Abstract

Abstract BACKGROUND Tumor Treating Fields (TTFields; approved anti-neoplastic treatment modality) are delivered via application of low intensity, intermediate frequency, alternating electrical fields. The electrical properties of cells (eg, permittivity and conductivity) determine the optimal TTFields frequency that would elicit the greatest cell count reduction. Currently, no predictive markers exist to determine TTFields response and optimal frequency for individual patient application. The study goal was to evaluate the correlation between electrical properties of cells and TTFields’s optimal frequency and sensitivity. The 3DEPTM reader (LabTech) determines cellular electrical properties, including permittivity and conductivity, by using dielectrophoresis (DEP) force. DEP is a physical effect that generates a force on polarizable particles, such as cells, subjected to non-uniform electric fields. METHODS Utilizing the 3DEP reader, baseline electrical properties (permittivity and conductivity) of 17 cell lines from different tumor-types were determined. Curves were analyzed using 2-way ANOVA. The optimal TTFields frequency of each cell line was determined by evaluating TTFields cytotoxicity at various frequencies using the inovitroTM system. Electrical properties of each cell line were compared with the optimal TTFields frequency and sensitivity. RESULTS Significant differences (P< 0.001) were demonstrated between the lower frequency range of the 3DEP curves that correspond to cellular membrane capacitance at TTFields optimal frequencies of 150 kHz (9 cell lines) and 200 kHz (8 cell lines). Also, membrane capacitance was a good predictor of TTFields sensitivity based on curve differences within the low-frequency range. CONCLUSIONS These results demonstrate that cell membrane capacitance correlates with TTFields optimal frequency and sensitivity. Based on these data, there is a strong rational to further explore the potential of measuring the electrical properties of cells as predictive markers to help determine the optimal TTFields frequency for individual patient application and to identify ideal treatment-responders to TTFields.

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