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

  • Matthew G. Rees
  • Brinton Seashore-Ludlow
  • Paul A. Clemons
Protocol
Part of the Methods in Molecular Biology book series (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.

Key words

Computational biology Chemical biology Pharmacogenomics Biomarkers Cancer dependencies Combination therapy Public datasets Data sharing Reproducibility 

Notes

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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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Matthew G. Rees
    • 1
  • Brinton Seashore-Ludlow
    • 2
  • Paul A. Clemons
    • 3
  1. 1.Cancer Biology ProgramBroad Institute of Harvard and MITCambridgeUSA
  2. 2.Department of Oncology-PathologyKarolinska InstitutetStockholmSweden
  3. 3.Chemical Biology and Therapeutics Science ProgramBroad Institute of Harvard and MITCambridgeUSA

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