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Cited by 684

The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.

Chemosensitivity prediction by transcriptional profiling

Open access
Staunton, Jane E., Slonim, Donna K., Coller, Hilary A., Tamayo, Pablo, Angelo, Michael J., Park, Johnny, Scherf, Uwe, Lee, Jae K., Reinhold, William O., Weinstein, John N., Mesirov, Jill P., Lander, Eric S., Golub, Todd R.·2001·Proceedings of the National Academy of Sciences

Abstract

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 6,817 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.

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Metadata

Authors
Staunton, J. E., Slonim, D. K., Coller, H. A., Tamayo, P., Angelo, M. J., Park, J., Scherf, U., Lee, J. K., Reinhold, W. O., Weinstein, J. N., Mesirov, J. P., Lander, E. S., & Golub, T. R.
Venue
Proceedings of the National Academy of Sciences
Published
2001-09-11
Volume
98
Issue
19
Pages
10787-10792
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2122128696
Cited by
684
References
19
FWCI
14.33
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Chemosensitivity prediction by transcriptional profiling. https://app.cochat.ai/papers/10.1073/pnas.191368598
The paper
Staunton, J. E., Slonim, D. K., Coller, H. A., Tamayo, P., Angelo, M. J., Park, J., Scherf, U., Lee, J. K., Reinhold, W. O., Weinstein, J. N., Mesirov, J. P., Lander, E. S., & Golub, T. R. (2001). Chemosensitivity prediction by transcriptional profiling. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.191368598

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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