Multiscale tumor modeling

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2014
Ünsal, Serbülent
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Cancer’s complex behavior decreases success rates of the cancer therapies. The usual steps cancer therapy are, deciding phase of the cancer and planing the therapy according to medical guidelines and there is no room or chance for personalized medicine. Simulation systems that use patient specific data as input and up-to-date scientific evidence as business rules has chance to help clinicians for evidence based personalized medicine practice.In this study our aim is creating a basic model to guide researchers who are eager to start tumor modeling. Developed model tries to simulate adenocarcinoma which is a subtype of non-small cell lung carcinoma. Parameters of model gathered from literature is based on A549. In simulations effects of oxygen concentration and mutation rate are examined. Tumor cell number decreases and apoptosis frequency increases proportionally with oxygen concentration’s decrease. When mutation rate decreases tumors become more vulnerable and apoptosis rate increases. All these results proves that model is consistent with tumor biology rules.
Tumors, Cancer, Cancer, Cellular automata.
http://etd.lib.metu.edu.tr/upload/12617036/index.pdf
https://hdl.handle.net/11511/23456
Graduate School of Informatics, Thesis

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Citation Formats
S. Ünsal, “Multiscale tumor modeling,” M.S. - Master of Science, Middle East Technical University, 2014.
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