Literature DB >> 8994024

An information-intensive approach to the molecular pharmacology of cancer.

J N Weinstein1, T G Myers, P M O'Connor, S H Friend, A J Fornace, K W Kohn, T Fojo, S E Bates, L V Rubinstein, N L Anderson, J K Buolamwini, W W van Osdol, A P Monks, D A Scudiero, E A Sausville, D W Zaharevitz, B Bunow, V N Viswanadhan, G S Johnson, R E Wittes, K D Paull.   

Abstract

Since 1990, the National Cancer Institute (NCI) has screened more than 60,000 compounds against a panel of 60 human cancer cell lines. The 50-percent growth-inhibitory concentration (GI50) for any single cell line is simply an index of cytotoxicity or cytostasis, but the patterns of 60 such GI50 values encode unexpectedly rich, detailed information on mechanisms of drug action and drug resistance. Each compound's pattern is like a fingerprint, essentially unique among the many billions of distinguishable possibilities. These activity patterns are being used in conjunction with molecular structural features of the tested agents to explore the NCI's database of more than 460,000 compounds, and they are providing insight into potential target molecules and modulators of activity in the 60 cell lines. For example, the information is being used to search for candidate anticancer drugs that are not dependent on intact p53 suppressor gene function for their activity. It remains to be seen how effective this information-intensive strategy will be at generating new clinically active agents.

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Year:  1997        PMID: 8994024     DOI: 10.1126/science.275.5298.343

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  273 in total

Review 1.  The complexity of radiation stress responses: analysis by informatics and functional genomics approaches.

Authors:  A J Fornace; S A Amundson; M Bittner; T G Myers; P Meltzer; J N Weinsten; J Trent
Journal:  Gene Expr       Date:  1999

2.  Establishment of a chemical synthetic lethality screen in cultured human cells.

Authors:  A Simons; N Dafni; I Dotan; Y Oron; D Canaani
Journal:  Genome Res       Date:  2001-02       Impact factor: 9.043

3.  A multivariate insight into the in vitro antitumour screen database of the National Cancer Institute: classification of compounds, similarities among cell lines and the influence of molecular targets.

Authors:  G Musumarra; D F Condorelli; A S Costa; M Fichera
Journal:  J Comput Aided Mol Des       Date:  2001-03       Impact factor: 3.686

Review 4.  Cell cycle checkpoints as therapeutic targets.

Authors:  Z A Stewart; J A Pietenpol
Journal:  J Mammary Gland Biol Neoplasia       Date:  1999-10       Impact factor: 2.673

5.  'Gene shaving' as a method for identifying distinct sets of genes with similar expression patterns.

Authors:  T Hastie; R Tibshirani; M B Eisen; A Alizadeh; R Levy; L Staudt; W C Chan; D Botstein; P Brown
Journal:  Genome Biol       Date:  2000-08-04       Impact factor: 13.583

6.  Gadd45, a p53-responsive stress protein, modifies DNA accessibility on damaged chromatin.

Authors:  F Carrier; P T Georgel; P Pourquier; M Blake; H U Kontny; M J Antinore; M Gariboldi; T G Myers; J N Weinstein; Y Pommier; A J Fornace
Journal:  Mol Cell Biol       Date:  1999-03       Impact factor: 4.272

7.  Mapping XML documents into databases: a Data-Driven Framework for bioinformatic data interchange.

Authors:  K Canfield; J Sorace
Journal:  Proc AMIA Symp       Date:  2000

8.  Discovering functional relationships between RNA expression and chemotherapeutic susceptibility using relevance networks.

Authors:  A J Butte; P Tamayo; D Slonim; T R Golub; I S Kohane
Journal:  Proc Natl Acad Sci U S A       Date:  2000-10-24       Impact factor: 11.205

9.  Chemosensitivity prediction by transcriptional profiling.

Authors:  J E Staunton; D K Slonim; H A Coller; P Tamayo; M J Angelo; J Park; U Scherf; J K Lee; W O Reinhold; J N Weinstein; J P Mesirov; E S Lander; T R Golub
Journal:  Proc Natl Acad Sci U S A       Date:  2001-09-11       Impact factor: 11.205

Review 10.  Data-driven methods to discover molecular determinants of serious adverse drug events.

Authors:  A P Chiang; A J Butte
Journal:  Clin Pharmacol Ther       Date:  2009-01-28       Impact factor: 6.875

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