Prediction and identification of synergistic compound combinations against pancreatic cancer cells.
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Authors
KalantarMotamedi, Yasaman
Choi, Ran Joo
Koh, Siang-Boon
Bramhall, Jo L
Fan, Tai-Ping
Publication Date
2021-09-24Journal Title
iScience
ISSN
2589-0042
Publisher
Elsevier BV
Volume
24
Issue
9
Pages
103080
Language
eng
Type
Article
This Version
VoR
Physical Medium
Electronic-eCollection
Metadata
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KalantarMotamedi, Y., Choi, R. J., Koh, S., Bramhall, J. L., Fan, T., & Bender, A. (2021). Prediction and identification of synergistic compound combinations against pancreatic cancer cells.. iScience, 24 (9), 103080. https://doi.org/10.1016/j.isci.2021.103080
Abstract
Resistance to current therapies is common for pancreatic cancer and hence novel treatment options are urgently needed. In this work, we developed and validated a computational method to select synergistic compound combinations based on transcriptomic profiles from both the disease and compound side, combined with a pathway scoring system, which was then validated prospectively by testing 30 compounds (and their combinations) on PANC-1 cells. Some compounds selected as single agents showed lower GI50 values than the standard of care, gemcitabine. Compounds suggested as combination agents with standard therapy gemcitabine based on the best performing scoring system showed on average 2.82-5.18 times higher synergies compared to compounds that were predicted to be active as single agents. Examples of highly synergistic in vitro validated compound pairs include gemcitabine combined with Entinostat, thioridazine, loperamide, scriptaid and Saracatinib. Hence, the computational approach presented here was able to identify synergistic compound combinations against pancreatic cancer cells.
Identifiers
External DOI: https://doi.org/10.1016/j.isci.2021.103080
This record's URL: https://www.repository.cam.ac.uk/handle/1810/330946
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