Finally, the most significant pathway elucidated by bioinformatics methods was subsequently validated. After protein identification, the peptides with qualified intensities of iTRAQ signature ions were selected for further quantitative analysis. Deviation of the iTRAQ signature ions intensities of peptides may exist due to measurement errors in the experiments and individual variations from biological replicates of samples. Therefore, normalization is necessary for accuracy in protein quantitation. We have tried seven different normalization methods. The details of the normalization methods and evaluation were described in Method S1. First, we use the dataset from the duplicate experiment, which contained 296 identified proteins and 1,159 qualified peptides for protein quantitation. Briefly, the normalized peptide iTRAQ signals were used for calculation of the S values, which represent the errors of the protein abundance ratios, followed by the calculation of mean of all S values. Considering normalization performed directly on the level of peptide iTRAQ signals, the methods 1 and 2, which had relative small mean of S VE-822 values were selected. In order to Cycloheximide clinical trial elucidate the proteomic change induced by citreoviridin in lung cancer xenograft tumors, differentially expressed proteins were selected by their relative protein abundance between control and citreoviridin-treated tumors. However, differences observed between control and treatment groups may arise from measurement errors in experiments and individual variations among tumors from different mice. Therefore, to positively select the differentially expressed proteins, we first calculated the cut-off values that indicate a significant degree of up-regulation or down-regulation. The large-scale experiment, which contains two biological replicates for both control and citreoviridin-treated tumor samples, is suitable for measuring the errors. The S value of each protein, which represents the error of protein abundance ratios, was calculated by its protein abundance ratios, T1/C1 and T2/C2. Each protein had one S value and the distribution of S values can be deemed as the distribution of errors. Assuming that the errors follow a normal distribution, a 1.96-fold of the standard deviation of S values is statistically significant and can be taken as the cut-off value. To elucidate the pathways induced by the ATP synthase inhibitor citreoviridin in tumors of lung cancer xenografts, we applied bioinformatics analysis to the differentially expressed proteins between control and citreoviridin-treated tumors. In the xenograft mouse model, mouse cells may be present in the subcutaneous tumors of human lung cancer.