Pathogenic Roles for RNASET2 in Clear Cell Renal Cell Carcinoma

A specific splicing isoform of RNASET2 is associated with worse oncologic outcomes in clear cell renal cell carcinoma (ccRCC). However, the interplay between wild-type RNASET2 and its splice variant and how this might contribute to the pathogenesis of ccRCC remains poorly understood. We sought to better understand the relationship of RNASET2 in the pathogenesis of ccRCC and the interplay with a pathogenic splicing isoform (RNASET2-SV) and the tumor immune microenvironment. Using data from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium, we correlated clinical variables to RNASET2 expression and the presence of a specific RNASET2-SV. Immunohistochemical staining with matched RNA sequencing of ccRCC patients was then utilized to understand the spatial relationships of RNASET2 with immune cells. Finally, in vitro studies were performed to demonstrate the oncogenic role of RNASET2 and highlight its potential mechanisms. RNASET2 gene expression is associated with higher grade tumors and worse overall survival in The Cancer Genome Atlas cohort. The presence of the RNASET2-SV was associated with increased expression of the wild-type RNASET2 protein and epigenetic modifications of the gene. Immunohistochemical staining revealed increased intracellular accumulation of RNASET2 in patients with increased RNA expression of RNASET2-SV. In vitro experiments reveal that this accumulation results in increased cell proliferation, potentially from altered metabolic pathways. RNASET2 exhibits a tumor-promoting role in the pathogenesis of ccRCC that is increased in the presence of a specific RNASET2-SV and associated with changes in the cellular localization of the protein.

Outcomes of Patients with Transformed Diffuse Large B-Cell Lymphoma (DLBCL)

PURPOSE/OBJECTIVE(S)

There is limited data regarding the results of treating transformed Diffuse Large B-Cell Lymphoma, including the influence of radiation therapy on their overall prognosis. Thus, we aimed to investigate the clinical outcomes of transformed DLBCL patients treated at a single institution.

MATERIALS/METHODS

We reviewed clinical features and outcomes of 27 patients with biopsy confirmed transformed Diffuse Large B-cell Lymphoma (DLBCL) treated at a single institution from 2005 and 2014. Response to therapy was based on the Deauville criteria. Kaplan-Meier method was used to estimate time to event outcomes and compared using log-rank tests. Associations between local recurrence and relevant clinical variables were analyzed using logistic regression.

RESULTS

The median age of patients was 63 (43-84). Eleven patients (40.7%) presented with bulky disease. The majority of patients (n = 16, 59.3%) had the activated B-cell (ABC) subtype, while 11 (40.7%) patients had germinal center B-cell (GCB) subtype. Most of the patients had early-stage disease 19 (70.4%). Double- and triple-hit expression was noted in 6 (22.2%) and 3 (11.1%) patients, respectively. The median international prognostic index (IPI) was 2. Median follow up was 37 months (range 2-168). Twelve (44.4%) patients received consolidative RT after systemic therapy with a median dose of 36 Gy (30-45). At 72 months, our RT cohort had an overall survival (OS), relapse-free survival (RFS) and local control (LC) rates of 63%, 64% and 81%, respectively. The OS did not differ between patients that received RT compared to those who did not (p = 0.124), although RT conferred statistically significant improvement in OS on MVA (HR 0.07; 95% CI, 0.007 to 0.718; p = 0.025). In the group that received RT, local control was worse among patients with double or triple-hit disease (p = 0.034).

CONCLUSION

Patients with transformed Diffuse Large B-cell Lymphoma treated with RT may have better outcomes than patients who did not receive RT. Presence of translocation (double-hit and/or triple-hit lymphomas) was significantly associated with worse local control in our RT cohort.

Sparse clusterability: testing for cluster structure in high dimensions

BACKGROUND

Cluster analysis is utilized frequently in scientific theory and applications to separate data into groups. A key assumption in many clustering algorithms is that the data was generated from a population consisting of multiple distinct clusters. Clusterability testing allows users to question the inherent assumption of latent cluster structure, a theoretical requirement for meaningful results in cluster analysis.

RESULTS

This paper proposes methods for clusterability testing designed for high-dimensional data by utilizing sparse principal component analysis. Type I error and power of the clusterability tests are evaluated using simulated data with different types of cluster structure in high dimensions. Empirical performance of the new methods is evaluated and compared with prior methods on gene expression, microarray, and shotgun proteomics data. Our methods had reasonably low Type I error and maintained power for many datasets with a variety of structures and dimensions. Cluster structure was not detectable in other datasets with spatially close clusters.

CONCLUSION

This is the first analysis of clusterability testing on both simulated and real-world high-dimensional data.

An original fibular shortening osteotomy technique in tibiotalar arthrodesis

Tibiotalar arthrodesis (TTA) is the gold-standard treatment for advanced ankle osteoarthritis. We describe an original fibular shortening osteotomy (FSO) performed during TTA, to allow complete talar ascension and reduce the nonunion rate. Forty-two FSOs were associated to TTA (19 fixed by cross-screwing and 23 by anatomic plates) and assessed clinically and radiographically. At 24.7 months' follow-up, fusion rates were 97.6% for TTA and 100% for FSO, with mean fusion time of 5.2 months. One infection and 1 nonunion (4.7%) required further surgery, with complete resolution. Radiological and clinical outcome in TTA, lack of specific complications of FSO and ease of implementation encourage us to publish the technique.

General and specific combining abilities in a maize (Zea mays L.) test-cross hybrid panel: relative importance of population structure and genetic divergence between parents

General and specific combining abilities of maize hybrids between 288 inbred lines and three tester lines were highly related to population structure and genetic distance inferred from SNP data. Many studies have attempted to provide reliable and quick methods to identify promising parental lines and combinations in hybrid breeding programs. Since the 1950s, maize germplasm has been organized into heterotic groups to facilitate the exploitation of heterosis. Molecular markers have proven efficient tools to address the organization of genetic diversity and the relationship between lines or populations. The aim of the present work was to investigate to what extent marker-based evaluations of population structure and genetic distance may account for general (GCA) and specific (SCA) combining ability components in a population composed of 800 inter and intra-heterotic group hybrids obtained by crossing 288 inbred lines and three testers. Our results illustrate a strong effect of groups identified by population structure analysis on both GCA and SCA components. Including genetic distance between parental lines of hybrids in the model leads to a significant decrease of SCA variance component and an increase in GCA variance component for all the traits. The latter suggests that this approach can be efficient to better estimate the potential combining ability of inbred lines when crossed with unrelated lines, and limits the consequences of tester choice. Significant residual GCA and SCA variance components of models taking into account structure and/or genetic distance highlight the variation available for breeding programs within structure groups.

Association mapping for phenology and plant architecture in maize shows higher power for developmental traits compared with growth influenced traits

Plant architecture, phenology and yield components of cultivated plants have repeatedly been shaped by selection to meet human needs and adaptation to different environments. Here we assessed the genetic architecture of 24 correlated maize traits that interact during plant cycle. Overall, 336 lines were phenotyped in a network of 9 trials and genotyped with 50K single-nucleotide polymorphisms. Phenology was the main factor of differentiation between genetic groups. Then yield components distinguished dents from lower yielding genetic groups. However, most of trait variation occurred within group and we observed similar overall and within group correlations, suggesting a major effect of pleiotropy and/or linkage. We found 34 quantitative trait loci (QTLs) for individual traits and six for trait combinations corresponding to PCA coordinates. Among them, only five were pleiotropic. We found a cluster of QTLs in a 5 Mb region around Tb1 associated with tiller number, ear row number and the first PCA axis, the latter being positively correlated to flowering time and negatively correlated to yield. Kn1 and ZmNIP1 were candidate genes for tillering, ZCN8 for leaf number and Rubisco Activase 1 for kernel weight. Experimental repeatabilities, numbers of QTLs and proportion of explained variation were higher for traits related to plant development such as tillering, leaf number and flowering time, than for traits affected by growth such as yield components. This suggests a simpler genetic determinism with larger individual QTL effects for the first category.

Dent and Flint maize diversity panels reveal important genetic potential for increasing biomass production

Genetic and phenotypic analysis of two complementary maize panels revealed an important variation for biomass yield. Flowering and biomass QTL were discovered by association mapping in both panels. The high whole plant biomass productivity of maize makes it a potential source of energy in animal feeding and biofuel production. The variability and the genetic determinism of traits related to biomass are poorly known. We analyzed two highly diverse panels of Dent and Flint lines representing complementary heterotic groups for Northern Europe. They were genotyped with the 50 k SNP-array and phenotyped as hybrids (crossed to a tester of the complementary pool) in a western European field trial network for traits related to flowering time, plant height, and biomass. The molecular information revealed to be a powerful tool for discovering different levels of structure and relatedness in both panels. This study revealed important variation and potential genetic progress for biomass production, even at constant precocity. Association mapping was run by combining genotypes and phenotypes in a mixed model with a random polygenic effect. This permitted the detection of significant associations, confirming height and flowering time quantitative trait loci (QTL) found in literature. Biomass yield QTL were detected in both panels but were unstable across the environments. Alternative kinship estimator only based on markers unlinked to the tested SNP increased the number of significant associations by around 40% with a satisfying control of the false positive rate. This study gave insights into the variability and the genetic architectures of biomass-related traits in Flint and Dent lines and suggests important potential of these two pools for breeding high biomass yielding hybrid varieties.

RASS: a web server for RNA alignment in the joint sequence-structure space

Comparison of ribonucleic acid (RNA) molecules is important for revealing their evolutionary relationships, predicting their functions and predicting their structures. Many methods have been developed for comparing RNAs using either sequence or three-dimensional (3D) structure (backbone geometry) information. Sequences and 3D structures contain non-overlapping sets of information that both determine RNA functions. When comparing RNA 3D structures, both types of information need to be taken into account. However, few methods compare RNA structures using both sequence and 3D structure information. Recently, we have developed a new method based on elastic shape analysis (ESA) that compares RNA molecules by combining both sequence and 3D structure information. ESA treats RNA structures as 3D curves with sequence information encoded on additional coordinates so that the alignment can be performed in the joint sequence-structure space. The similarity between two RNA molecules is quantified by a formal distance, geodesic distance. In this study, we implement a web server for the method, called RASS, to make it publicly available to research community. The web server is located at http://cloud.stat.fsu.edu/RASS/.

RNA global alignment in the joint sequence-structure space using elastic shape analysis

The functions of RNAs, like proteins, are determined by their structures, which, in turn, are determined by their sequences. Comparison/alignment of RNA molecules provides an effective means to predict their functions and understand their evolutionary relationships. For RNA sequence alignment, most methods developed for protein and DNA sequence alignment can be directly applied. RNA 3-dimensional structure alignment, on the other hand, tends to be more difficult than protein structure alignment due to the lack of regular secondary structures as observed in proteins. Most of the existing RNA 3D structure alignment methods use only the backbone geometry and ignore the sequence information. Using both the sequence and backbone geometry information in RNA alignment may not only produce more accurate classification, but also deepen our understanding of the sequence-structure-function relationship of RNA molecules. In this study, we developed a new RNA alignment method based on elastic shape analysis (ESA). ESA treats RNA structures as three dimensional curves with sequence information encoded on additional dimensions so that the alignment can be performed in the joint sequence-structure space. The similarity between two RNA molecules is quantified by a formal distance, geodesic distance. Based on ESA, a rigorous mathematical framework can be built for RNA structure comparison. Means and covariances of full structures can be defined and computed, and probability distributions on spaces of such structures can be constructed for a group of RNAs. Our method was further applied to predict functions of RNA molecules and showed superior performance compared with previous methods when tested on benchmark datasets. The programs are available at http://stat.fsu.edu/ ∼jinfeng/ESA.html.

[Development of an antigen for the diagnosis of Kilham rat parvovirus by hemagglutination inhibition test]

An antigen of rat parvovirus (Kilham virus) was developed for the diagnosis of viral infection in rat colonies by using hemagglutination inhibition (HAI) test. Primary cell cultures from rat embryos were infected with Kilham rat virus. Infected cells obtained at different time post infection were scraped, centrifuged, concentrated one hundred times, sonicated and centrifuged again. The supernatants obtained were titrated by hemagglutination. The specificity was confirmed with positive and negative reference sera. Ninety eight serum samples were studied by using HAI test. The results coincided with those obtained in a reference laboratory. Kilham rat parvovirus antigen obtained from 5 days-infected-cells was specific, sensitive, easy to prepare, with a high yield and it is useful to detect this virus in experimental and production rat colonies.