Post-translational modifications of FDA-approved plasma biomarkers in glioblastoma samples.

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.

One-dimensional proteomic profiling of Danio rerio embryo vitellogenin to estimate quantum dot toxicity.

BACKGROUND: Vitellogenin (Vtg) is the major egg yolk protein (YP) in most oviparous species and may be useful as an indicator in ecotoxicological testing at the biochemical level. In this study, we obtained detailed information about the Vtgs of Danio rerio embryos by cutting SDS-PAGE gel lanes into thin slices, and analyzing them slice-by-slice with (MALDI-TOF) mass spectrometry. RESULTS: We conducted three proteomic analyses, comparing embryonic Danio rerio Vtg cleavage products after exposure for 48 h to CdSecore/ZnSshell quantum dots (QDs), after exposure to a mixture of the components used for quantum dot synthesis (MCS-QDs), and in untreated embryos. The Vtg mass spectrometric profiles of the QDs-treated embryos differed from those of the unexposed or MCS-QDs-treated embryos. CONCLUSION: This study demonstrates the possible utility of Vtg profiling in D. rerio embryos as a sensitive diagnostic tool to estimate nanoparticle toxicity.

Applying of hierarchical clustering to analysis of protein patterns in the human cancer-associated liver.

BACKGROUND: There 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). RESULTS: We 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/SIGNIFICANCE: Our 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.

Computational approach to characterization of human liver drug-metabolizing enzymes.

Cytochromes P450 are the key enzymes for activating and inactivating many drugs; individual expression levels of CYPs may play a crucial role in drug safety and drug efficacy. Statistical comparison of biochemical profiles of 23 human liver microsomes have been used to characterize human liver samples. The profile included 12 parameters, namely activity of NADPH-cytochrome P450 reductase, cytochrome P450 content and cytochrome P450-dependent monooxygenase activities with marker substrates. Unsupervised statistical methods including cluster analysis and principal component analysis revealed with very high confidence the presence of two groups. Difference between the groups was explained by peculiarities of reductase activity and cytochrome P450 enzyme activities with 7-ethoxyresorufin, 7-methoxyresorufin, 7-methoxycoumarin, 7-benzyloxyresorufin and 7-benzyloxyquinoline. Results of biochemical assays coupled with multidimensional data analysis can be further used for targeted proteomic profiling of microsome oxidation mechanisms.