Chemosensitivity prediction by transcriptional profiling

AUTOR(ES)

Staunton, Jane E.

FONTE

The National Academy of Sciences

RESUMO

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.

Documentos Relacionados

• Prediction of Mechanisms of Action of Antibacterial Compounds by Gene Expression Profiling
• In vivo transcriptional profiling of Plasmodium falciparum
• Transcriptional Profiling of Lipopolysaccharide-Induced Acute Lung Injury
• Interfering with Different Steps of Protein Synthesis Explored by Transcriptional Profiling of Escherichia coli K-12†
• Genomic transcriptional profiling of the developmental cycle of Chlamydia trachomatis