Molecular Characteristics in MRI-Classified Group 1 Glioblastoma Multiforme.
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ABSTRACT:
SUBMITTER: Haskins WE
PROVIDER: S-EPMC3708153 | biostudies-literature | 2013
REPOSITORIES: biostudies-literature
Publications
Molecular Characteristics in MRI-Classified Group 1 Glioblastoma Multiforme.
Haskins William E WE Zablotsky Bethany L BL Foret Michael R MR Ihrie Rebecca A RA Alvarez-Buylla Arturo A Eisenman Robert N RN Berger Mitchel S MS Lin Chin-Hsing Annie CH
Frontiers in oncology 20130711
Glioblastoma multiforme (GBM) is a clinically and pathologically heterogeneous brain tumor. Previous studies of transcriptional profiling have revealed biologically relevant GBM subtypes associated with specific mutations and dysregulated pathways. Here, we applied a modified proteome to uncover abnormal protein expression profile in a MRI-classified group I GBM (GBM1), which has a spatial relationship with one of the adult neural stem cell niches, subventricular zone (SVZ). Most importantly, we ...[more]
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Project description:Congenital glioblastoma multiforme (cGBM) historically has been considered an aggressive tumor of infancy requiring extensive chemotherapy to achieve cure. We report on 4 patients at our institution with cGBMs who were treated with surgery and chemotherapy (carboplatin and etoposide every 21 days for 2-6 cycles). Four of four patients are progression free at a median time of 27.5 months (22-103 months). To characterize the molecular biology of cGBM, we compared the gene expression profiles of 3 cGBMs to 12 pediatric and 6 primary adult glioblastomas collected at our institution. Unsupervised hierarchical clustering showed cGBMs grouped together with other high-grade gliomas. cGBMs demonstrated marked similarity to both pediatric and adult GBMs, with only a total of 31 differentially expressed genes identified (FDR < 0.05). Unique molecular features of congenital GBMs identified included over-expression of multiple genes involved in glucose metabolism and tissue hypoxia pathways. Four tyrosine kinases were also mong the up-regulated genes (RET, RASGRF2, EFNA5, ALK). Thus, at our institution congenital GBMs, while similar both histologically and molecularly to other GBMs, appear to have a good prognosis with surgery in combination with relatively moderate chemotherapy. Further study is needed to determine if the few gene expression differences that were identified may contribute to the better survival seen in these tumors compared to pediatric or adult GBMs. Key Words: glioblastoma; congenital; pediatric; gene expression; microarray Molecular profiling of 18 AT/RT patient tumor samples was performed using Affymetrix U133 Plus2 GeneChips. Data were background corrected and normalized using gcRMA (as implemented in Bioconductor). Unsupervised agglomerative hierarchical clustering was performed to identify subsets of AT/RTs with similar gene expression. Limma (moderated t-tests; Bioconductor) was used to identify signature genes for each cluster. Bioinformatics web tool DAVID was used to identify enriched biological processes for each cluster. Survival was analyzed using Kaplan-Meier curves and Cox Hazard Ratio. Bioinformatics tools Gene Set Enrichment (GSEA) and Ingenuity Pathways Analysis were also used to gain further insight into cluster differences.
2012-05-20 | E-GEOD-32374 | biostudies-arrayexpress
Project description:Congenital glioblastoma multiforme (cGBM) historically has been considered an aggressive tumor of infancy requiring extensive chemotherapy to achieve cure. We report on 4 patients at our institution with cGBMs who were treated with surgery and chemotherapy (carboplatin and etoposide every 21 days for 2-6 cycles). Four of four patients are progression free at a median time of 27.5 months (22-103 months). To characterize the molecular biology of cGBM, we compared the gene expression profiles of 3 cGBMs to 12 pediatric and 6 primary adult glioblastomas collected at our institution. Unsupervised hierarchical clustering showed cGBMs grouped together with other high-grade gliomas. cGBMs demonstrated marked similarity to both pediatric and adult GBMs, with only a total of 31 differentially expressed genes identified (FDR < 0.05). Unique molecular features of congenital GBMs identified included over-expression of multiple genes involved in glucose metabolism and tissue hypoxia pathways. Four tyrosine kinases were also mong the up-regulated genes (RET, RASGRF2, EFNA5, ALK). Thus, at our institution congenital GBMs, while similar both histologically and molecularly to other GBMs, appear to have a good prognosis with surgery in combination with relatively moderate chemotherapy. Further study is needed to determine if the few gene expression differences that were identified may contribute to the better survival seen in these tumors compared to pediatric or adult GBMs. Key Words: glioblastoma; congenital; pediatric; gene expression; microarray
2012-05-21 | GSE32374 | GEO
Project description:Congenital glioblastoma multiforme (cGBM) historically has been considered an aggressive tumor of infancy requiring extensive chemotherapy to achieve cure. We report on 4 patients at our institution with cGBMs who were treated with surgery and chemotherapy (carboplatin and etoposide every 21 days for 2-6 cycles). Four of four patients are progression free at a median time of 27.5 months (22-103 months). To characterize the molecular biology of cGBM, we compared the gene expression profiles of 3 cGBMs to 12 pediatric and 6 primary adult glioblastomas collected at our institution. Unsupervised hierarchical clustering showed cGBMs grouped together with other high-grade gliomas. cGBMs demonstrated marked similarity to both pediatric and adult GBMs, with only a total of 31 differentially expressed genes identified (FDR < 0.05). Unique molecular features of congenital GBMs identified included over-expression of multiple genes involved in glucose metabolism and tissue hypoxia pathways. Four tyrosine kinases were also mong the up-regulated genes (RET, RASGRF2, EFNA5, ALK). Thus, at our institution congenital GBMs, while similar both histologically and molecularly to other GBMs, appear to have a good prognosis with surgery in combination with relatively moderate chemotherapy. Further study is needed to determine if the few gene expression differences that were identified may contribute to the better survival seen in these tumors compared to pediatric or adult GBMs. Key Words: glioblastoma; congenital; pediatric; gene expression; microarray Molecular profiling of 18 AT/RT patient tumor samples was performed using Affymetrix U133 Plus2 GeneChips. Data were background corrected and normalized using gcRMA (as implemented in Bioconductor). Unsupervised agglomerative hierarchical clustering was performed to identify subsets of AT/RTs with similar gene expression. Limma (moderated t-tests; Bioconductor) was used to identify signature genes for each cluster. Bioinformatics web tool DAVID was used to identify enriched biological processes for each cluster. Survival was analyzed using Kaplan-Meier curves and Cox Hazard Ratio. Bioinformatics tools Gene Set Enrichment (GSEA) and Ingenuity Pathways Analysis were also used to gain further insight into cluster differences.
| S-ECPF-GEOD-32374 | biostudies-other
Project description:Glioblastoma (GBM) is a highly aggressive brain cancer with limited therapeutic options. While efforts to identify genes responsible for GBM have revealed mutations and aberrant gene expression associated with distinct types of GBM, patients with GBM are often diagnosed and classified based on MRI features. Therefore, we seek to identify molecular representatives in parallel with MRI classification for group I and group II primary GBM associated with the subventricular zone (SVZ). As group I and II GBM contain stem-like signature, we compared gene expression profiles between these 2 groups of primary GBM and endogenous neural stem progenitor cells to reveal dysregulation of cell cycle, chromatin status, cellular morphogenesis, and signaling pathways in these 2 types of MRI-classified GBM. In the absence of IDH mutation, several genes associated with metabolism are differentially expressed in these subtypes of primary GBM, implicating metabolic reprogramming occurs in tumor microenvironment. Furthermore, histone lysine methyltransferase EZH2 was upregulated while histone lysine demethylases KDM2 and KDM4 were downregulated in both group I and II primary GBM. Lastly, we identified 9 common genes across large data sets of gene expression profiles among MRI-classified group I/II GBM, a large cohort of GBM subtypes from TCGA, and glioma stem cells by unsupervised clustering comparison. These commonly upregulated genes have known functions in cell cycle, centromere assembly, chromosome segregation, and mitotic progression. Our findings highlight altered expression of genes important in chromosome integrity across all GBM, suggesting a common mechanism of disrupted fidelity of chromosome structure in GBM.
| S-EPMC5405724 | biostudies-literature
Project description:Glioblastoma multiforme is the most common primary malignant brain tumor in adults. In addition to poor response to treatment, a high recurrence rate contributes to the poor prognosis. The purpose of this study was to investigate the genetical and clinical characteristics of recurrent glioblastoma. We used whole transcriptome sequencing data to examine the distribution of molecular subtypes and gene signatures in 22 recurrent glioblastoma taken from the Chinese population, and further analyzed biological progression of the tumors, when compared with primary glioblastoma. The proportion of the classical subtype in recurrent ones (22%) was lower than that in primary glioblastoma (36%). The frequency of IDH1 mutations in recurrent glioblastomas was nearly twice that in primary glioblastomas. TP53 mutations were fewer in proneural recurrent glioblastomas (20%) but frequent in classical recurrent glioblastomas (80%). The most common sites of recurrent glioblastomas were the temporal lobe (41%). In patients diagnosed with recurrent glioblastoma multiforme, 64% were younger than 50 years. Gene set enrichment analysis revealed that chromatin fracture, repair, and remodeling genes were enriched in recurrent glioblastoma. Our results highlight the differences in clinical features, molecular subtypes and gene alterations between primary and recurrent glioblastoma and may be helpful for targeted therapy for recurrent glioblastoma.
| S-EPMC4741581 | biostudies-literature
Project description:The Polycomb group (PcG) proteins play a critical role in histone mediated epigenetics which has been implicated in the malignant evolution of glioblastoma multiforme (GBM). By systematically interrogating The Cancer Genome Atlas (TCGA), we discovered widespread aberrant expression of the PcG members in GBM samples compared to normal brain. The most striking differences were upregulation of EZH2, PHF19, CBX8 and PHC2 and downregulation of CBX7, CBX6, EZH1 and RYBP. Interestingly, changes in EZH2, PHF19, CBX7, CBX6 and EZH1 occurred progressively as astrocytoma grade increased. We validated the aberrant expression of CBX6, CBX7, CBX8 and EZH2 in GBM cell lines by Western blotting and qRT-PCR, and further the aberrant expression of CBX6 in GBM tissue samples by immunohistochemical staining. To determine if there was functional significance to the diminished CBX6 levels in GBM, CBX6 was overexpressed in GBM cells resulting in decreased proliferative capacity. In conclusion, aberrant expression of PcG proteins in GBMs may play a role in the development or maintenance of the malignancy.
| S-EPMC3829908 | biostudies-literature
Project description:Standard-of-care multiparameter magnetic resonance imaging (MRI) scans of the brain were used to objectively subdivide glioblastoma multiforme (GBM) tumors into regions that correspond to variations in blood flow, interstitial edema, and cellular density. We hypothesized that the distribution of these distinct tumor ecological "habitats" at the time of presentation will impact the course of the disease. We retrospectively analyzed initial MRI scans in 2 groups of patients diagnosed with GBM, a long-term survival group comprising subjects who survived >36 month postdiagnosis, and a short-term survival group comprising subjects who survived ?19 month postdiagnosis. The single-institution discovery cohort contained 22 subjects in each group, while the multi-institution validation cohort contained 15 subjects per group. MRI voxel intensities were calibrated, and tumor voxels clustered on contrast-enhanced T1-weighted and fluid-attenuated inversion-recovery (FLAIR) images into 6 distinct "habitats" based on low- to medium- to high-contrast enhancement and low-high signal on FLAIR scans. Habitat 6 (high signal on calibrated contrast-enhanced T1-weighted and FLAIR sequences) comprised a significantly higher volume fraction of tumors in the long-term survival group (discovery cohort, 35% ± 6.5%; validation cohort, 34% ± 4.8%) compared with tumors in the short-term survival group (discovery cohort, 17% ± 4.5%, P < .03; validation cohort, 16 ± 4.0%, P < .007). Of the 6 distinct MRI-defined habitats, the fractional tumor volume of habitat 6 at diagnosis was significantly predictive of long- or short-term survival. We discuss a possible mechanistic basis for this association and implications for habitat-driven adaptive therapy of GBM.
| S-EPMC6403044 | biostudies-literature
Project description:Background:To evaluate the association of multiparametric and multiregional MRI-features with key molecular characteristics in patients with newly-diagnosed glioblastoma. Methods:Retrospective data evaluation was approved by the local ethics committee of the University of Heidelberg (ethics approval number: S-320/2012) and informed consent was waived. Preoperative MRI-features were correlated with key molecular characteristics within a single-institutional cohort of 152 patients with newly-diagnosed glioblastoma. Preoperative MRI-features (n=31) included multiparametric (anatomical, diffusion-, perfusion-, and susceptibility-weighted images) and multiregional (contrast enhancing and non-enhancing FLAIR-hyperintense) information with (histogram) quantification of tumor volumes, volume ratios, apparent diffusion coefficients, cerebral blood flow / volume (CBF / CBV) and intratumoral susceptibility signals. Molecular characteristics determined with the Illumina Infinium HumanMethylation450 array included global DNA-methylation subgroups (e.g. mesenchymal (MES), RTK I “PGFRA”, RTK II “classic”), MGMT-promoter methylation status and hallmark copy-number-variations (EGFR-, PDGFRA-, MDM4- and CDK4-amplification; PTEN-, CDKN2A-, NF1- and RB1-loss). Univariate analyses (voxel-lesion-symptom-mapping for tumor location, Wilcoxon-test for all other MRI-features) as well as machine-learning models were applied to study the strength of association and discriminative value of MRI-features for predicting underlying molecular characteristics. Results: There was no tumor location predilection for any of the assessed molecular parameters (permutation-adjusted p>0.05 each). Univariate imaging parameter associations were noted for EGFR amplification and CDKN2A loss, both demonstrating increased nrCBV and nrCBF values (performance of these parameters, as assessed by the area under the ROC curve ranged from 63 to 69%, FDR-adjusted p<0.05, respectively). Subjecting all MRI-features to machine-learning-based classification allowed to predict EGFR amplification status and the RTK II “classic” GB subgroup with a moderate, yet significantly greater accuracy (63% for EGFR [p<0.01] and 61% for RTK II [p=0.01]) than the prediction by chance, whereas prediction accuracy for all other molecular parameters was non-significant (p>0.05, all models). Conclusions: In summary, we found univariate associations between established MRI-features and molecular characteristics, however not of sufficient strength to allow the generation of machine-learning classification models for reliable and clinically meaningful prediction of the assessed molecular characteristics in patients with newly-diagnosed glioblastoma.
2016-11-23 | GSE85539 | GEO
Project description:BackgroundDespite recent discoveries of new molecular targets and pathways, the search for an effective therapy for Glioblastoma Multiforme (GBM) continues. A newly emerged field, radiogenomics, links gene expression profiles with MRI phenotypes. MRI-FLAIR is a noninvasive diagnostic modality and was previously found to correlate with cellular invasion in GBM. Thus, our radiogenomic screen has the potential to reveal novel molecular determinants of invasion. Here, we present the first comprehensive radiogenomic analysis using quantitative MRI volumetrics and large-scale gene- and microRNA expression profiling in GBM.MethodsBased on The Cancer Genome Atlas (TCGA), discovery and validation sets with gene, microRNA, and quantitative MR-imaging data were created. Top concordant genes and microRNAs correlated with high FLAIR volumes from both sets were further characterized by Kaplan Meier survival statistics, microRNA-gene correlation analyses, and GBM molecular subtype-specific distribution.ResultsThe top upregulated gene in both the discovery (4 fold) and validation (11 fold) sets was PERIOSTIN (POSTN). The top downregulated microRNA in both sets was miR-219, which is predicted to bind to POSTN. Kaplan Meier analysis demonstrated that above median expression of POSTN resulted in significantly decreased survival and shorter time to disease progression (P<0.001). High POSTN and low miR-219 expression were significantly associated with the mesenchymal GBM subtype (P<0.0001).ConclusionHere, we propose a novel diagnostic method to screen for molecular cancer subtypes and genomic correlates of cellular invasion. Our findings also have potential therapeutic significance since successful molecular inhibition of invasion will improve therapy and patient survival in GBM.
| S-EPMC3187774 | biostudies-literature
Project description:Understanding the interactions between tumors and the host immune system holds great promise to uncover biomarkers for targeted therapies, predict the prognosis of patients and guide clinical treatment. However, the immune signatures of glioblastoma multiforme (GBM) remain largely unstudied in terms of systematic analyses. We aimed to classify GBM samples according to immune-related genes and complement the existing immunotherapy system knowledge. In this study, we designed a strategy to identify 3 immune subtypes representing 3 different immune microenvironments (M1-M3) and associated with prognosis. The three subtypes were significantly different in terms of specific immune characteristics (immune cell subpopulations, immune responses, immune cells and checkpoint gene interactions). In additional, somatic alterations and methylation changes were identified that correlated with genes related to a worse prognosis subtype in the microenvironment. More importantly, in M3 (worst prognosis subtype) and M2 (best prognosis subtype), the interaction between immune cells and checkpoint genes was different, and this had an important effect on the prognosis. Finally, we used risk scores of immune cells and checkpoint genes to evaluate the prognosis of GBM patients and validated the results with 3 independent datasets. Disordered interactions between immune cells and checkpoint genes result in a change in the immune microenvironment and affects the prognosis of patients. We propose that a better understanding of the immune microenvironment of advanced cancers may provide new insights into immunotherapy.
2019-06-20 | GSE122586 | GEO