Article

Magnetic resonance imaging determination of tumor grade and early response to temozolomide in a genetically engineered mouse model of glioma

MIR Preclinical Services, Inc., Ann Arbor, Michigan, USA.
Clinical Cancer Research (Impact Factor: 8.19). 06/2007; 13(10):2897-904. DOI: 10.1158/1078-0432.CCR-06-3058
Source: PubMed

ABSTRACT The median survival for patients diagnosed with glioblastoma multiforme, the most common type of brain tumor, is less than 1 year. Animal glioma models that are more predictive of therapeutic response in human patients than traditional models and that are genetically and histologically accurate are an unmet need. The nestin tv-a (Ntv-a) genetically engineered mouse spontaneously develops glioma when infected with ALV-A expressing platelet-derived growth factor, resulting in autocrine platelet-derived growth factor signaling.
In the Ntv-a genetically engineered mouse model, T2-weighted and T1-weighted, contrast-enhanced magnetic resonance images were correlated with histology, glioma grade (high or low), and survival. Magnetic resonance imaging (MRI) was therefore used to enroll mice with high-grade gliomas into a second study that tested efficacy of the current standard of care for glioma, temozolomide (100 mg/kg qdx5 i.p., n=13).
The Ntv-a model generated a heterogeneous group of gliomas, some with high-grade growth rate and histologic characteristics and others with characteristics of lower-grade gliomas. We showed that MRI could be used to predict tumor grade and survival. Temozolomide treatment of high-grade tv-a gliomas provided a 14-day growth delay compared with vehicle controls. Diffusion MRI measurement of the apparent diffusion coefficient showed an early decrease in cellularity with temozolomide, similar to that observed in humans.
The use of MRI in the Ntv-a model allows determination of glioma grade and survival prediction, distribution of mice with specific tumor types into preclinical trials, and efficacy determination both by tumor growth and early apparent diffusion coefficient response.

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