Purpose: To evaluate the efficacy of fractionated stereotactic radiotherapy (FSRT) performed as reirradiation in 172 patients with recurrent low- and high-grade gliomas. Patients and Methods: Between 1990 and 2004, 172 patients with recurrent gliomas were treated with FSRT as reirradiation in a single institution. Seventy-one patients suffered from WHO grade 2 gliomas. WHO grade 3 gliomas were diagnosed in 42 patients, and 59 patients were diagnosed with glioblastoma multiforme (GBM). The median time between primary radiotherapy and reirradiation was 10 months for GBM, 32 months for WHO grade 3 tumors, and 48 months for grade 2 astrocytomas. FSRT was performed with a median dose of 36 Gy in a median fractionation of 5 × 2 Gy/wk. Results: Median overall survival after primary diagnosis was 21 months for patients with GBM, 50 months for patients with WHO grade 3 gliomas, and 111 months for patients with WHO grade 2 gliomas. Histologic grading was the strongest predictor for overall survival, together with the extent of neurosurgical resection and age at primary diagnosis. Median survival after reirradiation was 8 months for patients with GBM, 16 months for patients with grade 3 tumors, and 22 months for patients with low-grade gliomas. Only time to progression and histology were significant in influencing survival after reirradiation. Progression-free survival after FSRT was 5 months for GBM, 8 months for WHO grade 3 tumors, and 12 months for low-grade gliomas. Conclusion: FSRT is well tolerated and may be effective in patients with recurrent gliomas. Prospective studies are warranted for further evaluation.

Purpose: Stem-like tumor cells comprise a highly tumorigenic and therapy-resistant tumor subpopulation, which is believed to substantially influence tumor initiation and therapy resistance in glioma. Currently, therapeutic, drug-induced differentiation is considered as a promising approach to eradicate this tumor-driving cell population; retinoic acid is well known as a potent modulator of differentiation and proliferation in normal stem cells. In glioma, knowledge about the efficacy of retinoic acid–induced differentiation to target the stem-like tumor cell pool could have therapeutic implications. Experimental Design: Stem-like glioma cells (SLGC) were differentiated with all-trans retinoic acid–containing medium to study the effect of differentiation on angiogenesis, invasive growth, as well as radioresistance and chemoresistance of SLGCs. In vivo effects were studied using live microscopy in a cranial window model. Results: Our data suggest that in vitro differentiation of SLGCs induces therapy-sensitizing effects, impairs the secretion of angiogenic cytokines, and disrupts SLGCs motility. Further, ex vivo differentiation reduces tumorigenicity of SLGCs. Finally, we show that all-trans retinoic acid treatment alone can induce antitumor effects in vivo. Conclusions: Altogether, these results highlight the potential of differentiation treatment to target the stem-like cell population in glioblastoma. Clin Cancer Res; 16(10); 2715–28. ©2010 AACR.

Glioblastoma (GBM) is a highly invasive brain tumor, whose cells infiltrate surrounding normal brain tissue beyond the lesion outlines visible in the current medical scans. These infiltrative cells are treated mainly by radiotherapy. Existing radiotherapy plans for brain tumors derive from population studies and scarcely account for patient-specific conditions. Here, we provide a Bayesian machine learning framework for the rational design of improved, personalized radiotherapy plans using mathematical modeling and patient multimodal medical scans. Our method, for the first time, integrates complementary information from high-resolution MRI scans and highly specific FET-PET metabolic maps to infer tumor cell density in GBM patients. The Bayesian framework quantifies imaging and modeling uncertainties and predicts patient-specific tumor cell density with credible intervals. The proposed methodology relies only on data acquired at a single time point and, thus, is applicable to standard clinical settings. An initial clinical population study shows that the radiotherapy plans generated from the inferred tumor cell infiltration maps spare more healthy tissue thereby reducing radiation toxicity while yielding comparable accuracy with standard radiotherapy protocols. Moreover, the inferred regions of high tumor cell densities coincide with the tumor radioresistant areas, providing guidance for personalized dose-escalation. The proposed integration of multimodal scans and mathematical modeling provides a robust, non-invasive tool to assist personalized radiotherapy design.