Lesion volume measurements with magnetic resonance imaging are widely used to assess outcome in rodent models of stroke. In this study, we improved a mathematical framework to correct lesion size for edema which is based on manual delineation of the lesion and hemispheres. Furthermore, a novel MATLAB toolbox to register mouse brain MR images to the Allen brain atlas is presented. Its capability to calculate edema-corrected lesion size was compared to the manual approach. Automated image registration performed equally well in in a mouse middle cerebral artery occlusion model (Pearson r ¼ 0.976, p ¼ 2.265e-11). Information encapsulated in the registration was used to generate maps of edema induced tissue volume changes. These showed discrepancies to simplified tissue models underlying the manual approach. The presented techniques provide biologically more meaningful, voxel-wise biomarkers of vasogenic edema after stroke.

Promoter methylation status of O-6-methylguanine-DNA methyltransferase (MGMT), a DNA repair enzyme, is a critical biomarker in glioblastoma (GBM), as treatment decisions and clinical trial inclusion rely on its accurate assessment. However, interpretation of results is complicated by poor interassay reproducibility as well as a weak correlation between methylation status and expression levels of MGMT. This study systematically investigates the influence of tumor purity on tissue subjected to MGMT analysis. A quantitative, allele-specific realtime PCR (qAS-PCR) assay was developed to determine genotype and mutant allele frequency of telomerase promoter (pTERT) mutations as a direct measure of tumor purity. We studied tumor purity, pTERT mutation by Sanger sequencing, MGMT methylation by pyrosequencing, IDH1 mutation status, and clinical parameters in a cohort of high-grade gliomas (n ¼ 97). The qAS-PCR reliably predicted pTERT genotype and tumor purity compared with independent methods. Tumor purity positively and significantly correlated with the extent of methylation in MGMT methylated GBMs. Extent of MGMT methylation differed significantly with respect to pTERT mutation hotspot (C228T vs. C250T). Interestingly, frontal lobe tumors showed greater tumor purity than those in other locations. Above all, tumor purity was identified as an independent prognostic factor in GBM. In conclusion, we determined mutual associations of tumor purity with MGMT methylation and pTERT mutations and found that the extent of MGMT methylation reflects tumor purity. In turn, tumor purity is prognostic in IDH1 wild-type GBM.Implications: Tumor purity is an independent prognostic marker in glioblastoma and is associated with the extent of MGMT methylation. Mol Cancer Res; 15(5); 532-40. Ó2017 AACR.

The transcription factor ZEB1 has gained attention in tumor biology of epithelial cancers because of its function in epithelial-mesenchymal transition, DNA repair, stem cell biology and tumor-induced immunosuppression, but its role in gliomas with respect to invasion and prognostic value is controversial. We characterized ZEB1 expression at single cell level in 266 primary brain tumors and present a comprehensive dataset of high grade gliomas with Ki67, p53, IDH1, and EGFR immunohistochemistry, as well as EGFR FISH. ZEB1 protein expression in glioma stem cell lines was compared to their parental tumors with respect to gene expression subtypes based on RNA-seq transcriptomic profiles. ZEB1 is widely expressed in glial tumors, but in a highly variable fraction of cells. In glioblastoma, ZEB1 labeling index is higher in tumors with EGFR amplification or IDH1 mutation. Co-labeling studies showed that tumor cells and reactive astroglia, but not immune cells contribute to the ZEB1 positive population. In contrast, glioma cell lines constitutively express ZEB1 irrespective of gene expression subtype. In conclusion, our data indicate that immune infiltration likely contributes to differential labelling of ZEB1 and confounds interpretation of bulk ZEB1 expression data.

Background: Prediction of post-stroke outcome using the degree of subacute deficit or magnetic resonance imaging is well studied in humans. While mice are the most commonly used animals in preclinical stroke research, systematic analysis of outcome predictors is lacking. Methods: Data from 13 studies that included 45 min of middle cerebral artery occlusion on 148 mice were pooled. Motor function was measured using a modified protocol for the staircase test of skilled reaching. Phases of subacute and residual deficit were defined. Magnetic resonance images of stroke lesions were co-registered on the Allen Mouse Brain Atlas to characterize stroke topology. Different random forest prediction models that either used motor-functional deficit or imaging parameters were generated for the subacute and residual deficits. Results: We detected both a subacute and residual motor-functional deficit after stroke in mice. Different functional severity grades and recovery trajectories could be observed. In mice with small cortical lesions, lesion volume was the best predictor of the subacute deficit. The residual deficit could be predicted most accurately by the degree of the subacute deficit. When using imaging parameters for the prediction of the residual deficit, including information about the lesion topology increased prediction accuracy. A subset of anatomical regions within the ischemic lesion had particular impact on the prediction of long-term outcome. Prediction accuracy depended on the degree of functional impairment. Conclusions: For the first time, we identified and characterized predictors of post-stroke outcome in a large cohort of mice and found strong concordance with clinical data. These results are discussed in light of study design and imaging limitations. In the future, using outcome prediction can improve the design of preclinical studies and guide intervention decisions.