Systematic identification of genomic markers of drug sensitivity in cancer cells

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Abstract

Clinical responses to anticancer therapies are often restricted to a subset of patients. In some cases, mutated cancer genes are potent biomarkers for responses to targeted agents. Here, to uncover new biomarkers of sensitivity and resistance to cancer therapeutics, we screened a panel of several hundred cancer cell lines—which represent much of the tissue-type and genetic diversity of human cancers—with 130 drugs under clinical and preclinical investigation. In aggregate, we found that mutated cancer genes were associated with cellular response to most currently available cancer drugs. Classic oncogene addiction paradigms were modified by additional tissue-specific or expression biomarkers, and some frequently mutated genes were associated with sensitivity to a broad range of therapeutic agents. Unexpected relationships were revealed, including the marked sensitivity of Ewing’s sarcoma cells harbouring the EWS (also known as EWSR1)-FLI1 gene translocation to poly(ADP-ribose) polymerase (PARP) inhibitors. By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.

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Figure 1: A systematic screen in cancer cell lines identifies therapeutic biomarkers.
Figure 2: Biomarkers of drug sensitivity and resistance.
Figure 3: Multi-feature genomic signatures of drug response.
Figure 4: Ewing’s sarcoma cell lines are sensitive to PARP inhibition.

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Acknowledgements

We thank P. Lo Grasso of the Scripps Research Institute for providing the inhibitor JNK9L. This work was supported by a grant from the Wellcome Trust (086357; M.R.S., P.A.F., J.S., D.A.H.) and by grants from the National Institutes of Health (P41GM079575-02 to N.S.G. and 1U54HG006097-01 to N.S.G. and D.A.H.). S.R. is supported by a Physician-Scientist Early Career Award from the Howard Hughes Medical Institute. U.M. is supported by a Cancer Research UK Clinician Scientist Fellowship.

Author information

M.J.G., C.H.B., U.M. and S.V.S. supervised data collection. M.J.G., C.H.B., U.M. and S.R. supervised data analysis. C.D.G. and K.W.L. conceived and wrote the curve-fitting algorithm and performed the MANOVA; E.J.E. and S.R. performed elastic net analysis and analysed the data. P.G., I.R.T. and J.So. developed and managed screening databases with assistance from A.B. and W.Y.; S.J.H. performed most of the Ewing’s sarcoma related studies with contributions from D.S., A.D., X.L., F.K. and L.C., with I.S. and O.D. providing critical reagents; R.J.M., A.T.T., J.A.S., S.B., S.R.L., K.L., A.M.-D., J.L.B., X.M., T.M., H.T., L.R., F.J. and P.O’B. performed cell line screening experiments. S.P. performed MCL1 siRNA experiments. Q.L.,W.Z., T.Z., W.H., X.D., H.G.C. and J.W.C. synthesized screening compounds, and N.S.G. provided guidance on their selection and use; F.I. and J.S.-R. performed compound activity clustering; G.R.B. and H.D. performed cell line genotyping and genetic analysis; J.A.E. and J.B. provided guidance regarding clinical relevance of the work; M.J.G. and C.H.B. wrote the manuscript with major contributions from S.R., S.J.H. and U.M.; M.R.S., D.A.H., J.Se. and P.A.F. conceived the study, analysed the data and edited the manuscript.

Correspondence to Ultan McDermott or Cyril H. Benes.

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Competing interests

J.Se. is currently an employee of Genentech and is a shareholder of Roche.

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Supplementary Information

This file contains Supplementary Figures 1-22 and Supplementary Tables 1-3. (PDF 6338 kb)

Supplementary Data

This file contains Supplementary Data 1-11. This file was replaced on 13 April 2012, as the original file posted on line had corrupted, and some of the data was missing from tables 1 and 11. (ZIP 13116 kb)

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