Physical oncology: a bench-to-bedside quantitative and predictive approach

Hermann B. Frieboes, Mark A. J. Chaplain, Alastair M. Thompson, Elaine L. Bearer, John S. Lowengrub, Vittorio Cristini

    Research output: Contribution to journalReview article

    34 Citations (Scopus)

    Abstract

    Cancer models relating basic science to clinical care in oncology may fail to address the nuances of tumor behavior and therapy, as in the case, discussed herein, of the complex multiscale dynamics leading to the often-observed enhanced invasiveness, paradoxically induced by the very antiangiogenic therapy designed to destroy the tumor. Studies would benefit from approaches that quantitatively link the multiple physical and temporal scales from molecule to tissue in order to offer outcome predictions for individual patients. Physical oncology is an approach that applies fundamental principles from the physical and biological sciences to explain certain cancer behaviors as observable characteristics arising from the underlying physical and biochemical events. For example, the transport of oxygen molecules through tissue affects phenotypic characteristics such as cell proliferation, apoptosis, and adhesion, which in turn underlie the patient-scale tumor growth and invasiveness. Our review of physical oncology illustrates how tumor behavior and treatment response may be a quantifiable function of marginally stable molecular and/or cellular conditions modulated by inhomogeneity. By incorporating patient-specific genomic, proteomic, metabolomic, and cellular data into multiscale physical models, physical oncology could complement current clinical practice through enhanced understanding of cancer behavior, thus potentially improving patient survival. Cancer Res; 71(2); 298-302. (C) 2011 AACR.

    Original languageEnglish
    Pages (from-to)298-302
    Number of pages5
    JournalCancer Research
    Volume71
    Issue number2
    DOIs
    Publication statusPublished - 15 Jan 2011

    Keywords

    • NONLINEAR SIMULATION
    • MATHEMATICAL-MODELS
    • TUMOR-GROWTH
    • COMPUTER-SIMULATION
    • INVASION
    • ANGIOGENESIS
    • MORPHOLOGY
    • EVOLUTION
    • CELLS

    Cite this

    Frieboes, H. B., Chaplain, M. A. J., Thompson, A. M., Bearer, E. L., Lowengrub, J. S., & Cristini, V. (2011). Physical oncology: a bench-to-bedside quantitative and predictive approach. Cancer Research, 71(2), 298-302. https://doi.org/10.1158/0008-5472.CAN-10-2676