title: An information-intensive approach to the molecular pharmacology of cancer.
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.
authors.affiliation: Laboratory of Molecular Pharmacology (LMP), Division of Basic Science, National Cancer Institute (NCI), National Institutes of Health, Bethesda, MD 20892, USA. weinstein@dtpax2.ncifcrf.gov
authors.forename: J N
authors.initials: JN
authors.lastname: Weinstein
authors.forename: T G
authors.initials: TG
authors.lastname: Myers
authors.forename: P M
authors.initials: PM
authors.lastname: O'Connor
authors.forename: S H
authors.initials: SH
authors.lastname: Friend
authors.forename: A J
authors.initials: AJ
authors.lastname: Fornace
authors.forename: K W
authors.initials: KW
authors.lastname: Kohn
authors.forename: T
authors.initials: T
authors.lastname: Fojo
authors.forename: S E
authors.initials: SE
authors.lastname: Bates
authors.forename: L V
authors.initials: LV
authors.lastname: Rubinstein
authors.forename: N L
authors.initials: NL
authors.lastname: Anderson
authors.forename: J K
authors.initials: JK
authors.lastname: Buolamwini
authors.forename: W W
authors.initials: WW
authors.lastname: van Osdol
authors.forename: A P
authors.initials: AP
authors.lastname: Monks
authors.forename: D A
authors.initials: DA
authors.lastname: Scudiero
authors.forename: E A
authors.initials: EA
authors.lastname: Sausville
authors.forename: D W
authors.initials: DW
authors.lastname: Zaharevitz
authors.forename: B
authors.initials: B
authors.lastname: Bunow
authors.forename: V N
authors.initials: VN
authors.lastname: Viswanadhan
authors.forename: G S
authors.initials: GS
authors.lastname: Johnson
authors.forename: R E
authors.initials: RE
authors.lastname: Wittes
authors.forename: K D
authors.initials: KD
authors.lastname: Paull
mesh_terms: D000465:Algorithms; D000970:Antineoplastic Agents / Q000737:chemistry / Q000494:pharmacology*; D016000:Cluster Analysis; D019295:Computational Biology; D003195:Computer Communication Networks; D016208:Databases, Factual; D004354:Drug Screening Assays, Antitumor; D016158:Genes, p53; D006801:Humans; D015394:Molecular Structure; D009154:Mutation; D012984:Software; D014407:Tumor Cells, Cultured; D016159:Tumor Suppressor Protein p53 / Q000502:physiology
chemical_list: D000970:Antineoplastic Agents; D016159:Tumor Suppressor Protein p53