Modeling chemotherapy-induced stress to identify rational combination therapies in the DNA damage response pathway.
Ozan AlkanBirgit SchoeberlMillie ShahAlexander KoshkaryevTim HeinemannDaryl C DrummondMicheal B YaffeAndreas RauePublished in: Science signaling (2018)
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 rationally identify chemotherapy-potentiating drug combinations.
Keyphrases
- dna damage response
- cell fate
- chemotherapy induced
- dna repair
- dna damage
- cell death
- cell cycle arrest
- cell cycle
- induced apoptosis
- electronic health record
- oxidative stress
- big data
- locally advanced
- cell proliferation
- emergency department
- pi k akt
- squamous cell carcinoma
- machine learning
- stem cells
- single cell
- endoplasmic reticulum stress
- south africa
- data analysis
- artificial intelligence
- cancer therapy
- rectal cancer
- optical coherence tomography
- single molecule