Metabolomic profiling of oesophago-gastric cancer: a systematic review

Delactylase effects of SIRT1 on a positive feedback loop involving the H19-glycolysis-histone lactylation in gastric cancer

Histone lactylation, a novel epigenetic modification, is regulated by the lactate produced by glycolysis. Glycolysis is activated in various cancers, including gastric cancer (GC). However, the molecular mechanism and clinical impact of histone lactylation in GC remain poorly understood. Here, we demonstrate that histone H3K18 lactylation (H3K18la) is elevated in GC, correlating with a worse prognosis. SIRT1 overexpression decreases H3K18la levels, whereas SIRT1 knockdown increases H3K18la levels in GC cells. RNA-seq analysis demonstrates that lncRNA H19 is markedly downregulated in GC cells with SIRT1 overexpression and those grown under glucose free condition, which confirmed decreased H3K18la levels at its promoter region. H19 knockdown decreased the expression levels of LDHA and H3K18la, and LDHA knockdown impaired H19 and H3K18la expression, suggesting an H19/glycolysis/H3K18la-positive feedback loop. Combined treatment with low doses of the SIRT1-specific activator SRT2104 and the LDHA inhibitor oxamate exerted significant antitumor effects on GC cells, with limited adverse effects on normal gastric cells. The SIRT1-weak/H3K18la-strong signature was found to be an independent prognostic factor in patients with GC. Therefore, SIRT1 acts as a histone delactylase for H3K18, and loss of SIRT1 triggers a positive feedback loop involving H19/glycolysis/H3K18la. Targeting this pathway serves as a novel therapeutic strategy for GC treatment.

Causal association between metabolites and upper gastrointestinal tumors: A Mendelian randomization study

Upper gastrointestinal (UGI) tumors, notably gastric cancer (GC) and esophageal cancer (EC), are significant global health concerns due to their high morbidity and mortality rates. However, only a limited number of metabolites have been identified as biomarkers for these cancers. To explore the association between metabolites and UGI tumors, the present study conducted a comprehensive two‑sample Mendelian randomization (MR) analysis using publicly available genetic data. In the present study, the causal relationships were examined between 1,400 metabolites and UGI cancer using methods such as inverse variance weighting and weighted medians, along with sensitivity analyses for heterogeneity and pleiotropy. Functional experiments were conducted to validate the MR results. The analysis identified 57 metabolites associated with EC and 58 with GC. Key metabolites included fructosyllysine [EC: Odds ratio (OR)=1.450, 95% confidence interval (CI)=1.087‑1.934, P=0.011; GC: OR=1.728, 95% CI=1.202‑2.483, P=0.003], 2'‑deoxyuridine to cytidine ratio (EC: OR=1.464, 95% CI=1.111‑1.929, P=0.007; GC: OR=1.464, 95% CI=1.094‑1.957, P=0.010) and carnitine to protonylcarnitine (C3) ratio (EC: OR=0.655, 95% CI=0.499‑0.861, P=0.002; GC: OR=0.664, 95% CI=0.486‑0.906, P=0.010). Notably, fructosyllysine levels and the 2'‑deoxyuridine to cytidine ratio were identified as risk factors for both EC and GC, while the C3 ratio served as a protective factor. Functional experiments demonstrated that fructosyllysine and the 2'‑deoxyuridine to cytidine ratio promoted the proliferation of EC and GC cells, whereas carnitine inhibited their proliferation. In conclusion, the present findings provide insights into the causal factors and biomarkers associated with UGI tumors, which may be instrumental in guiding targeted dietary and pharmacological interventions, thereby contributing to the prevention and treatment of UGI cancer.

Lactylation-related gene signature accurately predicts prognosis and immunotherapy response in gastric cancer

Background

Gastric cancer (GC) is a malignant tumor associated with significant rates of morbidity and mortality. Hence, developing efficient predictive models and directing clinical interventions in GC is crucial. Lactylation of proteins is detected in gastric cancer tumors and is linked to the advancement of gastric cancer.

Methods

The The Cancer Genome Atlas (TCGA) was utilized to analyze the gene expression levels associated with lactylation. A genetic pattern linked to lactylation was created using Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. The predictive ability of the model was evaluated and confirmed in the Gene Expression Omnibus (GEO) cohort, where patients were divided into two risk groups based on their scores. The study examined the relationship between gene expression and the presence of immune cells in the context of immunotherapy treatment. In vitro cytotoxicity assays, ELISA and PD-1 and PD-L1interaction assays were used to assess the expression of PD-L1 while knocking down SLC16A7.

Results

29 predictive lactylation-related genes with differential expression were discovered. A signature consisting of three genes was developed and confirmed. Patients who had higher risk scores experienced worse clinical results. The group with lower risk showed increased Tumor Immune Dysfunction and Exclusion (TIDE) score and greater responsiveness to immunotherapy. The tumor tissues secrete more lactate acid than normal tissues and express more PD-L1 than normal tissues, that is, lactate acid promotes the immune evasion of tumor cells. In GC, the lactylation-related signature showed strong predictive accuracy. Utilizing both anti-lactylation and anti-PD-L1 may prove to be an effective approach for treating GC in clinical settings. We further proved that one of the lactate metabolism related genes, SCL16A7 could promote the expression of PD-L1 in GC cells.

Conclusion

The risk model not only provides a basis for better prognosis in GC patients, but also is a potential prognostic indicator to distinguish the molecular and immune characteristics, and the response from Immune checkpoint inhibitors (ICI) therapy and chemotherapy in GC.

Integrated gene-metabolite association network analysis reveals key metabolic pathways in gastric adenocarcinoma

Gastric adenocarcinoma is one of the most death cause cancers worldwide. Metabolomics is an effective approach for investigating the occurrence and progression of cancer and detecting prognostic biomarkers by studying the profiles of small bioactive molecules. To fully decipher the functional roles of the disrupted metabolites that modulate the cellular mechanism of gastric cancer, integrated gene-metabolite association network methods are critical to map the associations between metabolites and genes. In this study, we constructed a knowledge-based gene-metabolite association network of gastric cancer using the dysregulated metabolites and genes between gastric cancer patients and control group. The topological pathway analysis and gene-protein-metabolite-disease association analysis revealed four key gene-metabolite pathways which include eleven metabolites associated with modulated genes. The integrated gene-metabolite association network enables mechanistic investigation and provides a comprehensive overview regarding the investigation of molecular mechanisms of gastric cancer, which facilitates the in-depth understanding of metabolic biomarker roles in gastric cancer.

Phosphate-to-alanine ratio and bilirubin-to-androsterone glucuronide ratio are the hub metabolites in upper gastrointestinal cancers: a Mendelian randomisation (MR) study

Objective

Upper gastrointestinal (UGI) cancers, particularly esophageal cancer (EC) and gastric cancer (GC) represent a significant health burden with complex etiologies. Metabolic alterations are known to play a crucial role in cancer development and progression. Identifying key metabolic biomarkers may offer insights into the pathophysiology of UGI cancers and potential therapeutic targets. This study aimed to investigate the causal associations between 1,400 types of metabolites, specifically phosphate-to-alanine and bilirubin-to-androsterone glucuronide, and the risk of developing UGI cancers using Mendelian randomisation (MR) analysis.

Method

We conducted a two-sample MR study utilising genetic instruments identified from large-scale genome-wide association studies (GWASs) for metabolic traits. The outcomes were derived from GWAS datasets of UGI cancer patients, including EC and GC. Several MR methods were employed to ensure the robustness of the findings, including inverse variance weighted (IVW), MR-Egger and weighted median approaches.

Results

Our analysis found a total of 44 metabolites associated with EC and 15 metabolites associated with GC. The MR analyses revealed a significant causal relationship between the phosphate-to-alanine ratio (EC: OR = 1.002,95% CI = 1.00034-1.0037, p = 0.0037; GC: OR = 1.24,95% CI = 1.046-1.476, p = 0.01) and increased risk of UGI cancers. In contrast, the bilirubin-to-androsterone glucuronide ratio (EC: OR = 0.998,95% CI = 0.997-0.999, p = 0.03; GC: OR = 0.80,95% CI = 0.656-0.991, p = 0.04) was inversely associated with the risk, suggesting a potential protective effect.

Conclusion

Our findings suggest that the phosphate-to-alanine ratio and bilirubin-to-androsterone glucuronide ratio are key hub metabolites in the etiology of UGI cancers. These metabolic ratios could serve as potential biomarkers for early detection or targets for therapeutic intervention. Further research is warranted to elucidate the underlying biological mechanisms and to validate the clinical utility of these associations.

The relationship and clinical significance of lactylation modification in digestive system tumors

Lactylation, an emerging post-translational modification, plays a pivotal role in the initiation and progression of digestive system tumors. This study presents a comprehensive review of lactylation in digestive system tumors, underscoring its critical involvement in tumor development and progression. By focusing on metabolic reprogramming, modulation of the tumor microenvironment, and the molecular mechanisms regulating tumor progression, the potential of targeting lactylation as a therapeutic strategy is highlighted. The research reveals that lactylation participates in gene expression regulation and cell signaling by affecting the post-translational states of histones and non-histone proteins, thereby influencing metabolic pathways and immune evasion mechanisms in tumor cells. Furthermore, this study assesses the feasibility of lactylation as a therapeutic target, providing insights for clinical treatment of gastrointestinal cancers. Future research should concentrate on elucidating the mechanisms of lactylation, developing efficient lactylation inhibitors, and validating their therapeutic efficacy in clinical trials, which could transform current cancer treatment and immunotherapy approaches. In summary, this review emphasizes the crucial role of lactylation in tumorigenesis and progression through a detailed analysis of its molecular mechanisms and clinical significance.

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

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

Energy metabolism: a new target for gastric cancer treatment

Gastric cancer is the fifth most common malignancy worldwide having the fourth highest mortality rate. Energy metabolism is key and closely linked to tumour development. Most important in the reprogramming of cancer metabolism is the Warburg effect, which suggests that tumour cells will utilise glycolysis even with normal oxygen levels. Various molecules exert their effects by acting on enzymes in the glycolytic pathway, integral to glycolysis. Second, mitochondrial abnormalities in the reprogramming of energy metabolism, with consequences for glutamine metabolism, the tricarboxylic acid cycle and oxidative phosphorylation, abnormal fatty acid oxidation and plasma lipoprotein metabolism are important components of tumour metabolism. Third, inflammation-induced oxidative stress is a danger signal for cancer. Fourth, patterns of signalling pathways involve all aspects of metabolic transduction, and many clinical drugs exert their anticancer effects through energy metabolic signalling. This review summarises research on energy metabolism genes, enzymes and proteins and transduction pathways associated with gastric cancer, and discusses the mechanisms affecting their effects on postoperative treatment resistance and prognoses of gastric cancer. We believe that an in-depth understanding of energy metabolism reprogramming will aid the diagnosis and subsequent treatment of gastric cancer.

Effect of metabolic reprogramming on the immune microenvironment in gastric cancer

Gastric cancer (GC) is a malignant tumor of the gastrointestinal tract with a high mortality rate worldwide, a low early detection rate and a poor prognosis. The rise of metabolomics has facilitated the early detection and treatment of GC. Metabolism in the GC tumor microenvironment (TME) mainly includes glucose metabolism, lipid metabolism and amino acid metabolism, which provide energy and nutrients for GC cell proliferation and migration. Abnormal tumor metabolism can influence tumor progression by regulating the functions of immune cells and immune molecules in the TME, thereby contributing to tumor immune escape. Thus, in this review, we summarize the impact of metabolism on the TME during GC progression. We also propose novel strategies to modulate antitumor immune responses by targeting metabolism.

Multi-dimension metabolic prognostic model for gastric cancer

Background

Metabolic reprogramming is involved in different stages of tumorigenesis. There are six widely recognized tumor-associated metabolic pathways, including cholesterol catabolism process, fatty acid metabolism, glutamine metabolic process, glycolysis, one carbon metabolic process, and pentose phosphate process. This study aimed to classify gastric cancer patients into different metabolic bio-similar clusters.

Method

We analyzed six tumor-associated metabolic pathways and calculated the metabolic pathway score through RNA-seq data using single sample gene set enrichment analysis. The consensus clustering analysis was performed to classify patients into different bio-similar clusters by multi-dimensional scaling. Kaplan-Meier curves were presented between different metabolic bio-similar groups for OS analysis.

Results

A training set of 370 patients from the Cancer Genome Atlas database with primary gastric cancer was chosen. Patients were classified into four metabolic bio-similar clusters, which were identified as metabolic non-specificity, metabolic-active, cholesterol-silence, and metabolic-silence clusters. Survival analysis showed that patients in metabolic-active cluster and metabolic-silence cluster have significantly poor prognosis than other patients (p=0.031). Patients in metabolic-active cluster and metabolic-silence cluster had significantly higher intra-tumor heterogeneity than other patients (p=0.032). Further analysis was performed in metabolic-active cluster and cholesterol-silence cluster. Three cell-cycle-related pathways, including G2M checkpoints, E2F targets, and MYC targets, were significantly upregulated in metabolic-active cluster than in cholesterol-silence cluster. A validation set of 192 gastric cancer patients from the Gene Expression Omnibus data portal verified that metabolic bio-similar cluster can predict prognosis in gastric cancer.

Conclusion

Our study established a multi-dimension metabolic prognostic model in gastric cancer, which may be feasible for predicting clinical outcome.

Transcription factor TEAD4 facilitates glycolysis and proliferation of gastric cancer cells by activating PKMYT1

BACKGROUND

Gastric cancer (GC) ranks third for cancer deaths worldwide, and glycolysis is a hallmark of several cancers, including GC. TEAD4 plays a role in establishing an oncogenic cascade in cancers, including GC. Whether TEAD4 can influence the glycolysis of GC cells remains uncovered. Hence, this study attempted to investigate the impact on glycolysis of GC cells by TEAD4.

METHODS

By using bioinformatics analysis, differentially expressed mRNAs were screened, and downstream regulatory genes were predicted. Expression levels of TEAD4 and PKMYT1 were assessed by qRT-PCR. The binding sites between TEAD4 and PKMYT1 were predicted by the JASPAR database, meanwhile their modulatory relationship was confirmed through dual-luciferase assay and chromatin Immunoprecipitation (ChIP). Cell viability and proliferation were assayed via CCK-8 and colony formation assays. Glycolysis was measured by assaying extracellular acidification rate, oxygen consumption rate, and production of pyruvic acid, lactate, citrate, and malate. Expression levels of proteins (HK-2 and PKM2) related to glycolysis were assessed by Western blot.

RESULTS

TEAD4 was upregulated in GC tissues and cells. TEAD4 knockdown substantially repressed glycolysis and proliferation of GC cells. PKMYT1, the target gene downstream of TEAD4, was identified via bioinformatics prediction, and its expression was elevated in GC. Dual-luciferase and ChIP assay validated the targeted relationship between the promoter region of PKMYT1 and TEAD4. As revealed by rescue experiments, the knockdown of TEAD4 reversed the stimulative effect on GC cell glycolysis and proliferation by forced expression of PKMYT1.

CONCLUSION

TEAD4 activated PKMYT1 to facilitate the proliferation and glycolysis of GC cells. TEAD4 and PKMYT1 may be possible therapeutic targets for GC.

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.

Metabolic codependencies in the tumor microenvironment and gastric cancer: Difficulties and opportunities

Oncogenesis and the development of tumors affect metabolism throughout the body. Metabolic reprogramming (also known as metabolic remodeling) is a feature of malignant tumors that is driven by oncogenic changes in the cancer cells themselves as well as by cytokines in the tumor microenvironment. These include endothelial cells, matrix fibroblasts, immune cells, and malignant tumor cells. The heterogeneity of mutant clones is affected by the actions of other cells in the tumor and by metabolites and cytokines in the microenvironment. Metabolism can also influence immune cell phenotype and function. Metabolic reprogramming of cancer cells is the result of a convergence of both internal and external signals. The basal metabolic state is maintained by internal signaling, while external signaling fine-tunes the metabolic process based on metabolite availability and cellular needs. This paper reviews the metabolic characteristics of gastric cancer, focusing on the intrinsic and extrinsic mechanisms that drive cancer metabolism in the tumor microenvironment, and interactions between tumor cell metabolic changes and microenvironment metabolic changes. This information will be helpful for the individualized metabolic treatment of gastric cancers.

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.

Identification of lactylation related model to predict prognostic, tumor infiltrating immunocytes and response of immunotherapy in gastric cancer

Background

The epigenetic regulatory chemical lactate is a product of glycolysis. It can regulate gene expression through histone lactylation, thereby promoting tumor proliferation, metastasis, and immunosuppression.

Methods

In this study, a lactylation-related model for gastric cancer (GC) was constructed, and its relationships to prognosis, immune cell infiltration, and immunotherapy were investigated. By contrasting normal tissues and tumor tissues, four lactylation-related pathways that were substantially expressed in GC tissues were found in the GSEA database. Six lactylation-related genes were screened for bioinformatic analysis. The GC data sets from the TCGA and GEO databases were downloaded and integrated to perform cluster analysis, and the lactylation related model was constructed by secondary clustering.

Results

The fingding demonstrated that the lactylation score has a strong correlation with the overall survival rate from GC and the progression of GC. Mechanistic experiments showed that abundant immune cell infiltration (macrophages showed the highest degree of infiltration) and increased genetic instability are traits of high lactylation scores. Immune checkpoint inhibitors (ICIs) demonstrated a reduced response rate in GC with high lactylation scores. At the same time, tumors with high lactylation scores had high Tumor Immune Dysfunction and Exclusion scores, which means that they had a higher risk of immune evasion and dysfunction.

Discussion

These findings indicate that the lactylation score can be used to predict the malignant progression and immune evasion of GC. This model also can guide the treatment response to ICIs of GC. The constructed model of the lactate gene is also expected to become a potential therapeutic target for GC and diagnostic marker.

Natural compounds targeting glycolysis as promising therapeutics for gastric cancer: A review

Gastric cancer, a common malignant disease, seriously endangers human health and life. The high mortality rate due to gastric cancer can be attributed to a lack of effective therapeutic drugs. Cancer cells utilize the glycolytic pathway to produce energy even under aerobic conditions, commonly referred to as the Warburg effect, which is a characteristic of gastric cancer. The identification of new targets based on the glycolytic pathway for the treatment of gastric cancer is a viable option, and accumulating evidence has shown that phytochemicals have extensive anti-glycolytic properties. We reviewed the effects and mechanisms of action of phytochemicals on aerobic glycolysis in gastric cancer cells. Phytochemicals can effectively inhibit aerobic glycolysis in gastric cancer cells, suppress cell proliferation and migration, and promote apoptosis, via the PI3K/Akt, c-Myc, p53, and other signaling pathways. These pathways affect the expressions of HIF-1α, HK2, LDH, and other glycolysis-related proteins. This review further assesses the potential of using plant-derived compounds for the treatment of gastric cancer and sheds insight into the development of new drugs.

IMP4 Silencing Inhibits the Malignancy of Lung Adenocarcinoma via ERK Pathway

Our study aimed to elucidate the function of IMP U3 small nucleolar ribonucleoprotein 4 (IMP4) in lung adenocarcinoma (LUAD) and its potential molecular mechanisms. Cell counting kit-8, 5-ethynyl-20-deoxyuridine, flow cytometry, wound healing, and transwell assays were performed to examine the biological behaviour of LUAD cells. mRNA and protein expression levels were determined using quantitative real-time PCR, Western blotting, and immunohistochemistry. In addition, a mouse tumour xenograft model was used to evaluate the role of IMP4 in tumour progression. Furthermore, glycolysis-related indicators were measured. The levels of IMP4 were up-regulated in both human LUAD tissues and cells. IMP4 silencing significantly suppressed proliferation, migration, invasion, and glycolysis; promoted apoptosis; and induced cell cycle arrest in LUAD cells. IMP4 silencing also inactivated the extracellular signal-regulated kinase (ERK) pathway. Moreover, rescue experiments demonstrated that the function of LUAD cells induced by IMP4 overexpression could be reversed by treatment with an ERK pathway inhibitor (SCH772984). In vivo experiments further verified that IMP4 silencing repressed the growth of subcutaneous tumours and glycolysis. IMP4 silencing suppressed the malignancy of LUAD by inactivating ERK signalling.

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.

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

Background

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

Methods

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

Results

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

Conclusions

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

Metabolomic Profiling of Blood-Derived Microvesicles in Breast Cancer Patients

Malignant cells differ from benign ones in their metabolome and it is largely unknown whether this difference is reflected in the metabolic profile of their microvesicles (MV), which are secreted into the blood of cancer patients. Here, they are present together with MV from the various blood and endothelial cells. Harvesting MV from 78 breast cancer patients (BC) and 30 controls, we characterized the whole blood MV metabolome using targeted and untargeted mass spectrometry. Especially (lyso)-phosphatidylcholines and sphingomyelins were detected in a relevant abundance. Eight metabolites showed a significant discriminatory power between BC and controls. High concentrations of lysoPCaC26:0 and PCaaC38:5 were associated with shorter overall survival. Comparing BC subtype-specific metabolome profiles, 24 metabolites were differentially expressed between luminal A and luminal B. Pathway analysis revealed alterations in the glycerophospholipid metabolism for the whole cancer cohort and in the ether lipid metabolism for the molecular subtype luminal B. Although this mixture of blood-derived MV contains only a minor number of tumor MV, a combination of metabolites was identified that distinguished between BC and controls as well as between molecular subtypes, and was predictive for overall survival. This suggests that these metabolites represent promising biomarkers and, moreover, that they may be functionally relevant for tumor progression.

Metabolomic Characterization Reveals ILF2 and ILF3 Affected Metabolic Adaptions in Esophageal Squamous Cell Carcinoma

Esophageal cancer (EC) is a common malignant disease in eastern countries. However, a study of the metabolomic characteristics associated with other biological factors in esophageal squamous cell carcinoma (ESCC) is limited. Interleukin enhancer binding factor 2 (ILF2) and ILF3, double-stranded RNA-binding proteins, have been reported to contribute to the occurrence and development of various types of malignancy. Nevertheless, the underlying functions of ILF2 and ILF3 in ESCC metabolic reprogramming have never been reported. This study aimed to contribute to the metabolic characterization of ESCC and to investigate the metabolomic alterations associated with ILF2 and ILF3 in ESCC tissues. Here, we identified 112 differential metabolites, which were mainly enriched in phosphatidylcholine biosynthesis, fatty acid metabolism, and amino acid metabolism pathways, based on liquid chromatography–mass spectrometry and capillary electrophoresis–mass spectrometry approaches using ESCC tissues and paired para-cancer tissues from twenty-eight ESCC patients. In addition, ILF2 and ILF3 expression were significantly elevated in EC tissues compared to the histologically normal samples, and closely associated with PI3K/AKT and MAPK signaling pathways in ESCC. Moreover, in ESCC tissues with a high ILF2 expression, several short-chain acyl-carnitines (C3:0, C4:0, and C5:0) related to the BCAA metabolic pathway and long-chain acyl-carnitines (C14:0, C16:0, C16:0-OH, and C18:0) involved in the oxidation of fatty acids were obviously upregulated. Additionally, a series of intermediate metabolites involved in the glycolysis pathway, including G6P/F6P, F1,6BP, DHAP, G3P, and 2,3BPG, were remarkably downregulated in highly ILF3-expressed ESCC tissues compared with the corresponding para-cancer tissues. Overall, these findings may provide evidence for the roles of ILF2 and ILF3 during the process of ESCC metabolic alterations, and new insights into the development of early diagnosis and treatment for ESCC. Further investigation is needed to clarify the underlying mechanism of ILF2 and ILF3 on acyl-carnitines and the glycolysis pathway, respectively.

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.

Development and Validation of a Prognostic Classifier Based on Lipid Metabolism-Related Genes in Gastric Cancer

Background: Dysregulation of lipid metabolism plays important roles in the tumorigenesis and progression of gastric cancer (GC). The present study aimed to establish a prognostic model based on the lipid metabolism–related genes in GC patients.

Materials and Methods: Two GC datasets from the Gene Expression Atlas, GSE62254 (n = 300) and GSE26942 (n = 217), were used as training and validation cohorts to establish a risk predictive scoring model. The efficacy of this model was assessed by ROC analysis. The association of the risk predictive scores with patient characteristics and immune cell subtypes was evaluated. A nomogram was constructed based on the risk predictive score model and other prognostic factors.

Results: A risk predictive score model was established based on the expression of 19 lipid metabolism–related genes (LPL, IPMK, PLCB3, CDIPT, PIK3CA, DPM2, PIGZ, GPD2, GPX3, LTC4S, CYP1A2, GALC, SGMS1, SMPD2, SMPD3, FUT6, ST3GAL1, B4GALNT1, and ACADS). The time-dependent ROC analysis revealed that the risk predictive score model was stable and robust. Patients with high risk scores had significantly unfavorable overall survival compared with those with low risk scores in both the training and validation cohorts. A higher risk score was associated with more aggressive features, including a higher tumor grade, a more advanced TNM stage, and diffuse type of Lauren classification of GC. Moreover, distinct immune cell subtypes and signaling pathways were found between the high–risk and low–risk score groups. A nomogram containing patients’ age, tumor stage, adjuvant chemotherapy, and the risk predictive score could accurately predict the survival probability of patients at 1, 3, and 5 years.

Conclusion: A novel 19-gene risk predictive score model was developed based on the lipid metabolism–related genes, which could be a potential prognostic indicator and therapeutic target of GC.

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.

Identification and Validation of Plasma Metabolomic Signatures in Precancerous Gastric Lesions That Progress to Cancer

IMPORTANCE

Metabolic deregulation plays an important role in gastric cancer (GC) development. To date, no studies have comprehensively explored the metabolomic profiles along the cascade of gastric lesions toward GC.

OBJECTIVE

To draw a metabolic landscape and define metabolomic signatures associated with the progression of gastric lesions and risk of early GC.

DESIGN, SETTING, AND PARTICIPANTS

A 2-stage, population-based cohort study was initiated in 2017 in Linqu County, Shandong Province, China, a high-risk area for GC. Prospective follow-up was conducted during the validation stage (June 20, 2017, to May 27, 2020). A total of 400 individuals were included based on the National Upper Gastrointestinal Cancer Early Detection Program in China. The discovery stage involved 200 individuals with different gastric lesions or GC (high-grade intraepithelial neoplasia or invasive GC). The validation stage prospectively enrolled 152 individuals with gastric lesions who were followed up for 118 to 1063 days and 48 individuals with GC.

EXPOSURES

Metabolomic profiles and metabolite signatures were examined based on untargeted plasma metabolomics assay.

MAIN OUTCOMES AND MEASURES

The risk of GC overall and early GC (high-grade intraepithelial neoplasia), and progression of gastric lesions.

RESULTS

Of the 400 participants, 124 of 200 (62.0%) in the discovery set were men; mean (SD) age was 56.8 (7.5) years. In the validation set, 136 of 200 (68.0%) were men; mean (SD) age was 57.5 (8.1) years. Distinct metabolomic profiles were noted for gastric lesions and GC. Six metabolites, including α-linolenic acid, linoleic acid, palmitic acid, arachidonic acid, sn-1 lysophosphatidylcholine (LysoPC)(18:3), and sn-2 LysoPC(20:3) were significantly inversely associated with risk of GC overall and early GC (high-grade intraepithelial neoplasia). Among these metabolites, the first 3 were significantly inversely associated with gastric lesion progression, especially for the progression of intestinal metaplasia (α-linolenic acid: OR, 0.42; 95% CI, 0.18-0.98; linoleic acid: OR, 0.43; 95% CI, 0.19-1.00; and palmitic acid: OR, 0.32; 95% CI, 0.13-0.78). Compared with models including only age, sex, Helicobacter pylori infection, and gastric histopathologic findings, integrating these metabolites significantly improved the performance for predicting the progression of gastric lesions (area under the curve [AUC], 0.86; 95% CI, 0.70-1.00 vs AUC, 0.69; 95% CI, 0.50-0.88; P = .02) and risk of early GC (AUC, 0.83; 95% CI, 0.58-1.00 vs AUC, 0.61; 95% CI, 0.31-0.91; P = .03).

CONCLUSIONS AND RELEVANCE

This study defined metabolite signatures that might serve as meaningful biomarkers for assessing high-risk populations and early diagnosis of GC, possibly advancing targeted GC prevention and control.

Tick-Tock Consider the Clock: The Influence of Circadian and External Cycles on Time of Day Variation in the Human Metabolome-A Review

The past decade has seen a large influx of work investigating time of day variation in different human biofluid and tissue metabolomes. The driver of this daily variation can be endogenous circadian rhythms driven by the central and/or peripheral clocks, or exogenous diurnal rhythms driven by behavioural and environmental cycles, which manifest as regular 24 h cycles of metabolite concentrations. This review, of all published studies to date, establishes the extent of daily variation with regard to the number and identity of 'rhythmic' metabolites observed in blood, saliva, urine, breath, and skeletal muscle. The probable sources driving such variation, in addition to what metabolite classes are most susceptible in adhering to or uncoupling from such cycles is described in addition to a compiled list of common rhythmic metabolites. The reviewed studies show that the metabolome undergoes significant time of day variation, primarily observed for amino acids and multiple lipid classes. Such 24 h rhythms, driven by various factors discussed herein, are an additional source of intra/inter-individual variation and are thus highly pertinent to all studies applying untargeted and targeted metabolomics platforms, particularly for the construction of biomarker panels. The potential implications are discussed alongside proposed minimum reporting criteria suggested to acknowledge time of day variation as a potential influence of results and to facilitate improved reproducibility.

Metabolomic Profiling for Diagnosis and Prognostication in Surgery: A Scoping Review

OBJECTIVE

This review assimilates and critically evaluates available literature regarding the use of metabolomic profiling in surgical decision-making.

BACKGROUND

Metabolomic profiling is performed by nuclear magnetic resonance spectroscopy or mass spectrometry of biofluids and tissues to quantify biomarkers (ie, sugars, amino acids, and lipids), producing diagnostic and prognostic information that has been applied among patients with cardiovascular disease, inflammatory bowel disease, cancer, and solid organ transplants.

METHODS

PubMed was searched from 1995 to 2019 to identify studies investigating metabolomic profiling of surgical patients. Articles were included and assimilated into relevant categories per PRISMA-ScR guidelines. Results were summarized with descriptive analytical methods.

RESULTS

Forty-seven studies were included, most of which were retrospective studies with small sample sizes using various combinations of analytic techniques and types of biofluids and tissues. Results suggest that metabolomic profiling has the potential to effectively screen for surgical diseases, suggest diagnoses, and predict outcomes such as postoperative complications and disease recurrence. Major barriers to clinical adoption include a lack of high-level evidence from prospective studies, heterogeneity in study design regarding tissue and biofluid procurement and analytical methods, and the absence of large, multicenter metabolome databases to facilitate systematic investigation of the efficacy, reproducibility, and generalizability of metabolomic profiling diagnoses and prognoses.

CONCLUSIONS

Metabolomic profiling research would benefit from standardization of study design and analytic approaches. As technologies improve and knowledge garnered from research accumulates, metabolomic profiling has the potential to provide personalized diagnostic and prognostic information to support surgical decision-making from preoperative to postdischarge phases of care.

Screening for Early Gastric Cancer Using a Noninvasive Urine Metabolomics Approach

Simple Summary

There are currently no effective specific biomarkers for the screening of early gastric cancer. Recently, metabolomics has been used to profile small endogenous metabolites, demonstrating significant potential in the diagnosis/screening of cancer, owing to its ability to conduct a noninvasive sample analysis. Here, we performed a urine metabolomics analysis in the context of an early diagnosis of gastric cancer. This approach showed very high diagnostic sensitivity and specificity and performed significantly better than the analysis of serum tumor markers modalities. An additional genomic data analysis revealed the up-regulation of several genes in gastric cancer. This metabolomics-based early diagnosis approach may have the potential for mass screening an average-risk population and may facilitate endoscopic examination through risk stratification.

Abstract

The early detection of gastric cancer (GC) could decrease its incidence and mortality. However, there are currently no accurate noninvasive markers for GC screening. Therefore, we developed a noninvasive diagnostic approach, employing urine nuclear magnetic resonance (NMR) metabolomics, to discover putative metabolic markers associated with GC. Changes in urine metabolite levels during oncogenesis were evaluated using samples from 103 patients with GC and 100 age- and sex-matched healthy controls. Approximately 70% of the patients with GC (n = 69) had stage I GC, with the majority (n = 56) having intramucosal cancer. A multivariate statistical analysis of the urine NMR data well discriminated between the patient and control groups and revealed nine metabolites, including alanine, citrate, creatine, creatinine, glycerol, hippurate, phenylalanine, taurine, and 3-hydroxybutyrate, that contributed to the difference. A diagnostic performance test with a separate validation set exhibited a sensitivity and specificity of more than 90%, even with the intramucosal cancer samples only. In conclusion, the NMR-based urine metabolomics approach may have potential as a convenient screening method for the early detection of GC and may facilitate consequent endoscopic examination through risk stratification.

Metabolomic profiling of gastric cancer tissues identified potential biomarkers for predicting peritoneal recurrence

BACKGROUND

Metabolomics is useful for analyzing the nutrients necessary for cancer progression, as the proliferation is regulated by available nutrients. We studied the metabolomic profile of gastric cancer (GC) tissue to elucidate the associations between metabolism and recurrence.

METHODS

Cancer and adjacent non-cancerous tissues were obtained in a pair-wise manner from 140 patients with GC who underwent gastrectomy. Frozen tissues were homogenized and analyzed by capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS). Metabolites were further assessed based on the presence or absence of recurrence.

RESULTS

Ninety-three metabolites were quantified. In cancer tissues, the lactate level was significantly higher and the adenylate energy charge was lower than in non-cancerous tissues. The Asp, β-Ala, GDP, and Gly levels were significantly lower in patients with recurrence than in those without. Based on ROC analyses to determine the cut-off values of the four metabolites, patients were categorized into groups at high risk and low risk of peritoneal recurrence. Logistic regression and Cox proportional hazard analyses identified β-Ala as an independent predictor of peritoneal recurrence (hazard ratio [HR] 5.21 [95% confidence interval 1.07-35.89], p = 0.029) and an independent prognostic factor for the overall survival (HR 3.44 [95% CI 1.65-7.14], p < 0.001).

CONCLUSIONS

The metabolomic profiles of cancer tissues differed from those of non-cancerous tissues. In addition, four metabolites were significantly associated with recurrence in GC. β-Ala was both a significant predictor of peritoneal recurrence and a prognostic factor.

Systems Biology of Gastric Cancer: Perspectives on the Omics-Based Diagnosis and Treatment

Gastric cancer is the fifth most diagnosed cancer in the world, affecting more than a million people and causing nearly 783,000 deaths each year. The prognosis of advanced gastric cancer remains extremely poor despite the use of surgery and adjuvant therapy. Therefore, understanding the mechanism of gastric cancer development, and the discovery of novel diagnostic biomarkers and therapeutics are major goals in gastric cancer research. Here, we review recent progress in application of omics technologies in gastric cancer research, with special focus on the utilization of systems biology approaches to integrate multi-omics data. In addition, the association between gastrointestinal microbiota and gastric cancer are discussed, which may offer insights in exploring the novel microbiota-targeted therapeutics. Finally, the application of data-driven systems biology and machine learning approaches could provide a predictive understanding of gastric cancer, and pave the way to the development of novel biomarkers and rational design of cancer therapeutics.

Advances and challenges in pursuing biomarkers for obstructive sleep apnea: Implications for the cardiovascular risk

Obstructive sleep apnea (OSA) is a common clinical condition associated with increased cardiovascular morbidity and mortality. Recent evidence from clinical studies and animal models suggest that OSA can promote cardiovascular disease by inducing autonomic, hemodynamic, inflammatory and metabolic dysregulation. However, most of the evidence addressing hard endpoints in humans is derived from observational studies. Several challenges have been noted in the pursuit of a comprehensive knowledge base about the impact of OSA including: 1) the precise mechanisms by which OSA causes metabolic and cardiovascular consequences are not clear, which limits our current ability to address potential targets in OSA; 2) several patients with OSA, even with severe forms, present with no or mild daytime symptoms. Beyond the obvious challenges for obtaining good adherence for conventional OSA treatments, there is evidence that symptomatic vs. asymptomatic patients with OSA do not necessarily have the same metabolic and cardiovascular outcomes; and 3) the cardiovascular response to OSA treatment may vary even in those patients with good adherence. In this scenario, there is an obvious need to develop biomarkers in the OSA research area. This review focuses on describing the advances that have occurred so far in exploring potential OSA biomarkers with clear emphasis for the cardiovascular risk. Particular attention will be devoted to discuss molecular biomarkers including the potential role of microRNAs, proteomics and metabolomics. We also discuss the major challenges and perspectives in this growing research field.

HNF4α pathway mapping identifies wild-type IDH1 as a targetable metabolic node in gastric cancer

OBJECTIVE

Gastric cancer (GC) is a leading cause of cancer mortality. Previous studies have shown that hepatocyte nuclear factor-4α (HNF4α) is specifically overexpressed in GC and functionally required for GC development. In this study, we investigated, on a genome-wide scale, target genes of HNF4α and oncogenic pathways driven by HNF4α and HNF4α target genes.

DESIGN

We performed HNF4α chromatin immunoprecipitation followed by sequencing across multiple GC cell lines, integrating HNF4α occupancy data with (epi)genomic and transcriptome data of primary GCs to define HNF4α target genes of in vitro and in vivo relevance. To investigate mechanistic roles of HNF4α and HNF4α targets, we performed cancer metabolic measurements, drug treatments and functional assays including murine xenograft experiments.

RESULTS

Gene expression analysis across 19 tumour types revealed HNF4α to be specifically upregulated in GCs. Unbiased pathway analysis revealed organic acid metabolism as the top HNF4α-regulated pathway, orthogonally supported by metabolomic analysis. Isocitrate dehydrogenase 1 (IDH1) emerged as a convergent HNF4α direct target gene regulating GC metabolism. We show that wild-type IDH1 is essential for GC cell survival, and that certain GC cells can be targeted by IDH1 inhibitors.

CONCLUSIONS

Our results highlight a role for HNF4α in sustaining GC oncogenic metabolism, through the regulation of IDH1. Drugs targeting wild-type IDH1 may thus have clinical utility in GCs exhibiting HNF4α overexpression, expanding the role of IDH1 in cancer beyond IDH1/2 mutated malignancies.

A clinical metabolomics-based biomarker signature as an approach for early diagnosis of gastric cardia adenocarcinoma

Gastric cardia adenocarcinoma (GCA) has a high mortality rate worldwide; however, current early diagnostic methods lack efficacy. Therefore, the aim of the present study was to identify potential biomarkers for the early diagnosis of GCA. Global metabolic profiles were obtained from plasma samples collected from 21 patients with GCA and 48 healthy controls using ultra-performance liquid chromatography/quadrupole-time-of-flight mass spectrometry. The orthogonal partial least squares discrimination analysis model was applied to distinguish patients with GCA from healthy controls and to identify potential biomarkers. Metabolic pathway analysis was performed using MetaboAnalyst (version 4.0) and revealed that ‘glycerophospholipid metabolism’, ‘linoleic acid metabolism’, ‘fatty acid biosynthesis’ and ‘primary bile acid biosynthesis’ were significantly associated with GCA. In addition, an early diagnostic model for GCA was established based on the relative levels of four key biomarkers, including phosphorylcholine, glycocholic acid, L-acetylcarnitine and arachidonic acid. The area under the receiver operating characteristic curve revealed that the diagnostic model had a sensitivity and specificity of 0.977 and 0.952, respectively. The present study demonstrated that metabolomics may aid the identification of the mechanisms underlying the pathogenesis of GCA. In addition, the proposed diagnostic method may serve as a promising approach for the early diagnosis of GCA.

Gastric cancer depends on aldehyde dehydrogenase 3A1 for fatty acid oxidation

The major source of ATP in cancer cells remains unclear. Here, we examined energy metabolism in gastric cancer cells and found increased fatty acid oxidation and increased expression of ALDH3A1. Metabolic analysis showed that lipid peroxidation by reactive oxygen species led to spontaneous production of 4-hydroxynonenal, which was converted to fatty acids with NADH production by ALDH3A1, resulting in further fatty acid oxidation. Inhibition of ALDH3A1 by knock down using siRNA of ALDH3A1 resulted in significantly reduced ATP production by cancer cells, leading to apoptosis. Oxidative phosphorylation by mitochondria in gastric cancer cells was driven by NADH supplied via fatty acid oxidation. Therefore, blockade of ALDH3A1 together with mitochondrial complex I using gossypol and phenformin led to significant therapeutic effects in a preclinical gastric cancer model.

Comprehensive Multi-Omics Analysis Reveals Aberrant Metabolism of Epstein-Barr-Virus-Associated Gastric Carcinoma

The metabolic landscape of Epstein–Barr-virus-associated gastric cancer (EBVaGC) remains to be elucidated. In this study, we used transcriptomics, metabolomics, and lipidomics to comprehensively investigate aberrant metabolism in EBVaGC. Specifically, we conducted gene expression analyses using microarray-based data from gastric adenocarcinoma epithelial cell lines and tissue samples from patients with clinically advanced gastric carcinoma. We also conducted complementary metabolomics and lipidomics using various mass spectrometry platforms. We found a significant downregulation of genes related to metabolic pathways, especially the metabolism of amino acids, lipids, and carbohydrates. The effect of dysregulated metabolic genes was confirmed in a survival analysis of 3951 gastric cancer patients. We found 57 upregulated metabolites and 31 metabolites that were downregulated in EBVaGC compared with EBV-negative gastric cancer. Sixty-nine lipids, mainly ether-linked phospholipids and triacylglycerols, were downregulated, whereas 45 lipids, mainly phospholipids, were upregulated. In total, 15 metabolisms related to polar metabolites and 15 lipid-associated pathways were involved in alteration of metabolites by EBV in gastric cancer. In this work, we have described the metabolic landscape of EBVaGC at the multi-omics level. These findings could help elucidate the mechanism of EBVaGC oncogenesis.

Assessment of a Noninvasive Exhaled Breath Test for the Diagnosis of Oesophagogastric Cancer

Question

What is the diagnostic accuracy of a breath test for esophagogastric cancer?

Findings

In a multicenter diagnostic study of 335 patients, including 172 patients with esophagogastric cancer, the breath test demonstrated good diagnostic accuracy.

Meaning

This study suggests the potential of breath analysis as a noninvasive tool in the diagnosis of esophagogastric cancer.

Importance

Early esophagogastric cancer (OGC) stage presents with nonspecific symptoms.

Objective

The aim of this study was to determine the accuracy of a breath test for the diagnosis of OGC in a multicenter validation study.

Design, Setting, and Participants

Patient recruitment for this diagnostic validation study was conducted at 3 London hospital sites, with breath samples returned to a central laboratory for selected ion flow tube mass spectrometry (SIFT-MS) analysis. Based on a 1:1 cancer:control ratio, and maintaining a sensitivity and specificity of 80%, the sample size required was 325 patients. All patients with cancer were on a curative treatment pathway, and patients were recruited consecutively. Among the 335 patients included; 172 were in the control group and 163 had OGC.

Interventions

Breath samples were collected using secure 500-mL steel breath bags and analyzed by SIFT-MS. Quality assurance measures included sampling room air, training all researchers in breath sampling, regular instrument calibration, and unambiguous volatile organic compounds (VOCs) identification by gas chromatography mass spectrometry.

Main Outcomes and Measures

The risk of cancer was identified based on a previously generated 5-VOCs model and compared with histopathology-proven diagnosis.

Results

Patients in the OGC group were older (median [IQR] age 68 [60-75] vs 55 [41-69] years) and had a greater proportion of men (134 [82.2%]) vs women (81 [47.4%]) compared with the control group. Of the 163 patients with OGC, 123 (69%) had tumor stage T3/4, and 106 (65%) had nodal metastasis on clinical staging. The predictive probabilities generated by this 5-VOCs diagnostic model were used to generate a receiver operator characteristic curve, with good diagnostic accuracy, area under the curve of 0.85. This translated to a sensitivity of 80% and specificity of 81% for the diagnosis of OGC.

Conclusions and Relevance

This study shows the potential of breath analysis in noninvasive diagnosis of OGC in the clinical setting. The next step is to establish the diagnostic accuracy of the test among the intended population in primary care where the test will be applied.

Glycerophospholipids pathways and chromosomal instability in gastric cancer: Global lipidomics analysis

BACKGROUND

Based on the breakthrough of genomics analysis, The Cancer Genome Atlas Research Group recently proposed an integrative genomic analysis, dividing gastric cancer (GC) into four subtypes, characterized by the chromosomal instability (CIN) status. However, the CIN status of GC is still vaguely characterized and lacking the valuable easy-to-use CIN markers to diagnosis in molecular and histological detection.

AIM

To explore the associations of CIN with downstream lipidomics profiles.

METHODS

We collected cancerous and noncancerous tissue samples from 18 patients with GC; the samples were divided into CIN and non-CIN types based on the system of The Cancer Genome Atlas Research Group and 409 sequenced oncogenes and tumor suppressor genes. We identified the lipidomics profiles of the GC samples and samples of their adjacent noncancerous tissues by using liquid chromatography–mass spectrometry. Furthermore, we selected leading metabolites based on variable importance in projection scores of > 1.0 and P < 0.05.

RESULTS

Twelve men and six women participated in this study; the participants had a median age of 67.5 years (range, 52–87 years) and were divided into CIN (n = 9) and non-CIN (n = 9) groups. The GC samples exhibited distinct profiles of lysophosphocholine, phosphocholine, phosphatidylethanolamine, phosphatidylinositol, phosphoserine, sphingomyelin, ceramide, and triglycerides compared with their adjacent noncancerous tissues. The glycerophospholipid levels (phosphocholine, phosphatidylethanolamine, and phosphatidylinositol) were 1.4- to 2.3-times higher in the CIN group compared with the non-CIN group (P < 0.05). Alterations in the glycerolipid and glycerophospholipid pathways indicated progression of GC toward CIN.

CONCLUSION

The lipidomics profiles of GC samples were distinct from those of their adjacent noncancerous tissues. CIN status of GC is primarily associated with downstream lipidomics in the glycerophospholipid pathway.

Visceral Adipose Tissue Modulates Radiosensitivity in Oesophageal Adenocarcinoma

Oesophageal adenocarcinoma (OAC) is an exemplar model of obesity-associated cancer. Response to neoadjuvant chemoradiotherapy (NA CRT) is a clinical challenge. We examined if visceral adipose tissue and obesity status alter radiosensitivity in OAC. The radioresistant (OE33R) and radioresponsive (OE33P) OAC isogenic model was cultured with adipose tissue conditioned media from three patient cohorts: non-cancer patients, surgery only OAC patients and NA CRT OAC patients. Cell survival was characterised by clonogenic assay, metabolomic profiling by nuclear magnetic resonance spectroscopy and adipokine receptor gene expression by qPCR. A retrospective in vivo study compared tumour response to NA CRT in normal weight (n=53) versus overweight/obese patients (n=148). Adipose conditioned media (ACM) from all patient cohorts significantly increased radiosensitivity in radioresistant OE33R cells. ACM from the NA CRT OAC cohort increased radiosensitivity in OE33P cells. Metabolomic profiling demonstrated separation of the non-cancer and surgery only OAC cohorts and between the non-cancer and NA CRT OAC cohorts. Gene expression profiling of OE33P versus OE33R cells demonstrated differential expression of the adiponectin receptor-1 (AR1), adiponectin receptor-2 (AR2), leptin receptor (LepR) and neuropilin receptor-1 (NRP1) genes. In vivo overweight/obese OAC patients achieved an enhanced tumour response following NA CRT compared to normal weight patients. This study demonstrates that visceral adipose tissue modulates the cellular response to radiation in OAC.

Metabolomic Markers of Phthalate Exposure in Plasma and Urine of Pregnant Women

Phthalates are known endocrine disruptors and found in almost all people with several associated adverse health outcomes reported in humans and animal models. Limited data are available on the relationship between exposure to endocrine disrupting chemicals and the human metabolome. We examined the relationship of metabolomic profiles in plasma and urine of 115 pregnant women with eleven urine phthalate metabolites measured at 26 weeks of gestation to identify potential biomarkers and relevant pathways. Targeted metabolomics was performed by selected reaction monitoring liquid chromatography and triple quadrupole mass spectrometry to measure 415 metabolites in plasma and 151 metabolites in urine samples. We have chosen metabolites with the best defined peaks for more detailed analysis (138 in plasma and 40 in urine). Relationship between urine phthalate metabolites and concurrent metabolomic markers in plasma and urine suggested potential involvement of diverse pathways including lipid, steroid, and nucleic acid metabolism and enhanced inflammatory response. Most of the correlations were positive for both urine and plasma, and further confirmed by regression and PCA analysis. However, after the FDR adjustment for multiple comparisons, only 9 urine associations remained statistically significant (q-values 0.0001–0.0451), including Nicotinamide mononucleotide, Cysteine T2, Cystine, and L-Aspartic acid. Additionally, we found negative associations of maternal pre-pregnancy body mass index (BMI) with more than 20 metabolomic markers related to lipid and amino-acid metabolism and inflammation pathways in plasma (p = 0.01–0.0004), while Mevalonic acid was positively associated (p = 0.009). Nicotinic acid, the only significant metabolite in urine, had a positive association with maternal BMI (p = 0.002). In summary, when evaluated in the context of metabolic pathways, the findings suggest enhanced lipid biogenesis, inflammation and altered nucleic acid metabolism in association with higher phthalate levels. These results provide new insights into the relationship between phthalates, common in most human populations, and metabolomics, a novel approach to exposure and health biomonitoring.

Metabolomic alterations and chromosomal instability status in gastric cancer

AIM

To explore the correlation of metabolomics profiles of gastric cancer (GC) with its chromosomal instability (CIN) status.

METHODS

Nineteen GC patients were classified as CIN and non-CIN type by The Cancer Genome Atlas Research Group system, based on 409 oncogenes and tumor suppressor genes sequenced. The aqueous metabolites of the GC tumor and its surrounding adjacent healthy tissues were identified through liquid chromatography-mass spectrometry. Groups were compared by defining variable importance in projection score of > 1.2, a fold change value or its reciprocal of > 1.2, and a P value of < 0.05 as a significant difference.

RESULTS

In total, twelve men and seven women were enrolled, with a median age of 66 years (range, 47-87 years). The numbers of gene alterations in the CIN GC group were significantly higher than those in the non-CIN GC (32-218 vs 2-17; P < 0.0005). Compared with the adjacent healthy tissues, GC tumors demonstrated significantly higher aspartic acid, citicoline, glutamic acid, oxidized glutathione, succinyladenosine, and uridine diphosphate-N-acetylglucosamine levels, but significantly lower butyrylcarnitine, glutathione hydroxyhexanoycarnitine, inosinic acid, isovalerylcarnitine, and threonine levels (all P < 0.05). CIN tumors contained significantly higher phosphocholine and uridine 5’-monophosphate levels but significantly lower beta-citryl-L-glutamic acid levels than did non-CIN tumors (all P < 0.05). CIN GC tumors demonstrated additional altered pathways involving alanine, aspartate, and glutamate metabolism, glyoxylate and dicarboxylate metabolism, histidine metabolism, and phenylalanine, tyrosine, and tryptophan biosynthesis.

CONCLUSION

Metabolomic profiles of GC tumors and the adjacent healthy tissue are distinct, and the CIN status is associated with downstream metabolic alterations in GC.

A systematic review on metabolomics-based diagnostic biomarker discovery and validation in pancreatic cancer

INTRODUCTION

Metabolomics is an emerging approach for early detection of cancer. Along with the development of metabolomics, high-throughput technologies and statistical learning, the integration of multiple biomarkers has significantly improved clinical diagnosis and management for patients.

OBJECTIVES

In this study, we conducted a systematic review to examine recent advancements in the oncometabolomics-based diagnostic biomarker discovery and validation in pancreatic cancer.

METHODS

PubMed, Scopus, and Web of Science were searched for relevant studies published before September 2017. We examined the study designs, the metabolomics approaches, and the reporting methodological quality following PRISMA statement. RESULTS AND CONCLUSION: The included 25 studies primarily focused on the identification rather than the validation of predictive capacity of potential biomarkers. The sample size ranged from 10 to 8760. External validation of the biomarker panels was observed in nine studies. The diagnostic area under the curve ranged from 0.68 to 1.00 (sensitivity: 0.43-1.00, specificity: 0.73-1.00). The effects of patients' bio-parameters on metabolome alterations in a context-dependent manner have not been thoroughly elucidated. The most reported candidates were glutamic acid and histidine in seven studies, and glutamine and isoleucine in five studies, leading to the predominant enrichment of amino acid-related pathways. Notably, 46 metabolites were estimated in at least two studies. Specific challenges and potential pitfalls to provide better insights into future research directions were thoroughly discussed. Our investigation suggests that metabolomics is a robust approach that will improve the diagnostic assessment of pancreatic cancer. Further studies are warranted to validate their validity in multi-clinical settings.

Induction of Thioredoxin-Interacting Protein by a Histone Deacetylase Inhibitor, Entinostat, Is Associated with DNA Damage and Apoptosis in Esophageal Adenocarcinoma

In 2017, an estimated 17,000 individuals were diagnosed with esophageal adenocarcinoma (EAC), and less than 20% will survive 5 years. Positron emission tomography avidity is indicative of high glucose utilization and is nearly universal in EAC. TXNIP blocks glucose uptake and exhibits proapoptotic functions. Higher expression in EAC has been associated with improved disease-specific survival, lack of lymph node involvement, reduced perineural invasion, and increased tumor differentiation. We hypothesized that TXNIP may act as a tumor suppressor that sensitizes EAC cells to standard chemotherapeutics. EAC cell lines and a Barrett epithelial cell line were used. qRT-PCR, immunoblot, and immunofluorescence techniques evaluated gene expression. TXNIP was stably overexpressed or knocked down using lentiviral RNA transduction techniques. Murine xenograft methods examined growth following overexpression of TXNIP. Apoptosis and DNA damage were measured by annexin V and γH2AX assays. Activation of the intrinsic apoptosis was quantitated with green fluorescence protein-caspase 3 reporter assay. In cultured cells and an esophageal tissue array, TXNIP expression was higher in Barrett epithelia and normal tissue compared with EAC. Constitutive overexpression of TXNIP decreased proliferation, clonogenicity, and tumor xenograft growth. TXNIP overexpression increased, whereas knockdown abrogated, DNA damage and apoptosis following cisplatin treatment. An HDAC inhibitor, entinostat (currently in clinical trials), upregulated TXNIP and synergistically increased cisplatin-mediated DNA damage and apoptosis. TXNIP is a tumor suppressor that is downregulated in EACC. Its reexpression dramatically sensitizes these cells to cisplatin. Our findings support phase I/II evaluation of "priming" strategies to enhance the efficacy of conventional chemotherapeutics in EAC. Mol Cancer Ther; 17(9); 2013-23. ©2018 AACR.

MiR-422a regulates cellular metabolism and malignancy by targeting pyruvate dehydrogenase kinase 2 in gastric cancer

Increasing evidence indicates that dysregulation of microRNAs (miRNAs) plays a crucial role in human malignancies. Here, we showed that microRNA-422a (miR-422a) expression was dramatically downregulated in gastric cancer (GC) samples and cell lines compared with normal controls, and that its expression level was inversely related to tumor size and depth of infiltration. Functional studies revealed that the overexpression of miR-422a in GC tumor cells suppressed cell proliferation and migration, and drove a metabolic shift from aerobic glycolysis to oxidative phosphorylation. Mechanistic analysis suggested that miR-422a repressed pyruvate dehydrogenase kinase 2 (PDK2) to restore activity of the pyruvate dehydrogenase (PDH), the gatekeeping enzyme that catalyzes the decarboxylation of pyruvate to produce acetyl-CoA. Importantly, we further demonstrated that the mir-422a–PDK2 axis also influenced another metabolic pathway, de novo lipogenesis in cancer cells, and that it subsequently affected reactive oxygen species (ROS) and RB phosphorylation levels, ultimately resulting in cell cycle arrest in G1 phase. Our findings show that the miR-422a–PDK2 axis is an important mediator in metabolic reprogramming and a promising therapeutic target for antitumor treatment.

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

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

LINC00152/miR-139-5p regulates gastric cancer cell aerobic glycolysis by targeting PRKAA1

Gastric cancer is one of the most common cancers in the world and glycolysis is a major feature of gastric cancer. MicroRNAs (miRNAs) involve in gastric cancer cell proliferation, glycolysis and other cellular processes. MiR-139-5p is reported as a tumor suppressor in cancers, however, the role of miR-139-5p including glycolytic metabolism is unclear in gastric cancer. So, the purpose of the present study is to elucidate the underlying mechanism in gastric cancer metabolism mediated by miR-139-5p. Our results revealed that miR-139-5p inhibited glycolysis by regulating AMP-activated, alpha 1 catalytic subunit (PRKAA1) expression in gastric cancer cells. We also found that miR-139-5p was down-regulated by long intergenic non-coding RNA 152 (LINC00152) in gastric cancer cells. Our results indicate that LINC00152/miR-139-5p facilitates gastric cancer cell glycolysis by regulating PRKAA1 expression.

Metabolomic findings in sepsis as a damage of host-microbial metabolism integration

Metabolomics globally evaluates the totality of the endogenous metabolites in patient's body, at the same time reflecting gene function, enzyme activity and degree of organ dysfunction in sepsis. The authors performed the analysis of the main chemical classes of low molecular weight compounds (amino acids, polyols, fatty acids, hydroxy acids, amines, nucleotides and their derivatives) that quantitatively distinguish patients with sepsis from healthy ones. The following keywords were used to find papers published in the Scopus and Web of Science databases from 2008 to 2015: (marker OR biomarker) AND (sepsis OR critical ill OR pneumonia OR hypoxia). Key words for the search were the following: metabolomics, metabolic profiling, sepsis, metabolism, biomarkers, critically ill patients, multiple organ failure. Several metabolomic findings in sepsis are still waiting for an explanation. When assessing metabolomic analysis results in patients with sepsis we should take into account the intervention of microbial metabolism. Among the low molecular weight compounds detected in septic patient blood, a special attention should be paid to the molecules which could be attributed to "common metabolites" of man and bacteria. The genomic region overlap and the production of enzymes which are similar in function and final products could be a possible reason for this phenomenon. For example, microbial biodegradation products of aromatic compounds are increased many times in blood of patients with sepsis. On the one hand, it shows a high metabolic activity of the bacteria. On the other hand, these molecules are intermediates in the metabolism of aromatic amino acids such as tyrosine and phenylalanine in human body. It is important that there are many clinical studies, which confirmed the diagnostic and prognostic significance of series of aromatic metabolites, including those with intrinsic biological activity. We can't exclude the presence of signaling pathways, cell receptors, transmembrane transporters and others which are common for a human and bacteria and their direct participation in mechanisms of organ dysfunction and hypotension in sepsis. Thus, today, we should not limit ourselves studying eukaryotic cells while searching for new molecular mechanisms of sepsis-associated organ failure and septic shock. We should take into account and simulate in the experiments the changes of a human internal environment, which occur during the radical microbiome "restructuring" in critically ill patients. This approach opens up new prospects for an objective monitoring of diseases, carrying out an assessment of the integral metabolic profile in a given time on common metabolites (particularly aromatic), and in future will provide new targets for therapeutic effects.

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

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