Metabolic signatures of esophageal cancer: NMR-based metabolomics and UHPLC-based focused metabolomics of blood serum. Biochim Biophys Acta Mol Basis Dis. 2013;1832:1207-1216. [PMID: 23524237 DOI: 10.1016/j.bbadis.2013.03.009]

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.

Integrated aerobic exercise with LDE-docetaxel treatment: a novel approach to combat prostate cancer progression

The variability in response to conventional prostate cancer (PC) therapies, coupled with the emergent issue of drug resistance, underscores the critical need for innovative treatment strategies. Aerobic physical exercise reduced incidence of several cancers, but the mechanism underlying these effects associated the nanoemulsion not fully understood. The application of a lipid nanoemulsion (LDE) delivery system for docetaxel (DTX), showing marked enhancement in therapeutic efficacy when combined with aerobic physical exercise. This novel intervention potentiates the antitumor activity of LDE-delivered DTX by augmenting nanoparticle internalization and inducing cell cycle arrest. Our findings reveal that this synergistic treatment not only significantly reduces prostate weight and mitigates adenocarcinoma proliferation but also attenuates anti-apoptotic BCL-2 protein expression. Concurrently, it elevates pro-apoptotic proteins and diminishes inflammatory markers. Metabolic profiling of the combined therapy group disclosed additional benefits, such as reduced lipid and plasma glucose levels. Collectively, our data illuminate the profound impact of integrating LDE-mediated DTX delivery with structured physical exercise, which together spearhead a dual-front assault on PC. This multimodal approach heralds a new paradigm in PC management, accentuating the promise of combined pharmacological and non-pharmacological interventions to elevate tumor suppressor protein activity and refine patient outcomes.

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.

Metabolomics of Duodenal Juice for Biliary Tract Cancer Diagnosis

The poor prognosis of malignant biliary diseases is partially caused by their difficult early diagnosis. Therefore, many patients are only diagnosed at advanced stages. This study aimed to improve diagnosis by clarifying the differences in the duodenal juice metabolomes of benign and malignant biliary diseases. From October 2021 to January 2023, duodenal juice was obtained from 67 patients with suspected biliary diseases who required endoscopic ultrasonography and endoscopic retrograde cholangiography for diagnosis/treatment. The samples metabolomes were analyzed via nuclear magnet resonance spectroscopy using an 800-MHz spectrometer. Metabolomes of malignant and benign diseases were then compared, and multivariate analysis was performed to determine the relevant factors for malignancy/benignancy. For benignancy, no significant predictors were observed. For malignancy, acetone was a significant predictor, with higher concentrations in the malignant group than in the benign group. Regarding the receiver operating characteristic curve analysis for biliary tract carcinoma diagnosis, the predictive value of acetone in duodenal juice was comparable with serum CA19-9 levels (area under the curve: 0.7330 vs. 0.691, p = 0.697). In conclusion, duodenal juice metabolomics is a feasible method that is available for differential diagnosis in the biliary disease field.

Metabolomics of head and neck cancer in biofluids: an integrative systematic review

INTRODUCTION

Head and neck cancer (HNC) is the fifth most common cancer globally. Diagnosis at early stages are critical to reduce mortality and improve functional and esthetic outcomes associated with HNC. Metabolomics is a promising approach for discovery of biomarkers and metabolic pathways for risk assessment and early detection of HNC.

OBJECTIVES

To summarize and consolidate the available evidence on metabolomics and HNC in plasma/serum, saliva, and urine.

METHODS

A systematic search of experimental research was executed using PubMed and Web of Science. Available data on areas under the curve was extracted. Metabolic pathway enrichment analysis were performed to identify metabolic pathways altered in HNC. Fifty-four studies were eligible for data extraction (33 performed in plasma/serum, 15 in saliva and 6 in urine).

RESULTS

Metabolites with high discriminatory performance for detection of HNC included single metabolites and combination panels of several lysoPCs, pyroglutamate, glutamic acid, glucose, tartronic acid, arachidonic acid, norvaline, linoleic acid, propionate, acetone, acetate, choline, glutamate and others. The glucose-alanine cycle and the urea cycle were the most altered pathways in HNC, among other pathways (i.e. gluconeogenesis, glycine and serine metabolism, alanine metabolism, etc.). Specific metabolites that can potentially serve as complementary less- or non-invasive biomarkers, as well as metabolic pathways integrating the data from the available studies, are presented.

CONCLUSION

The present work highlights utility of metabolite-based biomarkers for risk assessment, early detection, and prognostication of HNC, as well as facilitates incorporation of available metabolomics studies into multi-omics data integration and big data analytics for personalized health.

Metabolomic Insights of Biosurfactant Activity from Bacillus niabensis against Planktonic Cells and Biofilm of Pseudomonas stutzeri Involved in Marine Biofouling

In marine environments, biofilm can cause negative impacts, including the biofouling process. In the search for new non-toxic formulations that inhibit biofilm, biosurfactants (BS) produced by the genus Bacillus have demonstrated considerable potential. To elucidate the changes that BS from B. niabensis promote in growth inhibition and biofilm formation, this research performed a nuclear magnetic resonance (NMR) metabolomic profile analysis to compare the metabolic differences between planktonic cells and biofilms of Pseudomonas stutzeri, a pioneer fouling bacteria. The multivariate analysis showed a clear separation between groups with a higher concentration of metabolites in the biofilm than in planktonic cells of P. stutzeri. When planktonic and biofilm stages were treated with BS, some differences were found among them. In planktonic cells, the addition of BS had a minor effect on growth inhibition, but at a metabolic level, NADP+, trehalose, acetone, glucose, and betaine were up-regulated in response to osmotic stress. When the biofilm was treated with the BS, a clear inhibition was observed and metabolites such as glucose, acetic acid, histidine, lactic acid, phenylalanine, uracil, and NADP+ were also up-regulated, while trehalose and histamine were down-regulated in response to the antibacterial effect of the BS.

Tumour catabolism independent of malnutrition and inflammation in upper GI cancer patients revealed by longitudinal metabolomics

BACKGROUND

The detrimental impact of malnutrition and cachexia in cancer patients subjected to surgical resection is well established. However, how systemic and local metabolic alterations in cancer patients impact the serum metabolite signature, thereby leading to cancer-specific differences, is poorly defined. In order to implement metabolomics as a potential tool in clinical diagnostics and disease follow-up, targeted metabolite profiling based on quantitative measurements is essential. We hypothesized that the quantitative metabolic profile assessed by ¹ H nuclear magnetic resonance (NMR) spectroscopy can be used to identify cancer-induced catabolism and potentially distinguish between specific tumour entities. Importantly, to prove tumour dependency and assess metabolic normalization, we additionally analysed the metabolome of patients' sera longitudinally post-surgery in order to assess metabolic normalization.

METHODS

Forty two metabolites in sera of patients with tumour entities known to cause malnutrition and cachexia, namely, upper gastrointestinal cancer and pancreatic cancer, as well as sera of healthy controls, were quantified by ¹ H NMR spectroscopy.

RESULTS

Comparing serum metabolites of patients with gastrointestinal cancer with healthy controls and pancreatic cancer patients, we identified at least 15 significantly changed metabolites in each comparison. Principal component and pathway analysis tools showed a catabolic signature in preoperative upper gastrointestinal cancer patients. The most specifically upregulated metabolite group in gastrointestinal cancer patients was ketone bodies (3-hydroxybutyrate, P < 0.0001; acetoacetate, P < 0.0001; acetone, P < 0.0001; false discovery rate [FDR] adjusted). Increased glycerol levels (P < 0.0001), increased concentration of the ketogenic amino acid lysine (P = 0.03) and a significant correlation of 3-hydroxybutyrate levels with branched-chained amino acids (leucine, P = 0.02; isoleucine, P = 0.04 [FDR adjusted]) suggested that ketone body synthesis was driven by lipolysis and amino acid breakdown. Interestingly, the catabolic signature was independent of the body mass index, clinically assessed malnutrition using the nutritional risk screening score, and systemic inflammation assessed by CRP and leukocyte count. Longitudinal measurements and principal component analyses revealed a quick normalization of key metabolic alterations seven days post-surgery, including ketosis.

CONCLUSIONS

Together, the quantitative metabolic profile obtained by ¹ H NMR spectroscopy identified a tumour-induced catabolic signature specific to upper gastrointestinal cancer patients and enabled monitoring restoration of metabolic homeostasis after surgery. This approach was critical to identify the obtained metabolic profile as an upper gastrointestinal cancer-specific signature independent of malnutrition and inflammation.

Fecal microbiota transplantation and short-chain fatty acids reduce sepsis mortality by remodeling antibiotic-induced gut microbiota disturbances

Objective

Sepsis is the leading cause of death in critically ill patients. The gastrointestinal tract has long been thought to play an important role in the pathophysiology of sepsis. Antibiotic therapy can reduce a patient's commensal bacterial population and raise their risk of developing subsequent illnesses, where gut microbiota dysbiosis may be a key factor.

Methods

In this study, we analyzed the 16S rRNA of fecal samples from both healthy people and patients with sepsis to determine if alterations in gut bacteria are associated with sepsis. Then, we developed a mouse model of sepsis using cecal ligation and puncture (CLP) in order to examine the effects of fecal microbiota transplantation (FMT) and short-chain fatty acids (SCFAs) on survival rate, systemic inflammatory response, gut microbiota, and mucosal barrier function.

Results

Sepsis patients' gut microbiota composition significantly differed from that of healthy people. At the phylum level, the amount of Proteobacteria in the intestinal flora of sepsis patients was much larger than that of the control group, whereas the number of Firmicutes was significantly lower. Mice with gut microbiota disorders (ANC group) were found to have an elevated risk of death, inflammation, and organ failure as compared to CLP mice. However, all of these could be reversed by FMT and SCFAs. FMT and SCFAs could regulate the abundance of bacteria such as Firmicutes, Proteobacteria, Escherichia Shigella, and Lactobacillus, restoring them to levels comparable to those of healthy mice. In addition, they increased the expression of the Occludin protein in the colon of mice with sepsis, downregulated the expression of the NLRP3 and GSDMD-N proteins, and reduced the release of the inflammatory factors IL-1β and IL-18 to inhibit cell pyroptosis, ultimately playing a protective role in sepsis.

Disccusion

FMT and SCFAs provide a microbe-related survival benefit in a mouse model of sepsis, suggesting that they may be a viable treatment for sepsis.

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.

Untargeted serum metabolomics reveals potential biomarkers and metabolic pathways associated with esophageal cancer

Metabolomics has been reported as an efficient tool to screen biomarkers that are related to esophageal cancer. However, the metabolic biomarkers identifying malignant degrees and therapeutic efficacy are still largely unknown in the disease. Here, GC-MS-based metabolomics was used to understand metabolic alteration in 137 serum specimens from patients with esophageal cancer, which is approximately two- to fivefold as many plasma specimens as the previous reports. The elevated amino acid metabolism is in sharp contrast to the reduced carbohydrate as a characteristic feature of esophageal cancer. Comparative metabolomics showed that most metabolic differences were determined between the early stage (0–II) and the late stage (III and IV) among the 0–IV stages of esophageal cancer and between patients who received treatment and those who did not receive treatment. Glycine, serine, and threonine metabolism and glycine were identified as the potentially overlapped metabolic pathway and metabolite, respectively, in both disease progress and treatment effect. Glycine, fructose, ornithine, and threonine can be a potential array for the evaluation of disease prognosis and therapy in esophageal cancer. These results highlight the means of identifying previously unknown biomarkers related to esophageal cancer by a metabolomics approach.

SP and KLF Transcription Factors in Cancer Metabolism

Tumor development and progression depend on reprogramming of signaling pathways that regulate cell metabolism. Alterations to various metabolic pathways such as glycolysis, oxidative phosphorylation, lipid metabolism, and hexosamine biosynthesis pathway are crucial to sustain increased redox, bioenergetic, and biosynthesis demands of a tumor cell. Transcription factors (oncogenes and tumor suppressors) play crucial roles in modulating these alterations, and their functions are tethered to major metabolic pathways under homeostatic conditions and disease initiation and advancement. Specificity proteins (SPs) and Krüppel-like factors (KLFs) are closely related transcription factors characterized by three highly conserved zinc fingers domains that interact with DNA. Studies have demonstrated that SP and KLF transcription factors are expressed in various tissues and regulate diverse processes such as proliferation, differentiation, apoptosis, inflammation, and tumorigenesis. This review highlights the role of SP and KLF transcription factors in the metabolism of various cancers and their impact on tumorigenesis. A better understanding of the role and underlying mechanisms governing the metabolic changes during tumorigenesis could provide new therapeutic opportunities for cancer treatment.

Correlation between stage of prostate cancer and tyrosine and tryptophan in urine samples measured electrochemically

Prostate cancer (PCa) is the second most common cancer in men and one of the leading causes of cancer-related deaths. Early detection is the key to successful treatment and provides the greatest chance to cure the patient. Currently, early detection involves screening for prostate-specific antigen levels in blood, which is not a tumor-specific biomarker. There is a critical need to develop clinically useful methods for screening for more reliable biomarkers. Here, we introduce an electrochemical biosensor that measures the concentrations of the amino acids tyrosine and tryptophan, and propose it as a possible diagnostic and prognostic tool for PCa. The limits of detection of tyrosine and tryptophan using the electrochemical sensors were 1.15 and 1.13 μmol/L in 1:10 urine: PBS, respectively. This study is the first to present electrochemical measurements of tyrosine and tryptophan directly in patient urine samples. We demonstrated an inverse correlation between the measured electrochemical signals and the severity of PCa. The most notable observation was a significant difference between controls and metastatic PCa patients (P ≤ 0.001). This observation was further validated using Liquid-Chromatography-Mass Spectrometry. Our data provides the basis for further research with electrochemical measurements of tyrosine and tryptophan as potential biomarkers for PCa.

Untargeted metabolomics analysis of esophageal squamous cell cancer progression

90% of esophageal cancer are esophageal squamous cell carcinoma (ESCC) and ESCC has a very poor prognosis and high mortality. Nevertheless, the key metabolic pathways associated with ESCC progression haven’t been revealed yet. Metabolomics has become a new platform for biomarker discovery over recent years. We aim to elucidate dominantly metabolic pathway in all ESCC tumor/node/metastasis (TNM) stages and adjacent cancerous tissues. We collected 60 postoperative esophageal tissues and 15 normal tissues adjacent to the tumor, then performed Liquid Chromatography with tandem mass spectrometry (LC–MS/MS) analyses. The metabolites data was analyzed with metabolites differential and correlational expression heatmap according to stage I vs. con., stage I vs. stage II, stage II vs. stage III, and stage III vs. stage IV respectively. Metabolic pathways were acquired by Kyoto Encyclopedia of Genes and Genomes. (KEGG) pathway database. The metabolic pathway related genes were obtained via Gene Set Enrichment Analysis (GSEA). mRNA expression of ESCC metabolic pathway genes was detected by two public datasets: gene expression data series (GSE)23400 and The Cancer Genome Atlas (TCGA). Receiver operating characteristic curve (ROC) analysis is applied to metabolic pathway genes. 712 metabolites were identified in total. Glycerophospholipid metabolism was significantly distinct in ESCC progression. 16 genes of 77 genes of glycerophospholipid metabolism mRNA expression has differential significance between ESCC and normal controls. Phosphatidylserine synthase 1 (PTDSS1) and Lysophosphatidylcholine Acyltransferase1 (LPCAT1) had a good diagnostic value with Area under the ROC Curve (AUC) > 0.9 using ROC analysis. In this study, we identified glycerophospholipid metabolism was associated with the ESCC tumorigenesis and progression. Glycerophospholipid metabolism could be a potential therapeutic target of ESCC progression.

Bean cultivars (Phaseolus vulgaris L.) under the spotlight of NMR metabolomics

The seeds of Phaseolus vulgaris are a rich source of protein consumed around the world and are considered as the most important source of proteins and antioxidants in the Mexican diet. This work reports on the 1H NMR metabolomics profiling of the cultivars Peruano (FPe), Pinto (FPi), Flor de mayo (FM), Negro (FN) and Flor de junio (FJ). Total phenolics, total flavonoids and total protein contents were determined to complement the nutritional facts in seeds and leaves. According to our results, the metabolomics fingerprint of beans seeds and leaves were very similar, showing the presence of 52 metabolites, 46 in seeds and 48 in leaves, including 8 sugars, 17 amino acids, 15 organic acids, 5 nucleosides and 7 miscellaneous compounds. In seeds, free amino acids were detected in higher concentrations than in the leaves, whereas organic acids were more abundant in leaves than in seeds. With multivariate and cluster analysis it was possible to rank the cultivars according to their nutritional properties according to NMR profiling, then a machine learning algorithm was used to reveal the most important differential metabolites which are the key for correct classification. The results coincide in highlighting the FN seeds and FPe leaves for the best nutritional facts. Finally, in terms of cultivars, FN and FM present the best nutritional properties, with high protein and flavonoids content, as well as, a high concentration of amino acids and nucleosides.

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.

The Role of Microbiota in the Pathogenesis of Esophageal Adenocarcinoma

Simple Summary

Esophageal adenocarcinoma has a poor 5-year survival rate and is among the highest mortality cancers. Changes in the esophageal microbiome have been associated with cancer pathogenesis; however, the molecular mechanism remains obscure. This review article critically analyzes the molecular mechanisms through which microbiota may mediate the development and progression of esophageal adenocarcinoma and its precursors-gastroesophageal reflux disease and Barrett’s esophagus. It summarizes changes in esophageal microbiome composition in normal and pathologic states and subsequently discusses the role of altered microbiota in disease progression. The potential role of esophageal microbiota in protecting against the development of esophageal adenocarcinoma is also discussed. By doing so, this article highlights specific directions for future research developing microbiome-mediated therapeutics for esophageal adenocarcinoma.

Abstract

Esophageal adenocarcinoma (EAC) is associated with poor overall five-year survival. The incidence of esophageal cancer is on the rise, especially in Western societies, and the pathophysiologic mechanisms by which EAC develops are of extreme interest. Several studies have proposed that the esophageal microbiome may play an important role in the pathophysiology of EAC, as well as its precursors—gastroesophageal reflux disease (GERD) and Barrett’s esophagus (BE). Gastrointestinal microbiomes altered by inflammatory states have been shown to mediate tumorigenesis directly and are now being considered as novel targets for both cancer treatment and prevention. Elucidating molecular mechanisms through which the esophageal microbiome potentiates the development of GERD, BE, and EAC will provide a foundation on which new therapeutic targets can be developed. This review summarizes current findings that elucidate the molecular mechanisms by which microbiota promote the pathogenesis of GERD, BE, and EAC, revealing potential directions for additional research on the microbiome-mediated pathophysiology of EAC.

Metabolic and Immunological Subtypes of Esophageal Cancer Reveal Potential Therapeutic Opportunities

BACKGROUND

Esophageal cancer has the sixth highest rate of cancer-associated deaths worldwide, with many patients displaying metastases and chemotherapy resistance. We sought to find subtypes to see if precision medicine could play a role in finding new potential targets and predicting responses to therapy. Since metabolism not only drives cancers but also serves as a readout, metabolism was examined as a key reporter for differences.

METHODS

Unsupervised and supervised classification methods, including hierarchical clustering, partial least squares discriminant analysis, k-nearest neighbors, and machine learning techniques, were used to discover and display two major subgroups. Genes, pathways, gene ontologies, survival, and immune differences between the groups were further examined, along with biomarkers between the groups and against normal tissue.

RESULTS

Esophageal cancer had two major unique metabolic profiles observed between the histological subtypes esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). The metabolic differences suggest that ESCC depends on glycolysis, whereas EAC relies more on oxidative metabolism, catabolism of glycolipids, the tricarboxylic acid (TCA) cycle, and the electron transport chain. We also noted a robust prognostic risk associated with COQ3 expression. In addition to the metabolic alterations, we noted significant alterations in key pathways regulating immunity, including alterations in cytokines and predicted immune infiltration. ESCC appears to have increased signature associated with dendritic cells, Th17, and CD8 T cells, the latter of which correlate with survival in ESCC. We bioinformatically observed that ESCC may be more responsive to checkpoint inhibitor therapy than EAC and postulate targets to enhance therapy further. Lastly, we highlight correlations between differentially expressed enzymes and the potential immune status.

CONCLUSION

Overall, these results highlight the extreme differences observed between the histological subtypes and may lead to novel biomarkers, therapeutic strategies, and differences in therapeutic response for targeting each esophageal cancer subtype.

1 H NMR-based metabolomics of paired esophageal tumor tissues and serum samples identifies specific serum biomarkers for esophageal cancer

Serum metabolites of healthy controls and esophageal cancer (EC) patients have previously been compared to predict cancer-specific profiles. However, the association between metabolic alterations in serum samples and esophageal tissues in EC patients remains unclear. Here, we analyzed 50 pairs of EC tissues and distant noncancerous tissues, together with patient-matched serum samples, using ¹ H NMR spectroscopy and pattern recognition algorithms. EC patients could be differentiated from the controls based on the metabolic profiles at tissue and serum levels. Some overlapping discriminatory metabolites, including valine, alanine, glucose, acetate, citrate, succinate and glutamate, were identified in both matrices. These results suggested deregulation of metabolic pathways, and potentially revealed the links between EC and several metabolic pathways, such as the tricarboxylic acid cycle, glutaminolysis, short-chain fatty acid metabolism, lipometabolism and pyruvate metabolism. Perturbation of the pyruvate metabolism was most strongly associated with EC progression. Consequently, an optimal serum metabolite biomarker panel comprising acetate and pyruvate was developed, as these two metabolites are involved in pyruvate metabolism, and changes in their serum levels were significantly correlated with alterations in the levels of some other esophageal tissue metabolites. In comparison with individual biomarkers, this panel exhibited better diagnostic efficiency for EC, with an AUC of 0.948 in the test set, and a good predictive ability of 82.5% in the validation set. Analysis of key genes related to pyruvate metabolism in EC patients revealed patterns corresponding to the changes in serum pyruvate and acetate levels. These correlation analyses demonstrate that there were distinct metabolic characteristics and pathway aberrations in the esophageal tumor tissue and in the serum. Changes in the serum metabolic signatures could reflect the alterations in the esophageal tumor profile, thereby emphasizing the importance of distinct serum metabolic profiles as potential noninvasive biomarkers for EC.

The Effect of Blood Contained in the Samples on the Metabolomic Profile of Mouse Brain Tissue: A Study by NMR Spectroscopy

(1) Recently, metabolic profiling of the tissue in the native state or extracts of its metabolites has become increasingly important in the field of metabolomics. An important factor, in this case, is the presence of blood in a tissue sample, which can potentially lead to a change in the concentration of tissue metabolites and, as a result, distortion of experimental data and their interpretation. (2) In this paper, the metabolomic profiling based on NMR spectroscopy was performed to determine the effect of blood contained in the studied samples of brain tissue on their metabolomic profile. We used 13 male laboratory CD-1^® IGS mice for this study. The animals were divided into two groups. The first group of animals (n = 7) was subjected to the perfusion procedure, and the second group of animals (n = 6) was not perfused. The brain tissues of the animals were homogenized, and the metabolite fraction was extracted with a water/methanol/chloroform solution. Samples were studied by high-frequency ¹H-NMR spectroscopy with subsequent statistical data analysis. The group comparison was performed with the use of the Student's test. We identified 36 metabolites in the brain tissue with the use of NMR spectroscopy. (3) For the major set of studied metabolites, no significant differences were found in the brain tissue metabolite concentrations in the native state and after the blood removal procedure. (4) Thus, it was shown that the presence of blood does not have a significant effect on the metabolomic profile of the brain in animals without pathologies.

Non-target metabolomic analysis reveals the therapeutic effect of Saposhnikovia divaricata decoction on collagen-induced arthritis rats

ETHNOPHARMACOLOGICAL RELEVANCE

Saposhnikovia divaricata (SD), a Chinese crude drug, has long been recognized for therapeutic effect to rheumatoid arthritis (RA). At present, the mechanisms of SD treatment in RA have not been fully understood especially on the perspective of metabolomics.

AIM OF THE STUDY

To study the pharmacodynamic effects of Saposhnikovia divaricata decoction on CIA rats, and explore the therapeutic mechanism by metabolomics methods.

MATERIALS AND METHODS

Wistar rats were randomly divided into normal group, CIA model group, dexamethasone group and SD decoction groups (10 g crude drug/kg, 5 g crude drug/kg and 2.5 g crude drug/kg of SDD). Body weight, arthritis scores, serum cytokine levels and histopathological parameters of rats were assessed. A metabolomics method based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOFMS) was established to collect the metabolic profiles of rats and explore the metabolic changes that occurred after SDD treatment.

RESULTS

SDD showed its protective effect on the affected joints, especially in the middle dosage group of SDD. Eighteen and 13 potential biomarkers for the SDD treatment of CIA rats were identified in the plasma and urine, respectively. SDD could regulate the disturbed metabolic pathways including tryptophan metabolism, glycerophospholipid catabolism, primary bile acid biosynthesis and fatty acid metabolism.

CONCLUSIONS

In summary, SDD treatment could effectively alleviate symptoms of RA and regulate metabolic disorders in CIA rats.

Differences in Several Factors in the Development of Erosive Esophagitis Among Patients at Various Stages of Metabolic Syndrome: A Cross-Sectional Study

BACKGROUND

Erosive esophagitis (EE) is strongly associated with metabolic syndrome (MS), but is not always recognized in individuals with MS and the prevalence of EE in individuals with non-MS is not low.

AIM

To examine the differences in clinical factors associated with EE at various stages of MS, as well as the differences in metabolites between subjects with MS, with and without EE.

METHODS

A total of 7,097 persons who underwent health checkups including esophagogastroduodenoscopy were analyzed. We examined the differences in clinical factors for EE among subjects with non-MS, pre-MS, and MS and compared metabolites between 34 subjects with MS, with and without EE.

RESULTS

EE prevalence was significantly higher in the MS and pre-MS groups than in the non-MS group (p < 0.001). EE severity was higher in the MS group than in the pre-MS and non-MS groups (p < 0.001). In the non-MS group, there were significant differences between subjects with and without EE with respect to Helicobacter pylori (H. pylori) and smoking. In the pre-MS and MS groups, there were significant differences in H. pylori, hiatal hernia, and drinking in those with and without EE. The levels of glutamine, hypoxanthine, and lactic acid metabolites were significantly different between subjects with MS, with and without EE (all p < 0.05).

CONCLUSION

Although H. pylori and lifestyle factors such as smoking and drinking are important for EE, differences in these factors should be considered at various stages of MS. Additionally, several metabolites may be involved in the development of EE in MS.

Metabolomics of Oral/Head and Neck Cancer

Oral/head and neck cancer is the sixth most common human malignancies in the world. Despite the treatment advances in surgery, chemotherapy, and radiotherapy, the patient survival has not been significantly improved in the past several decades. As a new methodological approach, metabolomics may help reveal the metabolic reprogramming mechanisms underlying head and neck cancer cell proliferation, invasion, and metastasis and may be used to identify metabolite biomarkers for clinical applications of the disease. In this chapter, we briefly review recent metabolomic applications in head and neck 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.

Unraveling the Microbial Mechanisms Underlying the Psychobiotic Potential of a Bifidobacterium breve Strain

SCOPE

The antidepressant-like effect of psychobiotics has been observed in both pre-clinical and clinical studies, but the molecular mechanisms of action are largely unclear. To address this, the psychobiotic strain Bifidobacterium breve CCFM1025 is investigated for its genomic features, metabolic features, and gut microbial and metabolic modulation effect.

METHODS AND RESULTS

Unlike B. breve FHLJDQ3M5, CCFM1025 significantly decreases the chronically stressed mice's depressive-like behaviors and neurological abnormalities. CCFM1025 has more genes encoding glycoside hydrolases (GHs) when comparing to FHLJDQ3M5's genome, which means CCFM1025 has a superior carbohydrate utilization capacity and living adaptivity in the gut. CCFM1025 also produces higher levels of neuromodulatory metabolites, including hypoxanthine, tryptophan, and nicotinate. The administration of CCFM1025 reshapes the gut microbiome of chronically stressed mice. It results in higher cecal xanthine, tryptophan, short-chain fatty acid levels, and enhances fatty acid and tryptophan biosynthesis capability in the gut-brain interaction (identified by in silico analyses) than FHLJDQ3M5-treated mice.

CONCLUSIONS

Genomic and metabolic features involving GHs and neuromodulatory metabolites may determine the antidepressant-like effect of B. breve CCFM1025. Psychobiotics' characterization in this manner may provide guidelines for developing novel psychopharmacological agents in the future.

Profile of gut flora in hypertensive patients with insufficient sleep duration

Recently, the contribution of both insufficient sleep duration and gut microbiome dysbiosis to hypertension (HTN) have been revealed, yet the profile of gut flora in hypertensive patients with insufficient sleep duration remains unknown. To examine this condition, the specific shifts in the fecal microbiome of 53 participants with or without HTN were investigated. The patients were divided into those who slept short (≤6 h) or optimal (6-9 h) duration per day. Comprehensive metagenomic sequencing analysis of fecal specimens was performed in healthy controls with sufficient sleep (s-CTR, n = 10), healthy controls with insufficient sleep (ins-CTR, n = 6), hypertensive patients with sufficient sleep (s-HTN, n = 25), and HTNs complicated by short sleep duration (ins-HTN, n = 12). We found that the α-diversity and β-diversity were quite similar between s-HTN and ins-HTN. Similarities were also observed in the enterotype distribution between s-HTN and ins-HTN subjects. In addition, the enrichment of gut bacteria was evident, such as Fusobacterium mortiferum and Roseburia inulinivorans in ins-HTN subjects. Several functional modules that were distinct between s-HTN and ins-HTN subjects were identified, which were unique to hypertensive patients with insufficient sleep duration. Overall, the data demonstrated that the gut microbial features were largely maintained in hypertensive participants with insufficient sleep duration.

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.

Volatile Organic Compounds in Human Exhaled Breath to Diagnose Gastrointestinal Cancer: A Meta-Analysis

Introduction

Human exhaled volatile organic compounds (VOCs) are being extensively studied for the purposes of noninvasive cancer diagnoses. This article was primarily to assess the feasibility of utilizing exhaled VOCs analysis for gastrointestinal cancer (GIC) diagnosis.

Methods

PRISMA-based system searches were conducted for related studies of exhaled VOCs in GIC diagnosis based on predetermined criteria. Relevant articles on colorectal cancer and gastroesophageal cancer were summarized, and meta analysis was performed on articles providing sensitivity and specificity data.

Results

From 2,227 articles, 14 were found to meet inclusion criteria, six of which were on colorectal cancer (CRC) and eight on Gastroesophageal cancer(GEC). Five articles could provide specific data of sensitivity and specificity in GEC, which were used for meta-analysis. The pooled sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) were calculated based on the combination of these data, and were 85.0% [95% confidence interval (CI): 79.0%-90.0%], 89.0% (95%CI: 86.0%-91.0%), 41.30 (21.56-79.10), and 0.93, respectively.

Conclusion

VOCs can distinguish gastrointestinal cancers from other gastrointestinal diseases, opening up a new avenue for the diagnosis and identification of gastrointestinal cancers, and the analysis of VOCs in exhaled breath has potential clinical application in screening. VOCs are promising tumor biomarkers for GIC diagnosis. Furthermore, limitations like the heterogeneity of diagnostic VOCs between studies should be minded.

Polycythemia Vera and Essential Thrombocythemia Patients Exhibit Unique Serum Metabolic Profiles Compared to Healthy Individuals and Secondary Thrombocytosis Patients

Simple Summary

Current diagnosis of myeloproliferative neoplasms (MPNs), including polycythemia vera (PV) and essential thrombocythemia (ET), is controversial due to limitations associated with the lack of reproducibility, subjectivity and the presence of common somatic mutations in the driver genes. Metabolomics represents a powerful approach to identify altered metabolites that can differentiate between disease status at the time of diagnosis. The objective of this study was to characterize the serum metabolic profile of MPNs patients (PV and ET) and compare it with healthy controls (HC) and secondary thrombocytosis (ST) patients. The analysis revealed metabolites following similar trends between PV and ET patients, as well as unique significant differences in the serum metabolite levels of MNPs patients compared to HC and ST patients. These results could contribute to better differentiate patients with these diseases from HC and ST patients.

Abstract

Most common myeloproliferative neoplasms (MPNs) include polycythemia vera (PV) and essential thrombocythemia (ET). Accurate diagnosis of these disorders remains a clinical challenge due to the lack of specific clinical or molecular features in some patients enabling their discrimination. Metabolomics has been shown to be a powerful tool for the discrimination between different hematological diseases through the analysis of patients’ serum metabolic profiles. In this pilot study, the potential of NMR-based metabolomics to characterize the serum metabolic profile of MPNs patients (PV, ET), as well as its comparison with the metabolic profile of healthy controls (HC) and secondary thrombocytosis (ST) patients, was assessed. The metabolic profile of PV and ET patients, compared with HC, exhibited higher levels of lysine and decreased levels of acetoacetic acid, glutamate, polyunsaturated fatty acids (PUFAs), scyllo-inositol and 3-hydroxyisobutyrate. Furthermore, ET patients, compared with HC and ST patients, were characterized by decreased levels of formate, N-acetyl signals from glycoproteins (NAC) and phenylalanine, while the serum profile of PV patients, compared with HC, showed increased concentrations of lactate, isoleucine, creatine and glucose, as well as lower levels of choline-containing metabolites. The overall analysis revealed significant metabolic alterations mainly associated with energy metabolism, the TCA cycle, along with amino acid and lipid metabolism. These results underscore the potential of metabolomics for identifying metabolic alterations in the serum of MPNs patients that could contribute to improving the clinical management of these diseases.

Serum Metabolomics for Biomarker Screening of Esophageal Squamous Cell Carcinoma and Esophageal Squamous Dysplasia Using Gas Chromatography-Mass Spectrometry

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is one of the most common malignancies with poor diagnosis. Esophageal squamous dysplasia (ESD) is considered as an immediate precancerous lesion of ESCC. Lack of biomarkers for discriminating ESCC and ESD from healthy subjects limits the early diagnosis and treatment of ESCC. Therefore, a serum metabolomic strategy was conducted to identify and validate potential metabolic markers for the screening of ESCC and ESD subjects.

METHODS

A total of 74 patients with ESCC, 72 patients with ESD, and 75 normal control (NC) subjects were enrolled in this study. Gas chromatography-mass spectrometry was used to acquire serum metabolic profiles. Pathway analysis was conducted to uncover the fluctuated metabolic pathways during ESCC. Multivariate analyses were used to screen and validate the biomarkers.

RESULTS

ESCC, ESD, and NC subjects revealed progressively altered metabolic profiles, in which amino acids globally increased, while fatty acids decreased in ESCCs compared with the control groups. Pathway analysis demonstrated the activated biosynthesis of amino acids and inhibited desaturation of saturated fatty acids. The panel constructed with propanoic acid, linoleic acid, glycerol-3-phosphate, and l-glutamine showed the area under the curve (AUC), sensitivity, and specificity of 0.817, 0.75, and 0.74, respectively, in the discrimination of ESCC/ESD patients from NC subjects. The panel constructed by propanoic acid, l-leucine, and hydroxyproline revealed the AUC, sensitivity, and specificity of 0.819, 0.76, and 0.72, respectively, in the discrimination of ESD from NC subjects. The combination of hypoxanthine, 2-ketoisocaproic acid, l-glutamate, and l-aspartate showed the AUC, sensitivity, and specificity of 0.818, 0.83, and 0.74, respectively, in the discrimination of ESCC patients from ESD subjects.

CONCLUSIONS

Our study revealed the systematic landscape for metabolic alterations in sera of ESD and ESCC patients. The defined metabolite markers showed reasonable performance in the discrimination of ESCC and ESD patients, and may provide helpful reference for clinicians and biologists.

Targeted Metabolomics Analyses Reveal Specific Metabolic Alterations in High-Grade Prostate Cancer Patients

Prostate cancer (PCa) is a hormone-dependent tumor characterized by an extremely heterogeneous prognosis. Despite recent advances in partially uncovering some of the biological processes involved in its progression, there is still an urgent need for identifying more accurate and specific prognostic procedures to differentiate between disease stages. In this context, targeted approaches, focused on mapping dysregulated metabolic pathways, could play a critical role in identifying the mechanisms driving tumorigenesis and metastasis. In this study, a targeted analysis of the nuclear magnetic resonance-based metabolomic profile of PCa patients with different tumor grades, guided by transcriptomics profiles associated with their stages, was performed. Serum and urine samples were collected from 73 PCa patients. Samples were classified according to their Gleason score (GS) into low-GS (GS < 7) and high-GS PCa (GS ≥ 7) groups. A total of 36 metabolic pathways were found to be dysregulated in the comparison between different PCa grades. Particularly, the levels of glucose, glycine and 1-methlynicotinamide, metabolites involved in energy metabolism and nucleotide synthesis were significantly altered between both groups of patients. These results underscore the potential of targeted metabolomic profiling to characterize relevant metabolic changes involved in the progression of this neoplastic process.

Novel Antiproliferative Biphenyl Nicotinamide: NMR Metabolomic Study of its Effect on the MCF-7 Cell in Comparison with Cisplatin and Vinblastine

A 1H-NMR-based metabolomic study was performed on MCF-7 cell lines treated with a novel nicotinamide derivative (DT-8) in comparison with two drugs characterized by a well-established mechanism of action, namely the DNA-metalating drug cisplatin (cis-diamminedichloridoplatinum(II), CDDP) and the antimitotic drug vinblastine (vinblastine, VIN). The effects of the three compounds, each one at the concentration corresponding to the IC50 value, were investigated, with respect to the controls (K), by the 1H-NMR of cells lysates and multivariate analysis (MVA) of the spectroscopic data. Relevant differences were found in the metabolic profiles of the different treatments with respect to the controls. A large overlap of the metabolic profiles in DT-8 vs. K and VIN vs. K suggests a similar biological response and mechanism of action, significantly diverse with respect to CDDP. On the other hand, DT8 seems to act by disorganizing the mitotic spindle and ultimately blocking the cell division, through a mechanism implying methionine depletion and/or S-adenosylmethionine (SAM) limitation.

Modulatory effects of Xihuang Pill on lung cancer treatment by an integrative approach

Lung cancer has a rapidly increasing incidence and remains the highest ranked cancer in terms of mortality worldwide. Xihuang Pill(XHW), a famous four-herb traditional Chinese formulation, has been used to treat lung cancer in China for more than 100 years. It is usually prescribed as a complementary and alternative medicine for cancer therapy. However, the main active ingredients of XHW that treat lung cancer and their regulatory effects remain unclear. Here, we revealed modulatory effects effects of XHW on lung cancer in a mouse model of Lewis lung cancer (LLC) by a comprehensive strategy combining network pharmacology with metabolomics. The results demonstrated that XHW inhibited tumour growth in this model. Additionally, 11 differentially expressed metabolites were identified in the XHW group compared to those in the model group or normal group by untargeted metabolomics. They were enriched in amino acid-related metabolic pathways, and the top three pathways were phenylalanine metabolism; phenylalanine, tyrosine and tryptophan biosynthesis; and aminoacyl-tRNA biosynthesis. A total of 107 active components derived from Niuhuang, Shexiang, Ruxiang and Moyao, directly acted on 13 important targets (NR3C2, AKR1D1, MPO, PNP, NT5E, TAAR1, ADRB2, ADRB1, ADRA1A, ADRA2B, ADRA2A, MAOA and MAOB) to regulate 4 metabolites (L-phenylalanine, l-adrenaline, corticosterone and guanosine). Our results suggested that the key metabolites of XHW involved in the treatment of lung cancer were regulated by a multi-component and multi-target interaction network. This research elucidated the modulatory effect and therapeutic advantages of XHW treatment for lung tumours through an integrated approach.

Angustoline Inhibited Esophageal Tumors Through Regulating LKB1/AMPK/ELAVL1/LPACT2 Pathway and Phospholipid Remodeling

Esophageal cancer is a type of gastrointestinal carcinoma and is among the 10 most common causes of cancer death worldwide. However, the specific mechanism and the biomarkers in the proliferation and metastasis of esophageal tumors are still unclear. Therefore, the development of several natural products which could inhibit esophageal tumors deserve attention. In the present study, different sources of cancer cells were used to select the sensitive cell line (esophageal cancer cell KYSE450) and the proper dose of angustoline, which were utilized in the following cell viability, migration and invasion assays. Then the lipidomic detection of clinical samples (tissue and blood plasma) from esophageal cancer patients was performed, to screen out the specific phospholipid metabolites [PC (16:0/18:1) and LPC (16:0)]. Considering lysophosphatidylcholine acyltransferase 2 (LPCAT2) was tightly relative with phospholipids conversion, serine/threonine-protein kinase 11 (LKB1), 5'-monophosphate (AMP)-activated protein kinase (AMPK) and embryonic lethal, and abnormal vision, drosophila-like 1 (ELAVL1) were investigated, to evaluate their expression levels in esophageal tumor tissue and KYSE450 cells. Additionally, KYSE450 tumor bearing mouse model was constructed, the role of angustoline in inhibiting esophageal tumors through regulating LKB1/AMPK/ELAVL1/LPCAT2 pathway was validated, and found that the conversion from LPC (16:0) to PC (16:0/18:1) was blocked by angustoline in some degree. The above results for the first time proved that angustoline suppressed esophageal tumors through activating LKB1/AMPK and inhibiting ELAVL1/LPCAT2, which consequently blocked phospholipid remodeling from LPC (16:0) to PC (16:0/18:1).

Revealing the sedative-hypnotic effect of the extracts of herb pair Semen Ziziphi spinosae and Radix Polygalae and related mechanisms through experiments and metabolomics approach

BACKGROUND

Semen Ziziphi spinosae and Radix Polygalae, two herbs commonly used together in Traditional Chinese Medicine for the treatment of insomnia and anxiety. The study aims to study the sedative-hypnotic effect of the active components of the herbal pair, the possible mechanisms of such effect, and related metabolic pathways in vivo.

METHODS

The sedative and hypnotic effect of the active components (EI30) of the herbal pair was studied by recording influence on the proportion of sleeping within 30 min, sleep latency and sleep length of pentobarbital sodium-induced sleeping on mice. Possible mechanisms of the sedative-hypnotic effect of the active components were investigated by measuring the content of neurotransmitters in the total protein of mice brain tissue. The main chemical compounds of the herbal pair were identified by Liquid Chromatography-Mass Spectrometry (LC-MS). Serum samples of mice were studied, and related differential metabolites between the normal group and model group, and between model group and treatment group were identified by Gas Chromatography Time-Of-Flight Mass Spectrometry (GC-TOF-MS), Principal Components Analysis (PCA), and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA).

RESULTS

Compared with the control group, high dose EI30 group and the Clonazepam group were with significantly higher proportions of sleep within 30 min (P = 0.027 and 0.005 respectively). Compared with the control group, all of the high, medium and low dose of EI30 groups were with significantly shorter sleep latency (P < 0.01) and prolonged sleeping time (P < 0.01). The herbal pair has good sedative-hypnotic effects, although it is weaker than the effect of Clonazepam. The sedative-hypnotic effect of EI30 is possibly related to the adjustment of neurotransmitters 5-hydroxytryptamine (5-HT), norepinephrine (NE), and dopamine (DA) in the total protein of mice brain tissue. There are five metabolic pathways in vivo most related to the sedative-hypnotic effect of EI30, and they are biosynthesis of valine, leucine, and isoleucine, metabolism of glyceride, metabolism of alanine, aspartic acid and glutamic acid, metabolism of phenylalanine, and metabolism of cysteine and methionine.

CONCLUSIONS

This study reveals the mechanisms of sedative and hypnotic effects of herbal pair Semen Ziziphi spinosae and Radix Polygalae by using metabolomics methods. This study provides a basis for further development and utilization of this herbal pair.

PM2.5 exposure perturbs lung microbiome and its metabolic profile in mice

Fine particulate matter (PM2.5) have become a major public health concern because of their adverse effects on health. Lungs are considered the primary organ affected by PM2.5. In order to understand the mechanism underlying PM2.5-induced lung injury, 16S rRNA gene sequencing, and liquid chromatography-mass spectrometry (LC-MS) metabolomics analysis were conducted to investigate the impact of PM2.5 exposure on lung microbiome and its metabolic profile. Mice were exposed to PM2.5 through intratracheal instillation and a lung injury model was established. 16S rRNA gene sequencing indicated that PM2.5 exposure significantly altered the richness, evenness, and composition of the lung microbiome. Metabolomics profiling showed that the levels of lung metabolites were perturbed after PM2.5 exposure. The altered metabolites mainly belonged to metabolic pathways, such as the citrate cycle, glyoxylate and dicarboxylate metabolism, pyruvate metabolism, purine and pyrimidine metabolism, and valine, leucine, and isoleucine metabolism. The altered lung microbiota showed significant correlations with lung metabolites. The levels of fumaric acid negatively correlated with the relative abundance of Ruminococcaceae, Enterobacteriaceae, and Pseudomonadaceae. These results revealed that PM2.5 exposure not only significantly altered the lung microbiome composition but also perturbed a number of metabolites involved in diverse metabolic pathways. This study improves our understanding of the mechanism of lung injury after PM2.5 exposure.

Identification of Lesional Tissues and Nonlesional Tissues in Early Gastric Cancer Endoscopic Submucosal Dissection Specimens Using a Fiber Optic Raman System

Aim

To identify lesional and nonlesional tissues from early gastric cancer (EGC) patients by Raman spectroscopy to build a diagnostic model and effectively diagnose EGC.

Method

Specimens were collected by endoscopic submucosal dissection from 13 patients with EGC, and 55 sets of standard Raman spectral data (each integrated 10 times) were obtained using the fiber optic Raman system; there were 33 sets of lesional tissue data, including 18 sets of high-grade intraepithelial neoplasia (HGIN) data and 15 sets of adenocarcinoma data, and 22 sets of nonlesional tissue data. After the preprocessing steps, the average Raman spectrum was obtained.

Results

The nonlesional tissues showed peaks at 891 cm⁻¹, 1103 cm⁻¹, 1417 cm⁻¹, 1206 cm⁻¹, 1234 cm⁻¹, 1479 cm⁻¹, 1560 cm⁻¹, and 1678 cm⁻¹. Compared with the peaks corresponding to nonlesional tissues, the peaks of the lesional tissues shifted by different magnitudes, and a new characteristic peak at 1324 cm⁻¹ was observed. Comparing the peak intensity ratio and the integral energy ratio of the lesional tissues with those of the nonlesional tissues revealed a significant difference between the two groups (independent-samplest-test, P < 0.05). Considering the peak intensity ratio of I1560 cm⁻¹/I1103 cm⁻¹ as a diagnostic indicator, the accuracy, sensitivity, and specificity of diagnosing EGC were 98.8%, 93.9%, and 91.9%, respectively. Considering the integral energy ratio (noncontinuous frequency band and continuous frequency band) as a diagnostic indicator, the accuracy, sensitivity, and specificity of diagnosing EGC were 99.2-99.6%, 93.9-97.0%, and 95.5%, respectively.

Conclusions

The integral energy ratio of the Raman spectrum could be considered an effective indicator for the diagnosis of EGC.

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.

Canine metabolomics advances

INTRODUCTION

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

OBJECTIVES

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

METHOD

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

RESULTS

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

CONCLUSIONS

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

Metabolic profiling of serum in patients with cartilage tumours using 1 H-NMR spectroscopy: A pilot study

Cartilage-forming lesions include tumours that can vary in severity from benign enchondromas to high-grade malignant chondrosarcomas. Chondrosarcoma is the second most frequent malignant bone tumour, accounting for 20-30% of all malignant bone neoplasms. Surgery is the standard treatment for cartilage tumours (CTs); however, their incidental diagnosis and the difficult differentiation of low-grade lesions like chondrosarcoma grade I from benign entities like enchondroma are challenges for clinical management. In this sense, the search for circulating biomarkers for early detection and prognosis is an ongoing interest. Targeted metabolomics is a powerful tool that can propose potential biomarkers in biological fluids as well as help to discover disturbed metabolic pathways to reveal tumour pathogenesis. In this context, the aim of this study was to investigate the ¹ H nuclear magnetic resonance metabolomic serum profile of patients with CTs contrasted with healthy controls. Forty-one metabolites were identified and quantified; the multivariate statistical methods principal component analysis and partial least squares discriminant analysis reveal a clear separation of the CT group, that is, the differential metabolites that were involved in two main metabolic pathways: the taurine and hypotaurine metabolism and synthesis and degradation of ketone bodies. Our results represent preliminary work for emergent serum-based diagnostics or prognostic methods for patients with chondrogenic tumours.

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.

Hyperspectral Raman microscopy can accurately differentiate single cells of different human thyroid nodules

We report on the use of line-scan hyperspectral Raman microscopy in combination with multivariate statistical analyses for identifying and classifying single cells isolated from clinical samples of human thyroid nodules based on their intrinsic Raman spectral signatures. A total of 248 hyperspectral Raman images of single cells from benign thyroid (n = 127) and classic variant of papillary carcinoma (n = 121) nodules were collected. Spectral differences attributed to phenylalanine, tryptophan, proteins, lipids, and nucleic acids were identified for benign and papillary carcinoma cells. Using principal component analysis and linear discriminant analysis, cells were identified with 97% diagnostic accuracy. In addition, preliminary data of cells from follicular adenoma (n = 20), follicular carcinoma (n = 25), and follicular variant of papillary carcinoma (n = 18) nodules suggest the feasibility of further discrimination of subtypes. Our findings indicate that hyperspectral Raman microscopy can potentially be developed into an objective approach for analyzing single cells from fine needle aspiration (FNA) biopsies to enable the minimally invasive diagnosis of "indeterminate" thyroid nodules and other challenging cases.

Recent advances in microfluidic methods in cancer liquid biopsy

Early cancer detection, its monitoring, and therapeutical prediction are highly valuable, though extremely challenging targets in oncology. Significant progress has been made recently, resulting in a group of devices and techniques that are now capable of successfully detecting, interpreting, and monitoring cancer biomarkers in body fluids. Precise information about malignancies can be obtained from liquid biopsies by isolating and analyzing circulating tumor cells (CTCs) or nucleic acids, tumor-derived vesicles or proteins, and metabolites. The current work provides a general overview of the latest on-chip technological developments for cancer liquid biopsy. Current challenges for their translation and their application in various clinical settings are discussed. Microfluidic solutions for each set of biomarkers are compared, and a global overview of the major trends and ongoing research challenges is given. A detailed analysis of the microfluidic isolation of CTCs with recent efforts that aimed at increasing purity and capture efficiency is provided as well. Although CTCs have been the focus of a vast microfluidic research effort as the key element for obtaining relevant information, important clinical insights can also be achieved from alternative biomarkers, such as classical protein biomarkers, exosomes, or circulating-free nucleic acids. Finally, while most work has been devoted to the analysis of blood-based biomarkers, we highlight the less explored potential of urine as an ideal source of molecular cancer biomarkers for point-of-care lab-on-chip devices.

1H-NMR spectroscopy identifies potential biomarkers in serum metabolomic signatures for early stage esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent types of upper gastrointestinal malignancies. Here, we used ¹H nuclear magnetic resonance spectroscopy (¹H-NMR) to identify potential serum biomarkers in patients with early stage ESCC.

METHODS

Sixty-five serum samples from early stage ESCC patients (n = 25) and healthy controls (n = 40) were analysed using ¹H-NMR spectroscopy. We distinguished between different metabolites through principal component analysis, partial least squares-discriminant analysis, and orthogonal partial least squares-discriminant analysis (OPLS-DA) using SIMCA-P+ version 14.0 software. Receiver operating characteristic (ROC) analysis was conducted to verify potential biomarkers.

RESULTS

Using OPLS-DA, 31 altered serum metabolites were successfully identified between the groups. Based on the area under the ROC curve (AUROC), and the biomarker panel with AUROC of 0.969, six serum metabolites (α-glucose, choline, glutamine, glutamate, valine, and dihydrothymine) were selected as potential biomarkers for early stage ESCC. Dihydrothymine particularly was selected as a new feasible biomarker associated with tumor occurrence.

CONCLUSIONS

¹H-NMR spectroscopy may be a useful tumour detection approach in identifying useful metabolic ESCC biomarkers for early diagnosis and in the exploration of the molecular pathogenesis of ESCC.

Exploring potential biomarkers of early stage esophageal squamous cell carcinoma in pre- and post-operative serum metabolomic fingerprint spectrum using 1H-NMR method

Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent types of upper gastrointestinal malignancy. Here, we used ¹H nuclear magnetic resonance spectroscopy (¹H-NMR) to identify potential pre- and post-operative serum biomarkers in patients with early stage ESCC using metabolomic fingerprint spectrum. Serum samples from preoperative patients with ESCC (ESCC, n = 25), postoperative patients with ESCC (PO, n = 24), and controls (n = 40) were analysed using ¹H-NMR spectroscopy. Using orthogonal partial least squares-discriminant analysis, 31 altered serum metabolites were successfully identified among the three groups. These metabolites are indicative of the changes that occur with glycometabolism, the metabolism of fatty acids, amino acids, choline, ketone bodies, nucleotides, and lipids. Based on receiver operating characteristic (ROC) curve analysis and a biomarker panel with an area under the curve (AUC) of 0.969, six serum metabolites (α-glucose, choline, glutamine, glutamate, valine, and dihydrothymine) were selected as potential diagnostic biomarkers for early stage ESCC. Additionally, four potential PO biomarkers (α-glucose, pyruvate, glutamate, and valine) with an AUC of 0.985 were selected to distinguish ESCC and PO. Many metabolites trended towards normalisation in PO patients, with only choline remaining high with an AUC of 0.858, suggesting that it may be a valuable potential biomarker for neoplasm progression, recurrence, chemoradiotherapy, and prognosis. ¹H-NMR spectroscopy may be a useful tumour detection approach in the early diagnosis of ESCC. These results also indicate that it is useful to differentiate pre- and post-operative ESCC, evaluate surgery therapeutic responses, and monitor postoperative chemoradiotherapy.

Diagnostic value of plasma tryptophan and symmetric dimethylarginine levels for acute kidney injury among tacrolimus-treated kidney transplant patients by targeted metabolomics analysis

Few literatures have evaluated the exact role of metabolomics in the identification process of potential biomarkers for acute kidney injury among the patients receiving renal transplantation. On top of this, the success of metabolomics in biomarker translation seems to lie in the robust quantitative method. As such, a single-center retrospective observational study was conducted enrolling 42 patients underwent renal transplantation with/without acute kidney injury, as well as 24 healthy volunteers, in Shanghai Changzheng Hospital. Plasma amino acid metabolic patterns for the participants were investigated by targeted UHPLC-MS/MS metabolic profiling. The most significant changes of the explored metabolites were related to the disturbance of tryptophan metabolism and arginine metabolism. Abnormal circulating tryptophan and symmetric dimethylarginine were identified to be potential biomarkers of acute kidney injury, combination of which showed a higher area under receiver-operator curve value (AUC = 0.901), improved sensitivity (0.889) and specificity (0.831) compared with creatinine only. Overall, these results revealed that targeted metabolomics analysis would be a potent and promising strategy for identification and pre-validation of biomarkers of acute kidney injury in renal transplantation patients.

A Framework for Development of Useful Metabolomic Biomarkers and Their Effective Knowledge Translation

Despite the significant advantages of metabolomic biomarkers, no diagnostic tests based on metabolomics have been introduced to clinical use. There are many reasons for this, centered around substantial obstacles in developing clinically useful metabolomic biomarkers. Most significant is the need for interdisciplinary teams with expertise in metabolomics, analysis of complex clinical and metabolomic data, and clinical care. Importantly, the clinical need must precede biomarker discovery, and the experimental design for discovery and validation must reflect the purpose of the biomarker. Standard operating procedures for procuring and handling samples must be developed from the beginning, to ensure experimental integrity. Assay design is another challenge, as there is not much precedent informing this. Another obstacle is that it is not yet clear how to protect any intellectual property related to metabolomic biomarkers. Viewing a metabolomic biomarker as a natural phenomenon would inhibit patent protection and potentially stifle commercial interest. However, demonstrating that a metabolomic biomarker is actually a derivative of a natural phenomenon that requires innovation would enhance investment in this field. Finally, effective knowledge translation strategies must be implemented, which will require engagement with end users (clinicians and lab physicians), patient advocate groups, policy makers, and payer organizations. Addressing each of these issues comprises the framework for introducing a metabolomic biomarker to practice.

Nuclear magnetic resonance spectroscopy as a new approach for improvement of early diagnosis and risk stratification of prostate cancer

Prostate cancer (PCa) is the second most common male cancer worldwide and the fifth leading cause of death from cancer in men. Early detection and risk stratification is the most effective way to improve the survival of PCa patients. Current PCa biomarkers lack sufficient sensitivity and specificity to cancer. Metabolite biomarkers are evolving as a new diagnostic tool. This review is aimed to evaluate the potential of metabolite biomarkers for early detection, risk assessment, and monitoring of PCa. Of the 154 identified publications, 27 and 38 were original papers on urine and serum metabolomics, respectively. Nuclear magnetic resonance (NMR) is a promising method for measuring concentrations of metabolites in complex samples with good reproducibility, high sensitivity, and simple sample processing. Especially urine-based NMR metabolomics has the potential to be a cost-efficient method for the early detection of PCa, risk stratification, and monitoring treatment efficacy.