Computational protocol: Plasma Metabolite Biomarkersfor the Detection ofPancreatic Cancer

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Protocol publication

[…] The metabonomic data obtained were normalized using internal standard p-chlorophenylalanine and calibrated using QC samples. All annotated metabolites from GC–TOFMS and LC–TOFMS data sets were combined and exported to SIMCA-P+ 12.0 software (Umetrics, Umeå, Sweden) for multivariate statistical analysis. Orthogonal partial least squares-discriminant analysis (OPLS-DA) were performed to discriminate between PC patients and controls. On the basis of a threshold of variable importance in the projection (VIP, value >1) from the 7-fold cross-validated OPLS-DA model, a panel of metabolites responsible for the difference in the metabolic profiles of patients and controls was obtained. In addition to the multivariate statistical method, Student’s t-test was also applied to measure the significance of each metabolite. The resultant p values for all metabolites were subsequently adjusted to account for multiple testing by a false discovery rate (FDR) method. Metabolites with both multivariate and univariate statistical significance (VIP > 1 and p < 0.05) were considered to be potential markers capable of differentiating PC from controls. The corresponding fold change was calculated to show how these selected differential metabolites varied in the cancer samples relative to the controls. Altered metabolic pathways in PC were analyzed by means of the quantitative enrichment analysis (QEA) algorithm represented in the metabolite set enrichment analysis (MSEA) method. Visualization of metabolic pathways was achieved by using Metscape 2 running on cytoscape., [...] Receiver operating characteristic (ROC) curve analysis and binary logistic regression were conducted using SPSS software (IBM SPSS Statistics 19, USA) following our previously published data analysis protocols. Briefly, a logistic regression model constructed using the binary outcome of PC and control as dependent variables was used to determine the best combination of plasma markers for PC prediction. The forward stepwise regression, the procedure to select the strongest variables (metabolites) until there are no more significant predictors in the data set, was used for potential biomarker selection. The Wald test was used to assess significance in logistic regression, and this test assigns a p value to each metabolite to assess significance. ROC curves for the logistic regression model were plotted with the fitted probabilities from the established model as possible cut-points for the computation of sensitivity and specificity. […]

Pipeline specifications

Software tools MetaboAnalyst, MetScape, SPSS
Applications Miscellaneous, Metabolic profiles analysis
Organisms Homo sapiens
Diseases Pancreatic Neoplasms
Chemicals Betaine, Choline, Methylguanidine