An Information-Intensive Approach to the Molecular Pharmacology of Cancer

John N. Weinstein(National Institutes of Health), Timothy G. Myers(National Institutes of Health), P M O'Connor(National Institutes of Health), Stephen Friend(Cape Town HVTN Immunology Laboratory / Hutchinson Centre Research Institute of South Africa), Albert J. Fornace(National Institutes of Health), Kurt W. Kohn(National Institutes of Health), Tito Fojo(Center for Cancer Research), Susan E. Bates(Center for Cancer Research), Larry Rubinstein(Center for Cancer Research), N L Anderson(Meso Scale Discovery (United States)), John K. Buolamwini(National Institutes of Health), William W. van Osdol(National Institutes of Health), Anne Monks(Cancer Research Center), Dominic A. Scudiero(Cancer Research Center), Edward A. Sausville(Office of the Director), Daniel Zaharevitz(National Institutes of Health), Barry Bunow(National Institutes of Health), Vellarkad N. Viswanadhan(National Institutes of Health), George S. Johnson(National Institutes of Health), Robert E. Wittes(Office of the Director), Kenneth D. Paull(National Institutes of Health)
Science
January 17, 1997
Cited by 1,179

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.


Related Papers

No related papers found

Powered by citation graph analysis