Profiling modifications for glioblastoma proteome using ultra-tolerant database search: Are the peptide mass shifts biologically relevant or chemically induced?

Publication date: Available online 17 May 2018
Source:Journal of Proteomics
Author(s): Irina A. Tarasova, Peter M. Chumakov, Sergei A. Moshkovskii, Mikhail V. Gorshkov
Peptide mass shifts were profiled using ultra-tolerant database search strategy for shotgun proteomics data sets of human glioblastoma cell lines demonstrating strong response to the type I interferon (IFNα-2b) treatment. The main objective of this profiling was revealing the cell response to IFN treatment at the level of protein modifications. To achieve this objective, statistically significant changes in peptide mass shift profiles between IFN treated and untreated glioblastoma samples were analyzed. Detailed analysis of MS/MS spectra allowed further interpretation of the observed mass shifts and differentiation between post-translational and artifact modifications.SignificanceMalignant cells typically acquire increased sensitivity to viruses due to the deregulated antiviral mechanisms. Therefore, a viral therapy is considered as one of the promising approaches to treat cancer. However, recent studies have demonstrated that malignant cells can preserve intact antiviral mechanisms, e.g. interferon signaling, and develop resistance to virus infection in response to interferon treatment. Post translational modifications, e.g. tyrosine phosphorylation, are the interferon signaling drivers. Thus, comprehensive characterization of modifications is crucially important, yet, most challenging problem in cancer proteomics. Here, we report on the application of the recently introduced ultra-tolerant search strategy for profiling peptide modifications in the human glioblastoma cell lines demonstrating strong response to the type I interferon (IFNα-2b) treatment. The specific aim of the study was identification of statistically significant changes in peptide mass shift profiles between IFN treated and untreated glioblastoma samples, as well as determination of whether these shifts represent the biologically relevant modification.



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