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Glioblastoma vasculogenic mimicry: signaling pathways progression and potential anti-angiogenesis targets

Overview of attention for article published in Biomarker Research, April 2015
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Title
Glioblastoma vasculogenic mimicry: signaling pathways progression and potential anti-angiogenesis targets
Published in
Biomarker Research, April 2015
DOI 10.1186/s40364-015-0034-3
Pubmed ID
Authors

Jin-ming Mao, Jing Liu, Geng Guo, Xing-gang Mao, Chang-xin Li

Abstract

Glioblastoma (GBM) is a highly angiogenic malignancy that is resistant to standard therapy; neo-formed vessels of this aggressive malignancy are thought to arise by sprouting of pre-existing brain capillaries. However, the conventional anti-angiogenic therapy, which seemed promising initially, shows transitory and incomplete efficacy. The discovery of vasculogenic mimicry (VM) has offered a new horizon for understanding tumor vascularization. VM is a tumor cell-constituted, matrix-embedded fluid-conducting meshwork that is independent of endothelial cells and is positively correlated with poor prognosis. Therefore, a better understanding of GBM vasculature is needed to optimize anti-angiogenic therapy. This review focuses on the signaling molecules and cascades involved in VM in relation to ongoing glioma research, as well as the clinical translational advances in GBM that have been offered by the development of optimized anti-angiogenesis treatment modalities.

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Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 1 2%
Brazil 1 2%
Unknown 53 96%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 12 22%
Student > Ph. D. Student 11 20%
Student > Doctoral Student 7 13%
Researcher 6 11%
Student > Master 6 11%
Other 9 16%
Unknown 4 7%
Readers by discipline Count As %
Medicine and Dentistry 15 27%
Biochemistry, Genetics and Molecular Biology 13 24%
Neuroscience 5 9%
Agricultural and Biological Sciences 4 7%
Engineering 4 7%
Other 7 13%
Unknown 7 13%