Lung cancer is a lethal disease, and early metastasis is the major cause of treatment failure and cancer-related death. Tyrosine phosphorylated (P-Tyr) proteins are involved in the invasive and metastatic behavior of lung cancer; however, only a limited number of targets were identified. We attempt to characterize P-Tyr proteins and events involved in the metastatic process. In a previous work, we have developed a strategy for identification of protein phosphorylation. Here, this strategy was used to characterize the tyrosine phosphoproteome of lung cancer cells that have different invasive abilities (CL1-0 vs. CL1-5). Using our analytical strategy, we report the identification of 335 P-Tyr sites from 276 phosphoproteins. Label-free quantitative analysis revealed that 36 P-Tyr peptides showed altered levels between CL1-0 and CL1-5 cells. From this list of sites, we extracted two novel consensus sequences and four known motifs for specific kinases and phosphatases including EGFR, Src, JAK2, and TC-PTP. Protein-protein interaction network analysis of the altered P-Tyr proteins illustrated that 11 proteins were linked to a network containing EGFR, c-Src, c-Myc, and STAT, which is known to be related to lung cancer metastasis. Among these 11 proteins, 7 P-Tyr proteins have not been previously reported to be associated with lung cancer metastasis and are of greatest interest for further study. The characterized tyrosine phosphoproteome and altered P-Tyr targets may provide a better comprehensive understanding of the mechanisms of lung cancer invasion/metastasis and discover potential therapies.

Protein phosphorylation is a vital post-translational modification that is involved in a variety of biological processes. Several mass spectrometry-based methods have been developed for phosphoprotein characterization. In our previous work, we demonstrated the capability of a computational algorithm in mining phosphopeptide signals in large LC-MS data sets by measuring the mass shifts due to phosphatase treatment (Wu, H. Y.; Tseng, V. S.; Liao, P. C. J. Proteome Res. 2007, 6, 1812-1821). Mass accuracy seems to play an important role in efficiently selecting out phosphopeptide signals. In recent years, the hybrid linear ion trap (LTQ)/Orbitrap mass spectrometer, which provides a high mass accuracy, has emerged as a powerful instrument in proteomic analysis. Here, we developed a process to incorporate LC-MS data that was generated from an LTQ/Orbitrap mass spectrometer into our strategy for taking advantage of the accurate mass measurement. LTQ/Orbitrap raw files were converted to the open file format mzXML via the ReAdW.exe program. To find peaks that were contained in each mzXML file, an open-source computer program, msInspect, was utilized to locate isotopes and assemble those isotopes into peptides. An in-house program, LcmsFormatConverter, was utilized for signal filtering and format transformation. A proposed in-house program, DeltaFinder, was modified and used for defining signals with an exact mass shift due to the dephosphorylation reaction, which generated a table that listed potential phosphopeptide signals. The retention times and m/z values of these selected LC-MS signals were used to program subsequent LC-MS/MS experiments to get high-confidence phosphorylation site determination. Compared to our previous work finished by using a quadrupole/time-of-flight mass spectrometer, a larger number of phosphopeptides in the casein mixture were identified by using LTQ/Orbitrap data, demonstrating the merit of high mass accuracy in our strategy. In addition, the characterization of the lung cancer cell tyrosine phosphoproteome revealed that the use of alkaline phosphatase treatment combined with accurate mass measurement in this strategy increased data repeatability and confidence.