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2,292 results for “Glioma”
TCGA Lower Grade Glioma (LGG) Clinical Data
<p><strong>Abstract:</strong></p> <p>The Cancer Genome Atlas (TCGA) was a large-scale collaborative project initiated by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). It aimed to comprehensively characterize the genomic and molecular landscape of various cancer types. This dataset includes curated survival data from the Pan-cancer Atlas paper titled <a href="http://www.cell.com/cell/fulltext/S0092-8674(18)30229-0">"An Integrated TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR) to drive high quality survival outcome analytics"</a>. The paper highlights four types of carefully curated survival endpoints, and <a href="http://www.cell.com/action/showFullTableImage?isHtml=true&tableId=tbl3&pii=S0092867418302290">recommends the use of the endpoints of OS, PFI, DFI, and DSS for each TCGA cancer type</a>. The dataset also includes phenotypic information about LGG. The Sample IDs are unique identifiers, which can be paired with the gene expression dataset. </p> <p><strong>Inspiration:</strong></p> <p>This dataset was uploaded to UBRITE for GTKB project. </p> <p><strong>Instruction:</strong></p> <p>The survival and phenotype data were merged into one file. Empty columns were removed. Columns with the same value for every sample were also removed. </p> <p><strong>Acknowledgments:</strong></p> <p>Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8</p> <p>Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11. <a href="https://doi.org/10.1016/j.cell.2018.02.052">https://doi.org/10.1016/j.cell.2018.02.052</a></p> <p>The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113–1120 (2013). https://doi.org/10.1038/ng.2764</p> <p><strong>U-BRITE last update: </strong>07/13/2023</p>
Deep Learning for Reaction-Diffusion Glioma Growth Modeling: Towards a Fully Personalized Model? — Supporting Data
<p>Supporting data for Martens et al. Deep Learning for Reaction-Diffusion Glioma Growth Modelling: Towards a Fully Personalised Model? arXiv:2111.13404.</p>
Dataset related to article: QUALITY ASSESSMENT OF THE MRI-RADIOMICS STUDIES FOR MGMT PROMOTER METHYLATION PREDICTION IN GLIOMA: A SYSTEMATIC REVIEW AND META-ANALYSIS
<p><strong><span>This table contains the raw data used to generate the heatmap illustrated in Fig 2. Each row of the table shows the distribution of the scores achieved by the studies for a domain. Colors from red to green denote progressive increase from minimum to maximum score obtainable for each domain.</span></strong></p>
Glioma spatialomics dataset
<p>Data related to the paper "Integrative spatial analysis reveals a multi-layered organization of glioblastoma" (Greenwald*<em>, </em>Galili-Darnell*<em>, </em>Hoefflin<em>*</em> et al., 2024. Cell 187(10): 2485-2501). </p> <p>See visium_dataset_description.csv and readme_CODEX.txt</p> <p>Thirteen fresh frozen GBM samples profiled by 10x Visium</p> <p>Six fresh frozen IDH mutant samples profiled by 10x Visium</p> <p>Twelve fresh frozen GBM samples profiled by CODEX</p> <p>One GBM organoid model profiled by CODEX</p> <p> </p>
DeepHisto: Dataset for glioma subtype classification from Whole Slide Images
<p>DeepHisto dataset contains tiles (patches) of hematoxylin and eosin stained Whole Slide Images (WSI) of 28 adult-type diffuse glioma cases collected at the National Center of Pathology (NCP), Luxembourg National Health Laboratory (Laboratoire national de santé - LNS) from 2017 to 2021. WSIs were acquired with an IntelliSite Ultra Fast digital slide scanner from Philips containing a 20x/0.75 NA Plan Apo objective with an average slide resolution of 0.25um/pixel.</p> <p>Three primary diffuse glioma subtypes are classified into IDH-mutant, 1p/19q codeleted oligodendroglioma, IDH-mutant astrocytoma, and IDH-wildtype glioblastoma according to the 5th edition of the WHO classification of central nervous system tumors. The brain WSIs of a non-cancer patients were used as normal brain (white and gray matter) controls.</p> <p>Region annotation of WSIs was done by a board-certified pathologist, and the regions of interest are further divided into square 512×512 tiles, each of them associated with a particular class denoting the respective tumor entity, normal brain tissue or necrosis.<br> Tiles are further divided into training and test subsets patient-wise.</p>
Supplement data for : Intratumoral drug-releasing microdevices allow in situ high throughput pharmaco phenotyping in patients with gliomas
<p>Transcriptomic and metabolomic data associated with the manuscript: Intratumoral drug-releasing microdevices allow in situ high throughput pharmaco phenotyping in patients with gliomas.</p> <p> </p>
Return to work following diagnosis of low-grade glioma: A nationwide matched cohort study
<p>Objective: Return-to-work (RTW) following diagnosis of infiltrative low-grade gliomas (LGG) is unknown. </p> <p>Methods: Swedish patients with histopathological verified WHO grade II diffuse glioma diagnosed between 2005-2015 were included. Data were acquired from several Swedish registries. A total of 381 patients aged 18-60 were eligible. A matched control population (n=1900) was acquired. Individual data on sick leave, compensations, comorbidity, and treatments assigned were assessed. Predictors were explored using multivariable logistic regression. </p> <p>Results: One year before surgery/index date, 88 % of cases were working compared to 91 % of controls. The proportion of controls working remained constant, while patients had a rapid increase in sick leave approximately six months prior to surgery. After one and two years respectively, 52 % and 63 % of the patients were working. Predictors for no-RTW after one year were previous sick leave (OR 0.92, 95 % CI 0.88-0.96, p <0.001), older age (OR 0.96, 95 % CI 0.94-0.99, p=0.005) and lower functional level (OR 0.64 95% CI, 0.45-0.91 p=0.01). Patients receiving adjuvant treatment were less likely to RTW within the first year. At two years, biopsy (as opposed to resection), female sex and co-morbidity were also unfavorable, while age and adjuvant treatment were no longer significant. </p> <p>Conclusions: Approximately half of the patients RTW within the first year. Lower functional status, previous sick leave, older age, and adjuvant treatment were risk factors for no-RTW at one year after surgery. Female sex, co-morbidity, and biopsy only were also unfavorable for RTW at two years.</p>
Reactivating PTEN to impair glioma stem cells by inhibiting cytosolic iron-sulfur assembly pathway
<p>Glioblastoma (GBM), the most lethal primary brain tumor, harbors glioma stem cells (GSCs) that not only initiate and maintain malignant phenotypes but also enhance therapeutic resistance. Although frequently mutated in GBMs, the function and regulation of PTEN in PTEN-intact GSCs are unknown. Here we found that PTEN directly interacts with MMS19 and competitively disrupts MMS19-based cytosolic iron-sulfur (Fe-S) cluster assembly (CIA) machinery in the differentiated glioma cells (DGCs). Interrogation of GSCs, when compared with their matched DGCs, revealed that PTEN is specifically succinated at cysteine (C) 211 in GSCs. Isotope tracing coupled with mass spectrometry analysis confirmed that fumarate, generated by adenylosuccinate lyase (ADSL) in <em>de novo</em> purine synthesis pathway which is highly activated in GSCs, promotes PTEN C211 succination. This modification abrogates the interaction between PTEN and MMS19, thereby reactivating CIA machinery pathway in GSCs. Functionally, inhibiting PTEN C211 succination through re-expressing PTEN C211S mutant, depleting ADSL, or consuming fumarate by N-acetylcysteine (NAC), an FDA-approved prescription drug, impairs GSC maintenance. Importantly, re-expressing PTEN C211S or treating with NAC sensitizes GSC-derived brain tumors to temozolomide and irradiation, the standard-of-care treatments for GBM patients, by retarding CIA machinery-mediated DNA damage repair. These findings reveal an immediately practicable strategy to target GSCs for treating GBMs by combined therapy with repurposing NAC.</p>
N-cadherin dynamically regulates pediatric glioma cell migration in complex environments
<p>Pediatric high-grade gliomas are highly invasive and essentially incurable. Glioma cells migrate between neurons and glia, along axon tracts, and through extracellular matrix surrounding blood vessels and underlying the pia. Mechanisms that allow adaptation to such complex environments are poorly understood. N-cadherin is highly expressed in pediatric gliomas and is associated with shorter survival. We found that inter-cellular homotypic N-cadherin interactions differentially regulate glioma migration according to the microenvironment, stimulating migration on cultured neurons or astrocytes but inhibiting invasion into reconstituted or astrocyte-deposited extracellular matrix. N-cadherin localizes to filamentous connections between migrating leader cells but to epithelial-like junctions between followers. Leader cells have more surface and recycling N-cadherin, increased YAP1/TAZ signaling, and increased proliferation relative to followers. YAP1/TAZ signaling is dynamically regulated as leaders and followers change position, leading to altered N-cadherin levels and organization. Together, the results suggest that pediatric glioma cells adapt to different microenvironments by regulating N-cadherin dynamics and cell-cell contacts.</p>
GlioHyper: Glioma Biopsy Hyperspectral Dataset
<p>A dataset of glioma biopsies which were examined using hyperspectral imaging. The details of the acquisition protocol and description of the data are provided in the accompaniying paper:</p> <p>"A transportable hyperspectral imaging setup based on fast, high-density spectral scanning for in situ quantitative biochemical mapping of fresh tissue biopsies", Luca Giannoni et. al.</p> <p> </p>
The profile of the gut microbiome in gliomas patients
<p>Through 16S rRNA sequecing of fecal samples from gliomas patients, we found the characteristics of the gut microbiome proflie.</p>
1H HRMAS NMR ERETIC-CPMG dataset for survival analysis and pathological classification of gliomas
<p>This repository contains the raw ERETIC-CPMG HRMAS NMR data to reproduce the results reported in the following preprint: PiDeeL: Pathway-informed deep learning model for survival analysis and pathological classification of gliomas</p> <p>The FID spectra can be found under the FID_Samples directory. The pathological classification and survival analysis labels can be found in the Dataset_Labels.xlsx file.</p>
Optical coherence tomography of the macular ganglion cell layer in children with neurofibromatosis type 1 is a useful tool in the assessment for optic pathway gliomas
<p><span>To investigate whether the ganglion cell layer assessed by OCT is a reliable measure to identify and detect relapses of symptomatic OPGs in children with NF1.</span></p>
Accurate and Rapid Molecular Subgrouping of High-Grade Glioma via Deep Learning-assisted Label-free Fiber-optic Raman Spectroscopy
<p>Dataset for the manuscript "<span>Accurate and Rapid Molecular Subgrouping of High-Grade Glioma via Deep Learning-assisted Label-free </span><span>F</span><span>iber-optic Raman Spectroscopy"</span></p>
Generating VISA scores on glioma bulk RNAseq and single cell RNAseq glioma
<p>Tissue stiffness is collectively determined by the stiffness of ECM and cells. Gliomas are characterized by dysregulated expression of ECM proteins, ECM crosslinking enzymes, and aberrant cellular contractility.While The RNA sequencing datasets have been comprehensively analyzed to interrogate tumor genomes, epigenomes, and transcriptomes, we realized an untapped potential: using transcriptomic data coupled with analysis of gene expression associated with ECM and actomyosin contractility to establish a bioinformatic tool, which we named VIrtual Stiffness Algorithm (VISA), capable of inferring tissue stiffness.</p> <p>This data repository is for reproducing VISA scores on glioma bulk RNAseq and single cell RNAseq glioma.</p>
Exploring the anti-glioma mechanism of the active components of Cortex Periplocae based on network pharmacology and iTRAQ proteomics in vitro
<p>Hierarchical clustering analysis of candidate proteins was illustrated in heat map, which showed obvious differences between CP-induced cells and controls (Fig. 6). Each column is a sample and each rowindicates a differentially expressed protein. Log values (log<sub>2</sub>expression) of significantly differentially expressed proteins in different samples are displayed in heat maps in different colors. GreenandRedrepresent up-regulation and down-regulation, respectively. The gray part represents no quantitative information of the proteins. T1, T2 and T3 means the CP-treated U251 cells group and C2, C2 and C3 means control group (n=3).</p>
A Study of DS-1001b in Patients With Chemotherapy- and Radiotherapy-Naive IDH1 Mutated WHO Grade II Glioma
ClinicalTrials.gov study NCT04458272. IPD Sharing: YES. Countries: 1. Publications: 2.
PNOC 001: Phase II Study of Everolimus for Recurrent or Progressive Low-grade Gliomas in Children
ClinicalTrials.gov study NCT01734512. IPD Sharing: NO. Countries: 1. Publications: 1.
Bevacizumab in Treating Patients With Recurrent or Progressive Glioma
ClinicalTrials.gov study NCT00337207. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Low Dose Naltrexone for Glioma Patients
ClinicalTrials.gov study NCT01303835. IPD Sharing: Not stated. Countries: 1. Publications: 1.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.