Abstract 151P
Background
Metabolic rearrangement has been shown to be an important characteristic for stomach adenocarcinomas. Here we aimed to improve our understanding of the tumorigenesis of gastric cancer by means of gene and protein expression profile analysis with a focus on metabolic genes and pathways.
Methods
Array-based gene expression profiling of fresh frozen cancer tissues and adjacent normal tissues were obtained from 8 patients with gastric cancer at early stage by using Affymetrix oligonucleotide microarray. Assays targeted 179 unique genes related to cancer metabolism. The raw expression data were normalized using nSolver Analysis Software 3.0 and a dataset of gene expression ratios for GC vs. controls was generated. The p values were calculated using a paired t-test, and the threshold for up- and down-regulated genes was set at p value < 0.05. The protein expression of the dysregualted genes were detected by immunohistochemistry (IHC) in the formalin fixed paraffin embedded tissue blocks. The signal was quantified by the Allred score system which represented the estimated intensity and proportion of positive-staining cells.
Results
Our microarray results showed increased expression of 20 metabolic genes and decreased expression of 6 metabolic genes in all cases of gastric cancer at early stage. Besides of the undetected NOX4, the protein levels of all the others dysregualted genes, detected by IHC, showed consistently results. Half of all dysregulated genes (AKT2, EGLN3, G6PD, GLS, HIF1A, HK2, HRAS, MAP2K1, NTRK3, PGK1, PLCG1, RET and RPS6KB1) are implicated in Carbon Metabolism, a pivotal metabolic approach involving in nucleic acid biosynthesis. Five genes (ARNT, EGLN1, EGLN3, HIF1A and NOX4) are molecules implicated in hypoxia signaling. Besides, the upregulated HIF1A is a cancer metabolism driver, which means that HIF1A may induce the oncogenesis of gastric cancer.
Conclusions
The gastric mucosa in gastric cancer at early stage is characterized by dysregulated expression of a limited repertoire of metabolic genes. The nature of the corresponding metabolic rearrangement and pathways may help guide further investigations into its etiology.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Fudan University Shanghai Cancer Center.
Funding
National Human Genetic Resources Sharing Service Platform (2005DKA21300), National Natural Science Foundation of China (81602078),.
Disclosure
All authors have declared no conflicts of interest.
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