Prognostic relevance of Centromere protein H expression in esophageal carcinoma

<p>Abstract</p> <p>Background</p> <p>Many kinetochore proteins have been shown to be associated with human cancers. The aim of the present study was to clarify the expression of Centromere protein H (CENP-H), one of the fundamental components of the human active kinetochore, in esophageal carcinoma and its correlation with clinicopathological features.</p> <p>Methods</p> <p>We examined the expression of CENP-H in immortalized esophageal epithelial cells as well as in esophageal carcinoma cells, and in 12 cases of esophageal carcinoma tissues and the paired normal esophageal tissues by RT-PCR and Western blot analysis. In addition, we analyzed CENP-H protein expression in 177 clinicopathologically characterized esophageal carcinoma cases by immunohistochemistry. Statistical analyses were applied to test for prognostic and diagnostic associations.</p> <p>Results</p> <p>The level of CENP-H mRNA and protein were higher in the immortalized cells, cancer cell lines and most cancer tissues than in normal control tissues. Immunohistochemistry showed that CENP-H was expressed in 127 of 171 ESCC cases (74.3%) and in 3 of 6 esophageal adenocarcinoma cases (50%). Statistical analysis of ESCC cases showed that there was a significant difference of CENP-H expression in patients categorized according to gender (<it>P </it>= 0.013), stage (<it>P </it>= 0.023) and T classification (<it>P </it>= 0.019). Patients with lower CENP-H expression had longer overall survival time than those with higher CENP-H expression. Multivariate analysis suggested that CENP-H expression was an independent prognostic marker for esophageal carcinoma patients. A prognostic value of CENP-H was also found in the subgroup of T3~T4 and N0 tumor classification.</p> <p>Conclusion</p> <p>Our results suggest that CENP-H protein is a valuable marker of esophageal carcinoma progression. CENP-H might be used as a valuable prognostic marker for esophageal carcinoma patients.</p

Histone deacetylase inhibitors: potential targets responsible for their anti-cancer effect

The histone deacetylase inhibitors (HDACi) have demonstrated anticancer efficacy across a range of malignancies, most impressively in the hematological cancers. It is uncertain whether this clinical efficacy is attributable predominantly to their ability to induce apoptosis and differentiation in the cancer cell, or to their ability to prime the cell to other pro-death stimuli such as those from the immune system. HDACi-induced apoptosis occurs through altered expression of genes encoding proteins in both intrinsic and extrinsic apoptotic pathways; through effects on the proteasome/aggresome systems; through the production of reactive oxygen species, possibly by directly inducing DNA damage; and through alterations in the tumor microenvironment. In addition HDACi increase the immunogenicity of tumor cells and modulate cytokine signaling and potentially T-cell polarization in ways that may contribute the anti-cancer effect in vivo. Here, we provide an overview of current thinking on the mechanisms of HDACi activity, with attention given to the hematological malignancies as well as scientific observations arising from the clinical trials. We also focus on the immune effects of these agents

Search for new physics with a monojet and missing transverse energy in pp collisions at √s=7 TeV

This is the pre-print version of the Published Article which can be accessed at the link below.A study of events with missing transverse energy and an energetic jet is performed using pp collision data at a center-of-mass energy of 7 TeV. The data were collected by the CMS detector at the LHC, and correspond to an integrated luminosity of 36  pb-1. An excess of these events over standard model contributions is a signature of new physics such as large extra dimensions and unparticles. The number of observed events is in good agreement with the prediction of the standard model, and significant extension of the current limits on parameters of new physics benchmark models is achieved