<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Laks DR</submitter><funding>National Institutes of Neurological Disorders and Stroke (NINDS)</funding><funding>NCATS NIH HHS</funding><funding>NICHD NIH HHS</funding><funding>California Institute of Regenerative Medicine (CIRM) Training Grant</funding><funding>NINDS NIH HHS</funding><funding>NCI NIH HHS</funding><funding>NINDS</funding><pagination>1367-78</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC5035518</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>18(10)</volume><pubmed_abstract>&lt;h4>Background&lt;/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.&lt;h4>Methods&lt;/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.&lt;h4>Results&lt;/h4>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 d</pubmed_abstract><journal>Neuro-oncology</journal><pubmed_title>Large-scale assessment of the gliomasphere model system.</pubmed_title><pmcid>PMC5035518</pmcid><funding_grant_id>R56 NS052563</funding_grant_id><funding_grant_id>R25 NS079198</funding_grant_id><funding_grant_id>TG2-01169</funding_grant_id><funding_grant_id>NS052563</funding_grant_id><funding_grant_id>P30 CA016042</funding_grant_id><funding_grant_id>R01 CA179071</funding_grant_id><funding_grant_id>UL1 TR000124</funding_grant_id><funding_grant_id>R01 NS052563</funding_grant_id><funding_grant_id>P30 NS062691</funding_grant_id><funding_grant_id>U54 HD087101</funding_grant_id><pubmed_authors>Garrett MC</pubmed_authors><pubmed_authors>Liau LM</pubmed_authors><pubmed_authors>Cloughesy TF</pubmed_authors><pubmed_authors>Laks DR</pubmed_authors><pubmed_authors>Lai A</pubmed_authors><pubmed_authors>Sperry J</pubmed_authors><pubmed_authors>Shih MY</pubmed_authors><pubmed_authors>Gao F</pubmed_authors><pubmed_authors>Coppola G</pubmed_authors><pubmed_authors>Mottahedeh J</pubmed_authors><pubmed_authors>Yong WH</pubmed_authors><pubmed_authors>Crisman TJ</pubmed_authors><pubmed_authors>Kornblum HI</pubmed_authors></additional><is_claimable>false</is_claimable><name>Large-scale assessment of the gliomasphere model system.</name><description>&lt;h4>Background&lt;/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.&lt;h4>Methods&lt;/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.&lt;h4>Results&lt;/h4>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 d</description><dates><release>2016-01-01T00:00:00Z</release><publication>2016 Oct</publication><modification>2026-05-05T05:43:05.37Z</modification><creation>2019-03-27T02:25:03Z</creation></dates><accession>S-EPMC5035518</accession><cross_references><pubmed>27116978</pubmed><doi>10.1093/neuonc/now045</doi></cross_references></HashMap>