Serum metabolomics analysis and establishment of diagnostic model of pancreatic cancer associated diabetes

Abstract

Objective To establish the diagnostic model based on detection of serum biomarkers in pancreatic cancer (PC) associated diabetes. Methods From June 2013 to July 2014, at Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, 30 patients diagnosed with PC companied with new onset diabetic mellitus and 30 patients with new onset type 2 diabetic mellitus, were enrolled. Serum samples were examined by liquid chromatography-mass spectrometry (LC-MS) for metabolomics analysis. Orthogonal partial least square (OPLS) was performed for raw data analysis to obtain the differentially expressed metabolites between two groups. The first 15 cases of each group were taken as training samples and the left as validation samples. The model was established using logistic regression via stepwise differentially expressed metabolites and clinical data input in training samples. The diagnostic efficiency of the model was verified in validating samples. Results Ten differentially expressed metabolites were identified in PC companied with new onset diabetic mellitus group and new onset type 2 diabetic mellitus group. The differentially expressed metabolites identified in positive ion mode were 3-ketosphingosine, arachidonoyl dopamine, phosphatidylethanolamine (18∶2), ubiquinone-1 and valine. The differentially expressed metabolites identified in negative ion mode were C16 sphingosine-1-phosphate, keto palmitic acid, isoleucine, N-succinyl-L-diaminopimelic acid and uridine. The diagnostic model was established in training samples: p=e(Xβ)/(1+ e(Xβ)), (Xβ)=-158.975-1.891 (age)+ 0.309 (phosphatidylethanolamine 18∶2)+ 1.035 (C16 sphingosine-1-phosphate)+ 0.084 (isoleucine)+ 1.114 5 (N-succinyl-L-diaminopimelic acid). The area under curve (AUC) of receiver operating characteristic (ROC) of this model was 0.982 in validation samples, the sensitivity and specificity were both 93.3%. Conclusion Serum metabolomics-based diagnostic approach is a promising method for screening PC from new onset diabetic mellitus. Key words: Pancreatic neoplasms; Diabetes mellitus; Serum metabolomics