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Computational Analyses Connect Small-Molecule Sensitivity to Cellular Features Using Large Panels of Cancer Cell Lines

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Systems Chemical Biology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1888))

Abstract

We recently pioneered several analyses of small-molecule sensitivity data collected from large-scale perturbation of hundreds of cancer cell lines with hundreds of small molecules, with cell viability measured as a readout of compound sensitivity. We performed these studies using cancer cell lines previously annotated with cellular, genomic, and basal gene-expression features. By combining small-molecule sensitivity data with these other datasets, we identified new candidate biomarkers of sensitivity, gained insights into small-molecule mechanisms of action, and proposed candidate hypotheses for cancer dependencies (including candidate combination therapies). Nevertheless, given the size of these datasets, we expect that many connections between cellular features and small-molecule sensitivity remain underexplored. In this chapter, we provide a step-by-step account of foundational data-analysis methods underlying our published studies, including working MATLAB code applied to our own public datasets. These procedures will allow others to repeat analyses of our data with new parameters, in additional contexts, and to adapt our procedures to their own datasets.

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Acknowledgments

Development of the code presented in the chapter was supported by the National Cancer Institute (NCI) through the Cancer Target Discovery and Development (CTD2) Network (grant numbers U01CA176152 and U01CA217848). The authors are grateful to Shubhroz Gill, Brittany Petros, and Bridget Wagner for helpful discussions on the manuscript.

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Authors and Affiliations

  1. Cancer Biology Program, Broad Institute of Harvard and MIT, Cambridge, MA, USA

    Matthew G. Rees

  2. Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden

    Brinton Seashore-Ludlow

  3. Chemical Biology and Therapeutics Science Program, Broad Institute of Harvard and MIT, Cambridge, MA, USA

    Paul A. Clemons

Authors
  1. Matthew G. Rees
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  2. Brinton Seashore-Ludlow
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  3. Paul A. Clemons
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Correspondence to Paul A. Clemons .

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Editors and Affiliations

  1. Department of Chemical Biology, Max Planck Institute of Molecular Physiology, Dortmund, Germany

    Slava Ziegler

  2. Department of Chemical Biology, Max Planck Institute of Molecular Physiology, Dortmund, Germany

    Herbert Waldmann

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Rees, M.G., Seashore-Ludlow, B., Clemons, P.A. (2019). Computational Analyses Connect Small-Molecule Sensitivity to Cellular Features Using Large Panels of Cancer Cell Lines. In: Ziegler, S., Waldmann, H. (eds) Systems Chemical Biology. Methods in Molecular Biology, vol 1888. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8891-4_14

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  • DOI: https://doi.org/10.1007/978-1-4939-8891-4_14

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