胶质母细胞瘤
纳米医学
脑癌
U87型
医学
血脑屏障
癌症
癌症研究
计算机科学
纳米技术
纳米颗粒
内科学
材料科学
中枢神经系统
作者
Elif Ozdemir-Kaynak,Amina A. Qutub,Özlem Yeşil-Çeliktaş
标识
DOI:10.3389/fphys.2018.00170
摘要
The most lethal form of brain cancer, glioblastoma multiforme, is characterized by rapid growth and invasion facilitated by cell migration and degradation of the extracellular matrix. Despite technological advances in surgery and radio-chemotherapy, glioblastoma remains largely resistant to treatment. New approaches to study glioblastoma and to design optimized therapies are greatly needed. One such approach harnesses computational modeling to support the design and delivery of glioblastoma treatment. In this paper, we critically summarize current glioblastoma therapy, with a focus on emerging nanomedicine and therapies that capitalize on cell-specific signaling in glioblastoma. We follow this summary by discussing computational modeling approaches focused on optimizing these emerging nanotherapeutics for brain cancer. We conclude by illustrating how mathematical analysis can be used to compare the delivery of a high potential anticancer molecule, delphinidin, in both free and nanoparticle loaded forms across the blood-brain barrier for glioblastoma.
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