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  • 1
    Publication Date: 2013-10-30
    Description: Presently, there are few validated biomarkers that can predict survival or treatment response for non-small cell lung cancer (NSCLC) and most are based on tumor markers. Biomarkers based on germ line DNA variations represent a valuable complementary strategy, which could have translational implications by subclassifying patients to tailored, patient-specific treatment. We analyzed single nucleotide polymorphisms (SNPs) in 53 inflammation-related genes among 651 NSCLC patients. Multivariable Cox proportional hazard models, adjusted for lung cancer prognostic factors, were used to assess the association of genotypes and haplotypes with overall survival. Four of the top 15 SNPs associated with survival were located in the TNF-receptor superfamily member 10b ( TNFRSF10B ) gene. The T-allele of the top ranked SNP (rs11785599) was associated with a 41% increased risk of death (95% confidence interval [CI] = 1.16–1.70) and the other three TNFRSF10B SNPs (rs1047275, rs4460370 and rs883429) exhibited a 35% (95% CI = 1.11–1.65), 29% (95% CI = 1.06–1.57) and 24% (95% CI = 0.99–1.54) increased risk of death, respectively. Haplotype analyses revealed that the most common risk haplotype ( TCTT ) was associated with a 78% (95% CI = 1.25–2.54) increased risk of death compared with the low-risk haplotype ( CGCC ). When the data were stratified by treatment, the risk haplotypes exhibited statistically significantly increased risk of death among patients who had surgery only and no statistically significant effects among patients who had surgery and adjuvant chemotherapy. These data suggest that possessing one or more risk alleles in TNFRSF10B is associated with an increased risk of death. Validated germ line biomarkers may have potential important clinical implications by optimizing patient-specific treatment.
    Print ISSN: 0143-3334
    Electronic ISSN: 1460-2180
    Topics: Medicine
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  • 2
    Publication Date: 2016-08-11
    Description: Motivations: Characterizing protein–protein interfaces and the hydrogen bonds is a first step to better understand proteins’ structures and functions toward high-resolution protein design. However, there are few large-scale surveys of hydrogen bonds of interfaces. In addition, previous work of shape complementarity of protein complexes suggested that lower shape complementarity in antibody–antigen interfaces is related to their evolutionary origin. Results: Using 6637 non-redundant protein–protein interfaces, we revealed peculiar features of various protein complex types. In contrast to previous findings, the shape complementarity of antibody–antigen interfaces resembles that of the other interface types. These results highlight the importance of hydrogen bonds during evolution of protein interfaces and rectify the prevailing belief that antibodies have lower shape complementarity. Contact: jgray@jhu.edu Supplementary Information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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  • 3
    Publication Date: 2012-09-13
    Description: More than 98% of a typical vertebrate genome does not code for proteins. Although non-coding regions are sprinkled with short (〈200 bp) islands of evolutionarily conserved sequences, the function of most of these unannotated conserved islands remains unknown. One possibility is that unannotated conserved islands could encode non-coding RNAs (ncRNAs); alternatively, unannotated conserved islands could serve as promoter-distal regulatory factor binding sites (RFBSs) like enhancers. Here we assess these possibilities by comparing unannotated conserved islands in the human and mouse genomes to transcribed regions and to RFBSs, relying on a detailed case study of one human and one mouse cell type. We define transcribed regions by applying a novel transcript-calling algorithm to RNA-Seq data obtained from total cellular RNA, and we define RFBSs using ChIP-Seq and DNAse-hypersensitivity assays. We find that unannotated conserved islands are four times more likely to coincide with RFBSs than with unannotated ncRNAs. Thousands of conserved RFBSs can be categorized as insulators based on the presence of CTCF or as enhancers based on the presence of p300/CBP and H3K4me1. While many unannotated conserved RFBSs are transcriptionally active to some extent, the transcripts produced tend to be unspliced, non-polyadenylated and expressed at levels 10 to 100-fold lower than annotated coding or ncRNAs. Extending these findings across multiple cell types and tissues, we propose that most conserved non-coding genomic DNA in vertebrate genomes corresponds to promoter-distal regulatory elements.
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 4
    Publication Date: 2013-10-08
    Description: Aberrant DNA methylation of CpG islands, CpG island shores and first exons is known to play a key role in the altered gene expression patterns in all human cancers. To date, a systematic study on the effect of DNA methylation on gene expression using high resolution data has not been reported. In this study, we conducted an integrated analysis of MethylCap-sequencing data and Affymetrix gene expression microarray data for 30 breast cancer cell lines representing different breast tumor phenotypes. As well-developed methods for the integrated analysis do not currently exist, we created a series of four different analysis methods. On the computational side, our goal is to develop methylome data analysis protocols for the integrated analysis of DNA methylation and gene expression data on the genome scale. On the cancer biology side, we present comprehensive genome-wide methylome analysis results for differentially methylated regions and their potential effect on gene expression in 30 breast cancer cell lines representing three molecular phenotypes, luminal, basal A and basal B. Our integrated analysis demonstrates that methylation status of different genomic regions may play a key role in establishing transcriptional patterns in molecular subtypes of human breast cancer.
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 5
    Publication Date: 2013-10-09
    Description: Low-density lipoprotein receptor related protein 6 ( Lrp6) mutational effects on neurulation were examined using gain ( Crooked tail, Lrp6 Cd ) and loss ( Lrp6 – ) of function mouse lines. Two features often associated with canonical Wnt signaling, dorsal–ventral patterning and proliferation, were no different from wild-type (WT) in the Lrp6 Cd/Cd neural tube. Lrp6 –/– embryos showed reduced proliferation and subtle patterning changes in the neural folds. Cell polarity defects in both Lrp6 Cd/Cd and Lrp6 – / – cranial folds were indicated by cell shape, centrosome displacement and failure of F-actin and GTP-RhoA accumulation at the apical surface. Mouse embryonic fibroblasts (MEFs) derived from Lrp6 Cd/Cd or Lrp6 – / – embryos exhibited elevated and decreased RhoA basal activity levels, respectively. While ligand-independent activation of canonical Wnt signaling, bypassing Lrp-Frizzled receptors, did not activate RhoA, non-canonical Wnt5a stimulation of RhoA activity was impaired in Lrp6 – / – MEFs. RhoA inhibition exacerbated NTDs in cultured Lrp6 knockout embryos compared with WT littermates. In contrast, a ROCK inhibitor rescued Lrp6 Cd/Cd embryos from NTDs. Lrp6 co-immunoprecipitated with Disheveled-associated activator of morphogenesis 1 (DAAM1), a formin promoting GEF activity in Wnt signaling. Biochemical and cell biological data revealed intracellular accumulation of Lrp6 Cd protein where interaction with DAAM1 could account for observed elevated RhoA activity. Conversely, null mutation that eliminates Lrp6 interaction with DAAM1 led to lower basal RhoA activity in Lrp6 – / – embryos. These results indicate that Lrp6 mediates not only canonical Wnt signaling, but can also modulate non-canonical pathways involving RhoA-dependent mechanisms to impact neurulation, possibly through intracellular complexes with DAAM1.
    Print ISSN: 0964-6906
    Electronic ISSN: 1460-2083
    Topics: Biology , Medicine
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  • 6
    Publication Date: 2014-05-24
    Description: Mutations are central to evolution, providing the genetic variation upon which selection acts. A mutation’s effect on the suitability of a gene to perform a particular function (gene fitness) can be positive, negative, or neutral. Knowledge of the distribution of fitness effects (DFE) of mutations is fundamental for understanding evolutionary dynamics, molecular-level genetic variation, complex genetic disease, the accumulation of deleterious mutations, and the molecular clock. We present comprehensive DFEs for point and codon mutants of the Escherichia coli TEM-1 β-lactamase gene and missense mutations in the TEM-1 protein. These DFEs provide insight into the inherent benefits of the genetic code’s architecture, support for the hypothesis that mRNA stability dictates codon usage at the beginning of genes, an extensive framework for understanding protein mutational tolerance, and evidence that mutational effects on protein thermodynamic stability shape the DFE. Contrary to prevailing expectations, we find that deleterious effects of mutation primarily arise from a decrease in specific protein activity and not cellular protein levels.
    Print ISSN: 0737-4038
    Electronic ISSN: 1537-1719
    Topics: Biology
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  • 7
    Publication Date: 2012-06-12
    Description: The Ron receptor tyrosine kinase (macrophage stimulating 1 receptor) is overexpressed in approximately 50% of human breast cancers. Transgenic mice overexpressing Ron in the mammary epithelium [mouse mammary tumor virus driven (MMTV)-Ron expressing mice] develop mammary tumors that exhibit up-regulation of β-catenin and β-catenin target genes. β-Catenin has been shown to be a mediator of mammary tumorigenesis in various breast cancer models, including downstream of Ron. However, the in vivo impact of a conditional loss of β-catenin downstream of Ron receptor overexpression on the onset, growth, turnover, and metastasis of mammary tumors has not been addressed. To determine the significance of β-catenin in the context of Ron overexpression, we conditionally deleted β-catenin in mammary epithelial cells of MMTV-Ron mice. Conditional deletion of β-catenin in the mammary epithelium, through the use of whey acidic protein (WAP)-Cre transgenic mice, significantly delayed the onset of mammary hyperplastic nodules, the presence of palpable mammary tumors, and ultimately decreased liver metastasis. β-Catenin loss in this model was also associated with decreased expression of cyclin D1. In total, these studies support an important role for β-catenin downstream of Ron receptor signaling during the development of mammary tumorigenesis.
    Keywords: TRANSLATIONAL RESEARCH IN ENDOCRINOLOGY AND METABOLISM, Translational Highlights from ENDO
    Print ISSN: 0013-7227
    Topics: Medicine
    Published by Oxford University Press on behalf of The Endocrine Society.
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  • 8
    Publication Date: 2012-10-20
    Description: Motivation: Protein signaling networks play a key role in cellular function, and their dysregulation is central to many diseases, including cancer. To shed light on signaling network topology in specific contexts, such as cancer, requires interrogation of multiple proteins through time and statistical approaches to make inferences regarding network structure. Results: In this study, we use dynamic Bayesian networks to make inferences regarding network structure and thereby generate testable hypotheses. We incorporate existing biology using informative network priors, weighted objectively by an empirical Bayes approach, and exploit a connection between variable selection and network inference to enable exact calculation of posterior probabilities of interest. The approach is computationally efficient and essentially free of user-set tuning parameters. Results on data where the true, underlying network is known place the approach favorably relative to existing approaches. We apply these methods to reverse-phase protein array time-course data from a breast cancer cell line (MDA-MB-468) to predict signaling links that we independently validate using targeted inhibition. The methods proposed offer a general approach by which to elucidate molecular networks specific to biological context, including, but not limited to, human cancers. Availability: http://mukherjeelab.nki.nl/DBN (code and data). Contact: s.hill@nki.nl ; gmills@mdanderson.org ; s.mukherjee@nki.nl Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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  • 9
    Publication Date: 2014-08-27
    Description: Motivation: Networks are widely used as structural summaries of biochemical systems. Statistical estimation of networks is usually based on linear or discrete models. However, the dynamics of biochemical systems are generally non-linear, suggesting that suitable non-linear formulations may offer gains with respect to causal network inference and aid in associated prediction problems. Results: We present a general framework for network inference and dynamical prediction using time course data that is rooted in non-linear biochemical kinetics. This is achieved by considering a dynamical system based on a chemical reaction graph with associated kinetic parameters. Both the graph and kinetic parameters are treated as unknown; inference is carried out within a Bayesian framework. This allows prediction of dynamical behavior even when the underlying reaction graph itself is unknown or uncertain. Results, based on (i) data simulated from a mechanistic model of mitogen-activated protein kinase signaling and (ii) phosphoproteomic data from cancer cell lines, demonstrate that non-linear formulations can yield gains in causal network inference and permit dynamical prediction and uncertainty quantification in the challenging setting where the reaction graph is unknown. Availability and implementation: MATLAB R2014a software is available to download from warwick.ac.uk/chrisoates. Contact: c.oates@warwick.ac.uk or sach@mrc-bsu.cam.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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  • 10
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    Oxford University Press
    Publication Date: 2015-06-16
    Description: Mathematicians use the word ‘deep’ to convey a high appreciation of a concept, theorem, or proof. This paper investigates the extent to which the term can be said to have an objective character by examining its first use in mathematics. It was a consequence of Gauss's work on number theory and the agreement among his successors that specific parts of Gauss's work were deep, on grounds that indicate that depth was a structural feature of mathematics for them. In contrast, French mathematicians had a less structural, more problem-oriented approach to mathematics and did not speak of depth so readily.
    Print ISSN: 0031-8019
    Electronic ISSN: 1744-6406
    Topics: Mathematics , Philosophy
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