2006
DOI: 10.1073/pnas.0608396103
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Analysis of oncogenic signaling networks in glioblastoma identifies ASPM as a molecular target

Abstract: Glioblastoma is the most common primary malignant brain tumor of adults and one of the most lethal of all cancers. Patients with this disease have a median survival of 15 months from the time of diagnosis despite surgery, radiation, and chemotherapy. New treatment approaches are needed. Recent works suggest that glioblastoma patients may benefit from molecularly targeted therapies. Here, we address the compelling need for identification of new molecular targets. Leveraging global gene expression data from two … Show more

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Cited by 603 publications
(611 citation statements)
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References 43 publications
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“…Studies suggest that highly centralized "hub" genes in the network architecture are more likely to be key drivers for cellular function (33). Characterization of these hub genes may help to give novel insight into bladder tumorigenesis and to develop additional novel drug targets for bladder cancer.…”
Section: Discussionmentioning
confidence: 99%
“…Studies suggest that highly centralized "hub" genes in the network architecture are more likely to be key drivers for cellular function (33). Characterization of these hub genes may help to give novel insight into bladder tumorigenesis and to develop additional novel drug targets for bladder cancer.…”
Section: Discussionmentioning
confidence: 99%
“…The importance of a gene is often dependent on how well it associates with other genes in a network. Studies suggest that more centralized genes in the network are more likely to be key drivers to proper cellular function than peripheral genes (nodes) (Horvath et al, 2006).…”
Section: Discussionmentioning
confidence: 99%
“…Application of analysis softwares such as DAVID (National Cancer Institute at Frederick; http:// david.abcc.ncifcrf.gov/), Pathway Assist by Stratagene (Agilent Technologies, Santa Clara, CA, USA) and others can indicate underlying biological themes. Recent advances in tools to group genes by variation of expression across individual samples have made possible the exploration of gene networks (109) . This type of analysis has been directed at diverse biological problems, for example, evolution of the human cortex (110) and genes differentially expressed during the progression of Alzheimer's disease (111) .…”
Section: Future Studiesmentioning
confidence: 99%