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Methods for High-throughput Drug Combination Screening and Synergy Scoring

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Cancer Systems Biology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1711))

Abstract

Gene products or pathways that are aberrantly activated in cancer but not in normal tissue hold great promises for being effective and safe anticancer therapeutic targets. Many targeted drugs have entered clinical trials but so far showed limited efficacy mostly due to variability in treatment responses and often rapidly emerging resistance. Toward more effective treatment options, we will need multi-targeted drugs or drug combinations, which selectively inhibit the viability and growth of cancer cells and block distinct escape mechanisms for the cells to become resistant. Functional profiling of drug combinations requires careful experimental design and robust data analysis approaches. At the Institute for Molecular Medicine Finland (FIMM), we have developed an experimental-computational pipeline for high-throughput screening of drug combination effects in cancer cells. The integration of automated screening techniques with advanced synergy scoring tools allows for efficient and reliable detection of synergistic drug interactions within a specific window of concentrations, hence accelerating the identification of potential drug combinations for further confirmatory studies.

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Acknowledgments

This work was supported by the Academy of Finland (grants 272437, 269862, 279163, 295504, and 292611 for TA, 272577 and 277293 for KW); the Integrative Life Science Doctoral Program at the University of Helsinki (LH), the Sigrid Jusélius Foundation (KW) and the Cancer Society of Finland (JT, TA, and KW). This project has received funding from the European Union’s Horizon 2020 research and innovation program 2014–2020 under Grant Agreement No 634143 (MedBioinformatics).

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Authors and Affiliations

  1. Institute for Molecular Medicine Finland (FIMM), University of Helsinki, PO Box 33, Helsinki, 00014, Finland

    Liye He, Evgeny Kulesskiy, Jani Saarela, Laura Turunen, Krister Wennerberg, Tero Aittokallio & Jing Tang

  2. Department of Mathematics and Statistics, University of Turku, Turku, Finland

    Tero Aittokallio & Jing Tang

  3. Institute of Biomedicine, University of Helsinki, Helsinki, Finland

    Jing Tang

Authors
  1. Liye He
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  2. Evgeny Kulesskiy
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  3. Jani Saarela
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  4. Laura Turunen
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  5. Krister Wennerberg
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  6. Tero Aittokallio
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  7. Jing Tang
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Corresponding author

Correspondence to Jing Tang .

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Editors and Affiliations

  1. NNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark

    Louise von Stechow

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He, L. et al. (2018). Methods for High-throughput Drug Combination Screening and Synergy Scoring. In: von Stechow, L. (eds) Cancer Systems Biology. Methods in Molecular Biology, vol 1711. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7493-1_17

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  • DOI: https://doi.org/10.1007/978-1-4939-7493-1_17

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7492-4

  • Online ISBN: 978-1-4939-7493-1

  • eBook Packages: Springer Protocols

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