Cathepsin D inhibits oxidative stress-induced cell death via activation of autophagy in cancer cells.

Cathepsin D (CatD), a lysosomal aspartic protease, plays an essential role in tumor progression and apoptosis. However, the function of CatD in cell death is not yet fully understood. In this study, we identified CatD as one of up-regulated proteins in human malignant glioblastoma M059J cells that lack the catalytic subunit of DNA-PK compared with its isogenic M059K cells with normal DNA-PK activity. M059J cells were relatively more resistant to genotoxic stress than M059K cells. Overexpression of wild-type CatD but not catalytically inactive mutant CatD (D295N) inhibited H(2)O(2)-induced cell death in HeLa cells. Furthermore, knockdown of CatD expression abolished anti-apoptotic effect by CatD in the presence of H(2)O(2). Interestingly, high expression of CatD in HeLa cells significantly activated autophagy: increase of acidic autophagic vacuoles, LC3-II formation, and GFP-LC3 puncta. These results suggest that CatD can function as an anti-apoptotic mediator by inducing autophagy under cellular stress. In conclusion, inhibition of autophagy could be a novel strategy for the adjuvant chemotherapy of CatD-expressing cancers.

Comparative analysis of fat and muscle proteins in fenofibrate-fed type II diabetic OLETF rats: the fenofibrate-dependent expression of PEBP or C11orf59 protein.

Fenofibrate, an agonist of PPARalpha, plays an important role in activating many proteins catalyzing lipid metabolism, and it also has a considerable effect on improvement of insulin sensitivity in the diabetic condition. To investigate fenofibrate-dependent expression of peripheral tissue proteins in diabetes, we analyzed whole muscle or fat proteins of fenofibrate-fed OLETF rats, an animal model of type II diabetes, using 2-dimensional gel electrophoresis. We found that many proteins were specifically expressed in a fenofibrate-dependent manner in these diabetic rats. In particular, a functionally unknown C11orf59 protein was differentially expressed in the muscle tissues (about 5-fold increase) in fenofibrate-fed OLETF rats as compared to control rats. Additionally, the signal proteins phosphatidylethanolamine binding protein and IkB interacting protein were differentially regulated in the fenofibrate-treated adipose tissues. We suggest here that these proteins might be involved in controlling lipid or carbohydrate metabolism in diabetes via PPARalpha activation.

Proteomic analysis in NSAIDs-treated primary cardiomyocytes.

NSAIDs (non-steroidal anti-inflammatory drugs) are widely used for the treatment of a variety of inflammatory diseases, but many of them were withdrawn from the market due to their cardiovascular toxicity. In this study, we tried to identify proteins responding to the cellular toxicity in NSAIDs-treated primarily cultured cardiomyocytes using 2-D proteomic analysis. We used seven different NSAIDs (celecoxib, rofecoxib, valdecoxib, diclofenac, naproxen, ibuprofen, and meloxicam) possessing each different degree of cardiovascular risk. Overall protein spots were similar in all NSAIDs-treated cells although numbers of decreased proteins were about 2-fold higher in celecoxib or rofecoxib-treated cells than in cells incubated with other NSAIDs. Many stress-related proteins, cardiac muscle movement proteins and proteins involved in membrane organization have been isolated. Among them, Septin-8, a filament scaffolding protein, showed its specific expression pattern depending on the extent of drug toxicity. Its expression level was low in cells treated by relatively high toxic drugs such as celecoxib, diclofenac, valdecoxib, and rofecoxib. On the contrary, Septin-8 was similarly expressed in control cells in the presence of less toxic drugs such ibuprofen, naproxen, and meloxicam. This data suggests that Septin-8 differentially responds to each NSAID.

Empirically controlled mapping of the Caenorhabditis elegans protein-protein interactome network.

To provide accurate biological hypotheses and elucidate global properties of cellular networks, systematic identification of protein-protein interactions must meet high quality standards.We present an expanded C. elegans protein-protein interaction network, or 'interactome' map, derived from testing a matrix of approximately 10,000 x approximately 10,000 proteins using a highly specific, high-throughput yeast two-hybrid system. Through a new empirical quality control framework, we show that the resulting data set (Worm Interactome 2007, or WI-2007) was similar in quality to low-throughput data curated from the literature. We filtered previous interaction data sets and integrated them with WI-2007 to generate a high-confidence consolidated map (Worm Interactome version 8, or WI8). This work allowed us to estimate the size of the worm interactome at approximately 116,000 interactions. Comparison with other types of functional genomic data shows the complementarity of distinct experimental approaches in predicting different functional relationships between genes or proteins

Network modeling links breast cancer susceptibility and centrosome dysfunction.

Many cancer-associated genes remain to be identified to clarify the underlying molecular mechanisms of cancer susceptibility and progression. Better understanding is also required of how mutations in cancer genes affect their products in the context of complex cellular networks. Here we have used a network modeling strategy to identify genes potentially associated with higher risk of breast cancer. Starting with four known genes encoding tumor suppressors of breast cancer, we combined gene expression profiling with functional genomic and proteomic (or 'omic') data from various species to generate a network containing 118 genes linked by 866 potential functional associations. This network shows higher connectivity than expected by chance, suggesting that its components function in biologically related pathways. One of the components of the network is HMMR, encoding a centrosome subunit, for which we demonstrate previously unknown functional associations with the breast cancer-associated gene BRCA1. Two case-control studies of incident breast cancer indicate that the HMMR locus is associated with higher risk of breast cancer in humans. Our network modeling strategy should be useful for the discovery of additional cancer-associated genes.

Systematic interactome mapping and genetic perturbation analysis of a C. elegans TGF-beta signaling network.

To initiate a system-level analysis of C. elegans DAF-7/TGF-beta signaling, we combined interactome mapping with single and double genetic perturbations. Yeast two-hybrid (Y2H) screens starting with known DAF-7/TGF-beta pathway components defined a network of 71 interactions among 59 proteins. Coaffinity purification (co-AP) assays in mammalian cells confirmed the overall quality of this network. Systematic perturbations of the network using RNAi, both in wild-type and daf-7/TGF-beta pathway mutant animals, identified nine DAF-7/TGF-beta signaling modifiers, seven of which are conserved in humans. We show that one of these has functional homology to human SNO/SKI oncoproteins and that mutations at the corresponding genetic locus daf-5 confer defects in DAF-7/TGF-beta signaling. Our results reveal substantial molecular complexity in DAF-7/TGF-beta signal transduction. Integrating interactome maps with systematic genetic perturbations may be useful for developing a systems biology approach to this and other signaling modules.