%0 Journal Article %A Anders Wallqvist %A John Connelly %A Edward A. Sausville %A David G. Covell %A Anne Monks %T Differential Gene Expression as a Potential Classifier of 2-(4-Amino-3-methylphenyl)-5-fluorobenzothiazole-Sensitive and -Insensitive Cell Lines %D 2006 %R 10.1124/mol.105.017061 %J Molecular Pharmacology %P 737-748 %V 69 %N 3 %X 2-(4-Amino-3-methylphenyl)-5-fluorobenzothiazole (5F-203) is a candidate antitumor agent empirically discovered with the aid of the National Cancer Institute (NCI) Anticancer Drug Screen. In an effort to determine whether basal expression of genes could be used to classify cell sensitivity to this agent, serial analysis of gene expression (SAGE) libraries were generated for three sensitive and two insensitive human tumor cell lines. When the SAGE tags expressed within these cell line libraries were compared and evaluated for differences, several genes seemed more highly expressed in 5F-203-sensitive cell lines than in the insensitive cell lines. Constitutive expressions of 15 genes identified by the analysis were then measured by quantitative reverse-transcription polymerase chain reaction in the 60 cell lines of the NCI Anticancer Drug Screen. This generated a pattern of relative basal gene expression across the cell lines and also confirmed the differential expression of SAGE-discovered genes within the initial set of five cell lines. Further analyses of these expression data in 60 cell lines suggested that a smaller subset of genes could be used to classify tumor cell sensitivity to 5F-203. In contrast, the same set of genes did not predict with equivalent precision sensitivity to unrelated active drugs, and another set of genes could not better classify the cell lines in terms of 5F-203 sensitivity. These results suggest that constitutive gene expression profiles, in which the genes are not necessarily known to be related to the mechanism of action of a given drug, may be viewed as a general tool to extend and improve the concept of a single predictive gene to groups of predictive genes. %U https://molpharm.aspetjournals.org/content/molpharm/69/3/737.full.pdf