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- Thomas S. Deisboeck
- Harvard-MIT (HST) Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129;
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- Zhihui Wang
- Harvard-MIT (HST) Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129;
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- Paul Macklin
- Division of Mathematics, University of Dundee, Dundee DD1 4HN, United Kingdom
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- Vittorio Cristini
- Department of Pathology, University of New Mexico, Albuquerque, New Mexico 87131
抄録
<jats:p> Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of this approach in providing quantitative insights in the initiation, progression, and treatment of cancer. In this review, we introduce the most recent and important multiscale cancer modeling works that have successfully established a mechanistic link between different biological scales. Biophysical, biochemical, and biomechanical factors are considered in these models. We also discuss innovative, cutting-edge modeling methods that are moving predictive multiscale cancer modeling toward clinical application. Furthermore, because the development of multiscale cancer models requires a new level of collaboration among scientists from a variety of fields such as biology, medicine, physics, mathematics, engineering, and computer science, an innovative Web-based infrastructure is needed to support this growing community. </jats:p>
収録刊行物
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- Annual Review of Biomedical Engineering
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Annual Review of Biomedical Engineering 13 (1), 127-155, 2011-08-15
Annual Reviews