Abstract
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
| Original language | English (US) |
|---|---|
| Pages (from-to) | 603-616 |
| Number of pages | 14 |
| Journal | Cell |
| Volume | 156 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jan 30 2014 |
Bibliographical note
Funding Information:The authors would like to thank the Holland and Michor labs and Jasmine Foo for discussions and comments and National Institutes of Health and National Science Foundation grants RO1 CA100688, U54 CA163167, U54 CA143798, U01 CA141502-01 (to E.C.H.), U54 CA143798 (to F.M.), NSF DMS-1224362, U54 CA143798 (to K.L.), MSTP GM07739, F31 NS076028 (to K.P.), and P01 CA085878 (to B.D.R.).
