Abstract 3195: The molecular mechanism of action and cellular targets of TTFields
Bibliographic record
Abstract
Abstract Tumor Treating Fields (TTFields) are AC electric fields of intensity 1-2 V/cm in the frequency range 100-300 kHz, which have been shown to be an effective FDA-approved adjuvant therapy for Glioblastoma Multiforme. However, the mechanism of action for TTFields is not well understood. It is known that microtubules (MTs) and actin filaments re-orient themselves and behave abnormally when subjected to external electric fields indicating that they may be cellular targets of TTFields. The purpose of our study was to determine the molecular mechanism of action of TTFields. Previously, using impedance spectroscopy we observed the effect of unpolymerized tubulin and microtubules on ionic conductivity of buffer solution, and found that unlike tubulin, microtubules increased electrical conductance, which peaked at TTField-like frequencies1. Microtubules have been modeled as conductive cables that attract and guide counterions to increase the solution's conductance. protonic transport through the lumen of the microtubule has also been modeled. To investigate the additional possibility of electronic transport along α, β- tubulin dimers we are performing spectroscopic characterization of MTs. Using Dynamic Light Scattering (DLS) we have characterized the thickness of the solvation layer around the tubulin dimer, which elucidates the mechanism of ionic conduction. We have found that the thickness of the solvation layer increases as the concentration of a highly polar molecule such as DMSO is increased. We have found that increasing the solution temperature leads to a reduction of the solvation layer's thickness and have also characterized response to changes in pH of solution. We have polymerized various morphologies of tubulin assemblies, e.g. planar zinc sheets and (300-500 nm diameter) macrotubes to gain insight into associated conductivity processes. We have imaged these interesting morphologies using Transmission Electron Microscopy (TEM) and epifluorescence microscopy. Impedance spectroscopy of microtubules and actin filaments decorated with ligands such as microtubule associated proteins and drugs and anesthetics is under way. Numerical estimates of the magnitudes of the currents, energy and power generated in a cancer cell using TTFields have been computed. This research provides physical insights into the subcellular mechanisms involved in TTField therapy and can assist in its' optimization. 1.Santelices, Iara B., et al. "Response to Alternating Electric Fields of Tubulin Dimers and Microtubule Ensembles in Electrolytic Solutions." Scientific Reports 7.1 (2017): 9594. Citation Format: Aarat P. Kalra, Jack Xiao, Cameron Hough, Piyush Kar, Vahid Rezania, John D. Lewis, Karthik Shankar, Jack A. Tuszynski. The molecular mechanism of action and cellular targets of TTFields [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3195.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".