A Framework for XML-based Integration of Data, Visualization and Analysis in a Biomedical Domain

Biomedical data are becoming increasingly complex and heterogeneous in nature. The data are stored in distributed information systems, using a variety of data models, and are processed by increasingly more complex tools that analyze and visualize them. We present in this paper our framework for integrating biomedical research data and tools into a unique Web front end. Our framework is applied to the University of Washington’s Human Brain Project. Specifically, we present solutions to four integration tasks: definition of complex mappings from relational sources to XML, distributed XQuery processing, generation of heterogeneous output formats, and the integration of heterogeneous data visualization and analysis tools

Most viral peptides displayed by class I MHC on infected cells are immunogenic

CD8+ T cells are essential effectors in antiviral immunity, recognizing short virus-derived peptides presented by MHC class I (pMHCI) on the surface of infected cells. However, the fraction of viral pMHCI on infected cells that are immunogenic has not been shown for any virus. To approach this fundamental question, we used peptide sequencing by high-resolution mass spectrometry to identify more than 170 vaccinia virus pMHCI presented on infected mouse cells. Next, we screened each peptide for immunogenicity in multiple virus-infected mice, revealing a wide range of immunogenicities. A surprisingly high fraction (>80%) of pMHCI were immunogenic in at least one infected mouse, and nearly 40% were immunogenic across more than half of the mice screened. The high number of peptides found to be immunogenic and the distribution of responses across mice give us insight into the specificity of antiviral CD8+ T cell responses.This work was supported by a Project Grant from the National Health and Medical Research Council Australia (NHMRC) (APP1084283) (to D.C.T., A.W.P., and N.P.C.); an NHMRC Senior Research Fellowship (APP1104329) (to D.C.T.); an NHMRC Principal Research Fellowship (APP1137739) (to A.W.P.); and a Viertel Fellowship, ARC Future Fellowship, and NHMRC Program Grant (APP1071916) (to N.L.L.G.)

Genotype-free demultiplexing of pooled single-cell RNA-seq.

A variety of methods have been developed to demultiplex pooled samples in a single cell RNA sequencing (scRNA-seq) experiment which either require hashtag barcodes or sample genotypes prior to pooling. We introduce scSplit which utilizes genetic differences inferred from scRNA-seq data alone to demultiplex pooled samples. scSplit also enables mapping clusters to original samples. Using simulated, merged, and pooled multi-individual datasets, we show that scSplit prediction is highly concordant with demuxlet predictions and is highly consistent with the known truth in cell-hashing dataset. scSplit is ideally suited to samples without external genotype information and is available at: https://github.com/jon-xu/scSplit

The Small Molecule Antagonist KCI807 Disrupts Association of the Amino-Terminal Domain of the Androgen Receptor with ELK1 by Modulating the Adjacent DNA Binding Domain

The androgen receptor (AR) is a crucial coactivator of ELK1 for prostate cancer (PCa) growth, associating with ELK1 through two peptide segments (358-457 and 514-557) within the amino-terminal domain (NTD) of AR. The small-molecule antagonist 5-hydroxy-2-(3-hydroxyphenyl)chromen-4-one (KCI807) binds to AR, blocking ELK1 binding and inhibiting PCa growth. We investigated the mode of interaction of KCI807 with AR using systematic mutagenesis coupled with ELK1 coactivation assays, testing polypeptide binding and Raman spectroscopy. In full-length AR, deletion of neither ELK1 binding segment affected sensitivity of residual ELK1 coactivation to KCI807. Although the NTD is sufficient for association of AR with ELK1, interaction of the isolated NTD with ELK1 was insensitive to KCI807. In contrast, coactivation of ELK1 by the AR-V7 splice variant, comprising the NTD and the DNA binding domain (DBD), was sensitive to KCI807. Deletions and point mutations within DBD segment 558-595, adjacent to the NTD, interfered with coactivation of ELK1, and residual ELK1 coactivation by the mutants was insensitive to KCI807. In a glutathione S-transferase pull-down assay, KCI807 inhibited ELK1 binding to an AR polypeptide that included the two ELK1 binding segments and the DBD but did not affect ELK1 binding to a similar AR segment that lacked the sequence downstream of residue 566. Raman spectroscopy detected KCI807-induced conformational change in the DBD. The data point to a putative KCI807 binding pocket within the crystal structure of the DBD and indicate that either mutations or binding of KCI807 at this site will induce conformational changes that disrupt ELK1 binding to the NTD

Design and implementation of the NUV/optical widefield Star Formation Camera for the Theia Observatory

The Star Formation Camera (SFC) is a wide-field (~19'×~15', >280 arcmin^2), high-resolution (18 mas pixels) UV/optical dichroic camera designed for the Theia 4-m space-borne space telescope concept. SFC will deliver diffraction-limited images at λ > 300 nm in both a blue (190-517nm) and a red (517-1075nm) channel simultaneously. The goal is to conduct a comprehensive and systematic study of the astrophysical processes and environments relevant for the births and life cycles of stars and their planetary systems, and to investigate the range of environments, feedback mechanisms, and other factors that most affect the outcome of star and planet formation

Caring for quality of care: symbolic violence and the bureaucracies of audit.

BACKGROUND: This article considers the moral notion of care in the context of Quality of Care discourses. Whilst care has clear normative implications for the delivery of health care it is less clear how Quality of Care, something that is centrally involved in the governance of UK health care, relates to practice. DISCUSSION: This paper presents a social and ethical analysis of Quality of Care in the light of the moral notion of care and Bourdieu's conception of symbolic violence. We argue that Quality of Care bureaucracies show significant potential for symbolic violence or the domination of practice and health care professionals. This generates problematic, and unintended, consequences that can displace the goals of practice. SUMMARY: Quality of Care bureaucracies may have unintended consequences for the practice of health care. Consistent with feminist conceptions of care, Quality of Care 'audits' should be reconfigured so as to offer a more nuanced and responsive form of evaluation

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

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

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

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment