Metabolomic profiling on plasma reveals potential biomarkers for screening and early diagnosis of intestinal-type gastric cancer and precancerous stages

Background: Gastric cancer (GC) with majority of intestinal-type adenocaricinoma remains one of the most common cancers all over the world. GC faces a great challenge in the clinical diagnosis, that it often can be detected at advanced stages, and leads to the loss of optimum time for treatment and poor prognosis. Thus, there is a critical need to develop effective and noninvasive strategies for early diagnosis of the disease process. Methods: Totally, 82 participants were enrolled in the study, including 50 chronic superficial gastritis (CSG) patients, 7 intestinal-type early gastric cancer (EGC) and 25 intestinal-type advanced gastric cancer (AGC) ones. Metabolites profiling on patient plasma was performed using ultra-high performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF/MS). Principal components analysis, orthogonal partial least squares-discriminant analysis as well as Random Forest were utilized to evaluate the variation on endogenous metabolites for intestinal-type GC patients and to screen potential biomarkers. Furthermore, the proposed biomarkers were used to create logistic regression models, which discrimination efficiency and accuracy was ascertained by receiver operating characteristic curve (ROC) analysis. Metabolic pathway analysis was carried out on MetaboAnalyst.Results: Totally 50 metabolites were detected with differentially expression among CSG, intestinal-type EGC and AGC patients. L-carnitine, L-proline, pyruvaldehyde, phosphatidylcholines (PC) (14:0/18:0), lysophosphatidylcholine (14:0) (LysoPC 14:0), lysinoalanine were defined as the potential biomarker panel for the diagnosis among CSG and EGC patients. Compared with EGC patients, 6 significantly changed metabolites, PC(O-18:0/0:0) and LysoPC(20:4(5Z,8Z,11Z,14Z)) were found to be up-regulated in AGC patients, whereas L-proline, L-valine, adrenic acid and pyruvaldehyde down-regulated. ROC analysis demonstrated a high diagnostic performance for metabolite panels with area under the curve (AUC) of 0.931 to 1. Moreover, the metabolomic pathway analysis revealed several metabolism pathway disorders, including amino acid and lipid metabolisms, in intestinal-type GC patients.Conclusions: In this study, a total of six metabolites were identified to contribute significantly to the diagnosis of intestinal-type GC and precancerous stages, respectively, and over 93.1% AUC value was achieved in AUC test on biomarker panels. It indicated that the biomarker panels are sensitive to the early diagnosis of intestinal-type GC disease, which is expected to be developed as a promising diagnostic and prognostic tool for disease stratification studies.