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Background Although Helicobacter pylori (Hp) as high risk factor for gastric cancer have been investigated from human trial, present data is inadequate to explain the effect of Hp on the changes of metabolic phenotype of gastric cancer in different stages. Purpose Herein, plasma of human superficial gastritis (Hp negative and positive), early gastric cancer and advanced gastric cancer analyzed by UPLC-HDMS metabolomics can not only reveal metabolic phenotype changes in patients with gastric cancer of different degrees (30 Hp negative, 30 Hp positive, 20 early gastric cancer patients, and 10 advanced gastric cancer patients), but also auxiliarily diagnose gastric cancer. Results Combined with multivariate statistical analysis, the results represented biomarkers different from Hp negative, Hp positive, and the alterations of metabolic phenotype of gastric cancer patients. Forty-three metabolites are involved in amino acid metabolism, and lipid and fatty acid metabolism pathways in the process of cancer occurrence, especially 2 biomarkers glycerophosphocholine and neopterin, were screened in this study. Neopterin was consistently increased with gastric cancer progression and glycerophosphocholine tended to consistently decrease from Hp negative to advanced gastric cancer. Conclusion This method could be used for the development of rapid targeted methods for biomarker identification and a potential diagnosis of gastric cancer.

N-trans-Feruloyloctopamine (FO), a natural compound, was reported in our previous study to inhibit a tumor cell malignant phenotype by AKT- and EMT-related signals and might be used as a promising drug for HCC treatment. However, the specific targets and detailed mechanisms still need to be clarified. Screening with RNA-Seq in Huh7 cells treated with FO revealed that 317 genes were modulated, of which 188 genes were upregulated and 129 genes were downregulated. Real-time cell analyzer and flow cytometry data reveal that tumor cell proliferation and apoptosis were impacted by FO. DAVID bioinformatic data showed that most of the biological process GO terms are related to proliferation and apoptosis. KEGG enrichment analysis showed that FO mainly regulates PI3K-AKT- and apoptosis-related signals, in which BBC3, DDIT3, NOXA, and CDKN1A on the surface serve as the novel targets of FO inducing HCC cell apoptosis. The result implied that FO might exacerbate HCC cell apoptosis by regulating BBC3, DDIT3, CDKN1A, and NOXA signals. The obstacle effect of FO can provide new targets and new credibility for the treatment of liver cancer.