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Genomic profiling of glioblastoma: convergence of fundamental biologic tenets and novel insights

Overview of attention for article published in Journal of Neuro-Oncology, October 2011
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Title
Genomic profiling of glioblastoma: convergence of fundamental biologic tenets and novel insights
Published in
Journal of Neuro-Oncology, October 2011
DOI 10.1007/s11060-011-0714-2
Pubmed ID
Authors

Kimberly Ng, Ryan Kim, Santosh Kesari, Bob Carter, Clark C. Chen

Abstract

With advances in genomic profiling and sequencing technology, we are beginning to understand the landscape of the genetic events that accumulated during the neoplastic process. The insights gleamed from these genomic profiling studies with regards to glioblastoma etiology has been particularly satisfying because it cemented the clinical pertinence of major concepts in cancer biology-concepts developed over the past three decades. This article will review how the glioblastoma genomic data set serves as an illustrative platform for the concepts put forward by Hanahan and Weinberg on the cancer phenotype. The picture emerging suggests that most glioblastomas evolve along a multitude of pathways rather than a single defined pathway. In this context, the article will further provide a discussion of the subtypes of glioblastoma as they relate to key principles of developmental neurobiology.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 5%
Netherlands 1 2%
United Kingdom 1 2%
Unknown 40 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 23%
Student > Master 6 14%
Professor > Associate Professor 6 14%
Researcher 5 11%
Professor 4 9%
Other 8 18%
Unknown 5 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 43%
Medicine and Dentistry 14 32%
Biochemistry, Genetics and Molecular Biology 2 5%
Neuroscience 1 2%
Unknown 8 18%