Dataset Information

Molecular differences between cerebral blood volume and vessel size in glioblastoma multiforme.

ABSTRACT: The purpose of this study was to investigate the molecular background of cerebral blood volume (CBV) and vessel size (VS) of capillaries in glioblastoma multiforme (GBM). Both parameters are derived from extended perfusion MR imaging.A prospective case study including 21 patients (median age 66 years, 10 females) was performed. Before operation, CBV and VS of contrast enhancing tumor were assessed. Tissue was sampled from the assessed areas under neuronavigation control. After RNA extraction, transcriptional data was analyzed by Weighted Gene Co-Expression Network Analysis (WGCNA) and split into modules based on its network affiliations. Gene Set Enrichment Analysis (GSEA) identified biological functions or pathways of the genetic modules. These were applied on 484 GBM samples of the TCGA database.Ten modules were highly correlated to CBV and VS. One module was exclusively associated to VS and highly correlated to hypoxia, another one exclusively to CBV showing strong enrichments in the Epithelial Growth Factor (EGF) pathway and Epithelial-to-Mesenchymal-Transition (EMT). Moreover, patients with increased CBV and VS predominantly showed a mesenchymal gene-expression, a finding that could be corroborated by TCGA data.In conclusion, CBV and VS mirror different genetic pathways and reflect certain molecular subclasses of GBM.

SUBMITTER: Heiland DH

PROVIDER: S-EPMC5355248 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Molecular differences between cerebral blood volume and vessel size in glioblastoma multiforme.

Heiland Dieter Henrik DH Demerath Theo T Kellner Elias E Kiselev Valerij G VG Pfeifer Dietmar D Schnell Oliver O Staszewski Ori O Urbach Horst H Weyerbrock Astrid A Mader Irina I

Oncotarget 20170201 7

The purpose of this study was to investigate the molecular background of cerebral blood volume (CBV) and vessel size (VS) of capillaries in glioblastoma multiforme (GBM). Both parameters are derived from extended perfusion MR imaging.A prospective case study including 21 patients (median age 66 years, 10 females) was performed. Before operation, CBV and VS of contrast enhancing tumor were assessed. Tissue was sampled from the assessed areas under neuronavigation control. After RNA extraction, tr ...[more]

PMID: 27613830

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Project description:Background and purposeVascular proliferation is a major criterion for grading gliomas on the basis of histology. Relative cerebral blood volume can provide pathophysiologic information about glioma grading. Vessel size imaging, in some animals, can be used to estimate the microvascular caliber of a glioma, but its clinical use remains unclear. Herein, we aimed to compare the predictive power of relative cerebral blood volume and vessel size imaging in glioma grading, with grading based on histology.Materials and methodsSeventy patients with glioma participated in the study; 30 patients underwent MR perfusion imaging with a spin-echo sequence and vessel size imaging with a gradient-echo and spin-echo sequence successively at 24-hour intervals before surgery. We analyzed the vessel size imaging values and relative cerebral blood volume of differently graded gliomas. The microvessel parameters were histologically evaluated and compared with those on MR imaging. The cutoff values of vessel size imaging and relative cerebral blood volume obtained from receiver operating characteristic curve analyses were used to predict glioma grading in another 40 patients.ResultsVessel size imaging values and relative cerebral blood volume were both increased in high-grade gliomas compared with low-grade gliomas (P < .01). Moreover, vessel size imaging values had higher specificity and sensitivity in differentiating high-grade from low-grade gliomas compared with relative cerebral blood volume. In addition, a significant correlation was observed between vessel size imaging values and microvessel diameters (r > 0.8, P < .05) and between relative cerebral blood volume and microvessel area (r = 0.6579, P < .05). Most important, the use of vessel size imaging cutoff values to predict glioma grading was more accurate (100%) than use of relative cerebral blood volume (85%) values.ConclusionsVessel size imaging can provide more accurate information on glioma grading and may serve as an effective biomarker for the prognosis of patients with gliomas.

Project description:Background and objective200 kHz tumor treating fields (TTFields) is clinically approved for newly-diagnosed glioblastoma (nGBM). Because its effects on conventional surveillance MRI brain scans are equivocal, we investigated its effects on perfusion MRI (pMRI) brain scans.MethodsEach patient underwent institutional standard pMRI: dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) pMRI at three time points: baseline, 2-, and 6-months on-adjuvant therapy. At each timepoint, the difference between T1 pre- versus post-contrast tumor volume (ΔT1) and these pMRI metrics were evaluated: normalized and standardized relative cerebral blood volume (nRCBV, sRCBV); fractional plasma volume (Vp), volume of extravascular extracellular space (EES) per volume of tissue (Ve), blood-brain barrier (BBB) permeability (Ktrans), and time constant for gadolinium reflux from EES back into the vascular system (Kep). Between-group comparisons were performed using rank-sum analysis, and bootstrapping evaluated likely reproducibility of the results.ResultsAmong 13 pMRI datasets (11 nGBM, 2 recurrent GBM), therapies included temozolomide-only (n = 9) and temozolomide + TTFields (n = 4). No significant differences were found in patient or tumor characteristics. Compared to temozolomide-only, temozolomide + TTFields did not significantly affect the percent-change in pMRI metrics from baseline to 2 months. But during the 2- to 6-month period, temozolomide + TTFields significantly increased the percent-change in nRCBV (+26.9% [interquartile range 55.1%] vs -39.1% [37.0%], p = 0.049), sRCBV (+9.5% [39.7%] vs -30.5% [39.4%], p = 0.049), Ktrans (+54.6% [1768.4%] vs -26.9% [61.2%], p = 0.024), Ve (+111.0% [518.1%] vs -13.0% [22.5%], p = 0.048), and Vp (+98.8% [2172.4%] vs -24.6% [53.3%], p = 0.024) compared to temozolomide-only.ConclusionUsing pMRI, we provide initial in-human validation of pre-clinical studies regarding the effects of TTFields on tumor blood volume and BBB permeability in GBM.

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.

Dataset Information

Molecular differences between cerebral blood volume and vessel size in glioblastoma multiforme.

Publications

Molecular differences between cerebral blood volume and vessel size in glioblastoma multiforme.

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