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A high-throughput drug combination screen of targeted small molecule inhibitors in cancer cell lines

While there is a high interest in drug combinations in cancer therapy, openly accessible datasets for drug combination responses are sparse. Here we present a dataset comprising 171 pairwise combinations of 19 individual drugs targeting signal transduction mechanisms across eight cancer cell lines,...

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Autores principales: Flobak, Åsmund, Niederdorfer, Barbara, Nakstad, Vu To, Thommesen, Liv, Klinkenberg, Geir, Lægreid, Astrid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6820772/
https://www.ncbi.nlm.nih.gov/pubmed/31664030
http://dx.doi.org/10.1038/s41597-019-0255-7
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author Flobak, Åsmund
Niederdorfer, Barbara
Nakstad, Vu To
Thommesen, Liv
Klinkenberg, Geir
Lægreid, Astrid
author_facet Flobak, Åsmund
Niederdorfer, Barbara
Nakstad, Vu To
Thommesen, Liv
Klinkenberg, Geir
Lægreid, Astrid
author_sort Flobak, Åsmund
collection PubMed
description While there is a high interest in drug combinations in cancer therapy, openly accessible datasets for drug combination responses are sparse. Here we present a dataset comprising 171 pairwise combinations of 19 individual drugs targeting signal transduction mechanisms across eight cancer cell lines, where the effect of each drug and drug combination is reported as cell viability assessed by metabolic activity. Drugs are chosen by their capacity to specifically interfere with well-known signal transduction mechanisms. Signalling processes targeted by the drugs include PI3K/AKT, NFkB, JAK/STAT, CTNNB1/TCF, and MAPK pathways. Drug combinations are classified as synergistic based on the Bliss independence synergy metrics. The data identifies combinations that synergistically reduce cancer cell viability and that can be of interest for further pre-clinical investigations.
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spelling pubmed-68207722019-11-07 A high-throughput drug combination screen of targeted small molecule inhibitors in cancer cell lines Flobak, Åsmund Niederdorfer, Barbara Nakstad, Vu To Thommesen, Liv Klinkenberg, Geir Lægreid, Astrid Sci Data Data Descriptor While there is a high interest in drug combinations in cancer therapy, openly accessible datasets for drug combination responses are sparse. Here we present a dataset comprising 171 pairwise combinations of 19 individual drugs targeting signal transduction mechanisms across eight cancer cell lines, where the effect of each drug and drug combination is reported as cell viability assessed by metabolic activity. Drugs are chosen by their capacity to specifically interfere with well-known signal transduction mechanisms. Signalling processes targeted by the drugs include PI3K/AKT, NFkB, JAK/STAT, CTNNB1/TCF, and MAPK pathways. Drug combinations are classified as synergistic based on the Bliss independence synergy metrics. The data identifies combinations that synergistically reduce cancer cell viability and that can be of interest for further pre-clinical investigations. Nature Publishing Group UK 2019-10-29 /pmc/articles/PMC6820772/ /pubmed/31664030 http://dx.doi.org/10.1038/s41597-019-0255-7 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Flobak, Åsmund
Niederdorfer, Barbara
Nakstad, Vu To
Thommesen, Liv
Klinkenberg, Geir
Lægreid, Astrid
A high-throughput drug combination screen of targeted small molecule inhibitors in cancer cell lines
title A high-throughput drug combination screen of targeted small molecule inhibitors in cancer cell lines
title_full A high-throughput drug combination screen of targeted small molecule inhibitors in cancer cell lines
title_fullStr A high-throughput drug combination screen of targeted small molecule inhibitors in cancer cell lines
title_full_unstemmed A high-throughput drug combination screen of targeted small molecule inhibitors in cancer cell lines
title_short A high-throughput drug combination screen of targeted small molecule inhibitors in cancer cell lines
title_sort high-throughput drug combination screen of targeted small molecule inhibitors in cancer cell lines
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6820772/
https://www.ncbi.nlm.nih.gov/pubmed/31664030
http://dx.doi.org/10.1038/s41597-019-0255-7
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