Liquid chromatography-tandem mass spectrometry was used to analyze plasma proteins of volunteers (control) and patients with glioblastoma multiform (GBM). A database search was pre-set with a variable post-translational modification (PTM): phosphorylation, acetylation or ubiquitination. There were no significant differences between the control and the GBM groups regarding the number of protein identifications, sequence coverage or number of PTMs. However, in GBM plasma, we unambiguously observed a decreased fraction in post-translationally modified peptides identified with high quality. The disease-specific PTM patterns were extracted and mapped to the set of FDA-approved plasma protein markers. Decreases of 46% and 24% in the number of acetylated and ubiquitinated peptides, respectively, were observed in the GBM samples. Significance of capturing disease-associated patterns of protein modifications was envisaged.
Background: Using human keratinocyte HaCaT cell line model, we screened for proteins that changed their content due to SDS exposure in non-toxic dose (25 μg/ml, as determined by the MTT assay and microscopic examination) during 48 h. Methods: The altered level of proteins from HaCaT keratinocytes exposed to SDS was analyzed by LC-MS/MS approach and quantified using Progenesis LC software. Results: The Pathview map of 131 upregulated proteins was built, and enhancement of glycolysis/gluconeogenesis was found. Conclusions:The results of our study admit the possibility of promotion of the cutaneous neoplasia and/or the peculiarity of the response of immortalized keratinocytes to the SDS treatment and provide new insights into possible role of SDS as integrator of diverse signaling that influence cell fate decisions.
BackgroundThere are two ways that statistical methods can learn from biomedical data. One way is to learn classifiers to identify diseases and to predict outcomes using the training dataset with established diagnosis for each sample. When the training dataset is not available the task can be to mine for presence of meaningful groups (clusters) of samples and to explore underlying data structure (unsupervised learning).ResultsWe investigated the proteomic profiles of the cytosolic fraction of human liver samples using two-dimensional electrophoresis (2DE). Samples were resected upon surgical treatment of hepatic metastases in colorectal cancer. Unsupervised hierarchical clustering of 2DE gel images (n = 18) revealed a pair of clusters, containing 11 and 7 samples. Previously we used the same specimens to measure biochemical profiles based on cytochrome P450-dependent enzymatic activities and also found that samples were clearly divided into two well-separated groups by cluster analysis. It turned out that groups by enzyme activity almost perfectly match to the groups identified from proteomic data. Of the 271 reproducible spots on our 2DE gels, we selected 15 to distinguish the human liver cytosolic clusters. Using MALDI-TOF peptide mass fingerprinting, we identified 12 proteins for the selected spots, including known cancer-associated species.Conclusions/SignificanceOur results highlight the importance of hierarchical cluster analysis of proteomic data, and showed concordance between results of biochemical and proteomic approaches. Grouping of the human liver samples and/or patients into differing clusters may provide insights into possible molecular mechanism of drug metabolism and creates a rationale for personalized treatment.
A method for constructing one-dimensional proteomic maps (1D-PM) based on mass spectrometric identification of proteins from adjacent slices of one-dimensional electrophoregram has been developed. For the proteomic mapping, gel lanes were sectioned into slices less than 0.2 mm thick and each slice was subjected to enzymatic hydrolysis. The resultant mixture of peptide fragments was analyzed by matrix-assisted laser desorption time-of-flight mass spectrometry (MALDI-TOF) and liquid chromatography electrospray ionization tandem mass spectrometry (LC-MS/MS). Proteins were identified by the mass spectra obtained. Data on peptide fragments and corresponding identified proteins were presented as a 1D-PM. Proteomic maps were constructed by assigning individual proteins to gel slices based on number of matching peptides in a corresponding MS-data. On 1D-PM of human liver microsomal fraction, 18 proteins were identified in the region of 40-65 kDa. These included 12 membrane proteins belonging to the superfamily of cytochromes P450. Pooling of mass spectrometric data, obtained from several adjacent gel slices (molecular zooming) increased sequence coverage of CYP2A (cytochrome P450 family 2A). The maximal coverage of 66% significantly exceeded the level of 48% that could be obtained using one (even the most informative) slice. This method can be applied to the proteomic profiling of membrane-bound proteins.
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