Chemosensitivity prediction by transcriptional profiling

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.

Identification of molecular mechanisms for cellular drug resistance by combining drug activity and gene expression profiles

“…This might be explained by several limiting factors as discussed above, and include differences in cell types, arrays, drugs and assays used. Even when different arrays were used to study the same samples, the gene -drug relationships were shown to differ (Scherf et al, 2000;Staunton et al, 2001). Furthermore, in the present study, the correlation coefficients for the drug -gene correlations were in general higher than in the previous studies.…”

Use of arrays to investigate the contribution of ATP-binding cassette transporters to drug resistance in cancer chemotherapy and prediction of chemosensitivity

“…A similar study of NCI-60 cell lines was also conducted, but instead used the Affymetrix oligonucleotide microarray Hu6800 (Table 2) containing 6 817 human genes including ABC transporters such as ABCA3, ABCA4, ABCB1, ABCB2, and ABCB3 [8]. The correlation of drug sensitivity to gene expression was generated from a training set of data and this was then used to predict the sensitivity of cell lines to any particular drug using data in a testing set.…”

Getting the right cells to the array: Gene expression microarray analysis of cell mixtures and sorted cells

“…At the same time, microarrays (MAs) can be used to monitor the effects of these treatments, especially of new (and old) drugs (12)(13)(14). The unique view that MAT offers of the cells and tissues also generated high hopes in the field of pathology.…”

“…On many occasions, MAT has generated more confusion than comprehension, and more questions than answers (14,18,19). Despite this fact, MAT has improved greatly in recent years.…”