Similar Datasets
Project description:Molecular differences between tumor endothelial cells from low- and high-grade gliomas
| PRJNA991575 | ENA
Project description:Glioblastoma (GB) is the most aggressive form of glioma and is characterized by a poor prognosis and high recurrence, despite intensive clinical interventions. To retrieve the key factors underlying the high malignancy of GB, we performed differential expression analysis between low and high-grade gliomas by using RNA-seq.
2021-11-30 | GSE185861 | GEO
Project description:Brain tumors lead to modifications of brain networks. Graph theory plays an important role in clarifying the principles of brain connectivity. Our objective was to investigate network modifications related to tumor grade and location using resting-state functional magnetic resonance imaging (fMRI) and graph theory. We retrospectively studied 30 low-grade (LGG), 30 high-grade (HGG) left-hemispheric glioma patients and 20 healthy controls (HC) with rs-fMRI. Tumor location was labeled as: frontal, temporal, parietal, insular or occipital. We collected patients' clinical data from records. We analyzed whole-brain and hemispheric networks in all patients and HC. Subsequently, we studied lobar networks in subgroups of patients divided by tumor location. Seven graph-theoretical metrics were calculated (FDR p < 0.05). Connectograms were computed for significant nodes. The two-tailed Student t-test or Mann-Whitney U-test (p < 0.05) were used to compare graph metrics and clinical data. The hemispheric network analysis showed increased ipsilateral connectivity for LGG (global efficiency p = 0.03) and decreased contralateral connectivity for HGG (degree/cost p = 0.028). Frontal and temporal tumors showed bilateral modifications; parietal and insular tumors showed only local effects. Temporal tumors led to a bilateral decrease in all graph metrics. Tumor grade and location influence the pattern of network reorganization. LGG may show more favorable network changes than HGG, reflecting fewer clinical deficits.
| S-EPMC9324249 | biostudies-literature
Project description:Glioblastoma (GB) is the most aggressive form of glioma and is characterized by a poor prognosis and high recurrence, despite intensive clinical interventions. To retrieve the key factors underlying the high malignancy of GB, we performed differential methylation analysis between low and high-grade gliomas by using Infinium MethylationEPIC beadchips.
2020-12-31 | GSE147391 | GEO
Project description:BackgroundGlioma is a type of tumor that develops in the central nerve system, mainly the brain. Alterations of genomic sequence and sequence segments (such as copy number variations or CNV and copy neutral loss of heterozygosities or cnLOH) are thought to be a major determinant of the tumor grade.MethodsWe mapped genomic variations between low-grade and high-grade gliomas (LGG and HGG) in Chinese population based on Illumina's Beadchip and validated the results using real-time qPCR.ResultsAT THE CYTOBAND LEVEL, WE DISCOVERED: (1) unique losses in LGG on 5q, 8p and 11q, and in HGG on 6q, 11p, 13q and 19q; (2) unique gains in the LGG on 1p and in HGG at 5p, 7p, 7q and 20q; and (3) cnLOH in HGG only on 3q, 8q, 10p, 14q, 15q, 17p, 17q, 18q and 21q. Subsequently, we confirmed well-characterized oncogenes among tumor-related loci (such as EGFR and KIT) and detected novel genes that gained chromosome sequences (such as AASS, HYAL4, NDUFA5 and SPAM1) in both LGG and HGG. In addition, we found gains, losses, and cnLOH in several genes, including VN1R2, VN1R4, and ZNF677, in multiple samples. Mapping grade-associated pathways and their related gene ontology (GO) terms, we classified LGG-associated functions as "arachidonic acid metabolism", "DNA binding" and "regulation of DNA-dependent transcription" and the HGG-associated as "neuroactive ligand-receptor interaction", "neuronal cell body" and "defense response to bacterium".ConclusionLGG and HGG appear to have different molecular signatures in genomic variations and our results provide invaluable information for the diagnosis and treatment of gliomas in patients with variable duration or diverse tumor differentiation.
| S-EPMC3579804 | biostudies-literature
Project description:Differential transcriptome between low and high-grade gliomas
| PRJNA771039 | ENA
Project description:ObjectiveGliomas are the most common primary brain tumors, and have been ranked as the fourth leading cause of cancer death. Tumor mesenchymal-like stem cells (tMSCs) contribute to the aggressive behavior of glial tumors by providing a favorable microenvironment for the malignant cells. The aim of our study was to identify differential proteome of tMSCs derived from low vs. high grade glioma tumors.Materials and methodsPatients with newly diagnosed low and high grade gliomas were included in this case control study. tMSCs were isolated from tumors using enzymatic digestion validated by flow cytometer analysis after sub-culturing. Differential proteomic analysis of tMSCs derived from low and high grade tumors was performed by two-dimensional gel electrophoresis and mass spectrometry. Protein spots with more than two fold differences and P values below 0.05 were considered as differentially expressed ones.ResultsIn tMSCs isolated from low and high grade gliomas, different isoforms of mesenchymal-related proteins vimentin and transgelin were differentially expressed. Overexpressed proteins in tMSCs isolated from low grade gliomas were mitochondrial manganese-containing superoxide dismutase (Mn-SOD), 40S ribosomal protein SA, and GTP-binding nuclear protein, while in tMSCs isolated from high grade gliomas, cathepsin B, endoplasmin, ezrin, peroxiredoxin1, and pyruvate kinase (PK) were found to be significantly overexpressed.ConclusionFor the first time, we analyzed the differential proteomic profiles of tMSCs isolated from glioma tumors with different grades. It was found that molecules related to mesenchymal cells (vimentin and transglin), in addition to those related to tumor aggressiveness with potential secretory behavior (e.g. cathepsin B) were among differentially expressed proteins.
| S-EPMC5412783 | biostudies-literature
Project description:BackgroundLow-grade gliomas (LGGs) are slow-growing, infiltrative tumors frequently associated with seizures. Predicting which patients will develop early tumor recurrence based on clinical indicators following initial surgical intervention remains a challenge. Seizure recurrence following surgery may be an early indicator of tumor recurrence, especially in patients presenting with increase in seizure frequency.MethodsThis study analyzed 148 patients meeting inclusion criteria (age >18 years, LGG diagnosis, at least 1 seizure event recorded before and after initial surgical intervention). All patients were treated at the Brain and Spine Center at The University of Texas MD Anderson Cancer Center from January 2000 to March 2013. Seizure frequency in a 6-month period before and after tumor resection was categorized as none, 1, few (2 to 3 seizures) or several (>3 seizures). Immediately postoperative seizures (up to 48 hours from surgery) were not included in the analysis.ResultsA total of 116 (78.4%) patients had seizures at initial presentation and most (95%) were started on antiepileptic drugs (AEDs). We found 2 clinical variables with a significant impact on progression-free survival (PFS): Higher seizure frequency during the 6-month postoperative period and seizure frequency increase between the 6-month pre- and the 6-month postoperative periods were both correlated to higher risk of early tumor recurrence (P = .007 and P = .004, respectively).ConclusionSeizure frequency following surgical resection of LGGs and the seizure frequency change between the 6-month preoperative and postoperative periods may serve as clinical predictors of early tumor recurrence in patients with LGGs who are also afflicted by seizures.
| S-EPMC6656314 | biostudies-literature
Project description:Differential DNA methylome between low and high-grade gliomas
| PRJNA614473 | ENA
Project description:BackgroundThe ability to accurately and non-invasively distinguish high-grade glioma from low-grade glioma remains a challenge despite advances in molecular and magnetic resonance imaging. We investigated the ability of fluciclovine (18F) PET as a means to identify and distinguish these lesions in patients with known gliomas and to correlate uptake with Ki-67.ResultsSixteen patients with a total of 18 newly diagnosed low-grade gliomas (n?=?6) and high grade gliomas (n?=?12) underwent fluciclovine PET imaging after histopathologic assessment. Fluciclovine PET analysis comprised tumor SUVmax and SUVmean, as well as metabolic tumor thresholds (1.3*, 1.6*, 1.9*) to normal brain background (TBmax, and TBmean). Comparison was additionally made to the proliferative status of the tumor as indicated by Ki-67 values. Fluciclovine uptake greater than normal brain parenchyma was found in all lesions studied. Time activity curves demonstrated statistically apparent flattening of the curves for both high-grade gliomas and low-grade gliomas starting 30 min after injection, suggesting an influx/efflux equilibrium. The best semiquantitative metric in discriminating HGG from LGG was obtained utilizing a metabolic 1 tumor threshold of 1.3* contralateral normal brain parenchyma uptake to create a tumor: background (TBmean1.3) cutoff of 2.15 with an overall sensitivity of 97.5% and specificity of 95.5%. Additionally, using a SUVmax?>?4.3 cutoff gave a sensitivity of 90.9% and specificity of 97.5%. Tumor SUVmean and tumor SUVmax as a ratio to mean normal contralateral brain were both found to be less relevant predictors of tumor grade. Both SUVmax (R?=?0.71, p?=?0.0227) and TBmean (TBmean1.3: R?=?0.81, p?=?0.00081) had a high correlation with the tumor proliferative index Ki-67.ConclusionsFluciclovine PET produces high-contrast images between both low-grade and high grade gliomas and normal brain by visual and semiquantitative analysis. Fluciclovine PET appears to discriminate between low-grade glioma and high-grade glioma, but must be validated with a larger sample size.
| S-EPMC6060188 | biostudies-literature