Tissue metabolic profiling of human gastric cancer assessed by (1)H NMR

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.

Uracil as a biomarker for spatial pyrimidine metabolism in the development of gingivobuccal oral squamous cell carcinoma

No biomarker has yet been identified that allows accurate diagnosis and prognosis of oral cancers. In this study, we investigated the presence of key metabolites in oral cancer using proton nuclear magnetic resonance (NMR) spectroscopy to identify metabolic biomarkers of gingivobuccal oral squamous cell carcinoma (GB-OSCC). NMR spectroscopy revealed that uracil was expressed in 83.09% of tumor tissues and pyrimidine metabolism was active in GB-OSCC; these results correlated well with immunohistochemistry (IHC) and RNA sequencing data. Based on further gene and protein analyses, we proposed a pathway for the production of uracil in GB-OSCC tissues. Uridinetriphosphate (UTP) is hydrolyzed to uridine diphosphate (UDP) by CD39 in the tumor microenvironment (TME). We hypothesized that UDP enters the cell with the help of the UDP-specific P2Y6 receptor for further processing by ENTPD4/5 to produce uracil. As the ATP reserves diminish, the weakened immune cells in the TME utilize pyrimidine metabolism as fuel for antitumor activity, and the same mechanism is hijacked by the tumor cells to promote their survival. Correspondingly, the differential expression of ENTPD4 and ENTPD5 in immune and tumor cells, respectively, indicatedtheir involvement in disease progression. Furthermore, higher uracil levels were detected in patients with lymph node metastasis, indicating that metastatic potential is increased in the presence of uracil. The presence of uracil and/or expression patterns of intermediate molecules in purine and pyrimidine pathways, such asCD39, CD73, and P2Y6 receptors together with ENTPD4 and ENTPD5, hold promise as biomarker(s) for oral cancer diagnosis and prognosis.

Metabolic Profiling of Aromatic Compounds

Metabolic profiling is a powerful modern tool in searching for novel biomarkers and indicators of normal or pathological processes in the body [...].

Research progress of metabolomics in cervical cancer

INTRODUCTION

Cervical cancer threatens women's health seriously. In recent years, the incidence of cervical cancer is on the rise, and the age of onset tends to be younger. Prevention, early diagnosis and specific treatment have become the main means to change the prognosis of cervical cancer patients. Metabolomics research can directly reflect the changes of biochemical processes and microenvironment in the body, which can provide a comprehensive understanding of the changes of metabolites in the process of disease occurrence and development, and provide new ways for the prevention and diagnosis of diseases.

OBJECTIVES

The aim of this study is to review the metabolic changes in cervical cancer and the application of metabolomics in the diagnosis and treatment.

METHODS

PubMed, Web of Science, Embase and Scopus electronic databases were systematically searched for relevant studies published up to 2022.

RESULTS

With the emergence of metabolomics, metabolic regulation and cancer research are further becoming a focus of attention. By directly reflecting the changes in the microenvironment of the body, metabolomics research can provide a comprehensive understanding of the patterns of metabolites in the occurrence and development of diseases, thus providing new ideas for disease prevention and diagnosis.

CONCLUSION

With the continuous, in-depth research on metabolomics research technology, it will bring more benefits in the screening, diagnosis and treatment of cervical cancer with its advantages of holistic and dynamic nature.

Methionine can reduce the sublethal risk of Chlorantraniliprole to honeybees (Apis mellifera L.): Based on metabolomics analysis

Bees, essential for pollination in agriculture and global economic growth. However, the great wax moth (Galleria mellonella, GWM), a Lepidopteran insect, poses a substantial threat to bee colonies, contributing to a global decline in bee populations. Chlorantraniliprole (CH) is one of the primary insecticide used to control GWM due to its efficacy and low toxicity to bees. To improve beekeeping safety and reduce the risk of GWM developing resistance to prolonged use of CH, we investigated the potential of combining methionine (MET) which has been found to have insecticidal activity against certain Lepidoptera pests, with chlorantraniliprole for use in the apiculture industry. This study assessed the combined effects of MET and CH on GWM and honeybees by employing the maximum concentration of MET (1 %, w/w), previously reported as safe for honeybees, and the practical concentration of CH (1 mg/kg) for GWM control. The results revealed limited acute lethal toxicity of MET to GWM and honeybees, whereas the combined chronic exposure of MET and CH (MIX) led to significant synergistic lethal effects on GWM mortality. Nevertheless, the protective effect of MET on honeybees exposed to CH was significant under chronic exposure. Potential mechanisms underlying the synergistic actions of MET and CH may stem from MET-induced protection of the "Cysteine and methionine" and the "Glycine, serine, and threonine" metabolism pathways. Furthermore, immune stress mitigation was also observed in honeybee immune-related gene transcripts treated by the combination of MET and CH under both acute and chronic exposure. The effects of MET on CH activity in GWM and honeybees are likely due to metabolic regulation. This study suggests the potential of developing MET as a promising biopesticide or protective agent in the future.

NMR-Based Mitochondria Metabolomic Profiling: A New Approach To Reveal Cancer-Associated Alterations

Studying metabolism may assist in understanding the relationship between normal and dysfunctional mitochondrial activity and various diseases, such as neurodegenerative, cardiovascular, autoimmune, psychiatric, and cancer. Nuclear magnetic resonance-based metabolomics represents a powerful method to characterize the chemical content of complex samples and has been successfully applied to studying a range of conditions. However, an optimized methodology is lacking for analyzing isolated organelles, such as mitochondria. In this study, we report the development of a protocol to metabolically profile mitochondria from healthy, tumoral, and metastatic tissues. Encouragingly, this approach provided quantitative information about up to 45 metabolites in one comprehensive and robust analysis. Our results revealed significant differences between whole-cell and mitochondrial metabolites, which supports a more refined approach to metabolic analysis. We applied our optimized methodology to investigate aggressive and metastatic breast cancer in mouse tissues, discovering that lung mitochondria exhibit an altered metabolic fingerprint. Specific amino acids, organic acids, and lipids showed significant increases in levels when compared with mitochondria from healthy tissues. Our optimized methodology could promote a better understanding of the molecular mechanisms underlying breast cancer aggressiveness and mitochondrial-related diseases and support the optimization of new advanced therapies.

Microbial-Related Metabolites May Be Involved in Eight Major Biological Processes and Represent Potential Diagnostic Markers in Gastric Cancer

Metabolites associated with microbes regulate human immunity, inhibit bacterial colonization, and promote pathogenicity. Integrating microbe and metabolome research in GC provides a direction for understanding the microbe-associated pathophysiological process of metabolic changes and disease occurrence. The present study included 30 GC patients with 30 cancerous tissues and paired non-cancerous tissues (NCs) as controls. LC-MS/MS metabolomics and 16S rRNA sequencing were performed to obtain the metabolic and microbial characteristics. Integrated analysis of the microbes and metabolomes was conducted to explore the coexistence relationship between the microbial and metabolic characteristics of GC and to identify microbial-related metabolite diagnostic markers. The metabolic analysis showed that the overall metabolite distribution differed between the GC tissues and the NC tissues: 25 metabolites were enriched in the NC tissues and 42 metabolites were enriched in the GC tissues. The α and β microbial diversities were higher in the GC tissues than in the NC tissues, with 11 differential phyla and 52 differential genera. In the correlation and coexistence integrated analysis, 66 differential metabolites were correlated and coexisted, with specific differential microbes. The microbes in the GC tissue likely regulated eight metabolic pathways. In the efficacy evaluation of the microbial-related differential metabolites in the diagnosis of GC, 12 differential metabolites (area under the curve [AUC] >0.9) exerted relatively high diagnostic efficiency, and the combined diagnostic efficacy of 5 to 6 microbial-related differential metabolites was higher than the diagnostic efficacy of a single feature. Therefore, microbial diversity and metabolite distribution differed between the GC tissues and the NC tissues. Microbial-related metabolites may be involved in eight major metabolism-based biological processes in GC and represent potential diagnostic markers.

Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review

An increasing number of cancer epidemiology studies use metabolomics assays. This scoping review characterizes trends in the literature in terms of study design, population characteristics, and metabolomics approaches and identifies opportunities for future growth and improvement. We searched PubMed/MEDLINE, Embase, Scopus, and Web of Science: Core Collection databases and included research articles that used metabolomics to primarily study cancer, contained a minimum of 100 cases in each main analysis stratum, used an epidemiologic study design, and were published in English from 1998 to June 2021. A total of 2,048 articles were screened, of which 314 full texts were further assessed resulting in 77 included articles. The most well-studied cancers were colorectal (19.5%), prostate (19.5%), and breast (19.5%). Most studies used a nested case-control design to estimate associations between individual metabolites and cancer risk and a liquid chromatography-tandem mass spectrometry untargeted or semi-targeted approach to measure metabolites in blood. Studies were geographically diverse, including countries in Asia, Europe, and North America; 27.3% of studies reported on participant race, the majority reporting White participants. Most studies (70.2%) included fewer than 300 cancer cases in their main analysis. This scoping review identified key areas for improvement, including needs for standardized race and ethnicity reporting, more diverse study populations, and larger studies.

Potential of in vitro nuclear magnetic resonance of biofluids and tissues in clinical research

Body fluids, cells, and tissues contain a wide variety of metabolites that consist of a mixture of various low-molecular-weight compounds, including amino acids, peptides, lipids, nucleic acids, and organic acids, which makes comprehensive analysis more difficult. Quantitative nuclear magnetic resonance (NMR) spectroscopy is a well-established analytical technique for analyzing the metabolic profiles of body fluids, cells, and tissues. It enables fast and comprehensive detection, characterization, a high level of experimental reproducibility, minimal sample preparation, and quantification of various endogenous metabolites. In recent times, NMR-based metabolomics has been appreciably utilized in diverse branches of medicine, including microbiology, toxicology, pathophysiology, pharmacology, nutritional intervention, and disease diagnosis/prognosis. In this review, the utility of NMR-based metabolomics in clinical studies is discussed. The significance of in vitro NMR-based metabolomics as an effective tool for detecting metabolites and their variations in different diseases are discussed, together with the possibility of identifying specific biomarkers that can contribute to early detection and diagnosis of disease.

Metabolomics Reveals Novel Serum Metabolic Signatures in Gastric Cancer by a Mass Spectrometry Platform

Gastric cancer (GAS) is one of the malignant tumors of the gastrointestinal system. Alterations in metabolite composition can reflect pathological processes of GAS and constitute a basis for diagnosis and treatment improvements. In this study, a total of 301 serum samples from 150 GAS patients at different tumor-node-metastasis (TNM) stages and 151 healthy controls were collected. Mass spectrometry platforms were performed to investigate the changes in GAS-related metabolites and explore the new potential serum biomarkers and the metabolic dysregulation associated with GAS progression. Twelve differential metabolites (ethyl 2,4-dimethyl-1,3-dioxolane-2-acetate, D-urobilinogen, 14-HDoHE, 13-hydroxy-9-methoxy-10-oxo-11-octadecenoic acid, 5,6-dihydroxyprostaglandin F1a, 9'-carboxy-gamma-tocotrienol, glutaric acid, alanine, tyrosine, C18:2(FFA), adipic acid, and suberic acid) were identified to establish the diagnosis model for GAS. The defined biomarker panel was also statistically significant for GAS progression with different TNM stages. KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment revealed the metabolic dysregulation associated with GAS progression. In conclusion, a diagnostic panel was established and validated, which could be used to further stage the early and advanced GAS patients from healthy controls. These findings may provide useful information for explaining the GAS metabolic alterations and try to facilitate the characterization of GAS patients in the early stage.

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.

A literature review on the potential clinical implications of streptococci in gastric cancer

Streptococcus is widely found in nature and the human body, and most species are not pathogenic. In recent years, studies have found that Streptococcus is associated with gastric cancer. Streptococcus was found to be enriched in the oral cavity, stomach and intestine of gastric cancer patients and found to be increased in gastric cancer tissues, suggesting that Streptococcus may be the pathogenic bacteria underlying gastric cancer. This review discusses the discovery of Streptococcus, the relationship between Streptococcus and gastric cancer, and the possible carcinogenic mechanism of Streptococcus and summarizes the progress of the research on the role of Streptococcus in gastric cancer to provide new ideas for the early detection, diagnosis and treatment of gastric cancer.

Sunitinib versus Pazopanib Dilemma in Renal Cell Carcinoma: New Insights into the In Vitro Metabolic Impact, Efficacy, and Safety

Sunitinib and pazopanib are tyrosine kinase inhibitors (TKIs) used as first-line therapy for metastatic renal cell carcinoma (RCC). Although these TKIs are associated with similar survival outcomes, some differences have been reported in their safety profiles. In this work, traditional toxicological endpoints (cell viability and growth, oxidative stress, and nuclear morphology) and ¹H NMR spectroscopy-based metabolomics analysis were used to provide new insights into the cytotoxicity and metabolic mechanisms underlying sunitinib and pazopanib treatments. Tumoral (Caki-1) and non-tumoral (HK-2) human renal cells were exposed to clinically relevant concentrations of sunitinib (2 µM) or pazopanib (50 µM). Sunitinib showed selectivity for cancer cells, inhibiting proliferation, and inducing apoptotic death of Caki-1 cells, whereas pazopanib had a similar cytotoxic effect in both tumoral and non-tumoral cells. ¹H-NMR metabolomics unveiled a higher impact of sunitinib on the levels of intracellular metabolites of Caki-1 cells (seven dysregulated metabolites), suggesting dysregulations on amino acid, glutathione and glycerophospholipid metabolisms. In contrast, pazopanib had a higher impact on the levels of extracellular metabolites of Caki-1 cells (seven dysregulated metabolites in culture medium), unveiling alterations on amino acid and energetic metabolisms. In HK-2 cells, sunitinib caused only a minor increase in intracellular isoleucine levels, whereas pazopanib induced several alterations on the intracellular (three dysregulated metabolites) and extracellular (three dysregulated metabolites) compartments suggesting changes on amino acid, glycerophospholipid, and energy metabolisms. Our results demonstrate that these TKIs elicit distinct cellular and metabolic responses, with sunitinib showing better in vitro efficacy against target RCC cells and lesser nephrotoxic potential than pazopanib.

Alterations in the gastric microbiota and metabolites in gastric cancer: An update review

Gastric cancer (GC) is one of the leading causes of cancer mortality worldwide. Numerous studies have shown that the gastric microbiota can contribute to the occurrence and development of GC by generating harmful microbial metabolites, suggesting the possibility of discovering biomarkers. Metabolomics has emerged as an advanced promising analytical method for the analysis of microbiota-derived metabolites, which have greatly accelerated our understanding of host-microbiota metabolic interactions in GC. In this review, we briefly compiled recent research progress on the changes of gastric microbiota and its metabolites associated with GC. And we further explored the application of metabolomics and gastric microbiome association analysis in the diagnosis, prevention and treatment of GC.

Serum metabolomic profiling for patients with adenocarcinoma of the esophagogastric junction

INTRODUCTION

The incidence of adenocarcinoma in the esophagogastric junction (AEG) has increased in the recent years. AEG is reported to have a worse prognosis compared with tumor confined to the stomach (non-AEG). Although the metabolic changes of non-AEG have been investigated in extensive studies, little effort focused on the metabolic profiling of AEG serum.

OBJECTIVES

Here we report an untargeted gas chromatography-mass spectrometry (GC-MS) method to explore the abnormal metabolism underlying AEG.

METHODS

GC-MS-based untargeted metabolomics approach combined with multivariate statistical analyses were used to study the metabolic profiling of serum samples from AEG patients (n = 70), non-AEG patients (n = 70) and health controls (n = 71).

RESULTS

A novel serum metabolic profiling of 18 metabolites from patients of AEG and non-AEG was indicated, in comparison with health controls. Moreover, AEG and non-AEG were also well-classified with 9 distinguishing metabolites including hypoxanthine, alanine, proline, pyroglutamate, glycine, lactate, succinic acid, glutamate and kynurenine, which produced a discriminatory model with an area under the Receiver Operating Characteristic (ROC) curve of 0.852, suggesting a distinct metabolic signature of AEG. Importantly, lactate and glutamate disclosed outcome-prediction values by multivariate cox-proportional hazard model and Kaplan-Meier method based on follow-up information for 2-5 years.

CONCLUSION

This is the first metabolomics study to identify serum metabolic signature of AEG. The distinguishing metabolites show a promising application on clinical diagnose and outcome prediction, and allow us to unveil several key metabolic variations coexisting in AEG, which may aid to understand the underlying metabolic mechanisms.

Progress in Metabolic Studies of Gastric Cancer and Therapeutic Implications

Background:

Worldwide, gastric cancer is ranked the fifth malignancy in incidence and the third malignancy in mortality. Gastric cancer causes an altered metabolism that can be therapeutically exploited.

Objective:

To provide an overview of the significant metabolic alterations caused by gastric cancer and propose a blockade.

Methods:

A comprehensive and up-to-date review of descriptive and experimental publications on the metabolic alterations caused by gastric cancer and their blockade. This is not a systematic review.

Results:

Gastric cancer causes high rates of glycolysis and glutaminolysis. There are increased rates of de novo fatty acid synthesis and cholesterol synthesis. Moreover, gastric cancer causes high rates of lipid turnover via fatty acid -oxidation. Preclinical data indicate that the individual blockade of these pathways via enzyme targeting leads to antitumor effects in vitro and in vivo. Nevertheless, there is no data on the simultaneous blockade of these five pathways, which is critical, as tumors show metabolic flexibility in response to the availability of nutrients. This means tumors may activate alternate routes when one or more are inhibited. We hypothesize there is a need to simultaneously blockade them to avoid or decrease the metabolic flexibility that may lead to treatment resistance.

Conclusions:

There is a need to explore the preclinical efficacy and feasibility of combined metabolic therapy targeting the pathways of glucose, glutamine, fatty acid synthesis, cholesterol synthesis, and fatty acid oxidation. This may have therapeutical implications because we have clinically available drugs that target these pathways in gastric cancer.

1H-NMR Based Metabolomics Technology Identifies Potential Serum Biomarkers of Colorectal Cancer Lung Metastasis in a Mouse Model

Background

Lung metastasis is a common metastasis site of colorectal cancer which largely reduces the quality of life and survival rates of patients. The discovery of potential novel diagnostic biomarkers is very meaningful for the early diagnosis of colorectal cancer with lung metastasis.

Methods

In the present study, the metabonomic profiling of serum samples of lung metastasis mice was analyzed by ¹H-nuclear magnetic resonance (¹H-NMR). Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to elucidate the distinguishing metabolites between different groups, and all achieved excellent separations, which indicated that metastatic mice could be differentiated from control mice based on the metabolic profiles at serum levels. Furthermore, during lung metastasis of colorectal cancer, metabolic phenotypes changed significantly, and some of metabolites were identified.

Results

Among these metabolites, approximately 15 were closely associated with the lung metastasis process. Pathway enrichment analysis results showed deregulation of metabolic pathways participating in the process of lung metastasis, such as synthesis and degradation of ketone bodies pathway, amino acid metabolism pathway and pyruvate metabolism pathway.

Conclusion

The present study demonstrated the metabolic disturbances of serum samples of mice during the lung metastasis process of colorectal cancer and provides potential diagnostic biomarkers for the disease.

Protein Phosphatase 1 Regulatory Subunit 3: A Prognostic Biomarker in Stomach Adenocarcinoma

Purpose

This study aimed to determine the potential application of the protein phosphatase 1 regulatory subunit 3 (PPP1R3B) gene as a prognostic marker in stomach adenocarcinoma (STAD), as well as its potential mediating biological processes and pathways.

Materials and Methods

Differential expression analyses were performed using the TIMER2.0 and UALCAN databases. Complete RNA-seq data and other relevant clinical and survival data were acquired from The Cancer Genome Atlas (TCGA). Univariate survival analyses, Cox regression modelling, and Kaplan–Meier curves were implemented to investigate the associations between PPP1R3B gene expression and clinical pathologic features. A genome wide gene set enrichment analysis (GSEA) was conducted to define the underlying molecular mechanisms mediating the observed associations between the PPP1R3B gene and STAD development.

Results

We found that PPP1R3B was overexpressed in STAD tissues, and that higher PPP1R3B expression correlated with worse prognoses in patients with STAD. Comprehensive survival analyses suggested that PPP1R3B might be an independent predictive factor for survival time in patients with STAD. The prognostic relationship between PPP1R3B and STAD was also verified using Kaplan–Meier curves. Patients with higher PPP1R3B levels had a shorter clinical survival time on average. Additionally, a GSEA demonstrated that PPP1R3B might be involved in multiple biological processes and pathways.

Conclusion

Our findings demonstrate that the PPP1R3B gene has utility as a potential molecular marker for STAD prognoses.

Tissue-based metabolomics reveals metabolic signatures and major metabolic pathways of gastric cancer with help of transcriptomic data from TCGA

PURPOSE

The aim of the present study was to screen differential metabolites of gastric cancer (GC) and identify the key metabolic pathways of GC.

METHODS

GC (n=28) and matched paracancerous (PC) tissues were collected, and LC-MS/MS analysis were performed to detect metabolites of GC and PC tissues. Metabolite pathways based on differential metabolites were enriched by MetaboAnalyst, and genes related to metabolite pathways were identified using the KEGGREST function of the R software package. Transcriptomics data from The Cancer Genome Atlas (TCGA) was analyzed to obtain differentially expressed genes (DEGs) of GC. Overlapping genes were acquired from metabonimics and transcriptomics data. Pathway enrichment analysis was performed using String. The protein expression of genes was validated by the Human Protein Atlas (HPA) database.

RESULTS

A total of 325 key metabolites were identified, 111 of which were differentially expressed between the GC and PC groups. Seven metabolite pathways enriched by MetaboAnalyst were chosen, and 361 genes were identified by KEGGREST. A total of 2831 DEGs were identified from the TCGA cohort. Of these, 1317 were down-regulated, and 1636 were up-regulated. Twenty-two overlapping genes were identified between genes related to metabolism and DEGs. Glycerophospholipid (GPL) metabolism is likely associated with GC, of which AGPAT9 and ETNPPL showed lower expressed in GC tissues.

CONCLUSIONS

We investigated the tissue-based metabolomics profile of GC, and several differential metabolites were identified. GPL metabolism may affect on progression of GC.

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.

Metabolic Profiling of Praziquantel-mediated Prevention of Opisthorchis viverrini-induced Cholangiocyte Transformation in the Hamster Model of Cholangiocarcinoma

BACKGROUND

Opisthorchis viverrini (Ov) infection-induced cholangiocarcinoma (CCA) is a major public health problem in northeastern Thailand. Praziquantel was shown to prevent CCA development in an Ov-infected hamster model; however, the molecular mechanism remains unknown.

MATERIALS AND METHODS

In this study, we used a hamster model with Ov and N-nitrosodimethylamine-induced CCA to study the mechanisms of praziquantel action. The liver tissues from the hamsters with and without praziquantel treatment were analyzed using ¹H nuclear magnetic resonance spectroscopy.

RESULTS

A total of 14 metabolites were found to be significantly different between the two groups. Furthermore, the combination of acetate, inosine and sarcosine was shown to exert an anti-inflammatory effect through interleukin-6 inhibition in a macrophage cell line, suggesting a mechanism by which praziquantel may prevent inflammation caused by Ov, cholangiocyte transformation and further CCA develpoment.

CONCLUSION

These findings might avail the development of a preventive strategy for CCA in high-risk populations.

NMR-Based Metabolomics in Cancer Research

Nuclear magnetic resonance (NMR) spectroscopy offers reproducible quantitative analysis and structural identification of metabolites in various complex biological samples, such as biofluids (plasma, serum, and urine), cells, tissue extracts, and even intact organs. Therefore, NMR-based metabolomics, a mainstream metabolomic platform, has been extensively applied in many research fields, including pharmacology, toxicology, pathophysiology, nutritional intervention, disease diagnosis/prognosis, and microbiology. In particular, NMR-based metabolomics has been successfully used for cancer research to investigate cancer metabolism and identify biomarker and therapeutic targets. This chapter highlights the innovations and challenges of NMR-based metabolomics platform and its applications in cancer research.

Circ_0000144 functions as a miR-623 sponge to enhance gastric cancer progression via up-regulating GPRC5A

BACKGROUND

Gastric cancer (GC) remains one of the most common malignancies worldwide. Increasing evidence has demonstrated that circRNAs serve as critical roles in human cancer, including GC. In the present study, we focused on the detailed function and mechanism of circ_0000144 on GC progression.

METHODS

The levels of circ_0000144, miR-623 and G-protein-coupled receptor, family C, group 5, member A (GPRC5A) were determined by quantitative real-time polymerase chain reaction (qRT-PCR). Targeted relationships among circ_0000144, miR-623 and GPRC5A were confirmed using dual-luciferase reporter and RNA immunoprecipitation (RIP) assays. Cell proliferation, colony formation, apoptosis, migration and invasion were evaluated by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), colony formation, flow cytometry and transwell assays. Measurement of glutamine and α-ketoglutarate (α-KG) levels was performed using a corresponding assay kit. GPRC5A protein expression was detected using Western blot. In vivo assays were used to explore the impact of circ_0000144 on tumor growth.

RESULTS

Our data indicated that circ_0000144 was up-regulated and miR-623 was down-regulated in GC tissues and cells. Circ_0000144 interacted with miR-623 through directly binding to miR-623. Moreover, the knockdown of circ_0000144 weakened GC cell proliferation, colony formation, migration, invasion and glutaminolysis and accelerated cell apoptosis by up-regulating miR-623. GPRC5A was a direct target of miR-623 and circ_0000144 protected against GPRC5A repression through sponging miR-623. Furthermore, miR-623-mediated regulation on GC cell progression was reversed by the stored expression of GPRC5A. Additionally, circ_0000144 depletion inhibited tumor growth in vivo.

CONCLUSION

Our study indicated that circ-0000144 knockdown repressed GC progression at least partly by regulating GPRC5A expression via sponging miR-623, illumining a novel therapeutic target for GC treatment.

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.

Salivary Microbiota for Gastric Cancer Prediction: An Exploratory Study

To characterize the salivary microbiota in patients at different progressive histological stages of gastric carcinogenesis and identify microbial markers for detecting gastric cancer, two hundred and ninety-three patients were grouped into superficial gastritis (SG; n = 101), atrophic gastritis (AG; n = 93), and gastric cancer (GC; n = 99) according to their histology. 16S rRNA gene sequencing was used to access the salivary microbiota profile. A random forest model was constructed to classify gastric histological types based on the salivary microbiota compositions. A distinct salivary microbiota was observed in patients with GC when comparing with SG and AG, which was featured by an enrichment of putative proinflammatory taxa including Corynebacterium and Streptococcus. Among the significantly decreased oral bacteria in GC patients including Haemophilus, Neisseria, Parvimonas, Peptostreptococcus, Porphyromonas, and Prevotella, Haemophilus, and Neisseria are known to reduce nitrite, which may consequently result in an accumulation of carcinogenic N-nitroso compounds. We found that GC can be distinguished accurately from patients with AG and SG (AUC = 0.91) by the random forest model based on the salivary microbiota profiles, and taxa belonging to unclassified Streptophyta and Streptococcus have potential as diagnostic biomarkers for GC. Remarkable changes in the salivary microbiota functions were also detected across three histological types, and the upregulation in the isoleucine and valine is in line with a higher level of these amino acids in the gastric tumor tissues that reported by other independent studies. Conclusively, bacteria in the oral cavity may contribute gastric cancer and become new diagnostic biomarkers for GC, but further evaluation against independent clinical cohorts is required. The potential mechanisms of salivary microbiota in participating the pathogenesis of GC may include an accumulation of proinflammatory bacteria and a decline in those reducing carcinogenic N-nitroso compounds.

The Distinctive Serum Metabolomes of Gastric, Esophageal and Colorectal Cancers

Simple Summary

Cancer of the stomach, esophagus and colon are often fatal. Ways are being sought to establish patient-friendly screening tests that would allow these cancers to be detected earlier. Examination of the metabolomics results of cancer patient’s serum for certain metabolites unique for a particular cancer was the goal of this review. From studies conducted within the past five years several metabolites were found to be changed in cancer compared to non-cancer patients for each of the three cancers. Further confirmation of what was discovered in this review coupled with establishment of standard protocols may allow for cancer screening on patient blood samples to become routine clinical tests.

Abstract

Three of the most lethal cancers in the world are the gastrointestinal cancers—gastric (GC), esophageal (EC) and colorectal cancer (CRC)—which are ranked as third, sixth and fourth in cancer deaths globally. Early detection of these cancers is difficult, and a quest is currently on to find non-invasive screening tests to detect these cancers. The reprogramming of energy metabolism is a hallmark of cancer, notably, an increased dependence on aerobic glycolysis which is often referred to as the Warburg effect. This metabolic change results in a unique metabolic profile that distinguishes cancer cells from normal cells. Serum metabolomics analyses allow one to measure the end products of both host and microbiota metabolism present at the time of sample collection. It is a non-invasive procedure requiring only blood collection which encourages greater patient compliance to have more frequent screenings for cancer. In the following review we will examine some of the most current serum metabolomics studies in order to compare their results and test a hypothesis that different tumors, notably, from EC, GC and CRC, have distinguishing serum metabolite profiles.

Identification of a metabolic-related gene signature predicting the overall survival for patients with stomach adenocarcinoma

Background

The reprogramming of energy metabolism and consistently altered metabolic genes are new features of cancer, and their prognostic roles remain to be further studied in stomach adenocarcinoma (STAD).

Methods

Messenger RNA (mRNA) expression profiles and clinicopathological data were downloaded from The Cancer Genome Atlas (TCGA) and the GSE84437 databases from the Gene Expression Omnibus (GEO) database. A univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression model established a novel metabolic signature based on TCGA. The area under the receiver operating characteristic (ROC) curve (AUROC) and a nomogram were calculated to assess the predictive accuracy.

Results

A novel metabolic-related signature (including acylphosphatase 1, RNA polymerase I subunit A, retinol dehydrogenase 12, 5-oxoprolinase, ATP-hydrolyzing, malic enzyme 1, nicotinamide N-methyltransferase, gamma-glutamyl transferase 5, deoxycytidine kinase, galactosidase alpha, DNA polymerase delta 3, glutathione S-transferase alpha 2, N-acyl sphingosine amidohydrolase 1, and N-acyl sphingosine amidohydrolase 1) was identified. In both TCGA and GSE84437, patients in the high-risk group showed significantly poorersurvival than the patients in the low-risk group. A good predictive value was shown by the AUROC and nomogram. Furthermore, gene set enrichment analyses (GSEAs) revealed several significantly enriched pathways, which may help in explaining the underlying mechanisms.

Conclusions

A novel robust metabolic-related signature for STAD prognosis prediction was conducted. The signature may reflect the dysregulated metabolic microenvironment and can provided potential biomarkers for metabolic therapy in STAD.

Prediction of Autoimmune Diseases by Targeted Metabolomic Assay of Urinary Organic Acids

Autoimmune diseases (ADs) are chronic disorders characterized by the loss of self-tolerance, and although being heterogeneous, they share common pathogenic mechanisms. Self-antigens and inflammation markers are established diagnostic tools; however, the metabolic imbalances that underlie ADs are poorly described. The study aimed to employ metabolomics for the detection of disease-related changes in autoimmune diseases that could have predictive value. Quantitative analysis of 28 urine organic acids was performed using Gas Chromatography-Mass Spectrometry in a group of 392 participants. Autoimmune thyroiditis, inflammatory bowel disease, psoriasis and rheumatoid arthritis were the most prevalent autoimmune diseases of the study. Statistically significant differences were observed in the tricarboxylate cycle metabolites, succinate, methylcitrate and malate, the pyroglutamate and 2-hydroxybutyrate from the glutathione cycle and the metabolites methylmalonate, 4-hydroxyphenylpyruvate, 2-hydroxyglutarate and 2-hydroxyisobutyrate between the AD group and the control. Artificial neural networks and Binary logistic regression resulted in the highest predictive accuracy scores (66.7% and 74.9%, respectively), while Methylmalonate, 2-Hydroxyglutarate and 2-hydroxybutyrate were proposed as potential biomarkers for autoimmune diseases. Urine organic acid levels related to the mechanisms of energy production and detoxification were associated with the presence of autoimmune diseases and could be an adjunct tool for early diagnosis and prediction.

Nuclear magnetic resonance-based tissue metabolomic analysis clarifies molecular mechanisms of gastric carcinogenesis

Gastric cancer (GC) is one of the deadliest cancers worldwide, and the progression of gastric carcinogenesis (GCG) covers multiple complicated pathological stages. Molecular mechanisms of GCG are still unclear. Here, we undertook NMR‐based metabolomic analysis of aqueous metabolites extracted from gastric tissues in an established rat model of GCG. We showed that the metabolic profiles were clearly distinguished among 5 histologically classified groups: control, gastritis, low‐grade gastric dysplasia, high‐grade gastric dysplasia (HGD), and GC. Furthermore, we carried out metabolic pathway analysis based on identified significant metabolites and revealed significantly disturbed metabolic pathways closely associated with the 4 pathological stages, including oxidation stress, choline phosphorylation, amino acid metabolism, Krebs cycle, and glycolysis. Three metabolic pathways were continually disturbed during the progression of GCG, including taurine and hypotaurine metabolism, glutamine and glutamate metabolism, alanine, aspartate, and glutamate metabolism. Both the Krebs cycle and glycine, serine, and threonine metabolism were profoundly impaired in both the HGD and GC stages, potentially due to abnormal energy supply for tumor cell proliferation and growth. Furthermore, valine, leucine, and isoleucine biosynthesis and glycolysis were significantly disturbed in the GC stage for higher energy requirement of the rapid growth of tumor cells. Additionally, we identified potential gastric tissue biomarkers for metabolically discriminating the 4 pathological stages, which also showed good discriminant capabilities for their serum counterparts. This work sheds light on the molecular mechanisms of GCG and is of benefit to the exploration of potential biomarkers for clinically diagnosing and monitoring the progression of GCG.

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.

Metabolic Profiling of Tumors, Sera, and Skeletal Muscles from an Orthotopic Murine Model of Gastric Cancer Associated-Cachexia

Cachexia is a complex metabolic derangement syndrome that affects approximately 50-80% of cancer patients. So far, few works have been reported to provide a global overview of gastric cancer cachexia (GCC)-related metabolic changes. We established a GCC murine model by orthotopicly implanting BGC823 cell line and conducted NMR-based metabolomic analysis of gastric tissues, sera, and gastrocnemius. The model with typical cachexia symptoms, confirmed by significant weight loss and muscle atrophy, showed distinctly distinguished metabolic profiles of tumors, sera, and gastrocnemius from sham mice. We identified 20 differential metabolites in tumors, 13 in sera, and 14 in gastrocnemius. Tumor extracts displayed increased pyruvate and lactate, and decreased hypoxanthine, inosine, and inosinate, indicating significantly altered glucose and nucleic acid metabolisms. Cachectic mice exhibited up-regulated serum lactate and glycerol, and down-regulated glucose, which were closely related to hyperlipidemia and hypoglycemia. Furthermore, gastrocnemius transcriptomic and metabolomic data revealed that GCC induced perturbed pathways mainly concentrated on carbohydrate and amino acid metabolism. Specifically, cachectic gastrocnemius exhibited increased α-ketoglutarate and decreased glucose. In vitro study indicated that α-ketoglutarate could prompt myoblasts proliferation and reduce glucose deficiency-induced myotubes atrophy. Overall, this work provides a global metabolic overview to understand the metabolic alterations associated with GCC-induced muscle atrophy.

Epigenetics and Metabolism in Health and Disease

In the next 10 years, one billion people are estimated to suffer from disabling consequences of metabolic disorders, making them the number one noncommunicable disease on a global scale by 2030. Lots of risk factors such as dietary intake, lack of exercise and other life style behaviors are considered to play a role in the development of metabolic disorders. Despite the efforts that have been undertaken to unravel their potential causes, the underlying molecular mechanisms remain elusive. Evidence suggests that the pathogenesis involves changes on chromatin and chromatin-modifying enzymes, which can contribute to a persistent dysregulated metabolic phenotype. Indeed, a rising number of studies links epigenetic alterations with the diagnosis and prognosis of metabolic disorders. A prerequisite for exploiting these findings for pharmacological intervention is a detailed understanding of how differential epigenetic modifications control cell metabolism. In this mini review, we summarize the recent advances in uncovering the interplay between epigenetics and metabolic pathways on a cellular level and highlight potential new avenues for alternative treatment strategies.

Free amino acid profiling of gastric juice as a method for discovering potential biomarkers of early gastric cancer

Background: Prior studies showed that aromatic amino acids (AAAs) could be used as potential gastric juice biomarkers in screening gastric cancer (GC). To identify new biomarkers for early diagnosis of GC, the characteristics of gastric juice free amino acid (GJFAA) profiling was determined. Method: First, gastric juice was collected from 130 consecutive patients who underwent gastroscopy. They were divided into GC group (n = 47) and non-neoplastic gastric disease (NGD) group (n = 83) according to the pathological diagnosis. The concentrations of 34 GJFAAs were examined by amino acid analyzer. Multivariate and univariate analyses were used for comparing the alterations of GJFAA profiles between the two groups. Then candidate differential GJFAAs were verified by LC-MS/MS in another set of patients, which included 32 GC patients and 38 NGD patients. The diagnostic performance of GJFAAs was evaluated by ROC curve. Results: Significant alterations in GJFAA profiles were observed in GC patients compared to NGD patients in the training set. A total of 14 amino acids were screened as differential GJFAAs. Leucine, threonine and serine were the most frequently altered. Combined AUC of the three non-AAAs [0.869 (95% CI, 0.805-0.934)] was superior to the combined three AAAs [0.841 (95% CI, 0.773-0.908)]. In addition, a combined AUC comprisingthe six ones was further improved to 0.871 (95% CI, 0.809-0.933) in the diagnosis of GC. A similar variation trend and diagnostic value were observed in the validation set. Conclusion: This study indicates the potential of GJFAA profiling as a promising approach for the early detection and screening of GC.

GC-MS-based urinary organic acid profiling reveals multiple dysregulated metabolic pathways following experimental acute alcohol consumption

Metabolomics studies of diseases associated with chronic alcohol consumption provide compelling evidence of several perturbed metabolic pathways. Moreover, the holistic approach of such studies gives insights into the pathophysiological risk factors associated with chronic alcohol-induced disability, morbidity and mortality. Here, we report on a GC-MS-based organic acid profiling study on acute alcohol consumption. Our investigation - involving 12 healthy, moderate-drinking young men - simulated a single binge drinking event, and indicated its metabolic consequences. We generated time-dependent data that predicted the metabolic pathophysiology of the alcohol intervention. Multivariate statistical modelling was applied to the longitudinal data of 120 biologically relevant organic acids, of which 13 provided statistical evidence of the alcohol effect. The known alcohol-induced increased NADH:NAD+ ratio in the cytosol of hepatocytes contributed to the global dysregulation of several metabolic reactions of glycolysis, ketogenesis, the Krebs cycle and gluconeogenesis. The significant presence of 2-hydroxyisobutyric acid supports the emerging paradigm that this compound is an important endogenous metabolite. Its metabolic origin remains elusive, but recent evidence indicated 2-hydroxyisobutyrylation as a novel regulatory modifier of histones. Metabolomics has thus opened an avenue for further research on the reprogramming of metabolic pathways and epigenetic networks in relation to the severe effects of alcohol consumption.

Discriminating gastric cancer and gastric ulcer using human plasma amino acid metabolic profile

Patients with gastric ulcer (GU) have a significantly higher risk of developing gastric cancer (GC), especially within 2 years after diagnosis. The main way to improve the prognosis of GC is to predict the tumorigenesis and metastasis in the early stage. The objective of this study was to demonstrate the ability of human plasma amino acid metabolic profile for discriminating GC and GU. In this study, we first used liquid chromatography-tandem mass spectrometry technique to characterize the plasma amino acid metabolism in GC and GU patients. Plasma samples were collected from 84 GC patients and 82 GU patients, and 22 amino acids were detected in each patient. Partial least squares-discriminant analysis model was performed to analyze the data of these amino acids. We observed seven differential amino acids between GC and GU. A regression analysis model was established using these seven amino acids. Finally, a panel of five differential amino acids, including glutamine, ornithine, histidine, arginine and tryptophan, was identified for discriminating GC and GU with good specificity and sensitivity. The receiver operating characteristic curve was used to evaluate diagnostic ability of the regression model and area under the curve was 0.922. In conclusion, this study demonstrated the potential values of plasma amino acid metabolic profile and metabolomic analysis technique in assisting diagnosis of GC. More studies are needed to highlight the theoretical strengths of metabolomics to understand the potential metabolic mechanisms in GC. © 2018 IUBMB Life, 70(6):553-562, 2018.

Metabolic Profile of Oral Squamous Carcinoma Cell Lines Relies on a Higher Demand of Lipid Metabolism in Metastatic Cells

Tumor cells are subjected to a broad range of selective pressures. As a result of the imposed stress, subpopulations of surviving cells exhibit individual biochemical phenotypes that reflect metabolic reprograming. The present work aimed at investigating metabolic parameters of cells displaying increasing degrees of metastatic potential. The metabolites present in cell extracts fraction of tongue fibroblasts and of cell lines derived from human tongue squamous cell carcinoma lineages displaying increasing metastatic potential (SCC9 ZsG, LN1 and LN2) were analyzed by ¹H NMR (nuclear magnetic resonance) spectroscopy. Living, intact cells were also examined by the non-invasive method of fluorescence lifetime imaging microscopy (FLIM) based on the auto fluorescence of endogenous NADH. The cell lines reproducibly exhibited distinct metabolic profiles confirmed by Partial Least-Square Discriminant Analysis (PLS-DA) of the spectra. Measurement of endogenous free and bound NAD(P)H relative concentrations in the intact cell lines showed that ZsG and LN1 cells displayed high heterogeneity in the energy metabolism, indicating that the cells would oscillate between glycolysis and oxidative metabolism depending on the microenvironment’s composition. However, LN2 cells appeared to have more contributions to the oxidative status, displaying a lower NAD(P)H free/bound ratio. Functional experiments of energy metabolism, mitochondrial physiology, and proliferation assays revealed that all lineages exhibited similar energy features, although resorting to different bioenergetics strategies to face metabolic demands. These differentiated functions may also promote metastasis. We propose that lipid metabolism is related to the increased invasiveness as a result of the accumulation of malonate, methyl malonic acid, n-acetyl and unsaturated fatty acids (CH₂)_n in parallel with the metastatic potential progression, thus suggesting that the NAD(P)H reflected the lipid catabolic/anabolic pathways.

Metabolic profiles of gastric cancer cell lines with different degrees of differentiation

Gastric cancer is a commonly found malignant tumor, yet research on biomarkers of gastric cancer still face tremendous challenges. This study is the first to use gas chromatography-mass spectrometry (GC-MS) to measure and compare the metabolic profiles of gastric cancer cell lines with varying degrees of differentiation (MKN-28, SGC-7901, and AGS) with that of a normal gastric epithelial cell line (GES-1). OPLS-DA models were established to distinguish gastric cancer cell lines from a normal gastric epithelial cell line. In this study, we identified 278 metabolites, of which 111 show similarity scores greater than 700. Most notably, 6 metabolites (alanine, α-ketoisocaproic acid, proline, glyceric acid, pantothenic acid, and adenosine) showed varying expression levels between gastric cancer cell lines and a normal gastric epithelial cell line. These metabolites are potential biomarkers of gastric cancer and may be of great significance for the diagnosis, treatment and prognosis of gastric cancer patients.

1H NMR metabolic profiling of gastric cancer patients with lymph node metastasis

INTRODUCTION

Gastric cancer (GC) is a malignant tumor worldwide. As primary pathway for metastasis, the lymphatic system is an important prognostic factor for GC patients. Although the metabolic changes of gastric cancer have been investigated in extensive studies, little effort focused on the metabolic profiling of lymph node metastasis (LNM)-positive or negative GC patients.

OBJECTIVES

We performed ¹H NMR spectrum of GC tissue samples with and without LNM to identify novel potential metabolic biomarkers in the process of LNM of GC.

METHODS

¹H NMR-based untargeted metabolomics approach combined with multivariate statistical analyses were used to study the metabolic profiling of tissue samples from LNM-positive GC patients (n = 40), LNM-negative GC patients (n = 40) and normal controls (n = 40).

RESULTS

There was a clear separation between GC patients and normal controls, and 33 differential metabolites were identified in the study. Moreover, GC patients were also well-classified according to LNM-positive or negative. Totally eight distinguishing metabolites were selected in the metabolic profiling of GC patients with LNM-positive or negative, suggesting the metabolic dysfunction in the process of LNM. According to further validation and analysis, especially BCAAs metabolism (leucine, isoleucine, valine), GSH and betaine may be as potential factors of diagnose and prognosis of GC patients with or without LNM.

CONCLUSION

To our knowledge, this is the first metabolomics study focusing on LNM of GC. The identified distinguishing metabolites showed a promising application on clinical diagnose and therapy prediction, and understanding the mechanism underlying the carcinogenesis, invasion and metastasis of GC.

Serum metabolic profiling of type 2 diabetes mellitus in Chinese adults using an untargeted GC/TOFMS

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a huge burden in China. The Chinese patients with T2DM have several special clinical characteristics. Metabolomics studies predominantly have identified several distinguishing metabolites associated with T2DM in Western ancestry population. However, few previous metabolomics studies were conducted in Chinese populations.

METHODS

We performed untargeted serum metabolic profiling between 30 T2DM patients and 30 healthy controls based on GC/TOFMS. Multivariate data analyses were applied to identify the distinguishing metabolites.

RESULTS

Excellent separation was obtained between the two cases. And overall 54 distinguishing metabolites were identified with VIP>1 and P<0.05, which were involved in metabolic pathways of amino acid, carbohydrate, lipids, membrane transport and nucleotides. To further analyze the correlation between the identified metabolites and T2DM, 17 metabolites were selected with FC>2.0, including gentisic acid, citraconic acid, succinic acid, 2-hydroxybutanoic acid and 3-hydroxy-l-proline, the corresponding FC were respectively 5.44, 2.21, 2.10, 2.21 and -2.04.

CONCLUSION

Our results demonstrated that untargeted GC/TOFMS-based metabolic approach processed well performance to identify serum distinguishing metabolites of T2DM in Chinese adults, which may be as potential biomarkers in diagnose and treatment of diabetes. And the results also provided new insight into understand the underlying molecular mechanism.

Overexpression of miR-15b-5p promotes gastric cancer metastasis by regulating PAQR3

Gastric cancer (GC) is the fifth most common cancer in the world, with 952,000 new cases diagnosed in 2012. Tumor metastasis is the major cause of cancer recurrence and death. miR-15b-5p has been reported to be dysregulated in numerous types of cancers. However, the role of miR-15b-5p in GC metastasis remains unclear. An miRNA microarray was adopted to analyze the miRNA expression profile. By employing quantitative real-time polymerase chain reaction (qRT-PCR), miR-15b-5p expression levels were detected in GC cell lines, tissues and plasma samples. In addition, the effects of miR-15b-5p on cell proliferation, migration and invasion were studied by applying gain-of-function approaches. Moreover, the target of miR-15b-5p was assessed by dual-luciferase assay, and the mechanism underlying the regulation of GC metastasis by miR-15b-5p was assessed by rescue experiments. The results revealed that miR-15b-5p was upregulated in GC cell lines, tissues and plasma samples. A high plasma level of miR-15b-5p was correlated with distant tumor metastasis. In addition, overexpression of miR‑15b-5p in GC cells promoted cell proliferation, migration, invasion and epithelial-mesenchymal transition (EMT). Moreover, progestin and adipoQ receptor family member 3 (PAQR3) was found to be a direct target of miR-15b-5p and re-expression of PAQR3 in miR-15b-5p-overexpressing GC cells partly attenuated the proliferation, migration and invasion. These findings revealed that miR-15b-5p promotes the metastasis of GC cells through PAQR3 and may represent a potential biomarker of GC.

1H NMR metabolomic signatures related to giant cell tumor of the bone

¹H NMR metabolomic profiling for giant cell tumor of the bone.