinetics of metabolite groups when comparing blood, tissue, and breath/saliva concentrations. Deregulation of amino acid metabolism was the most frequently reported theme.

CONCLUSION

Metabolite analysis has shown promising diagnostic performance, especially for oesophageal and head and neck ASCC subtypes, which are phenotypically similar. However, shortcomings in study design have led to inconsistencies between studies. To support future studies and ultimately clinical adoption, these limitations are discussed.

Metabolomics studies in gastrointestinal cancer: a systematic review

Introduction: This systemic review provides an overview of metabolic perturbations and possible mechanisms in gastrointestinal cancer. The authors discuss emerging challenges of technical and clinical applications.Areas covered: In this systemic review, the authors summarized the currently available results of metabolomic biomarkers linked to GI cancer, and discussed the altered metabolism pathways including carbohydrate metabolism, amino acid metabolism, lipids, and nucleotide metabolism and other metabolisms. Furthermore, future efforts need to adhere to normalize analysis procedures, validate with the larger cohort and utilize multiple-omics technologies. The search was conducted in PubMed with the following search terms (biomarker, gastrointestinal cancer, colorectal cancer, and esophageal cancer) from 2013 to 2019.Expert opinion: This systemic review summarized the currently available results of metabolomic biomarkers linked to gastrointestinal cancer, and discussed the altered metabolism pathways. The authors believe that metabolomics will benefit deeper understandings of the pathogenic mechanism, discovery of biomarkers and aid the search for drug targets as we move toward the era of personalized medicine. Personalized medication for tumors can improve the curative effect, avoid side effects and medical resource waste. As a promisingtool, metabolomics that targets the entire cancer-specific metabolite network should be applied more widely in cancer research.

Metabolomics technology and bioinformatics for precision medicine

Precision medicine is rapidly emerging as a strategy to tailor medical treatment to a small group or even individual patients based on their genetics, environment and lifestyle. Precision medicine relies heavily on developments in systems biology and omics disciplines, including metabolomics. Combination of metabolomics with sophisticated bioinformatics analysis and mathematical modeling has an extreme power to provide a metabolic snapshot of the patient over the course of disease and treatment or classifying patients into subpopulations and subgroups requiring individual medical treatment. Although a powerful approach, metabolomics have certain limitations in technology and bioinformatics. We will review various aspects of metabolomics technology and bioinformatics, from data generation, bioinformatics analysis, data fusion and mathematical modeling to data management, in the context of precision medicine.

Correlations between the metabolic profile and 18F-FDG-Positron Emission Tomography-Computed Tomography parameters reveal the complexity of the metabolic reprogramming within lung cancer patients

Several studies have demonstrated that the metabolite composition of plasma may indicate the presence of lung cancer. The metabolism of cancer is characterized by an enhanced glucose uptake and glycolysis which is exploited by ¹⁸F-FDG positron emission tomography (PET) in the work-up and management of cancer. This study aims to explore relationships between ¹H-NMR spectroscopy derived plasma metabolite concentrations and the uptake of labeled glucose (¹⁸F-FDG) in lung cancer tissue. PET parameters of interest are standard maximal uptake values (SUV_max), total body metabolic active tumor volumes (MATV_WTB) and total body total lesion glycolysis (TLG_WTB) values. Patients with high values of these parameters have higher plasma concentrations of N-acetylated glycoproteins which suggest an upregulation of the hexosamines biosynthesis. High MATV_WTB and TLG_WTB values are associated with higher concentrations of glucose, glycerol, N-acetylated glycoproteins, threonine, aspartate and valine and lower levels of sphingomyelins and phosphatidylcholines appearing at the surface of lipoproteins. These higher concentrations of glucose and non-carbohydrate glucose precursors such as amino acids and glycerol suggests involvement of the gluconeogenesis pathway. The lower plasma concentration of those phospholipids points to a higher need for membrane synthesis. Our results indicate that the metabolic reprogramming in cancer is more complex than the initially described Warburg effect.

Plasma metabolite profiling reveals potential biomarkers of giant cell tumor of bone by using NMR-based metabolic profiles: A cross-sectional study

Giant cell tumor (GCT) of bone is a locally aggressive bone tumor, which accounts for 4% to 5% of all primary bone tumors. At present, the early diagnosis and postoperative recurrence monitoring are still more difficult due to the lack of effective biomarkers in GCT. As an effective tool, metabolomics has played an essential role in the biomarkers research of many tumors. However, there has been no related study of the metabolomics of GCT up to now. The purpose of this study was to identify several key metabolites as potential biomarkers for GCT by using nuclear magnetic resonance (NMR)-based metabolic profiles.Patients with GCT in our hospital were recruited in this study and their plasma was collected as the research sample, and plasma collected from healthy subjects was considered as the control. NMR was then utilized to detect all samples. Furthermore, based on correlation coefficients, variable importance for the projection values and P values of metabolites obtained from multidimensional statistical analysis, the most critical metabolites were selected as potential biomarkers of GCT. Finally, relevant metabolic pathways involved in these potential biomarkers were determined by database retrieval, based on which the metabolic pathways were plotted.Finally, 28 GCT patients and 26 healthy volunteers agreed to participate in the study. In the multidimensional statistical analysis, all results showed that there was obvious difference between the GCT group and the control group. Ultimately, 18 metabolites with significant differences met the selection condition, which were identified as potential biomarkers. Through Kyoto Encyclopedia of Genes and Genomes (KEGG) and Human Metabolome Database (HMD) database searching and literature review, these metabolites were found to be mainly correlated with glucose metabolism, fat metabolism, amino acid metabolism, and intestinal microbial metabolism. These metabolic disorders might, in turn, reflect important pathological processes such as proliferation and migration of tumor cells and immune escape in GCT.Our work showed that these potential biomarkers identified appeared to have early diagnostic and relapse monitoring values for GCT, which deserve to be further investigated. In addition, it also suggested that metabolomics profiling approach is a promising screening tool for the diagnosis and relapse monitoring of GCT patients.

Gluconeogenesis in cancer cells - Repurposing of a starvation-induced metabolic pathway?

Cancer cells constantly face a fluctuating nutrient supply and interference with adaptive responses might be an effective therapeutic approach. It has been discovered that in the absence of glucose, cancer cells can synthesize crucial metabolites by expressing phosphoenolpyruvate carboxykinase (PEPCK, PCK1 or PCK2) using abbreviated forms of gluconeogenesis. Gluconeogenesis, which in essence is the reverse pathway of glycolysis, uses lactate or amino acids to feed biosynthetic pathways branching from glycolysis. PCK1 and PCK2 have been shown to be critical for the growth of certain cancers. In contrast, fructose-1,6-bisphosphatase 1 (FBP1), a downstream gluconeogenesis enzyme, inhibits glycolysis and tumor growth, partly by non-enzymatic mechanisms. This review sheds light on the current knowledge of cancer cell gluconeogenesis and its role in metabolic reprogramming, cancer cell plasticity, and tumor growth.

The plasma glutamate concentration as a complementary tool to differentiate benign PET-positive lung lesions from lung cancer

Background

Pulmonary imaging often identifies suspicious abnormalities resulting in supplementary diagnostic procedures. This study aims to investigate whether the metabolic fingerprint of plasma allows to discriminate between patients with lung inflammation and patients with lung cancer.

Methods

Metabolic profiles of plasma from 347 controls, 269 cancer patients and 108 patients with inflammation were obtained by ¹H-NMR spectroscopy. Models to discriminate between groups were trained by PLS-LDA. A test set was used for independent validation. A ROC curve was built to evaluate the diagnostic performance of potential biomarkers.

Results

Sensitivity, specificity, PPV and NPV of PET-CT to diagnose cancer are 96, 23, 76 and 71%. Metabolic profiles differentiate between cancer and inflammation with a sensitivity of 89%, a specificity of 87% and a MCE of 12%. Removal of the glutamate metabolite results in an increase of MCE (38%) and a decrease of both sensitivity and specificity (62%), demonstrating the importance of glutamate for discrimination. At the cut-off point 0.31 on the ROC curve, the relative glutamate concentration discriminates between cancer and inflammation with a sensitivity of 85%, a specificity of 81%, and an AUC of 0.88. PPV and NPV are 92 and 69%. In PET-positive patients with a relative glutamate level ≤ 0.31 the sensitivity to diagnose cancer reaches 100% with a PPV of 94%. In PET-negative patients, a relative glutamate level > 0.31 increases the specificity of PET from 23% to 58% and results in a high NPV of 100%. In case of discrepancy between SUV_max and the glutamate concentration, lung cancer is missed in 19% of the cases.

Conclusion

This study indicates that the ¹H-NMR-derived relative plasma concentration of glutamate allows discrimination between lung cancer and lung inflammation. A glutamate level ≤ 0.31 in PET-positive patients corresponds to the diagnosis of lung cancer with a higher specificity and PPV than PET-CT. Glutamate levels > 0.31 in patients with PET negative lung lesions is likely to correspond with inflammation. Caution is needed for patients with conflicting SUV_max values and glutamate concentrations. Confirmation is needed in a prospective study with external validation and by another analytical technique such as HPLC-MS.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4755-1) contains supplementary material, which is available to authorized users.

Metabolome analysis of esophageal cancer tissues using capillary electrophoresis-time-of-flight mass spectrometry

Reports of the metabolomic characteristics of esophageal cancer are limited. In the present study, we thus conducted metabolome analysis of paired tumor tissues (Ts) and non-tumor esophageal tissues (NTs) using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS). The Ts and surrounding NTs were surgically excised pair-wise from 35 patients with esophageal cancer. Following tissue homogenization and metabolite extraction, a total of 110 compounds were absolutely quantified by CE-TOFMS. We compared the concentrations of the metabolites between Ts and NTs, between pT1 or pT2 (pT1-2) and pT3 or pT4 (pT3-4) stage, and between node-negative (pN-) and node-positive (pN+) samples. Principal component analysis and hierarchical clustering analysis revealed clear metabolomic differences between Ts and NTs. Lactate and citrate levels in Ts were significantly higher (P=0.001) and lower (P<0.001), respectively, than those in NTs, which corroborated with the Warburg effect in Ts. The concentrations of most amino acids apart from glutamine were higher in Ts than in NTs, presumably due to hyperactive glutaminolysis in Ts. The concentrations of malic acid (P=0.015) and citric acid (P=0.008) were significantly lower in pT3-4 than in pT1-2, suggesting the downregulation of tricarboxylic acid (TCA) cycle activity in pT3-4. On the whole, in this study, we demonstrate significantly different metabolomic characteristics between tumor and non-tumor tissues and identified a novel set of metabolites that were strongly associated with the degree of tumor progression. A further understanding of cancer metabolomics may enable the selection of more appropriate treatment strategies, thereby contributing to individualized medicine.

Novel 1,3,4-thiadiazoles inhibit colorectal cancer via blockade of IL-6/COX-2 mediated JAK2/STAT3 signals as evidenced through data-based mathematical modeling

We attempted a preclinical study using DMH-induced CRC rat model to evaluate the antitumor potential of our recently synthesized 1,3,4-thiadiazoles. The molecular insights were confirmed through ELISA, qRT-PCR and western blot analyses. The CRC condition was produced in response to COX-2 and IL-6 induced activation of JAK2/STAT3 which, in turn, was due to the enhanced phosphorylation of JAK2 and STAT3. The treatment with 1,3,4-thiadiazole derivatives (VR24 and VR27) caused the significant blockade of this signaling pathway. The behavior of STAT3 populations in response to IL-6 and COX-2 stimulations was further confirmed through data-based mathematical modeling using the quantitative western blot data. Finally, VR24 and VR27 restored the perturbed metabolites associated to DMH-induced CRC as evidenced through ¹H NMR based serum metabolomics. The tumor protecting ability of VR24 and VR27 was found comparable or to some degree better than the marketed chemotherapeutics, 5-flurouracil.

Integrative Pathway Analysis of Genes and Metabolites Reveals Metabolism Abnormal Subpathway Regions and Modules in Esophageal Squamous Cell Carcinoma

Aberrant metabolism is one of the main driving forces in the initiation and development of ESCC. Both genes and metabolites play important roles in metabolic pathways. Integrative pathway analysis of both genes and metabolites will thus help to interpret the underlying biological phenomena. Here, we performed integrative pathway analysis of gene and metabolite profiles by analyzing six gene expression profiles and seven metabolite profiles of ESCC. Multiple known and novel subpathways associated with ESCC, such as 'beta-Alanine metabolism', were identified via the cooperative use of differential genes, differential metabolites, and their positional importance information in pathways. Furthermore, a global ESCC-Related Metabolic (ERM) network was constructed and 31 modules were identified on the basis of clustering analysis in the ERM network. We found that the three modules located just to the center regions of the ERM network-especially the core region of Module_1-primarily consisted of aldehyde dehydrogenase (ALDH) superfamily members, which contributes to the development of ESCC. For Module_4, pyruvate and the genes and metabolites in its adjacent region were clustered together, and formed a core region within the module. Several prognostic genes, including GPT, ALDH1B1, ABAT, WBSCR22 and MDH1, appeared in the three center modules of the network, suggesting that they can become potentially prognostic markers in ESCC.

1H-NMR-based metabolic profiling of a colorectal cancer CT-26 lung metastasis model in mice

Lung metastasis is an important cause for the low 5-year survival rate of colorectal cancer patients. Understanding the metabolic profile of lung metastasis of colorectal cancer is important for developing molecular diagnostic and therapeutic approaches. We carried out the metabonomic profiling of lung tissue samples on a mouse lung metastasis model of colorectal cancer using 1H-nuclear magnetic resonance (1H-NMR). The lung tissues of mice were collected at different intervals after marine colon cancer cell line CT-26 was intravenously injected into BALB/c mice. The distinguishing metabolites of lung tissue were investigated using 1H-NMR-based metabonomic assay, which is a highly sensitive and non-destructive method for biomarker identification. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were applied to analyze 1H-NMR profiling data to seek potential biomarkers. All of the 3 analyses achieved excellent separations between the normal and metastasis groups. A total of 42 metabolites were identified, ~12 of which were closely correlated with the process of metastasis from colon to lung. These altered metabolites indicated the disturbance of metabolism in metastatic tumors including glycolysis, TCA cycle, glutaminolysis, choline metabolism and serine biosynthesis. Our findings firstly identified the distinguishing metabolites in mouse colorectal cancer lung metastasis models, and indicated that the metabolite disturbance may be associated with the progression of lung metastasis from colon cancer. The altered metabolites may be potential biomarkers that provide a promising molecular approach for clinical diagnosis and mechanistic study of colorectal cancer with lung metastasis.

Formate: The Neglected Member of One-Carbon Metabolism

Formate, the only non-tetrahydrofolate (THF)-linked intermediate in one-carbon metabolism, is produced in mammals from a variety of metabolic sources. It occurs in serum of adults at a concentration of approximately 30 μM. Its principal function lies as a source of one-carbon groups for the synthesis of 10-formyl-THF and other one-carbon intermediates; these are primarily used for purine synthesis, thymidylate synthesis, and the provision of methyl groups for synthetic, regulatory, and epigenetic methylation reactions. Although formate is largely produced in mitochondria, these functions mostly occur in the cytoplasm and nucleus. Formate plays a significant role in embryonic development, as evidenced by the effectiveness of formate in the pregnant dam's drinking water on the incidence of neural tube defects in some genetic models. High formate concentrations in fetal lambs may indicate a role in fetal development and suggest that extracellular formate may play a role in the interorgan distribution of one-carbon groups.

GWAS follow-up study of esophageal squamous cell carcinoma identifies potential genetic loci associated with family history of upper gastrointestinal cancer

Based on our initial genome-wide association study (GWAS) on esophageal squamous cell carcinoma (ESCC) in Han Chinese, we conducted a follow-up study to examine the single nucleotide polymorphisms (SNPs) associated with family history (FH) of upper gastrointestinal cancer (UGI) cancer in cases with ESCC. We evaluated the association between SNPs and FH of UGI cancer among ESCC cases in a stage-1 case-only analysis of the National Cancer Institute (NCI, 541 cases with FH and 1399 without FH) and Henan GWAS (493 cases with FH and 869 without FH) data (discovery phase). The top SNPs (or their surrogates) from discovery were advanced to a stage-2 evaluation in additional Henan subjects (2801 cases with FH and 3136 without FH, replication phase). A total of 19 SNPs were associated with FH of UGI cancer in ESCC cases with P < 10^-5 in the stage-1 meta-analysis of NCI and Henan GWAS data. In stage-2, the association for rs79747906 (located at 18p11.31, P = 5.79 × 10^-6 in discovery) was replicated (P = 0.006), with a pooled-OR of 1.59 (95%CI: 1.11-2.28). We identified potential genetic variants associated with FH of UGI cancer. Our findings may provide important insights into new low-penetrance susceptibility regions involved in the susceptibility of families with multiple UGI cancer cases.

Integration of metabolomics, transcriptomics, and microRNA expression profiling reveals a miR-143-HK2-glucose network underlying zinc-deficiency-associated esophageal neoplasia

Esophageal squamous cell carcinoma (ESCC) in humans is a deadly disease associated with dietary zinc (Zn)-deficiency. In the rat esophagus, Zn-deficiency induces cell proliferation, alters mRNA and microRNA gene expression, and promotes ESCC. We investigated whether Zn-deficiency alters cell metabolism by evaluating metabolomic profiles of esophageal epithelia from Zn-deficient and replenished rats vs sufficient rats, using untargeted gas chromatography time-of-flight mass spectrometry (n = 8/group). The Zn-deficient proliferative esophagus exhibits a distinct metabolic profile with glucose down 153-fold and lactic acid up 1.7-fold (P < 0.0001), indicating aerobic glycolysis (the “Warburg effect”), a hallmark of cancer cells. Zn-replenishment rapidly increases glucose content, restores deregulated metabolites to control levels, and reverses the hyperplastic phenotype. Integration of metabolomics and our reported transcriptomic data for this tissue unveils a link between glucose down-regulation and overexpression of HK2, an enzyme that catalyzes the first step of glycolysis and is overexpressed in cancer cells. Searching our published microRNA profile, we find that the tumor-suppressor miR-143, a negative regulator of HK2, is down-regulated in Zn-deficient esophagus. Using in situ hybridization and immunohistochemical analysis, the inverse correlation between miR-143 down-regulation and HK2 overexpression is documented in hyperplastic Zn-deficient esophagus, archived ESCC-bearing Zn-deficient esophagus, and human ESCC tissues. Thus, to sustain uncontrolled cell proliferation, Zn-deficiency reprograms glucose metabolism by modulating expression of miR-143 and its target HK2. Our work provides new insight into critical roles of Zn in ESCC development and prevention.

Overexpression of the human DEK oncogene reprograms cellular metabolism and promotes glycolysis

The DEK oncogene is overexpressed in many human malignancies including at early tumor stages. Our reported in vitro and in vivo models of squamous cell carcinoma have demonstrated that DEK contributes functionally to cellular and tumor survival and to proliferation. However, the underlying molecular mechanisms remain poorly understood. Based on recent RNA sequencing experiments, DEK expression was necessary for the transcription of several metabolic enzymes involved in anabolic pathways. This identified a possible mechanism whereby DEK may drive cellular metabolism to enable cell proliferation. Functional metabolic Seahorse analysis demonstrated increased baseline and maximum extracellular acidification rates, a readout of glycolysis, in DEK-overexpressing keratinocytes and squamous cell carcinoma cells. DEK overexpression also increased the maximum rate of oxygen consumption and therefore increased the potential for oxidative phosphorylation (OxPhos). To detect small metabolites that participate in glycolysis and the tricarboxylic acid cycle (TCA) that supplies substrate for OxPhos, we carried out NMR-based metabolomics studies. We found that high levels of DEK significantly reprogrammed cellular metabolism and altered the abundances of amino acids, TCA cycle intermediates and the glycolytic end products lactate, alanine and NAD+. Taken together, these data support a scenario whereby overexpression of the human DEK oncogene reprograms keratinocyte metabolism to fulfill energy and macromolecule demands required to enable and sustain cancer cell growth.

Metabolic Perturbation and Potential Markers in Patients with Esophageal Cancer

Clinical diagnosis of esophageal cancer (EC) at early stage is rather difficult. This study aimed to profile the molecules in serum and tissue and identify potential biomarkers in patients with EC. A total of 64 volunteers were recruited, and 83 samples (24 EC serum samples, 21 serum controls, 19 paired EC tissues, and corresponding tumor-adjacent tissues) were analyzed. The gas chromatography time-of-flight mass spectrometry (GC/TOF-MS) was employed, and principal component analysis was used to reveal the discriminatory metabolites and identify the candidate markers of EC. A total of 41 in serum and 36 identified compounds in tissues were relevant to the malignant prognosis. A marked metabolic reprogramming of EC was observed, including enhanced anaerobic glycolysis and glutaminolysis, inhibited tricarboxylic acid (TCA) cycle, and altered lipid metabolism and amino acid turnover. Based on the potential markers of glucose, glutamic acid, lactic acid, and cholesterol, the receiver operating characteristic (ROC) curves indicated good diagnosis and prognosis of EC. EC patients showed distinct reprogrammed metabolism involved in glycolysis, TCA cycle, glutaminolysis, and fatty acid metabolism. The pivotal molecules in the metabolic pathways were suggested as the potential markers to facilitate the early diagnosis of human EC.

1H NMR-based metabolomics reveals neurochemical alterations in the brain of adolescent rats following acute methylphenidate administration

The psychostimulant methylphenidate (MPH) is increasingly used in the treatment of attention deficit hyperactivity disorder (ADHD). While there is little evidence for common brain pathology in ADHD, some studies suggest a right hemisphere dysfunction among people diagnosed with the condition. However, in spite of the high usage of MPH in children and adolescents, its mechanism of action is poorly understood. Given that MPH blocks the neuronal transporters for dopamine and noradrenaline, most research into the effects of MPH on the brain has largely focused on these two monoamine neurotransmitter systems. Interestingly, recent studies have demonstrated metabolic changes in the brain of ADHD patients, but the impact of MPH on endogenous brain metabolites remains unclear. In this study, a proton nuclear magnetic resonance (¹H NMR)-based metabolomics approach was employed to investigate the effects of MPH on brain biomolecules. Adolescent male Sprague Dawley rats were injected intraperitoneally with MPH (5.0 mg/kg) or saline (1.0 ml/kg), and cerebral extracts from the left and right hemispheres were analysed. A total of 22 variables (representing 13 distinct metabolites) were significantly increased in the MPH-treated samples relative to the saline-treated controls. The upregulated metabolites included: amino acid neurotransmitters such as GABA, glutamate and aspartate; large neutral amino acids (LNAA), including the aromatic amino acids (AAA) tyrosine and phenylalanine, both of which are involved in the metabolism of dopamine and noradrenaline; and metabolites associated with energy and cell membrane dynamics, such as creatine and myo-inositol. No significant differences in metabolite concentrations were found between the left and right cerebral hemispheres. These findings provide new insights into the mechanisms of action of the anti-ADHD drug MPH.

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

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

Identification of a RNA-Seq Based 8-Long Non-Coding RNA Signature Predicting Survival in Esophageal Cancer

Background

Accumulating evidence suggests the involvement of long non-coding RNAs (lncRNAs) as oncogenic or tumor suppressive regulators in the development of various cancers. In the present study, we aimed to identify a lncRNA signature based on RNA sequencing (RNA-seq) data to predict survival in esophageal cancer.

Material/Methods

The RNA-seq lncRNA expression data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed lncRNAs were screened out between esophageal cancer and normal tissues. Univariate and multivariate Cox regression analysis were performed to establish a lncRNA-related prognostic model. Receiver operating characteristic (ROC) analysis was conducted to test the sensitivity and specificity of the model. GO (gene ontology) functional and KEGG pathway enrichment analyses were performed for mRNAs co-expressed with the lncRNAs to explore the potential functions of the prognostic lncRNAs.

Results

A total of 265 differentially expressed lncRNAs were identified between esophageal cancer and normal tissues. After univariate and multivariate Cox regression analysis, eight lncRNAs (GS1-600G8.5, LINC00365, CTD-2357A8.3, RP11-705O24.1, LINC01554, RP1-90J4.1, RP11-327J17.1, and LINC00176) were finally screened out to establish a predictive model by which patients could be classified into high-risk and low-risk groups with significantly different overall survival. Further analysis indicated independent prognostic capability of the 8-lncRNA signature from other clinicopathological factors. ROC curve analysis demonstrated good performance of the 8-lncRNA signature. Functional enrichment analysis showed that the prognostic lncRNAs were mainly associated with esophageal cancer related biological processes such as regulation of glucose metabolic process and amino acid and lipids metabolism.

Conclusions

Our study developed a novel candidate model providing additional and more powerful prognostic information beyond conventional clinicopathological factors for survival prediction of esophageal cancer patients. Moreover, it also brings us new insights into the molecular mechanisms underlying esophageal cancer.

Magnetic resonance imaging for quantitative staging and evaluation of chemoradiotherapeutic effect in esophageal carcinoma

Esophageal carcinoma is a common digestive malignant tumor. Evaluation of the stage and response to chemoradiotherapy of the carcinoma is very important for the treatment decision making and adjustment of therapeutic protocol. To date, a variety of imaging techniques have been used for staging and monitoring response to therapy, but most of the procedures are invasive or of radiation exposure. Moreover, most of the techniques evaluating esophageal cancer are based on morphologic changes. As a non-invasive and non-ionising examination technique, magnetic resonance imaging can quantitatively evaluate this cancer. Nowadays magnetic resonance quantitative technique has progressed greatly in staging and monitoring response to therapy of esophageal carcinoma. This paper focuses on the quantitative evaluation of stage and chemoradiotherapeutic effect in esophageal carcinoma using magnetic resonance imaging.

Mass Spectrometric Analysis of Exhaled Breath for the Identification of Volatile Organic Compound Biomarkers in Esophageal and Gastric Adenocarcinoma

OBJECTIVE

The present study assessed whether exhaled breath analysis using Selected Ion Flow Tube Mass Spectrometry could distinguish esophageal and gastric adenocarcinoma from noncancer controls.

BACKGROUND

The majority of patients with upper gastrointestinal cancer present with advanced disease, resulting in poor long-term survival rates. Novel methods are needed to diagnose potentially curable upper gastrointestinal malignancies.

METHODS

A Profile-3 Selected Ion Flow Tube Mass Spectrometry instrument was used for analysis of volatile organic compounds (VOCs) within exhaled breath samples. All study participants had undergone upper gastrointestinal endoscopy on the day of breath sampling. Receiver operating characteristic analysis and a diagnostic risk prediction model were used to assess the discriminatory accuracy of the identified VOCs.

RESULTS

Exhaled breath samples were analyzed from 81 patients with esophageal (N = 48) or gastric adenocarcinoma (N = 33) and 129 controls including Barrett's metaplasia (N = 16), benign upper gastrointestinal diseases (N = 62), or a normal upper gastrointestinal tract (N = 51). Twelve VOCs-pentanoic acid, hexanoic acid, phenol, methyl phenol, ethyl phenol, butanal, pentanal, hexanal, heptanal, octanal, nonanal, and decanal-were present at significantly higher concentrations (P < 0.05) in the cancer groups than in the noncancer controls. The area under the ROC curve using these significant VOCs to discriminate esophageal and gastric adenocarcinoma from those with normal upper gastrointestinal tracts was 0.97 and 0.98, respectively. The area under the ROC curve for the model and validation subsets of the diagnostic prediction model was 0.92 ± 0.01 and 0.87 ± 0.03, respectively.

CONCLUSIONS

Distinct exhaled breath VOC profiles can distinguish patients with esophageal and gastric adenocarcinoma from noncancer controls.

Pathway, in silico and tissue-specific expression quantitative analyses of oesophageal squamous cell carcinoma genome-wide association studies data

BACKGROUND

Oesophageal cancer is the fourth leading cause of cancer death in China where essentially all cases are histologically oesophageal squamous cell carcinoma (ESCC). Agnostic pathway-based analyses of genome-wide association study (GWAS) data combined with tissue-specific expression quantitative trait loci (eQTL) analysis and publicly available functional data can identify biological pathways and/or genes enriched with functionally-relevant disease-associated variants.

METHOD

We used the adaptive multilocus joint test to analyse 1827 pathways containing 6060 genes using GWAS data from 1942 ESCC cases and 2111 controls with Chinese ancestry. We examined the function of risk alleles using in silico and eQTL analyses in oesophageal tissues.

RESULTS

Associations with ESCC risk were observed for 36 pathways predominantly involved in apoptosis, cell cycle regulation and DNA repair and containing known GWAS-associated genes. After excluding genes with previous GWAS signals, candidate pathways (and genes) for ESCC risk included taste transduction (KEGG_hsa04742; TAS2R13, TAS2R42, TAS2R14, TAS2R46,TAS2R50), long-patch base excision repair (Reactome_pid; POLD2) and the metabolics pathway (KEGG_hsa01100; MTAP, GAPDH, DCTD, POLD2, AMDHD1). We identified and validated CASP8 rs13016963 and IDH2 rs11630814 as eQTLs, and CASP8 rs3769823 and IDH2 rs4561444 as the potential functional variants in high-linkage disequilibrium with these single nucleotide polymorphisms (SNPs), respectively. Further, IDH2 mRNA levels were down-regulated in ESCC (tumour:normal-fold change = 0.69, P =  .75E-14).

CONCLUSION

Agnostic pathway-based analyses and integration of multiple types of functional data provide new evidence for the contribution of genes in taste transduction and metabolism to ESCC susceptibility, and for the functionality of both established and new ESCC risk-related SNPs.

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.

GC-MS-based metabolomic analysis of human papillary thyroid carcinoma tissue

Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Elucidating the molecular network that is altered in PTC may lead to the identification of the critical insight into the pathogenesis of PTC. Thus far, little is known regarding the global metabolomic alterations of PTC. Gas chromatography coupled with mass spectrometry-based metabolomics was used to analyze metabolomic alterations in matched PTC and normal thyroid tissues obtained from the patients. Multivariate statistical analyses were employed to determine the significant metabolomic differences. The mRNA levels of the associated metabolic enzyme genes were further assayed with reverse transcription-quantitative polymerase chain reaction analysis. Principal component analysis, partial least-squares discriminant analysis (PLS-DA) and orthogonal PLS-DA models were established, which could clearly separate human normal thyroid and PTC samples, and identified that metabolites in carbohydrate metabolism, including glucose, fructose, galactose, mannose, 2-keto-D-gluconic acid and rhamnose, consistently decreased, while metabolites in nucleotide metabolism, including malonic acid and inosine, and lipid metabolism, including cholesterol and arachidonic acid, significantly altered in PTC. Furthermore, the mRNA levels of metabolic enzyme genes, including glucose-6-phosphate dehydrogenase, phosphoglycerate kinase 1, lactate dehydrogenase A, phosphoglycerate dehydrogenase and prostaglandin-endoperoxide synthase 2, significantly increased in PTC. Based on the metabolomic and mRNA data, various metabolites may be used for increased synthesis of nucleotides and oncogenic lipids in PTC, which may contribute to the pathogenesis of PTC. The present study provides a new understanding of the dysregulated metabolism in PTC and identifies potential avenues for the therapeutic intervention for this disease.