Discovery of molecular subtypes in leiomyosarcoma through integrative molecular profiling.

Leiomyosarcoma (LMS) is a soft tissue tumor with a significant degree of morphologic and molecular heterogeneity. We used integrative molecular profiling to discover and characterize molecular subtypes of LMS. Gene expression profiling was performed on 51 LMS samples. Unsupervised clustering showed three reproducible LMS clusters. Array comparative genomic hybridization (aCGH) was performed on 20 LMS samples and showed that the molecular subtypes defined by gene expression showed distinct genomic changes. Tumors from the muscle-enriched cluster showed significantly increased copy number changes (P=0.04). A majority of the muscle-enriched cases showed loss at 16q24, which contains Fanconi anemia, complementation group A, known to have an important role in DNA repair, and loss at 1p36, which contains PRDM16, of which loss promotes muscle differentiation. Immunohistochemistry (IHC) was performed on LMS tissue microarrays (n=377) for five markers with high levels of messenger RNA in the muscle-enriched cluster (ACTG2, CASQ2, SLMAP, CFL2 and MYLK) and showed significantly correlated expression of the five proteins (all pairwise P<0.005). Expression of the five markers was associated with improved disease-specific survival in a multivariate Cox regression analysis (P<0.04). In this analysis that combined gene expression profiling, aCGH and IHC, we characterized distinct molecular LMS subtypes, provided insight into their pathogenesis, and identified prognostic biomarkers

The Evaluation Of Molecular Similarity And Molecular Diversity Methods Using Biological Activity Data

This paper reviews the techniques available for quantifying the effectiveness of methods for molecule similarity and molecular diversity, focusing in particular on similarity searching and on compound selection procedures. The evaluation criteria considered are based on biological activity data, both qualitative and quantitative, with rather different criteria needing to be used depending on the type of data available

Evaluation of protein surface roughness index using its heat denatured aggregates

Recent research works on potential of different protein surface describing parameters to predict protein surface properties gained significance for its possible implication in extracting clues on protein's functional site. In this direction, Surface Roughness Index, a surface topological parameter, showed its potential to predict SCOP-family of protein. The present work stands on the foundation of these works where a semi-empirical method for evaluation of Surface Roughness Index directly from its heat denatured protein aggregates (HDPA) was designed and demonstrated successfully. The steps followed consist, the extraction of a feature, Intensity Level Multifractal Dimension (ILMFD) from the microscopic images of HDPA, followed by the mapping of ILMFD into Surface Roughness Index (SRI) through recurrent backpropagation network (RBPN). Finally SRI for a particular protein was predicted by clustering of decisions obtained through feeding of multiple data into RBPN, to obtain general tendency of decision, as well as to discard the noisy dataset. The cluster centre of the largest cluster was found to be the best match for mapping of Surface Roughness Index of each protein in our study. The semi-empirical approach adopted in this paper, shows a way to evaluate protein's surface property without depending on its already evaluated structure

Structure-function mapping of a heptameric module in the nuclear pore complex.

The nuclear pore complex (NPC) is a multiprotein assembly that serves as the sole mediator of nucleocytoplasmic exchange in eukaryotic cells. In this paper, we use an integrative approach to determine the structure of an essential component of the yeast NPC, the ~600-kD heptameric Nup84 complex, to a precision of ~1.5 nm. The configuration of the subunit structures was determined by satisfaction of spatial restraints derived from a diverse set of negative-stain electron microscopy and protein domain-mapping data. Phenotypic data were mapped onto the complex, allowing us to identify regions that stabilize the NPC's interaction with the nuclear envelope membrane and connect the complex to the rest of the NPC. Our data allow us to suggest how the Nup84 complex is assembled into the NPC and propose a scenario for the evolution of the Nup84 complex through a series of gene duplication and loss events. This work demonstrates that integrative approaches based on low-resolution data of sufficient quality can generate functionally informative structures at intermediate resolution

The Extraction of Community Structures from Publication Networks to Support Ethnographic Observations of Field Differences in Scientific Communication

The scientific community of researchers in a research specialty is an important unit of analysis for understanding the field specific shaping of scientific communication practices. These scientific communities are, however, a challenging unit of analysis to capture and compare because they overlap, have fuzzy boundaries, and evolve over time. We describe a network analytic approach that reveals the complexities of these communities through examination of their publication networks in combination with insights from ethnographic field studies. We suggest that the structures revealed indicate overlapping sub- communities within a research specialty and we provide evidence that they differ in disciplinary orientation and research practices. By mapping the community structures of scientific fields we aim to increase confidence about the domain of validity of ethnographic observations as well as of collaborative patterns extracted from publication networks thereby enabling the systematic study of field differences. The network analytic methods presented include methods to optimize the delineation of a bibliographic data set in order to adequately represent a research specialty, and methods to extract community structures from this data. We demonstrate the application of these methods in a case study of two research specialties in the physical and chemical sciences.Comment: Accepted for publication in JASIS