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

<div><p>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.</p></div

GBM-negative and GBM-positive patterns’ counted for FDA-approved plasma proteins.

<p>GBM-negative and GBM-positive patterns’ counted for FDA-approved plasma proteins.</p

Sequence coverage for various protein PTMs.

<p>Identification by Mascot of ≥ 3 peptides per protein. The adjusted inverse normalized values are displayed as a violin plot, comparing distributions between control and GBM samples. Horizontal bars indicate the mean (dashed line) and median (solid line) values for each group.</p

MS/MS spectra of non-modified (A) and phosphomodified (B) peptide DSSPDSAEDVR (2+) of alpha-2-HS-glycoprotein (FETUA_HUMAN) GBM plasma.

<p>Monoisotopic mass of neutral peptide Mr (calc) 1,592.62. Variable modification S7–Phospho (ST) with neutral loss 97.98. [<i>y</i>(10)] in a non-modified peptide was not detected.</p

Number of identified proteins/peptides due to PTM-sensitive MS/MS search for control and GBM plasma samples.

<p>Number of identified proteins/peptides due to PTM-sensitive MS/MS search for control and GBM plasma samples.</p

Enrichment of plasma Alpha-2-HS-glycoprotein (FETUA_HUMAN, 367 aa) sequence coverage with peptides assembled from MS/MS search for phosphorylated peptides.

<p>Enrichment of plasma Alpha-2-HS-glycoprotein (FETUA_HUMAN, 367 aa) sequence coverage with peptides assembled from MS/MS search for phosphorylated peptides.</p

Applying of Hierarchical Clustering to Analysis of Protein Patterns in the Human Cancer-Associated Liver

<div><p>Background</p><p>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).</p><p>Results</p><p>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.</p><p>Conclusions/Significance</p><p>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.</p></div

Changes in the fractions of PTM peptides of FDA-approved plasma biomarkers in GBM compared to control.

<p>Changes in the fractions of PTM peptides of FDA-approved plasma biomarkers in GBM compared to control.</p

The number of protein spots after manual processing of 19 2DE gel images for the human liver cytosol using the proprietary GelEditor software.

<p>Gels belonging to cluster 1 are shown in white columns. Gels belonging to cluster 2 are shown in gray columns. Gel which removed from all subsequent data processing is shown in the shaded column.</p