Anti-LCOR monoclonal antibody Made to order

Nuclear receptors (NRs) regulate gene transcription by recruiting coregulators, involved in chromatin remodeling and assembly of the basal transcription machinery. The NR-associated protein ligand-dependent corepressor (LCoR) has previously been shown to suppress hepatic lipogenesis by decreasing the binding of steroid receptor coactivators to thyroid hormone receptor. However, the role of LCoR in adipogenesis has not been established. Here, we show that LCoR expression is reduced in the early stage of adipogenesis in vitro. LCoR overexpression inhibited 3T3-L1 adipocyte differentiation, whereas LCoR knockdown promoted it. Using an unbiased affinity purification approach, we identified CCAAT/enhancer-binding protein (C/EBP), a key transcriptional regulator in early adipogenesis, and corepressor C-terminal binding proteins as potential components of an LCoR-containing complex in 3T3-L1 adipocytes. We found that LCoR directly interacts with C/EBP through its C-terminal helix-turn-helix domain, required for LCoR's inhibitory effects on adipogenesis. LCoR overexpression also inhibited C/EBP transcriptional activity, leading to inhibition of mitotic clonal expansion and transcriptional repression of C/EBP and peroxisome proliferator-activated receptor 2 (PPAR2). However, LCoR overexpression did not affect the recruitment of C/EBP to the promoters of C/EBP and PPAR2 in 3T3-L1 adipocytes. Of note, restoration of PPAR2 or C/EBP expression attenuated the inhibitory effect of LCoR on adipogenesis. Mechanistically, LCoR suppressed C/EBP-mediated transcription by recruiting C-terminal binding proteins to the C/EBP and PPAR2 promoters and by modulating histone modifications. Taken together, our results indicate that LCoR negatively regulates early adipogenesis by repressing C/EBP transcriptional activity and add LCoR to the growing list of transcriptional corepressors of adipogenesis.

BackgroundThe understanding of the molecular biology of pediatric neuronal and mixed neuronal-glial brain tumors is still insufficient due to low frequency and heterogeneity of those lesions which comprise several subtypes presenting neuronal and/or neuronal-glial differentiation. Important is that the most frequent ganglioglioma (GG) and dysembryoplastic neuroepithelial tumor (DNET) showed limited number of detectable molecular alterations. In such cases analyses of additional genomic mechanisms seem to be the most promising. The aim of the study was to evaluate microRNA (miRNA) profiles in GGs, DNETs and pilocytic asytrocytomas (PA) and test the hypothesis of plausible miRNA connection with histopathological subtypes of particular pediatric glial and mixed glioneronal tumors.MethodsThe study was designed as the two-stage analysis. Microarray testing was performed with the use of the miRCURY LNA microRNA Array technology in 51 cases. Validation set comprised 107 samples used during confirmation of the profiling results by qPCR bioinformatic analysis.ResultsMicroarray data was compared between the groups using an analysis of variance with the Benjamini-Hochberg procedure used to estimate false discovery rates. After filtration 782 miRNAs were eligible for further analysis. Based on the results of 10x10-fold cross-validation J48 algorithm was identified as the most resilient to overfitting. Pairwise comparison showed the DNETs to be the most divergent with the largest number of miRNAs differing from either of the two comparative groups. Validation of array analysis was performed for miRNAs used in the classification model: miR-155-5p, miR-4754, miR-4530, miR-628-3p, let-7b-3p, miR-4758-3p, miRPlus-A1086 and miR-891a-5p. Model developed on their expression measured by qPCR showed weighted AUC of 0.97 (95% CI for all classes ranging from 0.91 to 1.00). A computational analysis was used to identify mRNA targets for final set of selected miRNAs using miRWalk database. Among genomic targets of selected molecules ZBTB20, LCOR, PFKFB2, SYNJ2BP and TPD52 genes were noted.ConclusionsOur data showed the existence of miRNAs which expression is specific for different histological types of tumors. miRNA expression analysis may be useful in in-depth molecular diagnostic process of the tumors and could elucidate their origins and molecular background.