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Vol. 53, Issue 2, 241-251, February 1998
Laboratory of Molecular Pharmacology (L.M.S., Y.F.,
P.M.O., J.N.W.),
Division of Basic Sciences, and Information Technology
Branch (T.G.M., K.D.P.), Division of Cancer Treatment, Diagnosis, and
Centers, National Cancer Institute, National Institutes of Health,
Bethesda, Maryland 20892; and
Fred Hutchinson Cancer Research
Center/National Cancer Institute (S.H.F.), Seattle, Washington 98104
The United States National Cancer Institute conducts an anticancer drug
discovery program in which ~10,000 compounds are screened every year
in vitro against a panel of 60 human cancer cell lines from different organs. To date, ~62,000 compounds have been tested in
the program, and a large amount of information on their activity patterns has been accumulated. For the current study, anticancer activity patterns of 112 ellipticine analogs were analyzed with the use
of a hierarchical clustering algorithm. A dramatic coherence between
molecular structures and their activity patterns could be seen from the
cluster tree: the first subgroup (compounds 1-66) consisted
principally of normal ellipticines, whereas the second subgroup
(compounds 67-112) consisted principally of
N2-alkyl-substituted ellipticiniums. Almost all apparent
discrepancies in this clustering were explainable on the basis of
chemical transformation to active forms under cell culture conditions.
Correlations of activity with p53 status and selective activity against
cells of central nervous system origin made this data set of special interest to us. The ellipticiniums, but not the ellipticines, were more
potent on average against p53 mutant cells than against p53 wild-type
ones (i.e., they seemed to be "p53-inverse") in this short term
assay. This study strongly supports the hypothesis that
"fingerprint" patterns of activity in the National Cancer Institute
in vitro cell screening program encode
incisive information on the mechanisms of action and other biological
behaviors of tested compounds. Insights gained by mining the activity
patterns could contribute to our understanding of anticancer drugs and the molecular pharmacology of cancer.
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