NDLI: Targeted cellular ablation based on the morphology of malignant cells

Content Provider	PubMed Central
Author	Ivey, Jill W. Latouche, Eduardo L. Sano, Michael B. Rossmeisl, John H. Davalos, Rafael V. Verbridge, Scott S.
Copyright Year	2015
Abstract	Treatment of glioblastoma multiforme (GBM) is especially challenging due to a shortage of methods to preferentially target diffuse infiltrative cells, and therapy-resistant glioma stem cell populations. Here we report a physical treatment method based on electrical disruption of cells, whose action depends strongly on cellular morphology. Interestingly, numerical modeling suggests that while outer lipid bilayer disruption induced by long pulses (~100 μs) is enhanced for larger cells, short pulses (~1 μs) preferentially result in high fields within the cell interior, which scale in magnitude with nucleus size. Because enlarged nuclei represent a reliable indicator of malignancy, this suggested a means of preferentially targeting malignant cells. While we demonstrate killing of both normal and malignant cells using pulsed electric fields (PEFs) to treat spontaneous canine GBM, we proposed that properly tuned PEFs might provide targeted ablation based on nuclear size. Using 3D hydrogel models of normal and malignant brain tissues, which permit high-resolution interrogation during treatment testing, we confirmed that PEFs could be tuned to preferentially kill cancerous cells. Finally, we estimated the nuclear envelope electric potential disruption needed for cell death from PEFs. Our results may be useful in safely targeting the therapy-resistant cell niches that cause recurrence of GBM tumors.
Related Links	http://dx.doi.org/10.1038/srep17157
Starting Page	17157
File Format	PDF
ISSN	20452322
e-ISSN	20452322
Journal	Scientific Reports
Volume Number	5
Language	English
Publisher	Nature Publishing Group
Publisher Date	2015-11-24
Access Restriction	Open
Rights Holder	Nature Publishing Group
Subject Keyword	Science and technology Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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