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Modeling chemotherapy-induced stress to identify rational combination therapies in the DNA damage response pathway

  • Cells respond to DNA damage by activating complex signaling networks that decide cell fate, promoting not only DNA damage repair and survival but also cell death. We have developed a multiscale computational model that quantitatively links chemotherapy-induced DNA damage response signaling to cell fate. The computational model was trained and calibrated on extensive data from U2OS osteosarcoma cells, including the cell cycle distribution of the initial cell population, signaling data measured by Western blotting, and cell fate data in response to chemotherapy treatment measured by time-lapse microscopy. The resulting mechanistic model predicted the cellular responses to chemotherapy alone and in combination with targeted inhibitors of the DNA damage response pathway, which we confirmed experimentally. Computational models such as the one presented here can be used to understand the molecular basis that defines the complex interplay between cell survival and cell death and to rationallyCells respond to DNA damage by activating complex signaling networks that decide cell fate, promoting not only DNA damage repair and survival but also cell death. We have developed a multiscale computational model that quantitatively links chemotherapy-induced DNA damage response signaling to cell fate. The computational model was trained and calibrated on extensive data from U2OS osteosarcoma cells, including the cell cycle distribution of the initial cell population, signaling data measured by Western blotting, and cell fate data in response to chemotherapy treatment measured by time-lapse microscopy. The resulting mechanistic model predicted the cellular responses to chemotherapy alone and in combination with targeted inhibitors of the DNA damage response pathway, which we confirmed experimentally. Computational models such as the one presented here can be used to understand the molecular basis that defines the complex interplay between cell survival and cell death and to rationally identify chemotherapy-potentiating drug combinations.show moreshow less

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Metadaten
Author:Ozan Alkan, Birgit Schoeberl, Millie Shah, Alexander Koshkaryev, Tim Heinemann, Daryl C. Drummond, Michael B. Yaffe, Andreas RaueORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1131653
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/113165
ISSN:1945-0877OPAC
ISSN:1937-9145OPAC
Parent Title (English):Science Signaling
Publisher:American Association for the Advancement of Science (AAAS)
Place of publication:Washington, DC
Type:Article
Language:English
Year of first Publication:2018
Publishing Institution:Universität Augsburg
Release Date:2024/05/24
Volume:11
Issue:540
First Page:eaat0229
DOI:https://doi.org/10.1126/scisignal.aat0229
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Modellierung und Simulation biologischer Prozesse
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Licence (German):Deutsches Urheberrecht