A novel Aurora-A-mediated phosphorylation of p53 inhibits its interaction with MDM2

Purpose: Crosstalk between Aurora-A kinase and p53 has been proposed. While the genetic amplification of Aurora-A has been observed in many human cancers, how p53 is regulated by Aurora-A remains ambiguous. In this study, Aurora-A-mediated phosphorylation of p53 was analyzed by mass spectrometry in order to identify a new phosphorylation site. Subsequently, the functional consequences of such phosphorylation were examined. Experimental design: In vitro phosphorylation of p53 by Aurora-A was performed and the phosphorylated protein was then digested with trypsin and enriched for phosphopeptides by immobilized metal affinity chromatography. Subsequently, a combination of β-elimination and Michael addition was applied to the phosphopeptides in order to facilitate the identification of phosphorylation sites by MS. The functional consequences of the novel phosphorylation of p53 on the protein–protein interactions, protein stability and transactivation activity were then examined using co-immunoprecipitation, Western blotting and reporter assays. Results: Ser-106 of p53 was identified as a novel site phosphorylated by Aurora-A. A serine-to-alanine mutation at this site was found to attenuate Aurora-A-mediated phosphorylation in vitro. In addition, phosphate-sensitive Phos-tag SDS-PAGE was used to confirm that the Ser-106 of p53 is in vivo phosphorylated by Aurora-A. Finally, co-immunoprecipitation studies suggested that Ser-106 phosphorylation of p53 decreases its interaction with MDM2 and prolongs the half-life of p53. Conclusions: The inhibition of the interaction between p53 and MDM2 by a novel Aurora-A-mediated p53 phosphorylation was identified in this study and this provides important information for further investigations into the interaction between p53 and Aurora-A in terms of cancer biology.     

Correlation of intensity-modulated radiation therapy at a specific radiation dose with the prognosis of nasal mucous damage after radiotherapy

Radiation and Environmental Biophysics - Objective of the present study was to investigate the tolerant radiation dose of nasal mucosa by observing and analyzing patients who received...     

Early Blood Biomarkers Distinguish Inflammation from Neonatal Hypoxic-Ischemia Encephalopathy

Neurochemical Research - Neonatal hypoxic–ischemic encephalopathy is the most common cause of neurological disability in infancy. Superimposed inflammation may further worsen neurological...     

HEF1 promotes epithelial mesenchymal transition and bone invasion in prostate cancer under the regulation of microRNA‐145

The principal problem arising from prostate cancer (PCa) is its propensity to metastasize to bones, and it's crucial to understand the mechanism of tumor progression to metastasis in order to develop therapies that may reduce the morbidity and mortality of PCa patients. Although we had identified that microRNA(miR)‐145 could repress bone metastasis of PCa via regulating epithelial–mesenchymal transition (EMT) in previous study, it is still unknown how miR‐145 regulated EMT. In the present study, we constructed a luciferase reporter system and identified HEF1 as a direct target of miR‐145. More importantly, HEF1 was shown to promote migration, invasion and EMT of PC‐3 cells, a human PCa cell line originated from a bone metastatic PCa specimen. And HEF1 was also shown to partially mediate miR‐145 suppression of EMT and invasion. Furthermore, inhibition of HEF1 repressed bone invasion of PC‐3 cells in vivo. Expression of HEF1 was negatively correlated with miR‐145 in primary PCa and bone metastatic specimens, but HEF1 was higher in samples which were more likely to commit to bone metastasis or those with higher free prostate‐specific antigen (fPSA) levels and Gleason scores. Taken together, these findings indicate that HEF1 promotes EMT and bone invasion in prostate cancer by directly targeted by miR‐145, and miR‐145 suppresses EMT and invasion, at least in part, through repressing HEF1. J. Cell. Biochem. 114: 1606–1615, 2013. © 2013 Wiley Periodicals, Inc.     

Structural,catalytic and stabilizing consequences of aromatic cluster variants in human carbonic anhydrase II

The presence of aromatic clusters has been found to be an integral feature of many proteins isolated from thermophilic microorganisms. Residues found in aromatic cluster interact via π–π or C–H?π bonds between the phenyl rings, which are among the weakest interactions involved in protein stability. The lone aromatic cluster in human carbonic anhydrase II (HCA II) is centered on F226 with the surrounding aromatics F66, F95 and W97 located 12 Å posterior the active site; a location which could facilitate proper protein folding and active site construction. The role of F226 in the structure, catalytic activity and thermostability of HCA II was investigated via site-directed mutagenesis of three variants (F226I/L/W) into this position. The measured catalytic rates of the F226 variants via ¹⁸O-mass spectrometry were identical to the native enzyme, but differential scanning calorimetry studies revealed a 3–4 K decrease in their denaturing temperature. X-ray crystallographic analysis suggests that the structural basis of this destabilization is via disruption and/or removal of weak C–H?π interactions between F226 to F66, F95 and W97. This study emphasizes the importance of the delicate arrangement of these weak interactions among aromatic clusters in overall protein stability.     

Inhibitory constituents from the aerial parts of Polygala tenuifolia on LPS-induced NO production in BV2 microglia cells

Five new phenolic glycosides, tenuisides A–E (1?5), and a new megastigmane glycoside, tenuiside F (6), along with seventeen known compounds (7–23) were isolated from the aerial parts of Polygala tenuifolia Willd. Their structures were established by detailed analysis of NMR and HRESIMS spectroscopic data, and the absolute configurations of compounds 5 and 6 were determined by CD spectra and in-NMR-tube Mosher’s method. The inhibitory effects of these compounds were evaluated on NO production in LPS-activated BV-2 microglia cells. Compound 17 showed the strongest activity, with an IC₅₀ value of 7.4 μM, while compounds 1, 8, 14, and 18 showed the moderate activities, with IC₅₀ values of 16.2–38.5 μM. And their primary structure–activity relationships (SARs) of NO inhibitory effects were also briefly discussed.     

Design,synthesis, and biological evaluation of novel histone deacetylase 1 inhibitors through click chemistry

We report the design, synthesis, and biological evaluation of a new series of HDAC1 inhibitors using click chemistry. Compound 17 bearing a phenyl ring at meta-position was identified to show much better selectivity for HDAC1 over HDAC7 than SAHA. The compond 17 also showed better in vitro anticancer activities against several cancer cell lines than that of SAHA. This work could serve as a foundation for further exploration of selective HDAC inhibitors using the compound 17 molecular scaffold.     

Identification of sparse neural functional connectivity using penalized likelihood estimation and basis functions

One key problem in computational neuroscience and neural engineering is the identification and modeling of functional connectivity in the brain using spike train data. To reduce model complexity, alleviate overfitting, and thus facilitate model interpretation, sparse representation and estimation of functional connectivity is needed. Sparsities include global sparsity, which captures the sparse connectivities between neurons, and local sparsity, which reflects the active temporal ranges of the input-output dynamical interactions. In this paper, we formulate a generalized functional additive model (GFAM) and develop the associated penalized likelihood estimation methods for such a modeling problem. A GFAM consists of a set of basis functions convolving the input signals, and a link function generating the firing probability of the output neuron from the summation of the convolutions weighted by the sought model coefficients. Model sparsities are achieved by using various penalized likelihood estimations and basis functions. Specifically, we introduce two variations of the GFAM using a global basis (e.g., Laguerre basis) and group LASSO estimation, and a local basis (e.g., B-spline basis) and group bridge estimation, respectively. We further develop an optimization method based on quadratic approximation of the likelihood function for the estimation of these models. Simulation and experimental results show that both group-LASSO-Laguerre and group-bridge-B-spline can capture faithfully the global sparsities, while the latter can replicate accurately and simultaneously both global and local sparsities. The sparse models outperform the full models estimated with the standard maximum likelihood method in out-of-sample predictions.