NDLI: Quantitative Modeling of Tumor Dynamics and Radiotherapy

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Quantitative Modeling of Tumor Dynamics and Radiotherapy

Content Provider	Springer Nature Link
Author	Enderling, Heiko Chaplain, Mark A. J. Hahnfeldt, Philip
Copyright Year	2010
Abstract	Cancer is a complex disease, necessitating research on many different levels; at the subcellular level to identify genes, proteins and signaling pathways associated with the disease; at the cellular level to identify, for example, cell-cell adhesion and communication mechanisms; at the tissue level to investigate disruption of homeostasis and interaction with the tissue of origin or settlement of metastasis; and finally at the systems level to explore its global impact, e.g. through the mechanism of cachexia. Mathematical models have been proposed to identify key mechanisms that underlie dynamics and events at every scale of interest, and increasing effort is now being paid to multi-scale models that bridge the different scales. With more biological data becoming available and with increased interdisciplinary efforts, theoretical models are rendering suitable tools to predict the origin and course of the disease. The ultimate aims of cancer models, however, are to enlighten our concept of the carcinogenesis process and to assist in the designing of treatment protocols that can reduce mortality and improve patient quality of life. Conventional treatment of cancer is surgery combined with radiotherapy or chemotherapy for localized tumors or systemic treatment of advanced cancers, respectively. Although radiation is widely used as treatment, most scheduling is based on empirical knowledge and less on the predictions of sophisticated growth dynamical models of treatment response. Part of the failure to translate modeling research to the clinic may stem from language barriers, exacerbated by often esoteric model renderings with inaccessible parameterization. Here we discuss some ideas for combining tractable dynamical tumor growth models with radiation response models using biologically accessible parameters to provide a more intuitive and exploitable framework for understanding the complexity of radiotherapy treatment and failure.
Starting Page	341
Ending Page	353
Page Count	13
File Format	PDF
ISSN	00015342
Journal	Acta Biotheoretica
Volume Number	58
Issue Number	4
e-ISSN	15728358
Language	English
Publisher	Springer Netherlands
Publisher Date	2010-07-24
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Mathematical model Cellular automaton Radiotherapy Accelerated repopulation cancer stem cells Evolutionary Biology Philosophy of Biology
Content Type	Text
Resource Type	Article
Subject	Philosophy Applied Mathematics Medicine Biochemistry, Genetics and Molecular Biology Environmental Science Agricultural and Biological Sciences

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