Dataset Information

Large-scale assessment of the gliomasphere model system.

ABSTRACT: Gliomasphere cultures are widely utilized for the study of glioblastoma (GBM). However, this model system is not well characterized, and the utility of current classification methods is not clear.We used 71 gliomasphere cultures from 68 individuals. Using gene expression-based classification, we performed unsupervised clustering and associated gene expression with gliomasphere phenotypes and patient survival.Some aspects of the gene expression-based classification method were robust because the gliomasphere cultures retained their classification over many passages, and IDH1 mutant gliomaspheres were all proneural. While gene expression of a subset of gliomasphere cultures was more like the parent tumor than any other tumor, gliomaspheres did not always harbor the same classification as their parent tumor. Classification was not associated with whether a sphere culture was derived from primary or recurrent GBM or associated with the presence of EGFR amplification or rearrangement. Unsupervised clustering of gliomasphere gene expression distinguished 2 general categories (mesenchymal and nonmesenchymal), while multidimensional scaling distinguished 3 main groups and a fourth minor group. Unbiased approaches revealed that PI3Kinase, protein kinase A, mTOR, ERK, Integrin, and beta-catenin pathways were associated with in vitro measures of proliferation and sphere formation. Associating gene expression with gliomasphere phenotypes and patient outcome, we identified genes not previously associated with GBM: PTGR1, which suppresses proliferation, and EFEMP2 and LGALS8, which promote cell proliferation.This comprehensive assessment reveals advantages and limitations of using gliomaspheres to model GBM biology, and provides a novel strategy for selecting genes for future study.

SUBMITTER: Laks DR

PROVIDER: S-EPMC5035518 | biostudies-other | 2016 Oct

REPOSITORIES: biostudies-other

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Large-scale assessment of the gliomasphere model system.

Laks Dan R DR Crisman Thomas J TJ Shih Michelle Y S MY Mottahedeh Jack J Gao Fuying F Sperry Jantzen J Garrett Matthew C MC Yong William H WH Cloughesy Timothy F TF Liau Linda M LM Lai Albert A Coppola Giovanni G Kornblum Harley I HI

Neuro-oncology 20160425 10

<h4>Background</h4>Gliomasphere cultures are widely utilized for the study of glioblastoma (GBM). However, this model system is not well characterized, and the utility of current classification methods is not clear.<h4>Methods</h4>We used 71 gliomasphere cultures from 68 individuals. Using gene expression-based classification, we performed unsupervised clustering and associated gene expression with gliomasphere phenotypes and patient survival.<h4>Results</h4>Some aspects of the gene expression-b ...[more]

PMID: 27116978

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Project description:Ungulates, in particular the Central European roe deer Capreolus capreolus and the North American white-tailed deer Odocoileus virginianus, are economically and ecologically important. The two species are risk factors for deer-vehicle collisions and as browsers of palatable trees have implications for forest regeneration. However, no large-scale management systems for ungulates have been implemented, mainly because of the high efforts and costs associated with attempts to estimate population sizes of free-living ungulates living in a complex landscape. Attempts to directly estimate population sizes of deer are problematic owing to poor data quality and lack of spatial representation on larger scales. We used data on >74,000 deer-vehicle collisions observed in 2006 and 2009 in Bavaria, Germany, to model the local risk of deer-vehicle collisions and to investigate the relationship between deer-vehicle collisions and both environmental conditions and browsing intensities. An innovative modelling approach for the number of deer-vehicle collisions, which allows nonlinear environment-deer relationships and assessment of spatial heterogeneity, was the basis for estimating the local risk of collisions for specific road types on the scale of Bavarian municipalities. Based on this risk model, we propose a new "deer-vehicle collision index" for deer management. We show that the risk of deer-vehicle collisions is positively correlated to browsing intensity and to harvest numbers. Overall, our results demonstrate that the number of deer-vehicle collisions can be predicted with high precision on the scale of municipalities. In the densely populated and intensively used landscapes of Central Europe and North America, a model-based risk assessment for deer-vehicle collisions provides a cost-efficient instrument for deer management on the landscape scale. The measures derived from our model provide valuable information for planning road protection and defining hunting quota. Open-source software implementing the model can be used to transfer our modelling approach to wildlife-vehicle collisions elsewhere.

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Large-scale assessment of the gliomasphere model system.

Publications

Large-scale assessment of the gliomasphere model system.

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