Anti-metastatic and differential effects on protein expression of epigallocatechin-3-gallate in HCCLM6 hepatocellular carcinoma cells

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the third highest cause of cancer-related mortality in humans. Epigallocatechin-3-gallate (EGCG) has been shown to inhibit the metastatic activity of certain cancer cells. The aim of this study was to determine the effects and molecular mechanism(s) of action of EGCG in human HCC cells. A migration and invasion assay for the metastatic behavior of HCCLM6 cells was performed. The anti-metastatic effects of EGCG were investigated by RT-PCR and gelatin zymography. A total cellular protein profile was obtained using 2-dimensional gel electrophoresis (2-DE), followed by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF-MS) analyses of proteins with significant differences in expression following treatment with EGCG. The results revealed that EGCG induced apoptosis and inhibited the metastasis of HCCLM6 cells. The anti-metastatic effects of EGCG were associated with the inhibition of matrix metalloproteinase (MMP)-2 and MMP-9 activity. The expression levels of far upstream element (FUSE) binding protein 1 (FUBP1), heat shock protein beta 1 (HSPB1), heat shock 60 kDa protein 1 (chaperonin) (CH60) and nucleophosmin (NPM) proteins, which are associated with metastasis, were significantly altered in the EGCG-treated HCCLM6 cells. The data from the present study suggest that EGCG has potential as a therapeutic agent for the treatment of HCC.

Synthesis and biological evaluation of novel folic acid receptor-targeted, β-cyclodextrin-based drug complexes for cancer treatment

Drug targeting is an active area of research and nano-scaled drug delivery systems hold tremendous potential for the treatment of neoplasms. In this study, a novel cyclodextrin (CD)-based nanoparticle drug delivery system has been assembled and characterized for the therapy of folate receptor-positive [FR(+)] cancer. Water-soluble folic acid (FA)-conjugated CD carriers (FACDs) were successfully synthesized and their structures were confirmed by 1D/2D nuclear magnetic resonance (NMR), matrix-assisted laser desorption ionization time-of-flight mass spectrometer (MALDI-TOF-MS), high performance liquid chromatography (HPLC), Fourier transform infrared spectroscopy (FTIR), and circular dichroism. Drug complexes of adamatane (Ada) and cytotoxic doxorubicin (Dox) with FACD were readily obtained by mixed solvent precipitation. The average size of FACD-Ada-Dox was 1.5-2.5 nm. The host-guest association constant Ka was 1,639 M-1 as determined by induced circular dichroism and the hydrophilicity of the FACDs was greatly enhanced compared to unmodified CD. Cellular uptake and FR binding competitive experiments demonstrated an efficient and preferentially targeted delivery of Dox into FR-positive tumor cells and a sustained drug release profile was seen in vitro. The delivery of Dox into FR(+) cancer cells via endocytosis was observed by confocal microscopy and drug uptake of the targeted nanoparticles was 8-fold greater than that of non-targeted drug complexes. Our docking results suggest that FA, FACD and FACD-Ada-Dox could bind human hedgehog interacting protein that contains a FR domain. Mouse cardiomyocytes as well as fibroblast treated with FACD-Ada-Dox had significantly lower levels of reactive oxygen species, with increased content of glutathione and glutathione peroxidase activity, indicating a reduced potential for Dox-induced cardiotoxicity. These results indicate that the targeted drug complex possesses high drug association and sustained drug release properties with good biocompatibility and physiological stability. The novel FA-conjugated β-CD based drug complex might be promising as an anti-tumor treatment for FR(+) cancer.

Zinc and DHA have opposing effects on the expression levels of histones H3 and H4 in human neuronal cells

Zn and DHA have putative neuroprotective effects and these two essential nutrients are known to interact biochemically. We aimed to identify novel protein candidates that are differentially expressed in human neuronal cell line M17 in response to Zn and DHA that would explain the molecular basis of this interaction. Two-dimensional gel electrophoresis and MS were applied to identify major protein expression changes in the protein lysates of human Ml7 neuronal cells that had been grown in the presence and absence of Zn and DHA. Proteomic findings were further investigated using Western immunoblot and real-time PCR analyses. Four protein spots, which had significant differential expression, were identified and selected for in-gel trypsin digestion followed by matrix-assisted laser desorption ionisation MS analysis. The resultant peptide mass fingerprint for each spot allowed their respective identities to be deduced. Two human histone variants H3 and H4 were identified. Both H3 and H4 were downregulated by Zn in the absence of DHA (Zn effect) and upregulated by DHA (DHA effect) in the presence of Zn (physiological condition). These proteomic findings were further supported by Western immunoblot and real-time PCR analyses using H3- and H4-specific monoclonal antibodies and oligonucleotide primers, respectively. We propose that dietary Zn and DHA cause a global effect on gene expression, which is mediated by histones. Such novel information provides possible clues to the molecular basis of neuroprotection by Zn and DHA that may contribute to the future treatment, prevention and management of neurodegenerative diseases such as Alzheimer's disease.

A provisional database for the silicon content of foods in the United Kingdom

Si may play an important role in bone formation and connective tissue metabolism. Although biological interest in this element has recently increased, limited literature exists on the Si content of foods. To further our knowledge and understanding of the relationship between dietary Si and human health, a reliable food composition database, relevant for the UK population, is required. A total of 207 foods and beverages, commonly consumed in the UK, were analysed for Si content. Composite samples were analysed using inductively coupled plasma–optical emission spectrometry following microwave-assisted digestion with nitric acid and H2O2. The highest concentrations of Si were found in cereals and cereal products, especially less refined cereals and oat-based products. Fruit and vegetables were highly variable sources of Si with substantial amounts present in Kenyan beans, French beans, runner beans, spinach, dried fruit, bananas and red lentils, but undetectable amounts in tomatoes, oranges and onions. Of the beverages, beer, a macerated whole-grain cereal product, contained the greatest level of Si, whilst drinking water was a variable source with some mineral waters relatively high in Si. The present study provides a provisional database for the Si content of UK foods, which will allow the estimation of dietary intakes of Si in the UK population and investigation into the role of dietary Si in human health.

Analysis of self-assembled monolayer interfaces by electrospray mass spectrometry : a gentle approach

A general mass spectrometry technique for the characterization of alkanethiol-modified surfaces is presented. Alkanethiol self-assembled onto a gold surface (in this case, peptides were attached to the gold surface via a thiolate bond) was reductively desorbed in 0.05 M KOH in the presence of octadecyl-derivatized silica gel. The peptide adsorbed onto the silica gel, whereupon it could be filtered, washed to remove any salts, and then eluted using a mixture of 4:1 v/v methanol/water. The eluant containing the peptide was injected into a Fourier transform ion-cyclotron resonance mass spectrometer (FTICR/MS) via electrospray ionization. The spectrum showed no fragmentation of the peptide, demonstrating the gentleness of the technique. This simple procedure is not limited to FTICR/MS and could be adapted to other mass spectrometers.

Dimensionality reduction of protein mass spectrometry data using random projection

Protein mass spectrometry (MS) pattern recognition has recently emerged as a new method for cancer diagnosis. Unfortunately, classification performance may degrade owing to the enormously high dimensionality of the data. This paper investigates the use of Random Projection in protein MS data dimensionality reduction. The effectiveness of Random Projection (RP) is analyzed and compared against Principal Component Analysis (PCA) by using three classification algorithms, namely Support Vector Machine, Feed-forward Neural Networks and K-Nearest Neighbour. Three real-world cancer data sets are employed to evaluate the performances of RP and PCA. Through the investigations, RP method demonstrated better or at least comparable classification performance as PCA if the dimensionality of the projection matrix is sufficiently large. This paper also explores the use of RP as a pre-processing step prior to PCA. The results show that without sacrificing classification accuracy, performing RP prior to PCA significantly improves the computational time.