Dataset Information

Metabolic Perturbation and Potential Markers in Patients with Esophageal Cancer.

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

SUBMITTER: Zhu X

PROVIDER: S-EPMC5415862 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Metabolic Perturbation and Potential Markers in Patients with Esophageal Cancer.

Zhu Xianlan X Wang Kun K Liu Gaoshuang G Wang Yuqing Y Xu Jin J Liu Linsheng L Li Mengjie M Shi Jian J Aa Jiye J Yu Lianzhen L

Gastroenterology research and practice 20170420

Clinical diagnosis of esophageal cancer (EC) at early stage is rather difficult. This study aimed to profile the molecules in serum and tissue and identify potential biomarkers in patients with EC. A total of 64 volunteers were recruited, and 83 samples (24 EC serum samples, 21 serum controls, 19 paired EC tissues, and corresponding tumor-adjacent tissues) were analyzed. The gas chromatography time-of-flight mass spectrometry (GC/TOF-MS) was employed, and principal component analysis was used to ...[more]

PMID: 28512469

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Project description:BackgroundEsophageal cancer has the sixth highest rate of cancer-associated deaths worldwide, with many patients displaying metastases and chemotherapy resistance. We sought to find subtypes to see if precision medicine could play a role in finding new potential targets and predicting responses to therapy. Since metabolism not only drives cancers but also serves as a readout, metabolism was examined as a key reporter for differences.MethodsUnsupervised and supervised classification methods, including hierarchical clustering, partial least squares discriminant analysis, k-nearest neighbors, and machine learning techniques, were used to discover and display two major subgroups. Genes, pathways, gene ontologies, survival, and immune differences between the groups were further examined, along with biomarkers between the groups and against normal tissue.ResultsEsophageal cancer had two major unique metabolic profiles observed between the histological subtypes esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). The metabolic differences suggest that ESCC depends on glycolysis, whereas EAC relies more on oxidative metabolism, catabolism of glycolipids, the tricarboxylic acid (TCA) cycle, and the electron transport chain. We also noted a robust prognostic risk associated with COQ3 expression. In addition to the metabolic alterations, we noted significant alterations in key pathways regulating immunity, including alterations in cytokines and predicted immune infiltration. ESCC appears to have increased signature associated with dendritic cells, Th17, and CD8 T cells, the latter of which correlate with survival in ESCC. We bioinformatically observed that ESCC may be more responsive to checkpoint inhibitor therapy than EAC and postulate targets to enhance therapy further. Lastly, we highlight correlations between differentially expressed enzymes and the potential immune status.ConclusionOverall, these results highlight the extreme differences observed between the histological subtypes and may lead to novel biomarkers, therapeutic strategies, and differences in therapeutic response for targeting each esophageal cancer subtype.

Project description:Background & aimsWe aimed to identify new serum biomarkers of esophageal adenocarcinoma (EAC).MethodsWe performed metabolomic analyses of serum samples from 2 sets of case-control pairs in the discovery phase, each consisting of 30 patients with histologically confirmed EAC (cases) from the University of Texas MD Anderson Cancer Center and 30 matched subjects without EAC (controls). We identified metabolites whose levels differed significantly between cases and controls and validated those with the greatest difference in an analysis of 321 EAC cases and 331 controls. We generated a metabolite risk score (MRS) for the metabolites.ResultsThe levels of 64 metabolites differed significantly between EAC cases and controls in the discovery phase. The metabolites with the greatest difference were amino acid L-proline (LP), ketone body 3-hydroxybutyrate (BHBA), and carbohydrate D-mannose (DM); these differences were confirmed in the validation set. Cases had lower mean levels of LP than controls (22.78 ± 6.79 μg/mL vs 28.24 ± 8.64 μg/mL; P < .001) and higher levels of BHBA (18.06 ± 17.84 μg/mL vs 7.73 ± 9.92 μg/mL; P < .001) and DM (9.87 ± 4.28 μg/mL vs 6.28 ± 3.61 μg/mL; P < .001). Levels of DM were significantly higher in patients with late-stage EAC than early-stage EAC (10.61 ± 4.79 μg/mL vs 8.97 ± 3.36 μg/mL; P = .005). Higher levels of LP were associated with significant decrease in risk of EAC (odds ratio [OR], 0.26; 95% confidence interval [CI], 0.18-0.38). A significant increase in risk of EAC was associated with higher levels of BHBA (OR, 4.05; 95% CI, 2.84-5.78) and DM (OR, 7.04; 95% CI, 4.79-10.34). Levels of all 3 metabolites associated with EAC risk in a dose response manner; the level of risk conferred by the metabolites increased jointly with smoking status and body mass index. Individuals with high MRS had significant (7.76-fold) increase in risk of EAC vs those with low MRS. Smokers with high MRS had the greatest risk of EAC (OR, 23.40; 95% CI, 10.95-50.00), compared with never smokers with low MRS.ConclusionsOn the basis of a case vs control metabolic profile analysis, levels of LP, BHBA, and DM are associated with risk of EAC. These markers might be used as risk and prognostic factors for patients with EAC.

Project description:ObjectiveTo identify the prognostic indicators of esophageal adenocarcinoma (EAC) for future EAC diagnosis and treatment.MethodsThe EAC dataset from The Cancer Genome Atlas was screened for differentially expressed microRNAs (miRNAs) and mRNAs associated with EAC. Weighted gene coexpression network analysis was performed to cluster miRNAs or mRNA with similar expression patterns to identify the miRNAs or mRNA that are highly associated with EAC. Prognostic miRNAs for overall survival (OS) were identified using Cox proportional-hazards regression analysis and least absolute shrinkage and selection operator based on survival duration and status. Two types of miRNAs were selected to develop a prognostic signature model for EAC using multiple Cox regression analysis. Furthermore, the signature was validated using internal validation sets 1 and 2. The receiver operating characteristic curve and concordance index were used to evaluate the accuracy of the signature and validation sets. The expression of miR-421, miR-550a-3p, and miR-550a-5p was assessed using quantitative polymerase chain reaction (qPCR). The proliferation, invasion, and migration of EAC cells were assessed using CCK8 and transwell assays. The OS of target mRNAs was assessed using Kaplan-Meier analysis. Functional enrichment analysis of the target mRNAs was performed using Metascape.ResultsThe prognostic signature and validation sets comprising mir-421 and mir-550a-1 had favorable predictive power in OS. Compared with the patients with EAC in the high-expression group, those assigned to the low-expression group displayed increased OS according to survival analysis. Differential and qPCR analysis showed that miR-421, miR-550a-3p, and miR-550a-5p were highly expressed in the EAC tissues and cell lines. Moreover, the downregulation of miR-421 and miR-550a-3p with inhibitor markedly suppressed the proliferation, invasion, and migration in OE33 cells compared with the negative control. A total of 20 target mRNAs of three miRNAs were predicted, among which seven target mRNAs-ASAP3, BCL2L2, LMF1, PPM1L, PTPN21, SLC18A2, and NR3C2-had prognostic value; PRKACB, PDCD4, RPS6KA5, and BCL2L2 were enriched in the miRNA cancer pathway.ConclusionPrognostic indicators of EAC may be useful in future EAC diagnosis and treatment.

Project description:Perturbed host metabolism is increasingly recognized as a pillar of sepsis pathogenesis, yet the dynamic alterations in metabolism and its relationship to other components of the host response remain incompletely understood. We sought to identify the early host-metabolic response in patients with septic shock and to explore biophysiological phenotyping and differences in clinical outcomes among metabolic subgroups.DesignWe measured serum metabolites and proteins reflective of the host-immune and endothelial response in patients with septic shock.SettingWe considered patients from the placebo arm of a completed phase II, randomized controlled trial conducted at 16 U.S. medical centers. Serum was collected at baseline (within 24 hr of the identification of septic shock), 24-hour, and 48-hour postenrollment. Linear mixed models were built to assess the early trajectory of protein analytes and metabolites stratified by 28-day mortality status. Unsupervised clustering of baseline metabolomics data was conducted to identify subgroups of patients.PatientsPatients with vasopressor-dependent septic shock and moderate organ dysfunction that were enrolled in the placebo arm of a clinical trial.InterventionsNone.Measurements and main resultsFifty-one metabolites and 10 protein analytes were measured longitudinally in 72 patients with septic shock. In the 30 patients (41.7%) who died prior to 28 days, systemic concentrations of acylcarnitines and interleukin (IL)-8 were elevated at baseline and persisted at T24 and T48 throughout early resuscitation. Concentrations of pyruvate, IL-6, tumor necrosis factor-α, and angiopoietin-2 decreased at a slower rate in patients who died. Two groups emerged from clustering of baseline metabolites. Group 1 was characterized by higher levels of acylcarnitines, greater organ dysfunction at baseline and postresuscitation (p < 0.05), and greater mortality over 1 year (p < 0.001).ConclusionsAmong patients with septic shock, nonsurvivors exhibited a more profound and persistent dysregulation in protein analytes attributable to neutrophil activation and disruption of mitochondrial-related metabolism than survivors.

Dataset Information

Metabolic Perturbation and Potential Markers in Patients with Esophageal Cancer.

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Metabolic Perturbation and Potential Markers in Patients with Esophageal Cancer.

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