Genetic Studies Identify Critical Biomarkers and Refine the Classification of Malignant Gliomas

Gliomagenesis is driven by a complex network of genetic alterations and while the glioma genome has been a focus of investigation for many years; critical gaps in our knowledge of this disease remain. The identification of novel molecular biomarkers remains a focus of the greater cancer community as a method to improve the consistency and accuracy of pathological diagnosis. In addition, novel molecular biomarkers are drastically needed for the identification of targets that may ultimately result in novel therapeutics aimed at improving glioma treatment. Through the identification of new biomarkers, laboratories will focus future studies on the molecular mechanisms that underlie glioma development. Here, we report a series of genomic analyses identifying novel molecular biomarkers in multiple histopathological subtypes of glioma and refine the classification of malignant gliomas. We have completed a large scale analysis of the WHO grade II-III astrocytoma exome and report frequent mutations in the chromatin modifier, alpha thalassemia mental retardation x-linked (ATRX), isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2), and mutations in tumor protein 53 (TP53) as the most frequent genetic mutations in low grade astrocytomas. Furthermore, by analyzing the status of recurrently mutated genes in 363 brain tumors, we establish that highly recurrent gene mutational signatures are an effective tool in stratifying homogeneous patient populations into distinct groups with varying outcomes, thereby capable of predicting prognosis. Next, we have established mutations in the promoter of telomerase reverse transcriptase (TERT) as a frequent genetic event in gliomas and in tissues with low rates of self renewal. We identify TERT promoter mutations as the most frequently mutated gene in primary glioblastoma. Additionally, we show that TERT promoter mutations in combination with IDH1 and IDH2 mutations are able to delineate distinct clinical tumor cohorts and are capable of predicting median overall survival more effectively than standard histopathological diagnosis alone. Taken together, these data advance our understanding of the genetic alterations that underlie the transformation of glial cells into neoplasms and we provide novel genetic biomarkers and multi – gene mutational signatures that can be utilized to refine the classification of malignant gliomas and provide opportunity for improved diagnosis.

Computational challenges in atomic, molecular and optical physics

Six challenges are discussed. These are the laser-driven helium atom; the laser-driven hydrogen molecule and hydrogen molecular ion: electron scattering (with ionization) from one-electron atoms; the vibrational and rotational structure of molecules such as H-3(+) and water at their dissociation limits; laser- heated clusters; and quantum degeneracy and Bose-Einstein condensation. The first four concern fundamental few-body systems where use of high-performance computing (HPC) is currently making possible accurate modelling from first principles. This leads to reliable predictions and support for laboratory experiment as well as true understanding of the dynamics. Important aspects of these challenges addressable only via a terascale facility are set out. Such a facility makes the last two challenges in the above list meaningfully accessible for the first time, and the scientific interest together with the prospective role for HPC in these is emphasized.

Support vector machine classification for large data sets via minimum enclosing ball clustering

Support vector machine (SVM) is a powerful technique for data classification. Despite of its good theoretic foundations and high classification accuracy, normal SVM is not suitable for classification of large data sets, because the training complexity of SVM is highly dependent on the size of data set. This paper presents a novel SVM classification approach for large data sets by using minimum enclosing ball clustering. After the training data are partitioned by the proposed clustering method, the centers of the clusters are used for the first time SVM classification. Then we use the clusters whose centers are support vectors or those clusters which have different classes to perform the second time SVM classification. In this stage most data are removed. Several experimental results show that the approach proposed in this paper has good classification accuracy compared with classic SVM while the training is significantly faster than several other SVM classifiers.

Stereochemical and mechanistic aspects of dioxygenase-catalysed benzylic hydroxylation of indene and chromane substrates

Toluene dioxygenase (TDO)-catalysed benzylic hydroxylation of indene substrates (8, 16 and 17), using whole cell cultures of Pseudomonas putida UV4, was found to yield inden-1-ol (14 and 22) and indan-1-one bioproducts (15 and 23). The formation of these bioproducts is consistent with the involvement of carbon-centred radical intermediates. TDO-catalysed oxidation of indenes 8 and 16 also gave cis-diols 13 and 18 respectively. TDO and naphthalene dioxygenase (NDO), used as both whole-cell preparations and as purified enzymes, were found to catalyse the benzylic hydroxylation of chromane 30, deuteriated (+/-)-chromane 30(D) and enantiomers (4S)-30(D) and (4R)-30(D) to yield (4R)- and (4S)-chroman-4-ols 31/31(D) respectively. The mechanism of benzylic hydroxylation of chromane 30/30(D) involves the stereoselective abstraction of a pro-R (with TDO) or a pro-S (with NDO) hydrogen atom at C-4 and a marked preference for retention of configuration.

Resolution of a taxonomic conundrum: an ultrastructural and molecular description of the life cycle of Pleistophora mulleri (Pfeiffer 1895; Georgevitch 1929)

The classification of a microsporidian parasite observed in the abdominal muscles of amphipod hosts has been repeatedly revised but still remains inconclusive. This parasite has variable spore numbers within a sporophorous vesicle and has been assigned to the genera Glugea, Pleistophora, Stempellia, and Thelohania. We used electron microscopy and molecular evidence to resolve the previous taxonomic confusion and confirm its identification as Pleistophora mulleri. The life cycle of P. mulleri is described from the freshwater amphipod host Gammarus duebeni celticus. Infection appeared as white tubular masses within the abdominal muscle of the host. Light and transmission electron microscope examination revealed the presence of an active microsporidian infection that was diffuse within the muscle block with no evidence of xenoma formation. Paucinucleate merogonial plasmodia were surrounded by an amorphous coat immediately external to the plasmalemma. The amorphous coat developed into a merontogenetic sporophorous vesicle that was present throughout sporulation. Sporogony was polysporous resulting in uninucleate spores, with a bipartite polaroplast, an anisofilar polar filament and a large posterior vacuole. SSU rDNA analysis supported the ultrastructural evidence clearly placing this parasite within the genus Pleistophora. This paper indicates that Pleistophora species are not restricted to vertebrate hosts.

Identification of gene networks associated with acute myeloid leukemia by comparative molecular methylation and expression profiling

Around 80% of acute myeloid leukemia (AML) patients achieve a complete remission, however many will relapse and ultimately die of their disease. The association between karyotype and prognosis has been studied extensively and identified patient cohorts as having favourable [e.g. t(8; 21), inv (16)/t(16; 16), t(15; 17)], intermediate [e.g. cytogenetically normal (NK-AML)] or adverse risk [e.g. complex karyotypes]. Previous studies have shown that gene expression profiling signatures can classify the sub-types of AML, although few reports have shown a similar feature by using methylation markers. The global methylation patterns in 19 diagnostic AML samples were investigated using the Methylated CpG Island Amplification Microarray (MCAM) method and CpG island microarrays containing 12,000 CpG sites. The first analysis, comparing favourable and intermediate cytogenetic risk groups, revealed significantly differentially methylated CpG sites (594 CpG islands) between the two subgroups. Mutations in the NPM1 gene occur at a high frequency (40%) within the NK-AML subgroup and are associated with a more favourable prognosis in these patients. A second analysis comparing the NPM1 mutant and wild-type research study subjects again identified distinct methylation profiles between these two subgroups. Network and pathway analysis revealed possible molecular mechanisms associated with the different risk and/or mutation sub-groups. This may result in a better classification of the risk groups, improved monitoring targets, or the identification of novel molecular therapies.

Tissue microarray study for classification of breast tumors

Clinical and pathological heterogeneity of breast cancer hinders selection of appropriate treatment for individual cases. Molecular profiling at gene or protein levels may elucidate the biological variance of tumors and provide a new classification system that correlates better with biological, clinical and prognostic parameters. We studied the immunohistochemical profile of a panel of seven important biomarkers using tumor tissue arrays. The tumor samples were then classified with a monothetic (binary variables) clustering algorithm. Two distinct groups of tumors are characterized by the estrogen receptor (ER) status and tumor grade (p = 0.0026). Four biomarkers, c-erbB2, Cox-2, p53 and VEGF, were significantly overexpressed in tumors with the ER-negative (ER-) phenotype. Eight subsets of tumors were further identified according to the expression status of VEGF, c-erbB2 and p53. The malignant potential of the ER-/VEGF+ subgroup was associated with the strong correlations of Cox-2 and c-erb132 with VEGF. Our results indicate that this molecular classification system, based on the statistical analysis of immunohistochemical profiling, is a useful approach for tumor grouping. Some of these subgroups have a relative genetic homogeneity that may allow further study of specific genetically-controlled metabolic pathways. This approach may hold great promise in rationalizing the application of different therapeutic strategies for different subgroups of breast tumors. (C) 2003 Elsevier Inc. All rights reserved.

Applied aspects of Rhodococcus genetics

Eubacteria of the genus Rhodococcus are a diverse group of microorganisms commonly found in many environmental niches from soils to seawaters and as plant and animal pathogens. They exhibit a remarkable ability to degrade many organic compounds and their economic importance is becoming increasingly apparent. Although their genetic organisation is still far from understood, there have been many advances in recent years. Reviewed here is the current knowledge of rhodococci relating to gene transfer, recombination, plasmid replication and functions, cloning vectors and reporter genes, gene expression and its control, bacteriophages, insertion sequences and genomic rearrangements. Further fundamental studies of Rhodococcus genetics and the application of genetic techniques to the these bacteria will be needed for their continued biotechnological exploitation.

Exploring statistical and population aspects of network complexity

The characterization and the definition of the complexity of objects is an important but very difficult problem that attracted much interest in many different fields. In this paper we introduce a new measure, called network diversity score (NDS), which allows us to quantify structural properties of networks. We demonstrate numerically that our diversity score is capable of distinguishing ordered, random and complex networks from each other and, hence, allowing us to categorize networks with respect to their structural complexity. We study 16 additional network complexity measures and find that none of these measures has similar good categorization capabilities. In contrast to many other measures suggested so far aiming for a characterization of the structural complexity of networks, our score is different for a variety of reasons. First, our score is multiplicatively composed of four individual scores, each assessing different structural properties of a network. That means our composite score reflects the structural diversity of a network. Second, our score is defined for a population of networks instead of individual networks. We will show that this removes an unwanted ambiguity, inherently present in measures that are based on single networks. In order to apply our measure practically, we provide a statistical estimator for the diversity score, which is based on a finite number of samples.

Defining the molecular basis for the first potent and selective orthosteric agonists of the FFA2 free fatty acid receptor

FFA2 is a G protein-coupled receptor that responds to short chain fatty acids (SCFAs) and has generated interest as a therapeutic target for metabolic and inflammatory conditions. However, definition of its functions has been slowed by a dearth of selective ligands that can distinguish it from the closely related FFA3. At present, the only selective ligands described for FFA2 suffer from either poor potency, altered signaling due to allosteric modes of action, or a lack of function at non-human orthologs of the receptor. To address the need for novel selective ligands, we synthesized two compounds potentially having FFA2 activity and examined the molecular basis of their function. These compounds were confirmed to be potent and selective FFA2 agonists that interact with the orthosteric binding site. A combination of ligand structure-activity relationship, pharmacological analysis, homology modeling, species ortholog comparisons and mutagenesis studies were then employed to define the molecular basis of selectivity and function of these ligands. From this, we identified key residues within both extracellular loop 2 (ECL2) and the transmembrane domain (TM) regions of FFA2 critical for ligand function. One of these ligands was active with reasonable potency at rodent orthologs of FFA2 and demonstrated the role of FFA2 in the regulation of lipolysis in murine 3T3-L1 adipocytes. Together, these findings describe the first potent and selective FFA2 orthosteric agonists and demonstrate key aspects of ligand interaction within the orthosteric binding site of FFA2 that will be invaluable in future ligand development at this receptor.

Classification of fundus autofluorescence patterns in early age-related macular disease

PURPOSE. To describe and classify patterns of abnormal fundus autofluorescence (FAF) in eyes with early nonexudative age-related macular disease (AMD). METHODS. FAF images were recorded in eyes with early AMD by confocal scanning laser ophthalmoscopy (cSLO) with excitation at 488 nm (argon or OPSL laser) and emission above 500 or 521 nm (barrier filter). A standardized protocol for image acquisition and generation of mean images after automated alignment was applied, and routine fundus photographs were obtained. FAF images were classified by two independent observers. The ? statistic was applied to assess intra- and interobserver variability. RESULTS. Alterations in FAF were classified into eight phenotypic patterns including normal, minimal change, focal increased, patchy, linear, lacelike, reticular, and speckled. Areas with abnormal increased or decreased FAF signals may or may not have corresponded to funduscopically visible alterations. For intraobserver variability, ? of observer I was 0.80 (95% confidence interval [CI]0.71-0.89) and of observer II, 0.74. (95% CI, 0.64-0.84). For interobserver variability, ? was 0.77 (95% CI, 0.67-0.87). CONCLUSIONS. Various phenotypic patterns of abnormal FAF can be identified with cSLO imaging. Distinct patterns may reflect heterogeneity at a cellular and molecular level in contrast to a nonspecific aging process. The results indicate that the classification system yields a relatively high degree of intra- and interobserver agreement. It may be applicable for determination of novel prognostic determinants in longitudinal natural history studies, for identification of genetic risk factors, and for monitoring of future therapeutic interventions to slow the progression of early AMD. Copyright © Association for Research in Vision and Ophthalmology.