Effect of Helicobacter Pylori on Plasma Metabolic Phenotype in Patients With Gastric Cancer

• Published in: Cancer control Vol. 28; p. 10732748211041881
• Main Authors: Wang, Yan-Ping, Wei, Ting, Ma, Xiao, Zhu, Xiao-Liang, Ren, Long-Fei, Zhang, Lei, Ding, Fang-Hui, Li, Xun, Wang, Hai-Ping, Bai, Zhong-Tian, Zhu, Ke-Xiang, Miao, Long, Yan, Jun, Zhou, Wen-Ce, Meng, Wen-Bo, Liu, Yu-Qin
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 2021; Sage Publications Ltd; SAGE Publishing
• Subjects: Amino acids; Biomarkers; Biomarkers, Tumor; Diagnosis, Differential; Gastric cancer; Gastritis; Gastritis - diagnosis; Gastritis - pathology; Genotype & phenotype; Helicobacter pylori - isolation & purification; Humans; Lipid metabolism; Metabolism; Metabolites; Metabolomics; Metabolomics - methods; Neoplasm Staging; Neopterin; Neopterin - blood; Original; Phenotype; Phenotypes; Principal Component Analysis; Risk factors; Statistical analysis; Stomach Neoplasms - diagnosis; Stomach Neoplasms - pathology; Helicobacter pylori; gastric cancer; metabolomics; biomarkers
• ISSN: 1073-2748; 1526-2359; 1526-2359; 1073-2748
• DOI: 10.1177/10732748211041881

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.