Tissue-based metabolomics profiling reveals metabolic signatures and major metabolic pathways of gastric cancer

Abstract Purpose This study was aimed to screen differential metabolites between gastric cancer (GC) and paracancerous (PC) tissues and find new biomarkers of GC. Methods GC (n = 28) and matched PC (n = 28) tissues were collected and LC-MS/MS analyses were performed to detect metabolites of GC and PC tissues in positive and negative models. Principal component analysis (PCA) and orthogonal projections to latent structures-discriminate analysis (OPLS-DA) were conducted to describe distribution of origin data and general separation and estimate the robustness and the predictive ability of our mode. Differential metabolites were screened based on criterion of variables with p value < 0.05 and VIP (variable importance in the projection) > 1.0. Receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic power of differential metabolites. Kyoto Encyclopedia of Genes and Genomes (KEGG) was performed to search for metabolite pathways and MetaboAnalyst was used for pathway enrichment analysis. Results Several metabolites were significantly changed in GC group compared with PC group. Thirteen metabolites with high VIP were chose and among which 1-methylnicotinamide, dodecanoic acid and sphinganine possessed high AUC values (AUC > 0.8) indicating an excellent discriminatory ability on GC. Pathways such as pentose phosphate pathway and histidine metabolism were focused based on differential metabolites demonstrating their effects on progress of GC. Conclusions In conclusion, we investigated the tissue-based metabolomics profile of GC and several differential metabolites and signaling pathways were focused. Further study is needed to verify those results.