Migratory Variations in Glioblastoma Subtypes
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Date
2015-05
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The Ohio State University
Abstract
The prognosis for glioblastoma multiforme (GBM) is currently very grim; median survival is 14.6 months for this high grade brain cancer. Complete eradication of GBM is very unlikely, and it is not curable with current chemotherapy or surgical treatment options. GBM’s reoccurrence is strongly related to its ability to infiltrate and migrate to other areas of the brain, as far as the opposite hemisphere. There is increasing evidence supporting the initiation of GBM through glioma stem cells. Recent evidence suggests that GBM has three subtypes with different genetic expression signatures. Even though prognosis is consistent, the responses to aggressive treatment differ between the subtypes. This suggests that identifying the predominant subtype between patients may allow for stronger, more individualized treatments. We hypothesize that these distinct genetic signatures will lead to different migration patterns through activation of different chemical pathways, which may serve as therapeutic targets. To investigate this, electrospun nanofiber models, which mimic white matter tracts, major migratory tracts for GBM invasion in the brain, were used to compare migration patterns between two, patient derived subtypes: “Proneural” and “Mesenchymal.” Confocal microscopy indicated that there is a clear distinction in cell adhesion and morphology, while time-lapse microscopy showed a statistical variance in and migration speed. Preliminary data suggests a potential clinical relevance in the treatment and prognosis of different types of GBM, particularly if the specific molecular pathways involved can be identified. Elucidating how individual molecular pathways affect subtype function is crucial in the treatment and understanding of these glioma stem cells. This system will ultimately function as a platform to delve deeper into the understanding of subtype migration and further analysis for targeted treatments
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Keywords
Cancer, Migration, Electrospun Nanofiber, Engineering