Abstract. Gastric cancer (GC) is the one of the most common types of cancer in Asia. To better understand the molecular mechanisms underlying GC, and to seek new markers of tumor progression, we used a proteomics strategy to analyze the protein expression patterns in matched pairs of GC tissue and normal gastric mucosa of 8 GC patients. Comparative proteomic analysis, using two-dimensional gel electrophoresis (2-DE) and matrix-assisted laser-desorption ionization timeof-flight mass spectrometry (MALDI-TOF-MS), revealed that 32 protein spots showed a >2-fold difference in intensity between tumor and normal tissues. Twenty-six proteins were up-regulated and 6 proteins were down-regulated in tumor tissue compared to control. Western blot analysis confirmed differential expression for 9 proteins, including AGR2, ENO1, GDI2, GRP78, GRP94, PPIA, PRDX1, PTEN and VDAC1. Immunohistochemical staining of a tissue microarray, derived from 145 GC patients, with antibodies for each of the 9 proteins demonstrated a significant association between the level of protein immunostaining and the clinical features of the disease in the donor. The identified proteins were functionally classified using bioinformatics methods, showing that the 9 proteins identified were related to BCL2, BAX, ERBB2 and CASP3 proteins and involved in the process of apoptosis. These proteomic data provide potentially valuable insights into both the biology of GC and the identity of biomarkers for tumor progression. We propose ENO1, GRP78, GRP94, PPIA, PRDX1 and PTEN as potential GC biomarkers.
The conformational state of C-terminally truncated staphylococcal nuclease R (SNR135), with and without bound ligands, has been studied by performing limited proteolysis with a specific endoproteinase Glu-C followed by electrophoresis and mass spectrometry. Comparison of the accessibility of the cleavage sites shows that the C-terminal truncation of 14 amino-acid residues causes significant unfolding of the C-terminal part of a helix 1 and the center of a helix 2, but there is little effect on other regions of the nuclease, in particular the N-terminal subdomain, which includes the active site of the nuclease. The truncation also makes the overall conformation of the nuclease more loose and flexible. Binding of ligands makes helices 1 and 2 more resistant to protease Glu-C attack and converts the partially unfolded state to a native-like state, although the conformational stability of the SNR135 complex is still much lower than that of the full-length enzyme. The results suggest that the amino-acid residues around the active site in the truncated nuclease are arranged in a similar topology to those in the full-length nuclease. The study shows that there is a clear-cut correlation between protease susceptibility and conformational stability of the protein, and the initial proteolytic events are the most critical for evaluating the conformational features of the protein. This study demonstrates how mass spectrometry can be combined with limited proteolysis to observe conformational changes induced by ligand binding.
In this study, we describe characterization of the human plasma proteome based on analysis with multifunctional chitosan-GMA-IDA-Cu(II) nanospheres. Chitosan-GMA-IDA-Cu(II) nanospheres with diameters of 20 to 100 nm have unique properties due to multifunctional chemical moieties, high surface area, high capacity, good dispersibility in buffer solution as well as good biocompatibility and chemical stability which improves their specific interaction with peptides and proteins of the human plasma using different binding buffers. Combining these chitosan-GMA-IDA-Cu(II) nanospheres with MS spectrometry results in a novel strategy which should make it possible to characterize the plasma proteome in a single test. Peptides and proteins adsorbed on the nanosphere can be directly detected by MALDI-TOF-MS. The eluted lower molecular weight peptides and proteins are identified by nano-LC-ESI-MS/MS. A total of 842 unique LMW peptides and 1,682 human unredundant proteins IDs were identified in two different binding buffers, which included relatively low-level proteins (e.g., pg/mL of IL3 Interleukin-3) co-distributed with high-abundance proteins (e.g., 35-55 mg/mL level serum albumin). As such, this nanosphere technique selectively enabled the identification of proteins over a dynamic range of greater than 8 orders of magnitude. Considering this capacity for selective enrichment of peptides and proteins in human plasma, and the large number of LMW peptides and proteins which can be identified, this method promises to accelerate discovery of biomarkers for clinical application.
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