Synergistic effects of complex drug combinations in colorectal cancer cells predicted by logical modelling
Drug combinations have been proposed to combat drug resistance in cancer, but due to the large number of possible drug targets, in vitro testing of all possible combinations of drugs is challenging. Computational models of a disease hold great promise as tools for prediction of response to treatment...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-02-01
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| Series: | Frontiers in Systems Biology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fsysb.2023.1112831/full |
| _version_ | 1797894291366871040 |
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| author | Evelina Folkesson B. Cristoffer Sakshaug Andrea D. Hoel Geir Klinkenberg Åsmund Flobak Åsmund Flobak |
| author_facet | Evelina Folkesson B. Cristoffer Sakshaug Andrea D. Hoel Geir Klinkenberg Åsmund Flobak Åsmund Flobak |
| author_sort | Evelina Folkesson |
| collection | DOAJ |
| description | Drug combinations have been proposed to combat drug resistance in cancer, but due to the large number of possible drug targets, in vitro testing of all possible combinations of drugs is challenging. Computational models of a disease hold great promise as tools for prediction of response to treatment, and here we constructed a logical model integrating signaling pathways frequently dysregulated in cancer, as well as pathways activated upon DNA damage, to study the effect of clinically relevant drug combinations. By fitting the model to a dataset of pairwise combinations of drugs targeting MEK, PI3K, and TAK1, as well as several clinically approved agents (palbociclib, olaparib, oxaliplatin, and 5FU), we were able to perform model simulations that allowed us to predict more complex drug combinations, encompassing sets of three and four drugs, with potentially stronger effects compared to pairwise drug combinations. All predicted third-order synergies, as well as a subset of non-synergies, were successfully confirmed by in vitro experiments in the colorectal cancer cell line HCT-116, highlighting the strength of using computational strategies to rationalize drug testing. |
| first_indexed | 2024-04-10T07:06:38Z |
| format | Article |
| id | doaj.art-d9ff8c0e77264f3ab637172d892f4cc1 |
| institution | Directory Open Access Journal |
| issn | 2674-0702 |
| language | English |
| last_indexed | 2024-04-10T07:06:38Z |
| publishDate | 2023-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Systems Biology |
| spelling | doaj.art-d9ff8c0e77264f3ab637172d892f4cc12023-02-27T07:28:30ZengFrontiers Media S.A.Frontiers in Systems Biology2674-07022023-02-01310.3389/fsysb.2023.11128311112831Synergistic effects of complex drug combinations in colorectal cancer cells predicted by logical modellingEvelina Folkesson0B. Cristoffer Sakshaug1Andrea D. Hoel2Geir Klinkenberg3Åsmund Flobak4Åsmund Flobak5Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, NorwayDepartment of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, NorwayDepartment of Biotechnology, SINTEF Materials and Chemistry, Trondheim, NorwayDepartment of Biotechnology, SINTEF Materials and Chemistry, Trondheim, NorwayDepartment of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, NorwayThe Cancer Clinic, St Olav’s University Hospital, Trondheim, NorwayDrug combinations have been proposed to combat drug resistance in cancer, but due to the large number of possible drug targets, in vitro testing of all possible combinations of drugs is challenging. Computational models of a disease hold great promise as tools for prediction of response to treatment, and here we constructed a logical model integrating signaling pathways frequently dysregulated in cancer, as well as pathways activated upon DNA damage, to study the effect of clinically relevant drug combinations. By fitting the model to a dataset of pairwise combinations of drugs targeting MEK, PI3K, and TAK1, as well as several clinically approved agents (palbociclib, olaparib, oxaliplatin, and 5FU), we were able to perform model simulations that allowed us to predict more complex drug combinations, encompassing sets of three and four drugs, with potentially stronger effects compared to pairwise drug combinations. All predicted third-order synergies, as well as a subset of non-synergies, were successfully confirmed by in vitro experiments in the colorectal cancer cell line HCT-116, highlighting the strength of using computational strategies to rationalize drug testing.https://www.frontiersin.org/articles/10.3389/fsysb.2023.1112831/fullcolorectal cancerlogical modellingdrug combinationssynergyprediction |
| spellingShingle | Evelina Folkesson B. Cristoffer Sakshaug Andrea D. Hoel Geir Klinkenberg Åsmund Flobak Åsmund Flobak Synergistic effects of complex drug combinations in colorectal cancer cells predicted by logical modelling Frontiers in Systems Biology colorectal cancer logical modelling drug combinations synergy prediction |
| title | Synergistic effects of complex drug combinations in colorectal cancer cells predicted by logical modelling |
| title_full | Synergistic effects of complex drug combinations in colorectal cancer cells predicted by logical modelling |
| title_fullStr | Synergistic effects of complex drug combinations in colorectal cancer cells predicted by logical modelling |
| title_full_unstemmed | Synergistic effects of complex drug combinations in colorectal cancer cells predicted by logical modelling |
| title_short | Synergistic effects of complex drug combinations in colorectal cancer cells predicted by logical modelling |
| title_sort | synergistic effects of complex drug combinations in colorectal cancer cells predicted by logical modelling |
| topic | colorectal cancer logical modelling drug combinations synergy prediction |
| url | https://www.frontiersin.org/articles/10.3389/fsysb.2023.1112831/full |
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