A DNA methylation prognostic signature of glioblastoma: identification of NPTX2-PTEN-NF-kappa B nexus

Glioblastoma (GBM) is the most common, malignant adult primary tumor with dismal patient survival, yet the molecular determinants of patient survival are poorly characterized. Global methylation profile of GBM samples (our cohort; n = 44) using high-resolution methylation microarrays was carried out. Cox regression analysis identified a 9-gene methylation signature that predicted survival in GBM patients. A risk-score derived from methylation signature predicted survival in univariate analysis in our and The Cancer Genome Atlas (TCGA) cohort. Multivariate analysis identified methylation risk score as an independent survival predictor in TCGA cohort. Methylation risk score stratified the patients into low-risk and high-risk groups with significant survival difference. Network analysis revealed an activated NF-kappa B pathway association with high-risk group. NF-kappa B inhibition reversed glioma chemoresistance, and RNA interference studies identified interleukin-6 and intercellular adhesion molecule-1 as key NF-kappa B targets in imparting chemoresistance. Promoter hypermethylation of neuronal pentraxin II (NPTX2), a risky methylated gene, was confirmed by bisulfite sequencing in GBMs. GBMs and glioma cell lines had low levels of NPTX2 transcripts, which could be reversed upon methylation inhibitor treatment. NPTX2 overexpression induced apoptosis, inhibited proliferation and anchorage-independent growth, and rendered glioma cells chemosensitive. Furthermore, NPTX2 repressed NF-kappa B activity by inhibiting AKT through a p53-PTEN-dependent pathway, thus explaining the hypermethylation and downregulation of NPTX2 in NF-kappa B-activated high-risk GBMs. Taken together, a 9-gene methylation signature was identified as an independent GBM prognosticator and could be used for GBM risk stratification. Prosurvival NF-kappa B pathway activation characterized high-risk patients with poor prognosis, indicating it to be a therapeutic target. (C) 2013 AACR.

Network, nodes and nexus: systems approach to multitarget therapeutics

Systems biology is revealing multiple layers of regulatory networks that manifest spatiotemporal variations. Since genes and environment also influence the emergent property of a cell, the biological output requires dynamic understanding of various molecular circuitries. The metabolic networks continually adapt and evolve to cope with the changing milieu of the system, which could also include infection by another organism. Such perturbations of the functional networks can result in disease phenotypes, for instance tuberculosis and cancer. In order to develop effective therapeutics, it is important to determine the disease progression profiles of complex disorders that can reveal dynamic aspects and to develop mutitarget systemic therapies that can help overcome pathway adaptations and redundancy.

Directed Synthesis of Rocksalt AuCl Crystals

We report the first-time experimental realization of rocksalt AuCl crystals. Our approach involves Au(III) complexing and reduction to Au(I) using an amine-terminated surfactant in a low dielectric permittivity solvent. The low charge screening in nonpolar solvents promotes crystallization of rocksalt AuCl, in which the bonding is predominantly ionic, in preference over tetragonal AuCl. The rocksalt AuCl crystals obtained here will facilitate studies to unveil the nexus between electronic structure and crystal structure in AuCl polymorphs, and provide insights on these relationships in other polymorphic crystal systems. Our approach provides a new means for crystallizing selective polymorphs of inorganic compounds by subtly influencing the cation electronic structure by varying the dielectric permittivity of the synthesis medium. In addition, the AuCl crystals can serve as inexpensive Au(I) precursors for forming a variety of Au nanostructures.

Effect of packing density and adsorption parameters on the throughput of a thermal compressor

Vapour adsorption refrigeration systems (VAdS) have the advantage of scalability over a wide range of capacities ranging from a few watts to several kilowatts. In the first instance, the design of a system requires the characteristics of the adsorbate-adsorbent pair. Invariably, the void volume in the adsorbent reduces the throughput of the thermal compressor in a manner similar to the clearance volume in a reciprocating compressor. This paper presents a study of the activated carbon +HFC-134a (1,1,1,2-tetrafluoroethane) system as a possible pair for a typical refrigeration application. The aim of this study is to unfold the nexus between the adsorption parameters, achievable packing densities of charcoal and throughput of a thermal compressor. It is shown that for a thermal compressor, the adsorbent should not only have a high surface area, but should also be able to provide a high packing density. Given the adsorption characteristics of an adsorbent-adsorbate pair and the operating conditions, this paper discloses a method for the calculation of the minimum packing density necessary for an effective throughput of a thermal compressor. (C) 2002 Elsevier Science Ltd. All rights reserved.