Exploratory data analytic techniques to evaluate anticancer agents screened in a cell culture panel

Abstract

Information theory is used to provide a measure of selectivity, i.e., the degree to which a drug has preferential toxicity or growth inhibition for one or a few cell lines from a large panel. The selectivity measure is intended to complement a measure of differential growth inhibition in evaluating the drug development potential of a new compound. Also, a similarity measure obtained from information theory is used to classify drugs according to their pattern of responses on the panel. Some structure-activity relations emerge. This work is applied to 176 agents selected to be tested by the National Cancer Institute in about 50 cell lines.

Cytotoxicity and characterization of an active metabolite of benzamide riboside, a novel inhibitor of IMP dehydrogenase

“…Examples of the COMPARE algorithms have been reported which capitalize on differential patterns generated in this panel and correlate with the coefficients produced by those agents whose mechanisms of action and cytotoxic profile have been well studied (Hodes et al, 1992).…”

“…The COMPARE algorithm is being developed at the National Cancer Institute to determine whether the differential cytotoxicity, observed with many compounds, toward the 60 human tumor-cell lines, was attributable to a given drug's mechanism of action (Paul1 et al, 1992). Examples of the COMPARE algorithms have been reported which capitalize on differential patterns generated in this panel and correlate with the coefficients produced by those agents whose mechanisms of action and cytotoxic profile have been well studied (Hodes et al, 1992).…”

The NCI In Vitro Anticancer Drug Discovery Screen

“…Reviews and other publications describing such studies are available (6,12,13,(40)(41)(42)(43)(44)48). As discussed recently (13), the appealingly simple mean-graph and COMPARE analysis methodologies provide useful support for a number of research applications.…”

A Cheminformatic Toolkit for Mining Biomedical Knowledge

“…Such similarity metrics can be used for predicting the binding of small molecules to proteins based on the shape of the binding pocket (65,69,83,87,89,(97)(98)(99)(100). However, when the goal is to analyze the behavior of a collection of molecules on different cell based assays, the diversity of chemical agents can also be analyzed in terms of similarities or differences in the phenotypic responses of cells to small molecules across multiple assays (16,27,41,(45)(46)(47)(57)(58)(59)(76)(77)(78)(79)(101)(102)(103)(104)(105)(106)(107) (Fig. 2).…”