562 research outputs found

    Comparing Union and Nonunion Staff Perceptions of the Higher Education Work Environment

    Full text link
    Evidence of substantial growth in unionization among university noninstructional staff over the past 20 years (Hurd and Woodhead, 1987) and the emergence of a quality movement in higher education linking employee attitudes toward the work environment with increased productivity point to the need for additional research into union and nonunion staff perceptions of the work environment. This paper describes a conceptually oriented, exploratory study of the university work environment as perceived and defined by union and nonunion noninstructional staff.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43620/1/11162_2004_Article_423996.pd

    COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer

    Get PDF
    COSMIC (http://www.sanger.ac.uk/cosmic) curates comprehensive information on somatic mutations in human cancer. Release v48 (July 2010) describes over 136 000 coding mutations in almost 542 000 tumour samples; of the 18 490 genes documented, 4803 (26%) have one or more mutations. Full scientific literature curations are available on 83 major cancer genes and 49 fusion gene pairs (19 new cancer genes and 30 new fusion pairs this year) and this number is continually increasing. Key amongst these is TP53, now available through a collaboration with the IARC p53 database. In addition to data from the Cancer Genome Project (CGP) at the Sanger Institute, UK, and The Cancer Genome Atlas project (TCGA), large systematic screens are also now curated. Major website upgrades now make these data much more mineable, with many new selection filters and graphics. A Biomart is now available allowing more automated data mining and integration with other biological databases. Annotation of genomic features has become a significant focus; COSMIC has begun curating full-genome resequencing experiments, developing new web pages, export formats and graphics styles. With all genomic information recently updated to GRCh37, COSMIC integrates many diverse types of mutation information and is making much closer links with Ensembl and other data resources

    I-TRAP: A method to identify transcriptional regulator activated promoters

    Get PDF
    BACKGROUND: The differential expression of virulence genes is often used by microbial pathogens in adapting to the environment of their host. The differential expression of such sets of genes can be regulated by RNA polymerase sigma factors. Some sigma factors are differentially expressed, which can provide a means to identifying other differentially expressed genes such as those whose expression are controlled by the sigma factor. METHODS: To identify sigma factor-regulated genes, we developed a method, termed I-TRAP, for the identification of transcriptional regulator activated promoters. The I-TRAP method is based on the fact that some genes will be differentially expressed in the presence and absence of a transcriptional regulator. I-TRAP uses a DNA library in a promoter-trap vector that contains two reporter genes, one to allow the selection of active promoters in the presence of the transcriptional regulator and a second to allow screening for promoter activity in the absence of the transcriptional regulator. RESULTS: To illustrate the development and use of the I-TRAP approach, the construction of the vectors, host strains, and library necessary to identify SigmaE-regulated genes of Mycobacterium tuberculosis is described. CONCLUSION: The I-TRAP method should be a versatile and useful method for identifying and characterizing promoter activity under a variety of conditions and in response to various regulatory proteins. In our study, we isolated 360 clones that may contain plasmids carrying SigmaE-regulated promoters genes of M. tuberculosis

    The prognostic role of intragenic copy number breakpoints and identification of novel fusion genes in paediatric high grade glioma

    Get PDF
    BACKGROUND: Paediatric high grade glioma (pHGG) is a distinct biological entity to histologically similar tumours arising in older adults, and has differing copy number profiles and driver genetic alterations. As functionally important intragenic copy number aberrations (iCNA) and fusion genes begin to be identified in adult HGG, the same has not yet been done in the childhood setting. We applied an iCNA algorithm to our previously published dataset of DNA copy number profiling in pHGG with a view to identify novel intragenic breakpoints. RESULTS: We report a series of 288 iCNA events in pHGG, with the presence of intragenic breakpoints itself a negative prognostic factor. We identified an increased number of iCNA in older children compared to infants, and increased iCNA in H3F3A K27M mutant tumours compared to G34R/V and wild-type. We observed numerous gene disruptions by iCNA due to both deletions and amplifications, targeting known HGG-associated genes such as RB1 and NF1, putative tumour suppressors such as FAF1 and KIDINS220, and novel candidates such as PTPRE and KCND2. We further identified two novel fusion genes in pHGG - CSGALNACT2:RET and the complex fusion DHX57:TMEM178:MAP4K3. The latter was sequence-validated and appears to be an activating event in pHGG. CONCLUSIONS: These data expand upon our understanding of the genomic events driving these tumours and represent novel targets for therapeutic intervention in these poor prognosis cancers of childhood.We are grateful for support from the Rosetrees Trust, the Brain Tumour Charity and Fundacao para a Ciencia e Tecnologia, Portugal (PhD Studentship SFRH/BD/33473/2008). DC, AM, LB and CJ acknowledge NHS funding to the Biomedical Research Centre

    An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

    Get PDF
    For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

    Get PDF
    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

    Get PDF
    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts
    corecore