GraphWeb: mining heterogeneous biological networks for gene modules with functional significance

Deciphering heterogeneous cellular networks with embedded modules is a great challenge of current systems biology. Experimental and computational studies construct complex networks of molecules that describe various aspects of the cell such as transcriptional regulation, protein interactions and metabolism. Groups of interacting genes and proteins reflect network modules that potentially share regulatory mechanisms and relate to common function. Here, we present GraphWeb, a public web server for biological network analysis and module discovery. GraphWeb provides methods to: (1) integrate heterogeneous and multispecies data for constructing directed and undirected, weighted and unweighted networks; (ii) discover network modules using a variety of algorithms and topological filters and (iii) interpret modules using functional knowledge of the Gene Ontology and pathways, as well as regulatory features such as binding motifs and microRNA targets. GraphWeb is designed to analyse individual or multiple merged networks, search for conserved features across multiple species, mine large biological networks for smaller modules, discover novel candidates and connections for known pathways and compare results of high-throughput datasets. The GraphWeb is available at http://biit.cs.ut.ee/graphweb/

Last Call for RHIC Predictions

This paper contains the individual contributions of all speakers of the session on 'Last Call for RHIC Predictions' at Quark Matter 99, and a summary by the convenor.Comment: 56 pages, psfig, epsf, epsfig, graphicx style files required, Proceedings of the XIV Int. Conf. on Nucleus-Nucleus Collisions, Quark Matter 99, Torino, Italy, May 10 - 15, 1999. Typographical mistakes corrected and figure numbers change

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

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

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

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

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

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

A Systematic Analysis of Cell Cycle Regulators in Yeast Reveals That Most Factors Act Independently of Cell Size to Control Initiation of Division

Upstream events that trigger initiation of cell division, at a point called START in yeast, determine the overall rates of cell proliferation. The identity and complete sequence of those events remain unknown. Previous studies relied mainly on cell size changes to identify systematically genes required for the timely completion of START. Here, we evaluated panels of non-essential single gene deletion strains for altered DNA content by flow cytometry. This analysis revealed that most gene deletions that altered cell cycle progression did not change cell size. Our results highlight a strong requirement for ribosomal biogenesis and protein synthesis for initiation of cell division. We also identified numerous factors that have not been previously implicated in cell cycle control mechanisms. We found that CBS, which catalyzes the synthesis of cystathionine from serine and homocysteine, advances START in two ways: by promoting cell growth, which requires CBS's catalytic activity, and by a separate function, which does not require CBS's catalytic activity. CBS defects cause disease in humans, and in animals CBS has vital, non-catalytic, unknown roles. Hence, our results may be relevant for human biology. Taken together, these findings significantly expand the range of factors required for the timely initiation of cell division. The systematic identification of non-essential regulators of cell division we describe will be a valuable resource for analysis of cell cycle progression in yeast and other organisms

Prenatal Arsenic Exposure Alters Gene Expression in the Adult Liver to a Proinflammatory State Contributing to Accelerated Atherosclerosis

The mechanisms by which environmental toxicants alter developmental processes predisposing individuals to adult onset chronic disease are not well-understood. Transplacental arsenic exposure promotes atherogenesis in apolipoprotein E-knockout (ApoE−/−) mice. Because the liver plays a central role in atherosclerosis, diabetes and metabolic syndrome, we hypothesized that accelerated atherosclerosis may be linked to altered hepatic development. This hypothesis was tested in ApoE−/− mice exposed to 49 ppm arsenic in utero from gestational day (GD) 8 to term. GD18 hepatic arsenic was 1.2 µg/g in dams and 350 ng/g in fetuses. The hepatic transcriptome was evaluated by microarray analysis to assess mRNA and microRNA abundance in control and exposed pups at postnatal day (PND) 1 and PND70. Arsenic exposure altered postnatal developmental trajectory of mRNA and microRNA profiles. We identified an arsenic exposure related 51-gene signature at PND1 and PND70 with several hubs of interaction (Hspa8, IgM and Hnf4a). Gene ontology (GO) annotation analyses indicated that pathways for gluconeogenesis and glycolysis were suppressed in exposed pups at PND1, and pathways for protein export, ribosome, antigen processing and presentation, and complement and coagulation cascades were induced by PND70. Promoter analysis of differentially-expressed transcripts identified enriched transcription factor binding sites and clustering to common regulatory sites. SREBP1 binding sites were identified in about 16% of PND70 differentially-expressed genes. Western blot analysis confirmed changes in the liver at PND70 that included increases of heat shock protein 70 (Hspa8) and active SREBP1. Plasma AST and ALT levels were increased at PND70. These results suggest that transplacental arsenic exposure alters developmental programming in fetal liver, leading to an enduring stress and proinflammatory response postnatally that may contribute to early onset of atherosclerosis. Genes containing SREBP1 binding sites also suggest pathways for diabetes mellitus and rheumatoid arthritis, both diseases that contribute to increased cardiovascular disease in humans