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Neural Engineering

Neural Engineering - Poster Session B

Poster K9 - Electrophysiology-based sorting of heterogeneous glioblastoma multiforme

Thursday, October 24, 2024
2:45 PM - 3:45 PM EST
Location: Exhibit Hall E, F & G

Introduction:  Glioblastoma multiforme (GBM) is the most common malignant tumor of the central nervous system. It is the most aggressive and invasive brain cancer, with its 5-year survival rate at a mere 5% and a median survival at less than 15 months. Standard therapies include surgical resection, high-dose external-beam radiation therapy, and regional or systemic chemotherapy. However, there is still no known cure. The difficulty in glioblastoma treatment derives from its massive inter-tumoral molecular heterogeneity, which current treatments fail to address. Due to the widely variable cell types in glioblastoma tumors, targeted therapies are challenging, as it is difficult to effectively target all tumor cells. Glioblastoma heterogeneity has been studied in terms of variations in the morphology and proliferative capacities of different tumor populations, but little is known about differences in electrical properties of glioblastoma, which could provide another means of isolating different populations.

Materials and

Methods:  In this study, we used a CytoRecovery machine to sort the glioblastoma multiforme (GBM) cell line (U-87) into three subpopulations based on the cells’ various trapping frequencies: Low (those that trap at xx kHz), moderate (those that trap at xx kHz), and high (those that trap at xx MHz). Additionally, zeta potential was measured with the Zeta analyzer (Malvern); and average cell cytoplasmic conductivity (σcyt), membrane conductance (σeff), and membrane capacitance (ceff) were recorded with the 3DEP. Three motility assays were used to characterize each of the three sorted subpopulations in terms of cell migration, invasion, and adhesion.

Results, Conclusions, and Discussions: Results suggest that glioblastoma heterogeneity can be sorted based on cells’ electrical characteristics. We found a relationship between the subpopulations’ electrophysiology, proliferation, and invasiveness, to determine if there is a correlation between metastatic potential and cellular electrophysiology. Results suggest a direct relationship: as the tumor cells’ crossover frequency increases, their invasiveness increases. This study demonstrates the potential of DEP and zeta potential for characterization of glioblastoma subpopulations based on motility and metastatic potential.

A better understanding of glioblastoma heterogeneity is essential to design effective therapies for this devastating cancer. Understanding correlations between tumor invasiveness and bioelectricity can guide and improve electrical therapies. For example, tumor electric fields therapy (TEFT) is a biophysical technology that inhibits the growth of cancer cells while sparing normal cells (Lan). However, the molecular mechanisms behind TEFT remain poorly understood. A better grasp on the electrical properties of glioblastoma could guide improvements to TEFT technology (Lan).

Acknowledgements (Optional):