Literature DB >> 16103895

Linking pathway gene expressions to the growth inhibition response from the National Cancer Institute's anticancer screen and drug mechanism of action.

R Huang1, A Wallqvist, N Thanki, D G Covell.   

Abstract

Novel strategies are proposed to quantitatively analyze and relate biological pathways to drug responses using gene expression and small-molecule growth inhibition data (GI(50)) derived from the National Cancer Institute's 60 cancer cells (NCI(60)). We have annotated groups of drug GI(50) responses with pathways defined by the Kyoto Encyclopedia of Genes and Genomes (KEGG) and BioCarta, and functional categories defined by Gene Ontology (GO), through correlations between pathway gene expression patterns and drug GI(50) profiles. Drug-gene-pathway relationships may then be utilized to find drug targets or target-specific drugs. Significantly correlated pathways and the gene products involved represent interesting targets for further exploration, whereas drugs that are significantly correlated with only certain pathways are more likely to be target specific. Separate pathway clustering finds that pathways engaged in the same biological process tend to have similar drug correlation patterns. The biological and statistical significances of our method are established by comparison to known small-molecule inhibitor-gene target relationships reported in the literature and by standard randomization procedures. The results of our pathway, gene expression and drug-induced growth inhibition associations, can serve as a basis for proposing testable hypotheses about potential anticancer drugs, their targets, and mechanisms of action.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 16103895     DOI: 10.1038/sj.tpj.6500331

Source DB:  PubMed          Journal:  Pharmacogenomics J        ISSN: 1470-269X            Impact factor:   3.550


  20 in total

1.  Large-scale elucidation of drug response pathways in humans.

Authors:  Yael Silberberg; Assaf Gottlieb; Martin Kupiec; Eytan Ruppin; Roded Sharan
Journal:  J Comput Biol       Date:  2012-02       Impact factor: 1.479

Review 2.  The use of genomic information to optimize cancer chemotherapy.

Authors:  Federico Innocenti; Nancy J Cox; M Eileen Dolan
Journal:  Semin Oncol       Date:  2011-04       Impact factor: 4.929

Review 3.  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 4.  Pharmacogenomic discovery using cell-based models.

Authors:  Marleen Welsh; Lara Mangravite; Marisa Wong Medina; Kelan Tantisira; Wei Zhang; R Stephanie Huang; Howard McLeod; M Eileen Dolan
Journal:  Pharmacol Rev       Date:  2009-12       Impact factor: 25.468

5.  Induction of tumor cell apoptosis by a proteasome deubiquitinase inhibitor is associated with oxidative stress.

Authors:  Slavica Brnjic; Magdalena Mazurkiewicz; Mårten Fryknäs; Chao Sun; Xiaonan Zhang; Rolf Larsson; Pádraig D'Arcy; Stig Linder
Journal:  Antioxid Redox Signal       Date:  2013-10-17       Impact factor: 8.401

6.  Gene expression associations with the growth inhibitory effects of small molecules on live cells: specificity of effects and uniformity of mechanisms.

Authors:  Kerby Shedden; Yang Yang; Gus Rosania
Journal:  Stat Anal Data Min       Date:  2009-09-01       Impact factor: 1.051

7.  Conditional drug screening shows that mitotic inhibitors induce AKT/PKB-insensitive apoptosis.

Authors:  Maria Berndtsson; Emma Hernlund; Maria C Shoshan; Stig Linder
Journal:  J Chem Biol       Date:  2009-03-31

8.  Evaluation of molecular descriptors for antitumor drugs with respect to noncovalent binding to DNA and antiproliferative activity.

Authors:  José Portugal
Journal:  BMC Pharmacol       Date:  2009-09-16

9.  Next-generation NAMPT inhibitors identified by sequential high-throughput phenotypic chemical and functional genomic screens.

Authors:  Christina J Matheny; Michael C Wei; Michael C Bassik; Alicia J Donnelly; Martin Kampmann; Masayuki Iwasaki; Obdulio Piloto; David E Solow-Cordero; Donna M Bouley; Rachel Rau; Patrick Brown; Michael T McManus; Jonathan S Weissman; Michael L Cleary
Journal:  Chem Biol       Date:  2013-10-31

Review 10.  Targeting karyotypic complexity and chromosomal instability of cancer cells.

Authors:  Anna V Roschke; Ilan R Kirsch
Journal:  Curr Drug Targets       Date:  2010-10       Impact factor: 3.465

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.