| Background:According to the latest report of the World Health Organization,Gastric cancer is one of the world's most common fatal tumors.With respect to worldwide cancer disease incidence and death,the morbidity of gastric cancer ranks number five and mortality ranks number three,which is second only to lung cancer and liver cancer.However,the pathogenesis of gastric cancer is not fully understood as yet,and the early diagnose of gastric cancer is very difficult,which brings serious psychological and physiological effects on patients,it is imperative to further study its pathogenesis and explore biomarkers for early diagnosis.Metabolomics(or metabonomics)is a hot topic of medical research in recent years.Metabolomics mainly studies all metabolites in biological systems with advanced analysis technology,reflects the complex,dynamic changes of these metabolites,as well as reveals the physiology and pathology of research subjects.Metabolomics has become an important tool in studying pathogenesis of disease and discovering biomarkers of early diagnose.Objective:In this research,a comprehensive metabolomics analysis on gastric cancer tissue and paracancerous tissue in gastric cancer patients was carried out based on the platform of ultrahigh performance liquid chromatography coupled to a high-resolution Orbitrap mass spectrometer(UHPLC-Q Exactive),which aimed at discovering characteristic metabolites for early diagnose of gastric cancer as well as exploring the pathogenesis and therapeutic target of gastric cancer.Methods:1 Sample preparation: In order to get polar and nonpolar metabolites,a two-step extraction process was used here which extracted tissue samples into aqueous and organic phases.And after high speed centrifugation,the supernatant was collected for further analysis.2 LC-MS analysis: Gastric cancer tissue samples and paracancerous tissue samples were analyzed with ultrahigh performance liquid chromatography coupled to a high-resolution Orbitrap mass spectrometer(UHPLC-Q Exactive),then we got the metabolic patterns and raw data files of gastric cancer tissue samples as well as paracancerous tissue samples.3 Data analysis: The raw data files were imported into Xcalibur 2.1 for pre-processing,and the missing values in obtained data were removed according to the “80% rule”.SIMCA-P 13.0 was used for pattern recognition analysis,and then we further studied the differences of metabolic profiles as well as selected and identified metabolites with significant differences between gastric cancer tissue samples and paracancerous tissue samples.Furthermore,the ROC curve analysis was adopted to evaluate the clinical diagnostic performance of these selected different metabolites,and the pathway analysis of metabolites with significant difference was processed via the MetaboAnalyst database.Results:1 In this study,the OPLS-DA models of gastric cancer tissue samplesparacancerous tissue samples in ESI+ and ESI-were successfully fabricated,and in each OPLS-DA model,a significant distinction was displayed between metabolic profiles of gastric cancer tissue samples and paracancerous tissue samples.2 In polar components of gastric cancer tissue samples and paracancerous tissue samples,16 metabolites with significant differences were identified,meanwhile 13 metabolites were identified in the nonpolar components.Compared with paracancerous tissues,content levels of 18 metabolites were significantly elevated:3-Methoxytyramine,N-Acetyl-L-aspartate,N-Methylputrescine,(z)-3-Peroxyaminoacrylate,Azelaic acid,Sebacic acid,Suberic acid,1,11-Undecanedicarboxylic acid,4-Hydroxy-L-threonine,Phenylacetaldehyde,N-Acetylputrescine,L-Aspartate,E-thaolamine phosphate,L-Glutamate,(R)-Mevalonate,D-Cathinone,6-Deoxy-L-galactose and 6-Pyruvoyltetrahydropterin.While content levels of 11 metabolites were significantly decreased: Niacinamide,Butyryl-L-Carnitine,2-Methylbututylcarnitine,Phosphocholine,Spermidine,Glycerophosphocholine,Adenosine 3'-monophosphat,Guanosine 3'-phosphate,2-Aminomuconate,4-Guanidinobutanamide and Cyclohexane-1,2-dione.3 Through the ROC curve analysis,13 metabolites with significant difference were found with moderate and above diagnostic value: Butyryl-L-Carnitine,2-Methylbututylcarnitine,Phosphocholine,Adenosine 3'-monophosphat,Guanosine3'-phosphate,N-Methylputrescine,(z)-3-Peroxyaminoacrylate,Sebacic acid,Suberic acid,1,11-Undecanedicarboxylic acid,4-Hydroxy-L-threonine,Phenylacetaldehyde and 6-Pyruvoyltetrahydropterin.4 The pathway analysis showed that 10 metabolic pathways were mainly involved by the differential metabolites between gastric cancer tissue samples and paracancerous tissue samples: Arginine and proline metabolism,Alanine,aspartate and glutamate metabolism,beta-Alanine metabolism,D-Glutamine and D-glutamate metabolism,Glycerophospholipid metabolism,Purine metabolism,Histidine metabolism,Nicotinate and nicotinamide metabolism,Glutathione metabolism and Aminoacyl-tRNA biosynthesis.Conclusion:Metabolomics approach based on the platform of ultrahigh performance liquid chromatography coupled to a high-resolution Orbitrap mass spectrometer(UHPLC-Q Exactive)revealed the detail information of metabolic profiles of gastric cancer tissue samples and paracancerous tissue samples,29 metabolites with significant difference were screened and identified,and 13 metabolites among these compounds were with moderate and above diagnostic value.At the same time,compared with paracancerous tissues,gastric cancer tissues exist metabolic disorders such as amino acid metabolism,glycerophospholipid metabolism,purine metabolism,nicotine and nicotinamide metabolism as well as aminoacyl-tRNA biosynthesis,which might be closely related to the occurrence and development of gastric cancer.These results might be useful to insight into the pathogenesis of gastric cancer and improve the early diagnose of gastric cancer. |
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