Methods for high-throughput drug combination screening and synergy scoring




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

He L. et al.

PublisherHumana Press Inc.

New York

2018

Cancer Systems Biology

Methods in Molecular Biology

Methods in Molecular Biology

1711

1711

351

398

48

978-1-4939-7492-4

978-1-4939-7493-1

1064-3745

DOIhttps://doi.org/10.1007/978-1-4939-7493-1_17

https://link.springer.com/protocol/10.1007/978-1-4939-7493-1_17#citeas



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.



Last updated on 2024-26-11 at 19:33