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Tumor treating fields (TTFields), a new modality of cancer treatment, are electric fields transmitted transdermally to tumors. The FDA has approved TTFields for the treatment of glioblastoma multiforme and mesothelioma, and they are currently under study in many other cancer types. While antimitotic effects were the first recognized biological anticancer activity of TTFields, data have shown that tumor treating fields achieve their anticancer effects through multiple mechanisms of action. TTFields therefore have the ability to be useful for many cancer types in combination with many different treatment modalities. Here, we review the current understanding of TTFields and their mechanisms of action.

Supplementary Figure from The Mechanisms of Action of Tumor Treating Fields

There is great interest in the pursuit of process-driven, algorithmic allocation of health-care resources, including computer-aided medical diagnosis and treatment (MDT). Little is understood regar...

Tumor treating fields (TTFields), a new modality of cancer treatment, are electric fields transmitted transdermally to tumors. The FDA has approved TTFields for the treatment of glioblastoma multiforme and mesothelioma, and they are currently under study in many other cancer types. While antimitotic effects were the first recognized biological anticancer activity of TTFields, data have shown that tumor treating fields achieve their anticancer effects through multiple mechanisms of action. TTFields therefore have the ability to be useful for many cancer types in combination with many different treatment modalities. Here, we review the current understanding of TTFields and their mechanisms of action.

Simple Summary The FDA recently approved a fourth approach (in addition to surgery, radiation therapy, and chemotherapy) for treating glioblastoma; namely, tumor treating fields (TTFields), a form of alternating electric fields (AEF) therapy that is delivered to the tumor via electrodes placed on the scalp. Despite prolonging overall survival by 5 months when combined with standard chemotherapy in patients with newly diagnosed glioblastoma, the mechanisms of action of TTFields are not fully understood and primarily involve its interruption of mitotic spindle formation which impairs cancer cell division. A novel mechanism of action of TTFields at the cell membrane was recently identified, in which TTFields increases cancer cell membrane permeability. This finding could be exploited to enhance drug delivery to cancer cells. Here, we review the likely mechanisms by which TTFields permeabilize cancer cell membranes, i.e., voltage-gated ion channels, bioelectrorheological effects, and electroporation. Finally, we discuss an explanatory formulation that incorporates all three models. Abstract The biological impact of exogenous, alternating electric fields (AEFs) and direct-current electric fields has a long history of study, ranging from effects on embryonic development to influences on wound healing. In this article, we focus on the application of electric fields for the treatment of cancers. In particular, we outline the clinical impact of tumor treating fields (TTFields), a form of AEFs, on the treatment of cancers such as glioblastoma and mesothelioma. We provide an overview of the standard mechanism of action of TTFields, namely, the capability for AEFs (e.g., TTFields) to disrupt the formation and segregation of the mitotic spindle in actively dividing cells. Though this standard mechanism explains a large part of TTFields’ action, it is by no means complete. The standard theory does not account for exogenously applied AEFs’ influence directly upon DNA nor upon their capacity to alter the functionality and permeability of cancer cell membranes. This review summarizes the current literature to provide a more comprehensive understanding of AEFs’ actions on cell membranes. It gives an overview of three mechanistic models that may explain the more recent observations into AEFs’ effects: the voltage-gated ion channel, bioelectrorheological, and electroporation models. Inconsistencies were noted in both effective frequency range and field strength between TTFields versus all three proposed models. We addressed these discrepancies through theoretical investigations into the inhomogeneities of electric fields on cellular membranes as a function of disease state, external microenvironment, and tissue or cellular organization. Lastly, future experimental strategies to validate these findings are outlined. Clinical benefits are inevitably forthcoming.

Since approved by the FDA for the treatment of glioblastoma brain cancer in 2015, tumor-treating fields (TTFields) have rapidly become the fourth modality to treat cancer, along with surgery, chemotherapy, and radiation [1]. TTFields are now in clinical trials for a variety of cancer types. While efficacy has been proven in the clinic, the higher efficacy is demonstrated in vitro and in animal models, which indicates much greater clinical efficacy is possible. To attain the great promise of TTFields, uncovering the mechanisms of action (MoA) is necessary.

We have truly entered the Age of the Connectome due to a confluence of advanced imaging tools, methods such as the flavors of functional connectivity analysis and inter-species connectivity comparisons, and computational power to simulate neural circuitry. The interest in connectomes is reflected in the exponentially rising number of articles on the subject. What are our goals? What are the “functional requirements” of connectome modelers? We give a perspective on these questions from our group whose focus is modeling neurological disorders, such as neuropathic back pain, epilepsy, Parkinson’s disease, and age-related cognitive decline, and treating them with neuromodulation.

Complex systems are found everywhere – from scheduling to traffic, food to climate, economics to ecology, the brain, and the universe. Complex systems typically have many elements, many modes of interconnectedness of those elements, and often exhibit sensitivity to initial conditions. Complex systems by their nature are generally unpredictable and can be highly unstable.

Background: Deep brain stimulation (DBS) has effects on axons that originate and terminate outside the DBS target area. Objective: We hypothesized that DBS generates action potentials (APs) in both directions in “axons of passage,” altering their information content and that of all downstream cells and circuits, and sought to quantify the change in fiber information content. Methods: We incorporated DBS parameters (fiber firing frequency and refractory time, and AP initiation location along the fiber and propagation velocity) in a filtering function determining the AP frequency reaching the postsynaptic cell. Using neural circuitry simulation software, we investigated the ability of the filtering function to predict the firing frequency of APs reaching neurons targeted by axons of passage. We calculated their entropy with and without DBS, and with the electrode applied at various distances from the cell body. Results: The predictability of the filtering function exceeded 98%. Entropy calculations showed that the entropy ratio “without DBS” to “with DBS” was always >1.0, thus DBS reduces fiber entropy. Conclusions: (1) The results imply that DBS effects are due to entropy reduction within fibers, i.e., a reduction in their information. (2) Where fibers of passage do not terminate in target regions, DBS may have side effects on nontargeted circuitry.

OBJECTIVES Burst and high-frequency spinal cord stimulation (SCS), in contrast to low-frequency stimulation (LFS

Objective While the efficacy of vagus nerve stimulation (VNS) to reduce seizures in pharmaco-resistant patients is clinically proven, its efficacy and side effects mechanisms are not fully understood. Our goals were 1) to use a finite element model (FEM) and axon models to examine different fiber activation and blocking thresholds and 2) examine fiber activation and blocking in three fiber groups likely to be responsible for efficacy and side effects. Methods Using FEM, we examined the field potential along axons within a vagus nerve model with fascicles. These data were input to a computational fiber model to estimate numbers of axons activated across all diameters. We estimated numbers of activated and blocked fibers by diameter. Results 1) At the low end of VNS amplitudes, little efficacy for seizure control is appreciated while large Aβ fibers associated with the recurrent laryngeal nerve are recruited. As amplitudes are increased, Aβ fibers can produce hoarseness, and next recruited are fast B fibers associated with the aortic fascicle. We hypothesize these B fibers are the source of efficacy in treating seizure. As amplitudes are further increased, coughing may occur, possibly due to recruitment of smaller and deeper pulmonary fibers. 2) Clinical parameters are in a range that could cause inadvertent blocking at the cathode and activation at the anode. Conversely, innovative approaches to field shape and charge-balancing can allow controlled fiber activation at the cathode for maximum activation of the fibers responsible for efficacy, and possibly blocking at the anode to minimize side effects and expand therapeutic range. In design and operation, the cathode and anode can each be approached as a band pass filter. Significance The B fiber group is necessary and possibly sufficient to produce VNS efficacy in epilepsy. This group may emanate from aortic baroreceptors that, via synapses in the solitary tract nucleus, stimulate the locus coeruleus, hypothalamus and other influential targets such as the hippocampus. Responder rates may be increased with a lead that fully encircles the nerve. With better identification of the fiber groups involved in VNS, efficacy, side effects, therapeutic range and responder rates can be optimized.

Objective Spinal cord stimulation (SCS) treats neuropathic pain through retrograde stimulation of dorsal column axons and their inhibitory effects on wide dynamic range (WDR) neurons. Typical SCS uses frequencies from 50–100 Hz. Newer stimulation paradigms use high-frequency stimulation (HFS) up to 10 kHz and produce pain relief but without paresthesia. Our hypothesis is that HFS preferentially blocks larger diameter axons (12–15 µm) based on dynamics of ion channel gates and the electric potential gradient seen along the axon, resulting in inhibition of WDR cells without paresthesia. Methods We input field potential values from a finite element model of SCS into an active axon model with ion channel subcomponents for fiber diameters 1–20 µm and simulated dynamics on a 0.001 msec time scale. Results Assuming some degree of wave rectification seen at the axon, action potential (AP) blockade occurs as hypothesized, preferentially in larger over smaller diameters with blockade in most medium and large diameters occurring between 4.5 and 10 kHz. Simulations show both ion channel gate and virtual anode dynamics are necessary. Conclusion At clinical HFS frequencies and pulse widths, HFS preferentially blocks larger-diameter fibers and concomitantly recruits medium and smaller fibers. These effects are a result of interaction between ion gate dynamics and the “activating function” (AF) deriving from current distribution over the axon. The larger fibers that cause paresthesia in low-frequency simulation are blocked, while medium and smaller fibers are recruited, leading to paresthesia-free neuropathic pain relief by inhibiting WDR cells.

Tubulin is an electrostatically negative protein that forms cylindrical polymers termed microtubules, which are crucial for a variety of intracellular roles. Exploiting the electrostatic behavior of tubulin and microtubules within functional microfluidic and optoelectronic devices is limited due to the lack of understanding of tubulin behavior as a function of solvent composition. This work displays the tunability of tubulin surface charge using dimethyl sulfoxide (DMSO) for the first time. Increasing the DMSO volume fractions leads to the lowering of tubulin's negative surface charge, eventually causing it to become positive in solutions >80% DMSO. As determined by electrophoretic mobility measurements, this change in surface charge is directionally reversible, i.e., permitting control between -1.5 and + 0.2 cm2 (V s)-1 . When usually negative microtubules are exposed to these conditions, the positively charged tubulin forms tubulin sheets and aggregates, as revealed by an electrophoretic transport assay. Fluorescence-based experiments also indicate that tubulin sheets and aggregates colocalize with negatively charged g-C3 N4 sheets while microtubules do not, further verifying the presence of a positive surface charge. This study illustrates that tubulin and its polymers, in addition to being mechanically robust, are also electrically tunable.

Why Is 4 V/cm Electric Field Strength Necessary for Maximum Tumor-Treating Fields Efficacy? INTRODUCTION: Tumor Treating Fields (TTFields) extend overall survival in glioblastoma patients. Threshold field strength for TTFields is typically cited as 2V/cm. Yet plots of cell death vs. field strength in vitro indicate a power law relationship asymptotic to 4 V/cm for 100% efficacy. The mechanisms of action (MoA) of TTFields underlying this relationship are currently under investigation. TTFields are suspected of disrupting critical mitotic processes performed by large polar cellular molecules such as microtubules (MT). METHODS: Using the power law relationship for the energy (intensity, I) carried by an electric field and its amplitude (Eq. 1), we calculated energy vs. TTFields amplitude. (1) RESULTS: We suggest Eq. 1 is a likely source of the relationship between TTFields' amplitude and cell death proportion that has been demonstrated empirically. Further, Table 1 shows energy transmitted per unit MT surface area per TTFields cycle, specifically, the energy per MT dimer band around an MT helix per TTFields period of 5 µs. TTFields Field Strength (V/cm)Radiant Flux Density (W/nm2)Energy/(Cycle-Area) (J/nm2)Energy/MT Dimer/Cycle (J)Energy/MT Dimer Band/Cycle (J)113.3 × 10−186.63 × 10−234.01 × 10−224.17 × 10−20253.1 × 10−1826.6 × 10−231.60 × 10−211.67 × 10−193119 × 10−1859.7 × 10−233.61 × 10−213.75 × 10−194212 × 10−18106 × 10−236.42 × 10−216.67 × 10−195332 × 10−18166 × 10−231.00 × 10−201.04 × 10−186478 × 10−18239 × 10−231.44 × 10−201.50 × 10−18 A metric for disruption of cellular processes is 1-2 orders of magnitude greater than the thermal background energy in the cell, kT = 4.3 × 10−21 J. Table 1 shows that the energy absorbed by a MT dimer is insufficient to disrupt cellular processes at 2 V/cm, while due to energy increasing with square of field strength, at 5 V/cm it may be disruptive. For an entire dimer band around the MT helix, 2 V/cm appears to be sufficient, while 4 V/cm seems amply strong to disrupt MT function, in accordance with in vitro experiments. CONCLUSION: Assuming the power law of energy vs. electric field strength and the resulting energy absorbed by microtubule components, we found a correlation between typical TTFields' amplitudes and estimated disruption thresholds of MT function. TTFields MoA. 4 V/cm, not 2V/cm, should be the target field strength to realize the full efficacy of TTFields. Citation Format: Kristen W. Carlson, Jack A. Tuszynski, Socrates Dokos, Nirmal Paudel, Zeev Bomzon. What electric field strength is necessary for maximum tumor-treating fields efficacy [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 472.

Our goal is to uncover the mechanism underlying tumour-treating fields’ efficacy in killing cancer cells. Modelling the effects of these 200 kHz alternating current electric fields on tumour cell sub-structures has led us to focus on the microtubules (MTs), C-termini and the motor protein kinesin, which are integral to the critical functions of MT transport of proteins during the delicate orchestration of cell division (mitosis). Leading hypotheses of the TTFields’ mechanism that we are modelling include disruption of mitosis functions (such as the ‘kinesin walk’ along MTs), C-termini state transitions and MT polymerization.

We propose a relatively novel use of dynamic models of neural circuitry in the process of new drug development for neurological disorders. A neural circuit model of depressive disorder was developed. Differences in synaptic activation represented variations in drug binding affinity strength for ten putative molecules. Circuit dynamics led to changes in firing rates compared to normal and depressed baselines. Differing abilities to affect circuitry dynamics not linearly related to binding affinity were appreciated, allowing molecules to be prioritized earlier for future study. Animal and human trial planning can use this information to streamline drug development, conserving cost and time.

Objective The purpose of this study was to examine how scar formation may affect electrical current distribution in the spinal cord when using paddle leads placed in the epidural space during treatment with spinal cord stimulation. Materials and Methods A finite element model of the spinal cord was used to examine changes in stimulation using a guarded cathode configuration with and without scar. Additionally, two potential “compensatory” programming patterns were examined in order to understand how the three-dimensional electrical field may be affected by scar. Direct comparisons with prior studies in the literature and use of known anatomy of dorsal column fiber distributions also enabled a computational estimate of the number of fibers likely reaching threshold with each stimulus pattern. Results Notable potential and current distribution changes were found related to the modeled scar. Compensatory stimulation patterns (both in spatial and in amplitude dimensions) affect the fiber activation patterns in complex ways that may not be easily predetermined by a programming specialist. Conclusions This study is one of the first to examine the effects of scar tissue on dorsal column stimulation and the only one using a detailed computational approach toward that end. It appears that different thickness and location of scar between electrode contacts and the dura may likely lead to a significant number and location of complex changes in the activated fibers. It is likely that a more complete assessment of scarring and its effect on the electrical environment of any given paddle lead would allow more accurate and predictable reprogramming of patients with commercially available systems in place.

Tumor Treating Fields (TTFields) have become a fourth modality for cancer treatment. Mild electric fields (~1-4 V/cm) produce few side effects and significantly extend overall survival of glioblastoma patients, and TTFields are in clinical trials for a variety of tumor cell types. Our goal is to uncover TTFields’ mechanism and cell signaling pathways by numerically modeling their effects on sub-cellular structures, such as microtubules (MTs) and their interactions with motor proteins. METHODS: We have built finite element models in COMSOL Multiphysics (tm) of the MT and its micro-environment to test hypotheses on TTFields’ mechanism of action by predicting effects on sub-cellular structures. RESULTS: One model prediction is that current density induced in the MT counter-ion layer by TTFields essentially shunts electric current within them. The strongest current flows through the counter-ion layer surrounding the MT’s C-termini and energy density in this layer likely exceeds the level to disrupt motor protein ‘walk’ along the MT. The energy density is predicted at 10-20 Joules when both the field and the MTs are aligned with the cell axis. A second mechanism examined by our model is disruption of the ‘foot’ of kinesin, released from its C-terminus contact by ATP (10-19 Joules). The final phase of the walk is driven by thermal buffeting of the forward foot randomly positioning it near enough to the C-terminus for electrostatic forces to bind it. A stall force ~10-19 - 10-16 N from TTFields would prevent diffusion and disrupt the kinesin walk. A recent clinical study segregating patient cohorts treated vs. not treated with dexamethasone found overall survival indefinitely for the non-dexamethosone cohort, leading us to hypothesize that TTFields activate the intrinsic Bcl2-mediated apoptotic signaling pathway. Future modeling will seek to tie disruption of motor protein transport along MTs to activating intrinsic apoptosis, e.g. via failure to silence the G2 cell cycle checkpoint. CONCLUSION: Our modeling predicts that TTFields in cytosol induce electric currents along MTs that are strong enough to disrupt key cellular functions such as the kinesin walk and C-termini transitions, both of which are crucial for motor protein transport. Hence, TTFields disrupt the most delicate mechanisms involved in the carefully-orchestrated succession of steps in mitosis. Citation Format: Kristen W. Carlson, Nirmal Paudel, Jack A. Tuszynski, Zeev Bomzon. Numerical simulation of tumor treating fields effects on cell structures: Mechanism and signaling pathway candidates [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3725.

Tumor Treating Fields (TTFields) are 100-500 kHz electric fields with intensities of about 1-4 V/cm. They are known to exert an antimitotic effect on cancer cells, most likely by exerting forces on highly polar tubulin dimers, thereby disrupting spindle formation. Calculations show that TTFields-tubulin interaction energy is negligible compared to the thermal energy in the cell (1). Therefore, this interaction is unlikely to disrupt cellular function. Conductivity of polymerized tubulin, microtubules (MTs), was measured to be 20 S/m, which is 400 times higher than that of the ambient cytosol (0.05 S/m) (2). Thus when TTFields penetrate the cytosol, they may induce electric currents along MTs that are strong enough to disrupt key cellular functions. In particular, if the power (energy per unit time) deposited by these currents is on par with that the power consumed by the molecular motor kinesin, then TTFields may disrupt the forces needed for cell division, thereby disrupting mitosis. To test this hypothesis, we performed numerical simulations evaluating the magnitude of the electric current along MTs exposed to TTFields at 200 kHz. Based on studies of MTs and their microenvironment, we model the MT as a layered cylindrical structure (1): Innermost is the lumen (15 nm in thickness), surrounded by 13 strands of alpha-beta tubulin dimers linked in a helix (4.5 nm). C-termini extend out from the helix with a thickness of 3.5 nm. MTs carry net negative charge; thus they are surrounded by a counter-ion layer (2 nm), and an outer nonconductive Bjerrum layer (3 nm). We built a finite element model in COMSOL Multiphysics (tm) incorporating these layers and examined the current density induced in each layer by TTFields for MTs varying in length from 1-10 µm within an ambient 200 kHz AC electric field of 1-4 V/cm. Our model shows that MTs act as electrical "shunts" that conduct electric current within them. The highest current flows through the counter-ion layer surrounding the C-termini. The current density in this layer exceeds the level likely to disrupt the motor protein kinesin "walk" along the C-termini. The current density is highest when both the field and the MTs are aligned with the cell axis, in accord with in vitro experiments (3). Our model is consistent with the hypothesis that when cells are exposed to TTFields, MTs act as cables carrying high-density electric currents strong enough to disrupt the function of molecular motors, ultimately disrupting mitosis. References: 1. Tuszynski JA et al. An overview of sub-cellular mechanisms involved in the action of TTFields. Int J Environ Res Public Health 2016. 2. Santelices IB et al. Response to alternating electric fields of tubulin dimers and microtubule ensembles in electrolytic solutions. Sci Rep 2017. 3. Kirson ED et al. Alternating electric fields arrest cell proliferation in animal tumor models and human brain tumors. Proc Natl Acad Sci U S A 2007. Citation Format: Kristen W. Carlson, Jack A. Tuszynski, Socrates Dokos. Numerical modeling of intracellular mechanisms in tumor-treating fields [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 3209.

Objective Stimulation of axons within the dorsal columns of the human spinal cord has become a widely used therapy to treat refractory neuropathic pain. The mechanisms have yet to be fully elucidated and may even be contrary to standard “gate control theory.” Our hypothesis is that a computational model provides a plausible description of the mechanism by which dorsal column stimulation (DCS) inhibits wide dynamic range (WDR) cell output in a neuropathic model but not in a nociceptive pain model. Materials and Methods We created a computational model of the human spinal cord involving approximately 360,000 individual neurons and dendritic processing of some 60 million synapses—the most elaborate dynamic computational model of the human spinal cord to date. Neuropathic and nociceptive “pain” signals were created by activating topographically isolated regions of excitatory interneurons and high-threshold nociceptive fiber inputs, driving analogous regions of WDR neurons. Dorsal column fiber activity was then added at clinically relevant levels (e.g., Aβ firing rate between 0 and 110 Hz by using a 210-μsec pulse width, 50–150 Hz frequency, at 1–3 V amplitude). Results Analysis of the nociceptive pain, neuropathic pain, and modulated circuits shows that, in contradiction to gate control theory, 1) nociceptive and neuropathic pain signaling must be distinct, and 2) DCS neuromodulation predominantly affects the neuropathic signal only, inhibiting centrally sensitized pathological neuron groups and ultimately the WDR pain transmission cells. Conclusion We offer a different set of necessary premises than gate control theory to explain neuropathic pain inhibition and the relative lack of nociceptive pain inhibition by using retrograde DCS. Hypotheses regarding not only the pain relief mechanisms of DCS were made but also regarding the circuitry of pain itself, both nociceptive and neuropathic. These hypotheses and further use of the model may lead to novel stimulation paradigms.