Chemosensitivity Prediction by Transcriptional Profiling

Proc. Natl. Acad. Sci. USA 98: 0787-10792. Published: 2001.09.10

Jane E. Staunton, Donna K. Slonim , Hilary A. Coller, Pablo Tamayo, Michael J. Angelo , Johnny Park , Uwe Scherf, Jae K. Lee, William O. Reinhold, John N. Weinstein, Jill P. Mesirov, Eric S. Landerand Todd R. Golub

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In an effort to develop a genomics-based approach to the prediction of drug response, we have developed an algorithm for classification of cell line chemosensitivity based on gene expression profiles alone. Using oligonucleotide microarrays, the expression levels of 6817 genes were measured in a panel of 60 human cancer cell lines (the NCI-60) for which the chemosensitivity profiles of thousands of chemical compounds have been determined. We sought to determine whether the gene expression signatures of untreated cells were sufficient for the prediction of chemosensitivity. Gene expression-based classifiers of sensitivity or resistance for 232 compounds were generated and then evaluated on independent sets of data. The classifiers were designed to be independent of the cells' tissue of origin. The accuracy of chemosensitivity prediction was considerably better than would be expected by chance. Eighty-eight of 232 expression-based classifiers performed accurately (with p < 0.05) on an independent test set, whereas only 12 of the 232 would be expected to do so by chance. These results suggest that at least for a subset of compounds, genomic approaches to chemosensitivity prediction are feasible.

Keywords: Chemosensitivity NCI60

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Supplemental Data

Description Link/Filename
Scaled expression data w/A_P calls NCI60_aug99_resfile.txt
Drug sensitivity GI50 raw GI50_RAW.txt.gz
List of scan names samples_for_nci60paper.txt
Raw CEL files, part 1 (20 scans, ~44MB) nci60_scans_part1.tar.gz
Raw CEL files, part 2 (20 scans, ~44MB) nci60_scans_part2.tar.gz
Raw CEL files, part 3 (20 scans, ~44MB) nci60_scans_part3.tar.gz
Paper (PDF) Staunton_et_al_2001.pdf