Abstract
Cancer stem cells (CSCs) are thought to promote resistance to chemotherapeutic drugs in glioblastoma, the most common and aggressive primary brain tumor. However, the use of high-throughput drug screens to discover novel small-molecule inhibitors for CSC has been hampered by their instability in long-term cell culture. We asked whether predictive models of drug response could be developed from gene expression signatures of established cell lines and applied to predict drug response in glioblastoma stem cells. Predictions for active compounds were confirmed both for 185 compounds in seven established glioma cell lines and 21 compounds in three glioblastoma stem cells. The use of established cell lines as a surrogate for drug response in CSC lines may enable the large-scale virtual screening of drug candidates that would otherwise be difficult or impossible to test directly in CSCs.
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Acknowledgements
We thank the Developmental Therapeutics Program (NCI) for providing drug sensitivity data for the NCI-60 cell lines and the Sanger Wellcome Trust for providing drug sensitivity and gene expression data for 485 cell lines.
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Riddick, G., Song, H., Holbeck, S. et al. An in silico screen links gene expression signatures to drug response in glioblastoma stem cells. Pharmacogenomics J 15, 347–353 (2015). https://doi.org/10.1038/tpj.2014.61
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DOI: https://doi.org/10.1038/tpj.2014.61
