Rosiglitazone sensitizes MDA-MB-231 breast cancer cells to anti-tumour effects of tumour necrosis factor-alpha, CH11 and CYC202.

Peroxisome proliferator-activated receptor-gamma (PPARgamma) is a member of the nuclear hormone superfamily and has multiple endogenous and pharmacological ligands, including 15-deoxy-Delta (12,14)-prostaglandin J(2) and two thiazolidinediones (TZD), rosiglitazone and pioglitazone, which are used clinically to treat type-2 diabetes mellitus. PPARgamma agonists regulate development, cellular growth and metabolism in various tissues and have been documented to decrease cellular proliferation and to induce apoptosis of various tumour phenotypes, including breast cancer. However, the full spectrum of anti-tumour effects occurs only at suprapharmacological doses. In this study, we investigated the mechanism of rosiglitazone-induced anti-tumour effects of MDA-MB-231 human breast cancer cells, and used that information to predict rosiglitazone-induced sensitization of breast cancer cells to the effects of other compounds. We first confirmed that 100 microM rosiglitazone, but not lower doses, decreases MDA-MB-231 cell viability in vitro. We then used microarray gene expression analysis to determine early rosiglitazone-induced gene expression changes after 4-h exposure, which included 1298 genes that we grouped into functional categories. We selectively confirmed rosiglitazone-mediated effects on expression of key regulators of breast cancer proliferation and apoptosis, including p53, p21 and Bax. Finally, we used this information to predict that rosiglitazone would sensitize MDA-MB-231 cells to the anti-tumour effects of CH11, which trimerizes Fas, as well as tumour necrosis factor-alpha. Moreover, we used the confirmed array data to predict cooperative activity of rosiglitazone and R-roscovitine (CYC202), an inhibitor of multiple cyclin-dependent kinases. We conclude that microarray analysis can determine early TZD-modulated changes in gene expression that help to predict effective in vitro drug combinations.

PI3K is involved in PDGF-beta receptor upregulation post-PDGF-BB treatment in mouse HSC.

Increased expression of PDGF-beta receptors is a landmark of hepatic stellate cell activation and transdifferentiation into myofibroblasts. However, the molecular mechanisms that regulate the fate of the receptor are lacking. Recent studies suggested that N-acetylcysteine enhances the extracellular degradation of PDGF-beta receptor by cathepsin B, thus suggesting that the absence of PDGF-beta receptors in quiescent cells is due to an active process of elimination and not to a lack of expression. In this communication we investigated further molecular mechanisms involved in PDGF-beta receptor elimination and reappearance after incubation with PDGF-BB. We showed that in culture-activated hepatic stellate cells there is no internal protein pool of receptor, that the protein is maximally phosphorylated by 5 min and completely degraded after 1 h by a lysosomal-dependent mechanism. Inhibition of receptor autophosphorylation by tyrphostin 1296 prevented its degradation, but several proteasomal inhibitors had no effect. We also showed that receptor reappearance is time and dose dependent, being more delayed in cells treated with 50 ng/ml (48 h) compared with 10 ng/ml (24 h).

List of lists-annotated (LOLA): a database for annotation and comparison of published microarray gene lists.

Microarray profiling of RNA expression is a powerful tool that generates large lists of transcripts that are potentially relevant to a disease or treatment. However, because the lists of changed transcripts are embedded in figures and tables, they are typically inaccessible for search engines. Due to differences in gene nomenclatures, the lists are difficult to compare between studies. LOLA (Lists of Lists Annotated) is an internet-based database for comparing gene lists from microarray studies or other genomic-scale methods. It serves as a common platform to compare and reannotate heterogeneous gene lists from different microarray platforms or different genomic methodologies such as serial analysis of gene expression (SAGE) or proteomics. LOLA () provides researchers with a means to store, annotate, and compare gene lists produced from different studies or different analyses of the same study. It is especially useful in identifying potentially "high interest" genes which are reported as significant across multiple studies and species. Its application to the fields of stem cell, cancer, and aging research is demonstrated by comparing published papers.