This service exclusively searches for literature that cites resources. Please be aware that the total number of searchable documents is limited to those containing RRIDs and does not include all open-access literature.
Diagnosis of a glioblastoma (GBM) is triggered by the onset of symptoms and is based on cerebral imaging and histological examination. Serum-based biomarkers may support detection of GBM. Here, we explored serum protein concentrations of GBM patients and used data mining to explore profiles of biomarkers and determine whether these are associated with the clinical status of the patients. Gene and protein expression data for astrocytoma and GBM were used to identify secreted proteins differently expressed in tumors and in normal brain tissues. Tumor expression and serum concentrations of 14 candidate proteins were analyzed for 23 GBM patients and nine healthy subjects. Data-mining methods involving all 14 proteins were used as an initial evaluation step to find clinically informative profiles. Data mining identified a serum protein profile formed by BMP2, HSP70, and CXCL10 that enabled correct assignment to the GBM group with specificity and sensitivity of 89 and 96%, respectively (p < 0.0001, Fischer's exact test). Survival for more than 15 months after tumor resection was associated with a profile formed by TSP1, HSP70, and IGFBP3, enabling correct assignment in all cases (p < 0.0001, Fischer's exact test). No correlation was found with tumor size or age of the patient. This study shows that robust serum profiles for GBM may be identified by data mining on the basis of a relatively small study cohort. Profiles of more than one biomarker enable more specific assignment to the GBM and survival group than those based on single proteins, confirming earlier attempts to correlate single markers with cancer. These conceptual findings will be a basis for validation in a larger sample size.
We and others have demonstrated that MYC-amplified medulloblastoma (MB) cells are susceptible to class I histone deacetylase inhibitor (HDACi) treatment. However, single drug treatment with HDACi has shown limited clinical efficacy. We hypothesized that addition of a second compound acting synergistically with HDACi may enhance efficacy.
Current evidence supports a maximized extent of resection (EOR) in low-grade gliomas (LGG), regardless of different histological subtypes and molecular markers. We therefore evaluated the prognostic impact of extensive, mainly intraoperative (i)MRI-guided surgery in low-grade astrocytomas stratified for IDH1 mutation status. Retrospective assessment of 46 consecutive cases of newly diagnosed supratentorial WHO grade II astrocytomas treated during the last decade was performed. IDH1 mutation status was obtained for all patients. Volumetric analysis of tumor volumes was performed pre-, intra-, early postoperatively and at first follow-up. Survival analysis was conducted with uni-and multivariate regression models implementing clinical parameters and continuous volumetric variables. Median EOR was 90.4 % (range 17.5-100 %) and was increased to 94.9 % (range 34.8-100 %) in iMRI-guided resections (n = 33). A greater EOR was prognostic for increased progression-free survival (HR 0.23, p = 0.031) and time to re-intervention (TTR) (HR 0.23, p = 0.03). In IDH1 mutant patients, smaller residual tumor volumes were associated with increased TTR (HR 1.01, p = 0.03). IDH1 mutation (38/46 cases) was an independent positive prognosticator for overall survival (OS) in multivariate analysis (HR 0.09, p = 0.002), while extensive surgery had limited impact upon OS. In a subgroup of patients with ≥40 % EOR (n = 39), however, initial and residual tumor volumes were prognostic for OS (HR 1.03, p = 0.005 and HR 1.08, p = 0.007, respectively), persistent to adjustment for IDH1. No association between EOR and neurologic morbidity was found. In this analysis of low-grade astrocytomas stratified for IDH1, extensive tumor resections were prognostic for progression and TTR and, in patients with ≥40 % EOR, for OS.
Although pediatric low-grade gliomas (pLGG) are the most common pediatric brain tumors, patient-derived cell lines reflecting pLGG biology in culture are scarce. This also applies to the most common pLGG subtype pilocytic astrocytoma (PA). Conventional cell culture approaches adapted from higher-grade tumors fail in PA due to oncogene-induced senescence (OIS) driving tumor cells into arrest. Here, we describe a PA modeling workflow using the Simian Virus large T antigen (SV40-TAg) to circumvent OIS.
Welcome to the FDI Lab - SciCrunch.org Resources search. From here you can search through a compilation of resources used by FDI Lab - SciCrunch.org and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that FDI Lab - SciCrunch.org has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on FDI Lab - SciCrunch.org then you can log in from here to get additional features in FDI Lab - SciCrunch.org such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into FDI Lab - SciCrunch.org you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the facets that you can filter your papers by.
From here we'll present any options for the literature, such as exporting your current results.
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.
Year:
Count: