Exploring The Potential Biomarkers For Diagnosis And Classification Of Lung Cancer By Non-Targeting And Targeted Metabonomics

Objective:Lung cancer is one of the leading lethal cancers in the world.Early diagnosis of it may improve its survival rate.Novel diagnostic metabolic markers would be explored by tissue metabonomics.In the dissertation,the metabolites in tissue differentiating lung cancer tissues from paracancerous tissues were firstly identified by ~1H NMR based metabonomics.For the purpose of early diagnosis,the serum samples of lung cancer patients and healthy groups were further analyzed by mass spectrometry and the serum markers(combinations)related to the diagnosis and classification of lung cancer were obtained.Method:1.Lung cancer tissues from 47 patients(30 adenocarcinomas and 17 squamous carcinomas)and corresponding adjacent tissue samples were analyzed by ~1H NMR.The altered metabolites,associated metabolic pathways and networks were identified and their potential applications in clinical diagnosis were evaluated by ROC analysis.2.A UPLC-MS/MS method was established for measuring the contents of metabolites in choline or puring related pathway.The conditions are as follows:ACQUITY UPLC liquid chromatography system,Xevo G2-XS QTof mass spectrometry system,ACOQUITY UPLC BEH BEH HILIC(2.1 x 100nm,1.7 U)column separation column,electrospray ion source,multiple reaction monitoring mode(MRM).3.The sample size was expanded.The contents of metabolites related to choline and purine metabolic pathways in serum,lung cancer tissues and adjacent tissues of lung cancer patients,healthy control group were further determined by the UPLC-MS/MS.The correlation between lung cancer tissues and adjacent tissues were also investigated.The optimal combination of metabolites for diagnosis and classification of lung cancer was screened by Logistic regression and evaluated by ROC curve analysis.Result:1.The results of ~1H NMR metabolomic analysis of lung cancer tissues showed that lipid,lactate and betaine are significantly altered between lung cancer tissues/paracancerous tissues,indicating that the detection of methylation-related metabolites may be helpful for the diagnosis and classification of lung cancer.2.A UPLC-MS/MS method was established and validated for measuring the contents of 19 metabolites in choline or puringmetabolic pathway.3.Compared with the adjacent tissues,the contents of purines in lung cancer tissues were observed to be generally increased.Combined with adenine,hypoxanthine,inosine and acetylcarnitine,the AUC was 0.985 for diagnosis of adjacent tissues/cancer tissues.Compared with squamous cell carcinomas,the contents of choline-related metabolic pathways in adenocarcinomas are generally higher.Combination of tissue contents of adenosine,guanine,acetylcarnitine and carnitine could effectively differentiate adenocarcinoma from squamous cell carcinoma with AUC value of 0.981.4.Serum xanthine nucleoside,uridine,guanosine,adenine,adenosine,guanine,uric acid,inosine,choline,carnitine,creatinine,dimethylglycine,acetylcarnitine and cysteine were significantly altered in lung cancer/health group.Combined with serum guanosine,adenine,uric acid and cystathioninec could diagnose lung cancer from healthy people and the AUC value was 0.993,with sensitivity and specificity greater than 85%.5.Serum S-adenosylmethionine,CEA and SCC can identify adenocarcinoma and squamous cell carcinoma with AUC of 0.959 and Logistic prediction accuracy of88.4%;Serum xanthine,NSE and SCC were used to differentiate squamous cell carcinoma and small cell lung cancer.The AUC was 0.978,and the logistic prediction accuracy was 93.2%.Serum CEA,NSE and S-adenosylmethionine were used to differentially diagnose adenocarcinoma and small cell lung cancer.The accuracy of Logistic prediction was 96.7%,and the AUC was 0.989.Conclusion:Combination of non-target and target metabonomic techniques is helpful to explore and quantify biomarkers in body fluids for establishing diagnostic models.some of the choline and purine metabolites could be used as potential serum markers for the diagnosis and classification of lung cancer(adenocarcinoma,squamous cell carcinoma,small cell carcinoma),which is worth further study and validation by expanded clinical size.Our findings are of great theoretical value and important clinical significance.