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Metabolomic analysis reveals altered metabolic pathways in a rat model of gastric carcinogenesis.

ABSTRACT: Gastric cancer (GC) is one of the most malignant tumors with a poor prognosis. Alterations in metabolic pathways are inextricably linked to GC progression. However, the underlying molecular mechanisms remain elusive. We performed NMR-based metabolomic analysis of sera derived from a rat model of gastric carcinogenesis, revealed significantly altered metabolic pathways correlated with the progression of gastric carcinogenesis. Rats were histologically classified into four pathological groups (gastritis, GS; low-grade gastric dysplasia, LGD; high-grade gastric dysplasia, HGD; GC) and the normal control group (CON). The metabolic profiles of the five groups were clearly distinguished from each other. Furthermore, significant inter-metabolite correlations were extracted and used to reconstruct perturbed metabolic networks associated with the four pathological stages compared with the normal stage. Then, significantly altered metabolic pathways were identified by pathway analysis. Our results showed that oxidative stress-related metabolic pathways, choline phosphorylation and fatty acid degradation were continually disturbed during gastric carcinogenesis. Moreover, amino acid metabolism was perturbed dramatically in gastric dysplasia and GC. The GC stage showed more changed metabolite levels and more altered metabolic pathways. Two activated pathways (glycolysis; glycine, serine and threonine metabolism) substantially contributed to the metabolic alterations in GC. These results lay the basis for addressing the molecular mechanisms underlying gastric carcinogenesis and extend our understanding of GC progression.

SUBMITTER: Gu J

PROVIDER: S-EPMC5312368 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Metabolomic analysis reveals altered metabolic pathways in a rat model of gastric carcinogenesis.

Gu Jinping J Hu Xiaomin X Shao Wei W Ji Tianhai T Yang Wensheng W Zhuo Huiqin H Jin Zeyu Z Huang Huiying H Chen Jiacheng J Huang Caihua C Lin Donghai D

Oncotarget 20160901 37

Gastric cancer (GC) is one of the most malignant tumors with a poor prognosis. Alterations in metabolic pathways are inextricably linked to GC progression. However, the underlying molecular mechanisms remain elusive. We performed NMR-based metabolomic analysis of sera derived from a rat model of gastric carcinogenesis, revealed significantly altered metabolic pathways correlated with the progression of gastric carcinogenesis. Rats were histologically classified into four pathological groups (gas ...[more]

PMID: 27527852

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Project description:Gastric Carcinoma is one of the most common cancers in the world. A large number of differentially expressed genes have been identified as being associated with gastric cancer progression, however, little is known about the underlying regulatory mechanisms. To address this problem, we developed a differential networking approach that is characterized by including a nascent methodology, differential coexpression analysis (DCEA), and two novel quantitative methods for differential regulation analysis. We first applied DCEA to a gene expression dataset of gastric normal mucosa, adenoma and carcinoma samples to identify gene interconnection changes during cancer progression, based on which we inferred normal, adenoma, and carcinoma-specific gene regulation networks by using linear regression model. It was observed that cancer genes and drug targets were enriched in each network. To investigate the dynamic changes of gene regulation during carcinogenesis, we then designed two quantitative methods to prioritize differentially regulated genes (DRGs) and gene pairs or links (DRLs) between adjacent stages. It was found that known cancer genes and drug targets are significantly higher ranked. The top 4% normal vs. adenoma DRGs (36 genes) and top 6% adenoma vs. carcinoma DRGs (56 genes) proved to be worthy of further investigation to explore their association with gastric cancer. Out of the 16 DRGs involved in two top-10 DRG lists of normal vs. adenoma and adenoma vs. carcinoma comparisons, 15 have been reported to be gastric cancer or cancer related. Based on our inferred differential networking information and known signaling pathways, we generated testable hypotheses on the roles of GATA6, ESRRG and their signaling pathways in gastric carcinogenesis. Compared with established approaches which build genome-scale GRNs, or sub-networks around differentially expressed genes, the present one proved to be better at enriching cancer genes and drug targets, and prioritizing disease-related genes on the dataset we considered. We propose this extendable differential networking framework as a promising way to gain insights into gene regulatory mechanisms underlying cancer progression and other phenotypic changes.

Project description:BackgroundNitrogen (N) fertilizer is commonly considered as one of the most important limiting factors in the agricultural production. As a result, a large amount of N fertilizer is used to improve the yield in modern tea production. Unfortunately, the large amount of N fertilizer input has led to increased plant nitrogen-tolerance and decreased amplitude of yield improvement, which results in significant N loss, energy waste and environment pollution. However, the effects of N-deficiency on the metabolic profiles of tea leaves and roots are not well understood.ResultsIn this study, seedlings of Camellia sinensis (L.) O. Kuntze Chunlv 2 were treated with 3 mM NH4NO3 (Control) or without NH4NO3 (N-deficiency) for 4 months by sandy culture. The results suggested that N-deficiency induced tea leaf chlorosis, impaired biomass accumulation, decreased the leaf chlorophyll content and N absorption when they were compared to the Control samples. The untargeted metabolomics based on GC-TOF/MS approach revealed a discrimination of the metabolic profiles between N-deficient tea leaves and roots. The identification and classification of the altered metabolites indicated that N deficiency upregulated the relative abundances of most phenylpropanoids and organic acids, while downregulated the relative abundances of most amino acids in tea leaves. Differentially, N-deficiency induced the accumulation of most carbohydrates, organic acids and amino acids in tea roots. The potential biomarkers screened in N-deficient leaves compared to Control implied that N deficiency might reduce the tea quality. Unlike the N-deficient leaves, the potential biomarkers in N-deficient roots indicated an improved stress response might occur in tea roots.ConclusionsThe results demonstrated N deficiency had different effects on the primary and secondary metabolism in tea leaves and roots. The findings of this study will facilitate a comprehensive understanding of the N-deficient tea plants and provide a valuable reference for the optimized N nutrient management and the sustainable development in the tea plantations.

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Metabolomic analysis reveals altered metabolic pathways in a rat model of gastric carcinogenesis.

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Metabolomic analysis reveals altered metabolic pathways in a rat model of gastric carcinogenesis.

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