This data set contains the expression of 48 known human ABC transporters with patterns of drug activity in 60 diverse cancer cell lines (the NCI-60) used by the National Cancer Institute to screen for anticancer activity.
data(multidrug)A list containing the following components:
ABC.transdata matrix with 60 rows and 48 columns. The expression of the 48 human ABC transporters.
compounddata matrix with 60 rows and 1429 columns. The activity of 1429 drugs for the 60 cell lines.
comp.namecharacter vector. The names or the NSC No. of the 1429 compounds.
cell.linea list containing two character vector components:
Sample the names of the 60 cell line which were analysed, and Class the
phenotypes of the 60 cell lines.
The data come from a pharmacogenomic study (Szakacs et al., 2004) in which two kinds of measurements acquired on the NCI-60 cancer cell lines are considered:
the expression of the 48 human ABC transporters measured by real-time quantitative RT-PCR for each cell line;
the activity of 1429 drugs expressed as \(GI_{50}\) which corresponds to the concentration at which the drug induces \(50\%\) inhibition of cellular growth for the cell line tested.
The NCI- 60 panel includes cell lines derived from cancers of colorectal (7 cell lines), renal(8), ovarian(6), breast(8), prostate(2), lung(9) and central nervous system origin(6), as well as leukemias(6) and melanomas(8). It was set up by the Developmental Therapeutics Program of the National Cancer Institute (NCI, one of the U.S. National Institutes of Health) to screen the toxicity of chemical compound repositories. The expressions of the 48 human ABC transporters is available as a supplement to the paper of Szak?cs et al. (2004).
The drug dataset consiste of 118 compounds whose mechanisms of action are putatively classifiable (Weinstein et al., 1992) and a larger set of 1400 compounds that have been tested multiple times and whose screening data met quality control criteria described elsewhere (Scherf et al., 2000). The two were combined to form a joint dataset that included 1429 compounds.
Scherf, U., Ross, D. T., Waltham, M., Smith, L. H., Lee, J. K., Tanabe, L., Kohn, K. W., Reinhold, W. C., Myers, T. G., Andrews, D. T., Scudiero, D. A., Eisen, M. B., Sausville, E. A., Pommier, Y., Botstein, D., Brown, P. O. and Weinstein, J. N. (2000). A Gene Expression Database for the Molecular Pharmacology of Cancer. Nature Genetics, 24, 236-244.
Szakacs, G., Annereau, J.-P., Lababidi, S., Shankavaram, U., Arciello, A., Bussey, K. J., Reinhold, W., Guo, Y., Kruh, G. D., Reimers, M., Weinstein, J. N. and Gottesman, M. M. (2004). Predicting drug sensivity and resistance: Profiling ABC transporter genes in cancer cells. Cancer Cell 4, 147-166.
Weinstein, J.N., Kohn, K.W., Grever, M.R., Viswanadhan, V.N., Rubinstein, L.V., Monks, A.P., Scudiero, D.A., Welch, L., Koutsoukos, A.D., Chiausa, A.J. et al. 1992. Neural computing in cancer drug development: Predicting mechanism of action. Science 258, 447-451.