Mathematical modeling of PDGF-driven glioblastoma reveals optimized radiation dosing schedules.
Glioblastomas (GBMs) are the most common and malignant primary brain tumors and are aggressively treated with surgery, chemotherapy, and radiotherapy. Despite this treatment, recurrence is inevitable and survival has improved minimally over the last 50 years. Recent studies have suggested that GBMs exhibit both heterogeneity and instability of differentiation states and varying sensitivities of these states to radiation. Here, we employed an iterative combined theoretical and experimental strategy that takes into account tumor cellular heterogeneity and dynamically acquired radioresistance to predict the effectiveness of different radiation schedules. Using this model, we identified two delivery schedules predicted to significantly improve efficacy by taking advantage of the dynamic instability of radioresistance. These schedules led to superior survival in mice. Our interdisciplinary approach may also be applicable to other human cancer types treated with radiotherapy and, hence, may lay the foundation for significantly increasing the effectiveness of a mainstay of oncologic therapy. PAPERCLIP:
Department of Industrial and Systems Engineering, University of Minnesota, Minneapolis, MN 55455, USA.
Kevin
K
Leder
Brain Tumor Center, Department of Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA.
Ken
K
Pitter
Brain Tumor Center, Department of Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA.
Quincey
Q
LaPlant
Departments of Neurosciences and Molecular Medicines, Cleveland, OH 44195, USA.
Dolores
D
Hambardzumyan
Center for Molecular Imaging and Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA.
Brian D
BD
Ross
Human Oncology and Pathogenesis Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA.
Timothy A
TA
Chan
Division of Human Biology, Alvord Brain Tumor Center, University of Washington, Seattle, WA 98109, USA.
Eric C
EC
Holland
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02215, USA.
Franziska
F
Michor
D000818:Animals; D001932:Brain Neoplasms / Q000473:pathology / Q000532:radiotherapy*; D005909:Glioblastoma / Q000473:pathology / Q000532:radiotherapy*; D006801:Humans; D051379:Mice; D008954:Models, Biological; D011829:Radiation Dosage