Project description:Purpose Integrated genomics approaches have identified at least four distinct biological variants in medulloblastoma: WNT, SHH, group C, and group D. Non-WNT/Non-SHH tumors are associated with metastatic dissemination and an unfavorable prognosis. Additional markers may enhance outcome prediction in Non-WNT/Non-SHH medulloblastomas. Experimental Design We combined transcriptomic and DNA copy-number analyses for 64 primary medulloblastomas. Bioinformatic tools were applied to discover marker genes of molecular variants. Differentially expressed transcripts were evaluated for prognostic value in the screening cohort. Immunopositivity for FSTL5 was correlated with molecular and prognostic subgroups for 235 non-overlapping medulloblastoma samples on two independent tissue microarrays (TMA). Results Unsupervised clustering analyses of transcriptome profiles confirmed four distinct molecular variants. Stable subgroup separation was achieved using only the 300 most varying transcripts. Specific distributions of clinical and molecular characteristics were noted for each cluster. Distinct expression patterns of FSTL5 in each molecular subgroup were confirmed by quantitative real-time PCR. Immunopositivity of FSTL5 identified a large cohort of patients (84 of 235 patients; 36%) at high risk for relapse and death. Importantly, over 50% of Non-WNT/Non-SHH tumors displayed FSTL5 negativity, delineating a large patient cohort with an excellent prognosis who would be considered intermediate/high-risk based on current molecular subtyping. Conclusions Comprehensive analyses of transcriptomic and genetic alterations delineate four distinct variants of medulloblastoma. The addition of FSTL5 immunohistochemistry to existing molecular stratification schemes can effectively identify those Non-WNT/Non-SHH tumors with a poor outcome. Immunohistochemical staining for FSTL5 could be a high-quality and practical tool for stratification and prognostication in future clinical trials of medulloblastoma. Whole-genome transcriptional profiling of human medulloblastomas. Subgrouping based on mRNA expression profiles. Fresh frozen tumor material was collected during tumor resection. Dye-swap design used for expression profiling. Reference was a pool of normal cerebellum tissue from 24 donors. Gene expression profiles illustrate distinct expression pattern at diagnosis. This submission represents the gene expression component of the study.
Project description:Sampling the natural world and built environment underpins much of science, yet systems for managing material samples and associated (meta)data are fragmented across institutional catalogs, practices for identification, and discipline-specific (meta)data standards. The Internet of Samples (iSamples) is a standards-based collaboration to uniquely, consistently, and conveniently identify material samples, record core metadata about them, and link them to other samples, data, and research products. iSamples extends existing resources and best practices in data stewardship to render a cross-domain cyberinfrastructure that enables transdisciplinary research, discovery, and reuse of material samples in 21st century natural science.
Project description:Expression and differential expression analysis of breast cancer patient samples and normal samples from breast reduction operations. Fresh frozen tumor biopsies from early breast cancer cases were collected from 920 patients included in the Oslo Micrometastasis (MicMa) Study -- Oslo I from various hospitals between 1995 and 1998 (Naume et al. "Presence of bone marrow micrometastasis is associated with different recurrence risk within molecular subtypes of breast cancer." Mol Oncol 2007, 1: 160-171; Wiedswang et al. "Detection of isolated tumor cells in bone marrow is an independent prognostic factor in breast cancer." J Clin Oncol 2003, 21: 3469-3478.). Breast tissue samples from breast reduction operations were provided from the Colosseum Clinic, Oslo in co-operation with Akershus University Hospital, Lørenskog and are referred to as normal tissue. Expression and differential expression was assessed by using an Agilent custom microarray (244K, nONCOchip). The custom array contains probes for genomic regions that have been found to be differentially expressed (i) throughout cell cycle progression, (ii) in response to the anti-proliferative and pro-apoptotic p53 pathway, and (iii) the anti-apoptotic and pro-proliferative STAT-3 pathway by employing TAS (Kampa et al. "Novel RNAs identified from an in-depth analysis of the transcriptome of human chromosomes 21 and 22". Genome Research, 14:331-42, 2004). In addition, the Agilent custom array (244K) interrogates probes for genomic regions predicted to contain a conserved secondary structure identified by RNAz (Washietl et al. "Fast and reliable prediction of noncoding RNAs." Proc Natl Acad Sci USA. 102:2454-9, 2005.) or Evofold (Pedersen et al. "Identification and classification of conserved RNA secondary structures in the human genome." PLoS Comput Biol. 2:e33, 2006.), as well as known non-coding RNAs from public databases, and the Agilent mRNA probe set 014850. We analyzed 5 to 6 arrays each for breast cancer patient samples and normal samples.
Project description:Application of recent techniques to detect current pathogens in archival effluent samples collected and concentrated in 1987 lead to the characterization of norovirus GGII.6 Seacroft, unrecognized until 1990 in a clinical sample. Retrospective studies will likely increase our knowledge about waterborne transmission of emerging pathogens.
Project description:In analytical ultracentrifugation it is often very useful to resuspend samples in situ after sedimentation experiments for further investigation. This can be achieved by manually subjecting the entire sample cell assembly to gentle motion that causes the air bubble in the sample compartment to repeatedly move through the solution and thereby cause convection. Here we describe a cell mixing device that can accomplish the same through axial rotation and slow rocking motion. This cell mixer is low-cost, open-source, and can be easily assembled from readily available components. It can efficiently mix multiple sample cells side-by-side and may be used with various centerpiece designs.
Project description:In a typical predictive modeling task, we are asked to produce a final predictive model to employ operationally for predictions, as well as an estimate of its out-of-sample predictive performance. Typically, analysts hold out a portion of the available data, called a Test set, to estimate the model predictive performance on unseen (out-of-sample) records, thus "losing these samples to estimation." However, this practice is unacceptable when the total sample size is low. To avoid losing data to estimation, we need a shift in our perspective: we do not estimate the performance of a specific model instance; we estimate the performance of the pipeline that produces the model. This pipeline is applied on all available samples to produce the final model; no samples are lost to estimation. An estimate of its performance is provided by training the same pipeline on subsets of the samples. When multiple pipelines are tried, additional considerations that correct for the "winner's curse" need to be in place.
Project description:The application of a genomics assay to samples from a cohort is a frequently applied experimental design in cancer genomics studies. The collection and analysis of cancer sequencing data in the clinical setting is an elaborate process that may involve consenting patients, obtaining possibly-multiple DNA samples, sequencing and analysis. Many of these steps are manual. At any stage mistakes can occur that cause a DNA sample to be labelled incorrectly. However, there is a paucity of methods in the literature to identify such swaps specifically in cancer studies.Here, we introduce a simple method, HYSYS, to estimate the relatedness of samples and test for sample swaps and contamination. The test uses the concordance of homozygous SNPs between samples. The method is motivated by the observation that homozygous germline population variants rarely change in the disease and are not affected by loss of heterozygosity. Our tools include visualization and a testing framework to flag possible sample swaps. We demonstrate the utility of this approach on a small cohort.http://github.com/PapenfussLab/HaveYouSwappedYourSamples.papenfuss@wehi.edu.au.Supplementary data are available at Bioinformatics online.
Project description:The interplay between magnetism and crystal structures in three CaFe2As2 samples is studied. For the nonmagnetic quenched crystals, different crystalline domains with varying lattice parameters are found, and three phases (orthorhombic, tetragonal, and collapsed tetragonal) coexist between TS=95?K and 45?K. Annealing of the quenched crystals at 350°C leads to a strain relief through a large (~1.3%) expansion of the c-parameter and a small (~0.2%) contraction of the a-parameter, and to local ~0.2?Å displacements at the atomic-level. This annealing procedure results in the most homogeneous crystals for which the antiferromagnetic and orthorhombic phase transitions occur at TN/TS=168(1) K. In the 700°C-annealed crystal, an intermediate strain regime takes place, with tetragonal and orthorhombic structural phases coexisting between 80 to 120?K. The origin of such strong shifts in the transition temperatures are tied to structural parameters. Importantly, with annealing, an increase in the Fe-As length leads to more localized Fe electrons and higher local magnetic moments on Fe ions. Synergistic contribution of other structural parameters, including a decrease in the Fe-Fe distance, and a dramatic increase of the c-parameter, which enhances the Fermi surface nesting in CaFe2As2, are also discussed.
Project description:Contemporary genotyping and sequencing methods do not provide information on linkage phase in diploid organisms. The application of statistical methods to infer and reconstruct linkage phase in samples of diploid sequences is a potentially time- and labor-saving method. The Stephens-Smith-Donnelly (SSD) algorithm is one such method, which incorporates concepts from population genetics theory in a Markov chain-Monte Carlo technique. We applied a modified SSD method, as well as the expectation-maximization and partition-ligation algorithms, to sequence data from eight loci spanning >1 Mb on the human X chromosome. We demonstrate that the accuracy of the modified SSD method is better than that of the other algorithms and is superior in terms of the number of sites that may be processed. Also, we find phase reconstructions by the modified SSD method to be highly accurate over regions with high linkage disequilibrium (LD). If only polymorphisms with a minor allele frequency >0.2 are analyzed and scored according to the fraction of neighbor relations correctly called, reconstructions are 95.2% accurate over entire 100-kb stretches and are 98.6% accurate within blocks of high LD.