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Genomic profiling of lower‐grade gliomas uncovers cohesive disease groups: implications for diagnosis and treatment

Overview of attention for article published in Cancer Communications, January 2016
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Title
Genomic profiling of lower‐grade gliomas uncovers cohesive disease groups: implications for diagnosis and treatment
Published in
Cancer Communications, January 2016
DOI 10.1186/s40880-015-0071-1
Pubmed ID
Authors

Chang‐Ming Zhang, Daniel J. Brat

Abstract

Lower-grade gliomas (including low- and intermediate-grade gliomas, World Health Organization grades II and III) are diffusely infiltrative neoplasms that arise most often in the cerebral hemispheres of adults and have traditionally been classified based on their presumed histogenesis as astrocytomas, oligodendrogliomas, or oligoastrocytomas. Although the histopathologic classification of lower-grade glioma has been the accepted standard for nearly a century, it suffers from high intra- and inter-observer variability and does not adequately predict clinical outcomes. Based on integrated analysis of multiplatform genomic data from The Cancer Genome Atlas, lower-grade gliomas have been found to segregate into three cohesive, clinically relevant molecular classes. Molecular classes were closely aligned with the status of isocitrate dehydrogenase (IDH) mutations, tumor protein 53 mutations and the co-deletion of chromosome arms 1p and 19q, but were not closely aligned with histologic classes. These findings emphasize the potential for improved definition of clinically relevant disease subsets using integrated molecular approaches and highlight the importance of biomarkers for brain tumor classification.

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Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Other 8 32%
Student > Master 5 20%
Student > Bachelor 3 12%
Researcher 2 8%
Student > Postgraduate 2 8%
Other 3 12%
Unknown 2 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 24%
Biochemistry, Genetics and Molecular Biology 5 20%
Medicine and Dentistry 5 20%
Neuroscience 3 12%
Psychology 1 4%
Other 2 8%
Unknown 3 12%