SnapShot: TCGA-Analyzed Tumors.

This SnapShot provides a list of the tumor types characterized by The Cancer Genome Atlas (TCGA) program. Key findings shown are the most relevant discoveries described in each marker paper for the tumor type.

Simulating the Impact of Sugar-Sweetened Beverage Warning Labels in Three Cities.

INTRODUCTION: A number of locations have been considering sugar-sweetened beverage point-of-purchase warning label policies to help address rising adolescent overweight and obesity prevalence. METHODS: To explore the impact of such policies, in 2016 detailed agent-based models of Baltimore, Philadelphia, and San Francisco were developed, representing their populations, school locations, and food sources, using data from various sources collected between 2005 and 2014. The model simulated, over a 7-year period, the mean change in BMI and obesity prevalence in each of the cities from sugar-sweetened beverage warning label policies. RESULTS: Data analysis conducted between 2016 and 2017 found that implementing sugar-sweetened beverage warning labels at all sugar-sweetened beverage retailers lowered obesity prevalence among adolescents in all three cities. Point-of-purchase labels with 8% efficacy (i.e., labels reducing probability of sugar-sweetened beverage consumption by 8%) resulted in the following percentage changes in obesity prevalence: Baltimore: -1.69% (95% CI= -2.75%, -0.97%, p<0.001); San Francisco: -4.08% (95% CI= -5.96%, -2.2%, p<0.001); Philadelphia: -2.17% (95% CI= -3.07%, -1.42%, p<0.001). CONCLUSIONS: Agent-based simulations showed how warning labels may decrease overweight and obesity prevalence in a variety of circumstances with label efficacy and literacy rate identified as potential drivers. Implementing a warning label policy may lead to a reduction in obesity prevalence. Focusing on warning label design and store compliance, especially at supermarkets, may further increase the health impact.

Genetic Intersection of Tsix and Hedgehog Signaling during the Initiation of X-Chromosome Inactivation.

X-chromosome inactivation (XCI) silences one X chromosome in the female mammal and is essential to peri-implantation development. XCI is thought to be cell autonomous, with all factors required being produced within each cell. Nevertheless, external cues may exist. Here, we search for such developmental signals by combining bioinformatic, biochemical, and genetic approaches. Using ex vivo and in vivo models, we identify the Hedgehog (HH) paracrine system as a candidate signaling cascade. HH signaling keeps XCI in check in pluripotent cells and is transduced by GLI transcription factors to binding sites in Tsix, the antisense repressor of XCI. GLI potentiates Tsix expression and impedes XCI. In vivo, mutating Indian Hedgehog results in a sex ratio bias against females, and the female lethality is rescued by a second-site mutation in Tsix. These data demonstrate a genetic and functional intersection between HH and XCI and support a role for intercellular signaling during XCI.

Genome-wide identification of autosomal genes with allelic imbalance of chromatin state.

In mammals, monoallelic gene expression can result from X-chromosome inactivation, genomic imprinting, and random monoallelic expression (RMAE). Epigenetic regulation of RMAE is not fully understood. Here we analyze allelic imbalance in chromatin state of autosomal genes using ChIP-seq in a clonal cell line. We identify approximately 3.7% of autosomal genes that show significant differences between chromatin states of two alleles. Allelic regulation is represented among several functional gene categories including histones, chromatin modifiers, and multiple early developmental regulators. Most cases of allelic skew are produced by quantitative differences between two allelic chromatic states that belong to the same gross type (active, silent, or bivalent). Combinations of allelic states of different types are possible but less frequent. When different chromatin marks are skewed on the same gene, their skew is coordinated as a result of quantitative relationships between these marks on each individual allele. Finally, combination of allele-specific densities of chromatin marks is a quantitative predictor of allelic skew in gene expression.

Modeling The Economic And Health Impact Of Increasing Children's Physical Activity In The United States.

Increasing physical activity among children is a potentially important public health intervention. Quantifying the economic and health effects of the intervention would help decision makers understand its impact and priority. Using a computational simulation model that we developed to represent all US children ages 8-11 years, we estimated that maintaining the current physical activity levels (only 31.9 percent of children get twenty-five minutes of high-calorie-burning physical activity three times a week) would result each year in a net present value of $1.1 trillion in direct medical costs and $1.7 trillion in lost productivity over the course of their lifetimes. If 50 percent of children would exercise, the number of obese and overweight youth would decrease by 4.18 percent, averting $8.1 billion in direct medical costs and $13.8 billion in lost productivity. Increasing the proportion of children who exercised to 75 percent would avert $16.6 billion and $23.6 billion, respectively.

Widespread changes in nucleosome accessibility without changes in nucleosome occupancy during a rapid transcriptional induction.

Activation of transcription requires alteration of chromatin by complexes that increase the accessibility of nucleosomal DNA. Removing nucleosomes from regulatory sequences has been proposed to play a significant role in activation. We tested whether changes in nucleosome occupancy occurred on the set of genes that is activated by the unfolded protein response (UPR). We observed no decrease in occupancy on most promoters, gene bodies, and enhancers. Instead, there was an increase in the accessibility of nucleosomes, as measured by micrococcal nuclease (MNase) digestion and ATAC-seq (assay for transposase-accessible chromatin [ATAC] using sequencing), that did not result from removal of the nucleosome. Thus, changes in nucleosome accessibility predominate over changes in nucleosome occupancy during rapid transcriptional induction during the UPR.

Mutation of a nucleosome compaction region disrupts Polycomb-mediated axial patterning.

Nucleosomes play important structural and regulatory roles by tightly wrapping the DNA that constitutes the metazoan genome. The Polycomb group (PcG) proteins modulate nucleosomes to maintain repression of key developmental genes, including Hox genes whose temporal and spatial expression is tightly regulated to guide patterning of the anterior-posterior body axis. CBX2, a component of the mammalian Polycomb repressive complex 1 (PRC1), contains a compaction region that has the biochemically defined activity of bridging adjacent nucleosomes. Here, we demonstrate that a functional compaction region is necessary for proper body patterning, because mutating this region leads to homeotic transformations similar to those observed with PcG loss-of-function mutations. We propose that CBX2-driven nucleosome compaction is a key mechanism by which PcG proteins maintain gene silencing during mouse development.

H3K27 modifications define segmental regulatory domains in the Drosophila bithorax complex.

The bithorax complex (BX-C) in Drosophila melanogaster is a cluster of homeotic genes that determine body segment identity. Expression of these genes is governed by cis-regulatory domains, one for each parasegment. Stable repression of these domains depends on Polycomb Group (PcG) functions, which include trimethylation of lysine 27 of histone H3 (H3K27me3). To search for parasegment-specific signatures that reflect PcG function, chromatin from single parasegments was isolated and profiled. The H3K27me3 profiles across the BX-C in successive parasegments showed a 'stairstep' pattern that revealed sharp boundaries of the BX-C regulatory domains. Acetylated H3K27 was broadly enriched across active domains, in a pattern complementary to H3K27me3. The CCCTC-binding protein (CTCF) bound the borders between H3K27 modification domains; it was retained even in parasegments where adjacent domains lack H3K27me3. These findings provide a molecular definition of the homeotic domains, and implicate precisely positioned H3K27 modifications as a central determinant of segment identity.

The long noncoding RNAs NEAT1 and MALAT1 bind active chromatin sites.

Mechanistic roles for many lncRNAs are poorly understood, in part because their direct interactions with genomic loci and proteins are difficult to assess. Using a method to purify endogenous RNAs and their associated factors, we mapped the genomic binding sites for two highly expressed human lncRNAs, NEAT1 and MALAT1. We show that NEAT1 and MALAT1 localize to hundreds of genomic sites in human cells, primarily over active genes. NEAT1 and MALAT1 exhibit colocalization to many of these loci, but display distinct gene body binding patterns at these sites, suggesting independent but complementary functions for these RNAs. We also identified numerous proteins enriched by both lncRNAs, supporting complementary binding and function, in addition to unique associated proteins. Transcriptional inhibition or stimulation alters localization of NEAT1 on active chromatin sites, implying that underlying DNA sequence does not target NEAT1 to chromatin, and that localization responds to cues involved in the transcription process.

The effectiveness of cranberry products to reduce urinary tract infections in females: a literature review.

Cranberry products, especially cranberry juice, have been posited to prevent or treat urinary tract infections (UTIs) in females. Antimicrobial resistance has been correlated to repeated antibiotic treatment. Thus, evaluating cranberry products as a possible alternative to conventional antibiotic therapy is appropriate. This review of the literature evaluated research in which cranberry-based products are used to prevent or treat UTIs.

RIDDLE: reflective diffusion and local extension reveal functional associations for unannotated gene sets via proximity in a gene network.

The growing availability of large-scale functional networks has promoted the development of many successful techniques for predicting functions of genes. Here we extend these network-based principles and techniques to functionally characterize whole sets of genes. We present RIDDLE (Reflective Diffusion and Local Extension), which uses well developed guilt-by-association principles upon a human gene network to identify associations of gene sets. RIDDLE is particularly adept at characterizing sets with no annotations, a major challenge where most traditional set analyses fail. Notably, RIDDLE found microRNA-450a to be strongly implicated in ocular diseases and development. A web application is available at http://www.functionalnet.org/RIDDLE.

A census of human soluble protein complexes.

Cellular processes often depend on stable physical associations between proteins. Despite recent progress, knowledge of the composition of human protein complexes remains limited. To close this gap, we applied an integrative global proteomic profiling approach, based on chromatographic separation of cultured human cell extracts into more than one thousand biochemical fractions that were subsequently analyzed by quantitative tandem mass spectrometry, to systematically identify a network of 13,993 high-confidence physical interactions among 3,006 stably associated soluble human proteins. Most of the 622 putative protein complexes we report are linked to core biological processes and encompass both candidate disease genes and unannotated proteins to inform on mechanism. Strikingly, whereas larger multiprotein assemblies tend to be more extensively annotated and evolutionarily conserved, human protein complexes with five or fewer subunits are far more likely to be functionally unannotated or restricted to vertebrates, suggesting more recent functional innovations.

Prioritizing candidate disease genes by network-based boosting of genome-wide association data.

Network "guilt by association" (GBA) is a proven approach for identifying novel disease genes based on the observation that similar mutational phenotypes arise from functionally related genes. In principle, this approach could account even for nonadditive genetic interactions, which underlie the synergistic combinations of mutations often linked to complex diseases. Here, we analyze a large-scale, human gene functional interaction network (dubbed HumanNet). We show that candidate disease genes can be effectively identified by GBA in cross-validated tests using label propagation algorithms related to Google's PageRank. However, GBA has been shown to work poorly in genome-wide association studies (GWAS), where many genes are somewhat implicated, but few are known with very high certainty. Here, we resolve this by explicitly modeling the uncertainty of the associations and incorporating the uncertainty for the seed set into the GBA framework. We observe a significant boost in the power to detect validated candidate genes for Crohn's disease and type 2 diabetes by comparing our predictions to results from follow-up meta-analyses, with incorporation of the network serving to highlight the JAK-STAT pathway and associated adaptors GRB2/SHC1 in Crohn's disease and BACH2 in type 2 diabetes. Consideration of the network during GWAS thus conveys some of the benefits of enrolling more participants in the GWAS study. More generally, we demonstrate that a functional network of human genes provides a valuable statistical framework for prioritizing candidate disease genes, both for candidate gene-based and GWAS-based studies.

A role for central spindle proteins in cilia structure and function.

Cytokinesis and ciliogenesis are fundamental cellular processes that require strict coordination of microtubule organization and directed membrane trafficking. These processes have been intensely studied, but there has been little indication that regulatory machinery might be extensively shared between them. Here, we show that several central spindle/midbody proteins (PRC1, MKLP-1, INCENP, centriolin) also localize in specific patterns at the basal body complex in vertebrate ciliated epithelial cells. Moreover, bioinformatic comparisons of midbody and cilia proteomes reveal a highly significant degree of overlap. Finally, we used temperature-sensitive alleles of PRC1/spd-1 and MKLP-1/zen-4 in C. elegans to assess ciliary functions while bypassing these proteins' early role in cell division. These mutants displayed defects in both cilia function and cilia morphology. Together, these data suggest the conserved reuse of a surprisingly large number of proteins in the cytokinetic apparatus and in cilia.

It's the machine that matters: Predicting gene function and phenotype from protein networks.

Increasing knowledge about the organization of proteins into complexes, systems, and pathways has led to a flowering of theoretical approaches for exploiting this knowledge in order to better learn the functions of proteins and their roles underlying phenotypic traits and diseases. Much of this body of theory has been developed and tested in model organisms, relying on their relative simplicity and genetic and biochemical tractability to accelerate the research. In this review, we discuss several of the major approaches for computationally integrating proteomics and genomics observations into integrated protein networks, then applying guilt-by-association in these networks in order to identify genes underlying traits. Recent trends in this field include a rising appreciation of the modular network organization of proteins underlying traits or mutational phenotypes, and how to exploit such protein modularity using computational approaches related to the internet search algorithm PageRank. Many protein network-based predictions have recently been experimentally confirmed in yeast, worms, plants, and mice, and several successful approaches in model organisms have been directly translated to analyze human disease, with notable recent applications to glioma and breast cancer prognosis.

Modularity of stress response evolution.

Responses to extracellular stress directly confer survival fitness by means of complex regulatory networks. Despite their complexity, the networks must be evolvable because of changing ecological and environmental pressures. Although the regulatory networks underlying stress responses are characterized extensively, their mechanism of evolution remains poorly understood. Here, we examine the evolution of three candidate stress response networks (chemotaxis, competence for DNA uptake, and endospore formation) by analyzing their phylogenetic distribution across several hundred diverse bacterial and archaeal lineages. We report that genes in the chemotaxis and sporulation networks group into well defined evolutionary modules with distinct functions, phenotypes, and substitution rates as compared with control sets of randomly chosen genes. The evolutionary modules vary in both number and cohesiveness among the three pathways. Chemotaxis has five coherent modules whose distribution among species shows a clear pattern of interdependence and rewiring. Sporulation, by contrast, is nearly monolithic and seems to be inherited vertically, with three weak modules constituting early and late stages of the pathway. Competence does not seem to exhibit well defined modules either at or below the pathway level. Many of the detected modules are better understood in engineering terms than in protein functional terms, as we demonstrate using a control-based ontology that classifies gene function according to roles such as "sensor," "regulator," and "actuator." Moreover, we show that combinations of the modules predict phenotype, yet surprisingly do not necessarily correlate with phylogenetic inheritance. The architectures of these three pathways are therefore emblematic of different modes and constraints on evolution.

Parsing the effects of binding, signaling, and trafficking on the mitogenic potencies of granulocyte colony-stimulating factor analogues.

The pharmacodynamic potency of a therapeutic cytokine interacting with a cell-surface receptor can be attributed primarily to three central properties: [1] cytokine/receptor binding affinity, [2] cytokine/receptor endocytic trafficking dynamics, and [3] cytokine/receptor signaling. Thus, engineering novel or second-generation cytokines requires an understanding of the contribution of each of these to the overall cell response. We describe here an efficient method toward this goal in demonstrated application to the clinically important cytokine granulocyte colony-stimulating factor (GCSF) with a chemical analogue and a number of genetic mutants. Using a combination of simple receptor-binding and dose-response proliferation assays we construct an appropriately scaled plot of relative mitogenic potency versus ligand concentration normalized by binding affinity. Analysis of binding and proliferation data in this manner conveniently indicates which of the cytokine properties-binding, trafficking, and/or signaling-are contributing substantially to altered potency effects. For the GCSF analogues studied here, two point mutations as well as a poly(ethylene glycol) chemical conjugate were found to have increased potencies despite comparable or slightly lower affinities, and trafficking was predicted to be the responsible mechanism. A third point mutant exhibiting comparable binding affinity but reduced potency was predicted to have largely unchanged trafficking properties. Surprisingly, another mutant possessing an order-of-magnitude weaker binding affinity displayed enhanced potency, and increased ligand half-life was predicted to be responsible for this net beneficial effect. Each of these predictions was successfully demonstrated by subsequent measurements of depletion of these five analogues from cell culture medium. Thus, for the GCSF system we find that ligand trafficking dynamics can play a major role in regulating mitogenic potency. Our results demonstrate that cytokine analogues can exhibit pharmacodynamic behaviors across a diverse spectrum of "binding-potency space" and that our analysis through normalization can efficiently elucidate hypotheses for the underlying mechanisms for further dedicated testing. We have also extended the Black-Leff model of pharmacological agonism to include trafficking effects along with binding and signaling, and this model provides a framework for parsing the effects of these factors on pharmacodynamic potency.

Haplotype and linkage disequilibrium architecture for human cancer-associated genes.

To facilitate association-based linkage studies we have studied the linkage disequilibrium (LD) and haplotype architecture around five genes of interest for cancer risk: ATM, BRCA1, BRCA2, RAD51, and TP53. Single nucleotide polymorphisms (SNPs) were identified and used to construct haplotypes that span 93-200 kb per locus with an average SNP density of 12 kb. These markers were genotyped in four ethnically defined populations that contained 48 each of African Americans, Asian Americans, Hispanic Americans, and European Americans. Haplotypes were inferred using an expectation maximization (EM) algorithm, and the data were analyzed using D', R(2), Fisher's exact P-values, and the four-gamete test for recombination. LD levels varied widely between loci from continuously high LD across 200 kb to a virtual absence of LD across a similar length of genome. LD structure also varied at each gene and between populations studied. This variation indicates that the success of linkage-based studies will require a precise description of LD at each locus and in each population to be studied. One striking consistency between genes was that at each locus a modest number of haplotypes present in each population accounted for a high fraction of the total number of chromosomes. We conclude that each locus has its own genomic profile with regard to LD, and despite this there is the widespread trend of relatively low haplotype diversity. As a result, a low marker density should be adequate to identify haplotypes that represent the common variation at a locus, thereby decreasing costs and increasing efficacy of association studies.