Literature DB >> 16386875

Comprehensive analysis of pathway or functionally related gene expression in the National Cancer Institute's anticancer screen.

Ruili Huang1, Anders Wallqvist, David G Covell.   

Abstract

We have analyzed the level of gene coregulation, using gene expression patterns measured across the National Cancer Institute's 60 tumor cell panels (NCI(60)), in the context of predefined pathways or functional categories annotated by KEGG (Kyoto Encyclopedia of Genes and Genomes), BioCarta, and GO (Gene Ontology). Statistical methods were used to evaluate the level of gene expression coherence (coordinated expression) by comparing intra- and interpathway gene-gene correlations. Our results show that gene expression in pathways, or groups of functionally related genes, has a significantly higher level of coherence than that of a randomly selected set of genes. Transcriptional-level gene regulation appears to be on a "need to be" basis, such that pathways comprising genes encoding closely interacting proteins and pathways responsible for vital cellular processes or processes that are related to growth or proliferation, specifically in cancer cells, such as those engaged in genetic information processing, cell cycle, energy metabolism, and nucleotide metabolism, tend to be more modular (lower degree of gene sharing) and to have genes significantly more coherently expressed than most signaling and regular metabolic pathways. Hierarchical clustering of pathways based on their differential gene expression in the NCI(60) further revealed interesting interpathway communications or interactions indicative of a higher level of pathway regulation. The knowledge of the nature of gene expression regulation and biological pathways can be applied to understanding the mechanism by which small drug molecules interfere with biological systems.

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Year:  2006        PMID: 16386875     DOI: 10.1016/j.ygeno.2005.11.011

Source DB:  PubMed          Journal:  Genomics        ISSN: 0888-7543            Impact factor:   5.736


  19 in total

Review 1.  A cheminformatic toolkit for mining biomedical knowledge.

Authors:  Gus R Rosania; Gordon Crippen; Peter Woolf; David States; Kerby Shedden
Journal:  Pharm Res       Date:  2007-03-24       Impact factor: 4.200

Review 2.  Dissecting the Genetics of Osteoporosis using Systems Approaches.

Authors:  Basel M Al-Barghouthi; Charles R Farber
Journal:  Trends Genet       Date:  2018-11-20       Impact factor: 11.639

3.  An integrative method to predict signalling perturbations for cellular transitions.

Authors:  Gaia Zaffaroni; Satoshi Okawa; Manuel Morales-Ruiz; Antonio Del Sol
Journal:  Nucleic Acids Res       Date:  2019-07-09       Impact factor: 16.971

4.  Proteomic and transcriptomic analyses reveal genes upregulated by cis-dichloroethene in Polaromonas sp. strain JS666.

Authors:  Laura K Jennings; Michelle M G Chartrand; Georges Lacrampe-Couloume; Barbara Sherwood Lollar; Jim C Spain; James M Gossett
Journal:  Appl Environ Microbiol       Date:  2009-04-10       Impact factor: 4.792

5.  Chemical-agnostic hazard prediction: statistical inference of in vitro toxicity pathways from proteomics responses to chemical mixtures.

Authors:  Jeffrey A Ross; Barbara Jane George; Maribel Bruno; Yue Ge
Journal:  Comput Toxicol       Date:  2017-05

6.  Integrating constitutive gene expression and chemoactivity: mining the NCI60 anticancer screen.

Authors:  David G Covell
Journal:  PLoS One       Date:  2012-10-02       Impact factor: 3.240

7.  A small molecule (pluripotin) as a tool for studying cancer stem cell biology: proof of concept.

Authors:  Susan D Mertins; Dominic A Scudiero; Melinda G Hollingshead; Raymond D Divelbiss; Michael C Alley; Anne Monks; David G Covell; Karen M Hite; David S Salomon; John E Niederhuber
Journal:  PLoS One       Date:  2013-02-21       Impact factor: 3.240

8.  Shared molecular and functional frameworks among five complex human disorders: a comparative study on interactomes linked to susceptibility genes.

Authors:  Ramesh Menon; Cinthia Farina
Journal:  PLoS One       Date:  2011-04-21       Impact factor: 3.240

9.  A network-based approach to prioritize results from genome-wide association studies.

Authors:  Nirmala Akula; Ancha Baranova; Donald Seto; Jeffrey Solka; Michael A Nalls; Andrew Singleton; Luigi Ferrucci; Toshiko Tanaka; Stefania Bandinelli; Yoon Shin Cho; Young Jin Kim; Jong-Young Lee; Bok-Ghee Han; Francis J McMahon
Journal:  PLoS One       Date:  2011-09-06       Impact factor: 3.240

10.  An analysis of the transcriptome of Teladorsagia circumcincta: its biological and biotechnological implications.

Authors:  Ranjeeta Menon; Robin B Gasser; Makedonka Mitreva; Shoba Ranganathan
Journal:  BMC Genomics       Date:  2012-12-13       Impact factor: 3.969

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