Clinical-scale high-throughput human plasma proteome clinical analysis: Lung adenocarcinoma

Clinical proteomics requires the stable and reproducible analysis of a large number of human samples. We report a high-throughput comprehensive protein profiling system comprising a fully automated, on-line, two-dimensional microflow liquid chromatography/tandem mass spectrometry (2-D mu LC-MS/MS) system for use in clinical proteomics. A linear ion-trap mass spectrometer (ITMS) also known as a 2-D ITMS instrument, which is characterized by high scan speed, was incorporated into the mu LC-MS/MS system in order to obtain highly improved sensitivity and resolution in MS/MS acquisition. This system was used to evaluate bovine serum albumin and human 26S proteasome. Application of these high-throughput mu LC conditions and the 2-D ITMS resulted in a 10-fold increase in sensitivity in protein identification. Additionally, peptide fragments from the 26S proteasome were identified three-fold more efficiently than by the conventional 3-D ITMS instrument. In this study, the 2-D mu LC-MS/MS system that uses linear 2-D ITMS has been applied for the plasma proteome analysis of a few samples from healthy individuals and lung adenocarcinoma patients. Using the 2-D and 1-D mu LC-MS/MS analyses, approximately 250 and 100 different proteins were detected, respectively, in each HSA- and IgG-depleted sample, which corresponds to only 0.4 mu L of blood plasma. Automatic operation enabled the completion of a single run of the entire 1-D and 2-D mu LC-MS/MS analyses within 11 h. Investigation of the data extracted from the protein identification datasets of both healthy and adenocarcinoma groups revealed that several of the group-specific proteins could be candidate protein disease markers expressed in the human blood plasma. Consequently, it was demonstrated that this high-throughput mu LC-MS/MS protein profiling system would be practically applicable to the discovery of protein disease markers, which is the primary objective in clinical plasma proteome projects.