Abstract 2830: Understanding chemotherapy-induced replicative stress to identify rational combination therapies

Abstract

Abstract 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 multi-scale computational model using the U2OS osteosarcoma cancer cell line that quantitatively links chemotherapy-induced DNA damage response signaling to cell fate. The computational model was trained and calibrated based on an extensive data set that comprises cell cycle distribution of the initial cell population, signaling data measured by western blot, and cell fate data in response to chemotherapy treatment measured by time-lapse microscopy. The resulting mechanistic model can predict the cellular responses to chemotherapy alone and in combination with targeted inhibitors of the DNA damage response pathway, which we were able to confirm experimentally. Computational models, like the one presented here, can be used to understand the molecular basis that defines the complex interplay between cell survival and cell death, as well as to rationally identify chemotherapy-potentiating drug combinations. Citation Format: Ozan Alkan, Birgit Schoeberl, Millie Shah, Alexander Koshkaryev, Tim Heinemann, Daryl Drummond, Michael B. Yaffe, Andreas Raue. Understanding chemotherapy-induced replicative stress to identify rational combination therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2830.