title: Toward a science of tumor forecasting for clinical oncology.
abstract: We propose that the quantitative cancer biology community makes a concerted effort to apply lessons from weather forecasting to develop an analogous methodology for predicting and evaluating tumor growth and treatment response. Currently, the time course of tumor response is not predicted; instead, response is only assessed post hoc by physical examination or imaging methods. This fundamental practice within clinical oncology limits optimization of a treatment regimen for an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. With a successful methodology toward tumor forecasting, it should be possible to integrate large tumor-specific datasets of varied types and effectively defeat one cancer patient at a time.
authors.affiliation: Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee. Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, Tennessee. Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee. Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee. Department of Cancer Biology, Vanderbilt University, Nashville, Tennessee. Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, Tennessee. thomas.yankeelov@vanderbilt.edu.
authors.forename: Thomas E
authors.initials: TE
authors.lastname: Yankeelov
authors.affiliation: Department of Cancer Biology, Vanderbilt University, Nashville, Tennessee. Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, Tennessee.
authors.forename: Vito
authors.initials: V
authors.lastname: Quaranta
authors.affiliation: Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Nashville, Tennessee.
authors.forename: Katherine J
authors.initials: KJ
authors.lastname: Evans
authors.affiliation: Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee.
authors.forename: Erin C
authors.initials: EC
authors.lastname: Rericha
mesh_terms: D005544:Forecasting; D006801:Humans; D008495:Medical Oncology / Q000639:trends*; D055904:Meteorology; D008962:Models, Theoretical