|Year : 2019 | Volume
| Issue : 2 | Page : 61-67
Tumor treating fields therapy for glioblastoma: An update
Eric T Wong
Brain Tumor Center and Neuro-Oncology Unit, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
|Date of Web Publication||27-Jun-2019|
Dr. Eric T Wong
Brain Tumor Center and Neuro-Oncology Unit, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215
Source of Support: None, Conflict of Interest: None
Tumor treating fields are alternating electric fields that have a therapeutic effect on newly diagnosed and recurrent glioblastomas. The fields act on cellular proteins with large dipole moment that are critical for tumor cells undergoing mitosis. This putative mechanism of mitotic disruption translates into a superior survival benefit for newly diagnosed glioblastoma patients when tested in a randomized clinical trial comparing tumor treating fields and temozolomide with temozolomide alone in the adjuvant setting. This review provides an updated summary of preclinical and clinical data, including the cell biology effects of tumor treating fields, computer simulation of the electric field distribution in patients, and the clinical efficacy data of this new therapeutic modality against glioblastoma.
Keywords: Clinical trials, electric fields, glioblastoma, mitosis, septin, tubulin, tumor treating fields
|How to cite this article:|
Wong ET. Tumor treating fields therapy for glioblastoma: An update. Glioma 2019;2:61-7
| Introduction|| |
Tumor treating fields (TTFields) are alternating electric fields at a frequency of 200 kHz that have anti-cancer effects. These fields are delivered by the TTFields therapy device, which consists of an assembly of an electric field generator and a portable lithium-ion battery, through two pairs of orthogonally positioned transducer arrays applied to the patient's shaved scalp. This device was approved by the United States Food and Drug Administration on April 8, 2011, for the treatment of progressive glioblastoma and on October 5, 2015, for newly diagnosed glioblastoma in the adjuvant setting after initial radiotherapy and daily temozolomide. The latter approval was based on a randomized Phase III clinical trial that demonstrated a significant survival benefit. This review will summarize the preclinical data on the physics and the cell biology effect on dividing tumor cells, as well as efficacy data from randomized clinical trials. Studies included in this review were obtained from PubMed with the search term of TTFields or alternating electric fields.
| Tumor Treating Fields Interrupt the Progression of Mitosis|| |
TTFields disrupt the division of tumor cells in culture. Kirson et al. initially observed cellular disruption during mitosis and the cells exhibited various structural abnormalities on immunofluorescent microscopy, including polypoid prophase, rosette, poorly aligned chromosomes on metaphase, multi-spindled metaphase, single-spindled metaphase, and asymmetric chromosome segregation in anaphase [Figure 1]. The maximal effect occurred on cells with their dividing axes parallel to the direction of the applied alternating electric fields. Furthermore, these cellular phenomena were dependent on the frequency, with an effective range from 100 to 300 kHz and a maximum at 200 kHz for glioma cell lines. The maximal effect also depended on the cell size and perhaps this is the reason that the optimal frequency is slightly lower at 150 kHz for mesothelioma cell lines (H2052 and MSTO-211H), lung adenocarcinoma cells (A549 and H1299) and breast adenocarcinomas (MCF-7 and MDA-MB-231) due to their smaller size. Collectively, these data indicate that TTFields affect a structural protein critical to the proper progression of mitosis and Tubulin fulfills this requirement due to its high dipole moment and its assembly into higher order microtubules, which are critical for the alignment of the chromosomes at the metaphase plate and the subsequent migration of sister chromatids during anaphase.
|Figure 1: Immunohistochemical staining of aberrant mitotic figures as a result of tumor treating fields. (A–F) Melanoma cells were stained with monoclonal antibodies for microtubules (green), actin (red), and DNA (blue) demonstrating polyploid prophase (A), rosette (B), poorly separated metaphase (C), multi-spindled metaphase (D), single-spindled metaphase (E) and asymmetric anaphase (F). Scale bar: 10 μm. (Reprinted with permission from Kirson et al. Cancer Res 2004;64:3288-95.)|
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TTFields also cause disruption of the cytoplasmic membrane during mitosis. Gera et al. demonstrated membrane blebbing that was coincident with the initiation of anaphase, and these aberrant contractions were due to abnormal distribution of the contractile elements resulting in ectopic furrow formation. The Septin complex mediates the contraction of the cytoplasmic furrow, and it also possesses a high dipole moment, allowing it to be perturbed when exposed to TTFields [Figure 2]. Indeed, TTFields inhibit the localization of Septin to the anaphase spindle midline and cytokinetic furrow, as well as its association with microtubules. The downstream effects include tetraploidy or uneven distribution of chromosomes into daughter cells, which may lead to cell death or cellular stress. Therefore, these observations support the notion that TTFields disrupt another protein – Septin – critical to the proper progression of mitosis.
|Figure 2: Model for mitotic disruption by tumor treating fields. Septin 2, 6, 7 complex is recruited to the Anaphase spindle midline and the cytokinetic cleavage furrow by Anillin where it self-assembles into a fibrous lattice due to lateral interactions between parallel Septin filaments. By inducing rotational movement within the parallel fibers at a slightly more than a right angle to their lateral axis, tumor treating fields are able to block lattice formation by disrupting the binding of individual fibers to each other. In the absence of proper Septin function, contractile elements of the cytokinetic furrow are dispersed from the equatorial midline of the cell, resulting in ectopic furrow malfunction that leads to violent membrane contractions at the onset of anaphase followed by aberrant mitotic exit. (Reprinted from Gera et al. PLoS One 2015;10:e0125269.)|
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Another mechanism by which TTFields exerts its anti-tumor effect is the disruption of DNA repair mechanisms. Comparative gene expression analysis of lung cancer cell lines after exposure revealed that BRCA1 responsive genes were downregulated and this effect was more extensively seen in responsive (H157 and H4006) than nonresponsive (A549 and H1299) cell lines. Specifically, the responsive cell lines had increased foci of DNA double-strand breaks and sub-G1 population of cells on flow cytometry, indicating a higher rate of apoptosis. Therefore, TTFields have a persistent effect on dividing cells in the telophase near the end of mitosis and G2/M checkpoint just before the next round of mitosis.
A major downstream consequence of TTFields effect on tumor cells being stressed is likely to be the induction of effector immune response from the host. This is based on the observation that mice injected with syngeneic B16F10 melanoma cells had fewer lung metastases when TTFields were externally applied to their torso compared to sham-treated mice. In addition, in another treatment, paradigm in which VX-2 tumors were implanted into the renal capsule of rabbits and TTFields were applied to the abdomen and retroperitoneum, these rabbits also had fewer lung metastases compared to sham-treated ones, suggesting an indirect mechanism of tumor control. Indeed, tumor cells in culture treated with TTFields have increased calreticulin expression on their surfaces and secretion of the Alarmin/damage-associated molecular pattern protein high-mobility group protein B1, potentially enabling their recognition and eventual destruction by the immune system. Therefore, TTFields have both direct and indirect mechanisms of action on tumor cells, and their anti-tumor efficacy is most effective when the effector immune system of the host is also engaged.
| Cellular Modeling Reveals Vulnerability of Dividing Cells to Tumor Treating Fields|| |
TTFields induce changes in dividing tumor cells, and these alterations are dependent on a number of physical factors, including the frequency and intensity of the electric fields, the orientation of the dividing cells relative to the vector of the applied electric fields and the geometry of the dividing cells. In this regard, computational modeling provides a means of analyzing and predicting the effects of TTFields in cell cultures. Wenger et al. used this method to confirm the observed biological effect of TTFields, and they noted that at low frequency, <10 kHz, the applied electric field did not penetrate the cell membrane. However, TTFields at 200 kHz induced the greatest electric field penetration during mid-telophase when most of the fields were concentrated at the cytokinetic furrow. This is probably a result of the hour-glass geometry of the cytokinetic furrow in mid-telophase compared to cell at early telophase or metaphase, which respectively have an optimal frequency of 500 kHz and 10 MHz. Furthermore, the effect of the applied fields also has a directional component. A maximum field intensity was noted in the cytokinetic furrow when the direction of the dividing cells was oriented parallel (0°) to the applied electric fields, and the intensity was at a minimum when the cells were oriented perpendicular (90°) to the fields [Figure 3]. Partial field effect was also seen between 0° and 90°, and the field intensity diminished progressively as the cells were oriented from 0° to 90°. Therefore, computational modeling of intracellular TTFields provides supportive data for a number of observed effects in cell culture experiments.
|Figure 3: Electric field distribution induced in a cell during three stages of telophase (columns) for varying angle between the division axis and the electric field (rows). The field has a frequency of 200 kHz, an intensity of 1 V/cm, and it is applied from left to right. The maximum field (max(E)) in a spherical region of interest (white circle) is presented in each panel in white and the corresponding average electric field (avg[E]) in the whole cell in black. (Reprinted with permission from Wenger et al. IEEE Rev Biomed Eng 2018;11:195-207.)|
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| Patient Modeling Provides a Quantitative Measure of Tumor Treating Fields|| |
Electric field mapping in patients can provide valuable data on the strength of TTFields applied to the glioblastoma. This is usually accomplished by first acquiring the MP-RAGE dataset of the patient's head magnetic resonance imaging. Segmentation masks are created using ScanIP 7.0 (Simpleware Ltd., UK) for critical neuroanatomical structures, including the scalp, skull, dura, cerebrospinal fluid, white matter, gray matter, brainstem, cerebellum, orbits, and bilateral ventricles, where grayscale thresholding methods are applied to initially segmented tissues, followed by manual correction on these masks. In addition, T1 and T2 magnetic resonance imaging sequences are also imported into ScanIP, and they are co-registered with the segmented masks for delineation of the gross tumor volume (GTV) and the necrotic core. The GTV and necrotic core are both manually segmented by the treating physician based on visible enhancements shown on the co-registered postgadolinium T1- and T2-weighted image datasets. After the transducer arrays are manually placed on the surface of the scalp, a three-dimensional finite element mesh is generated using ScanIP. This mesh is then imported into COMSOL Multiphysics (COMSOL, Burlington, MA, USA), where material properties, boundary conditions, and appropriate physics parameters are assigned and applied to solve for the electric field distribution.
The solved electric fields and energy absorbed in the brain can be visualized as a series of dose-volume histograms, including the electric field-volume histogram and the specific absorption ratio-volume histogram. The electric field-volume histogram is generated for the comparison of electric field strength between different models and it is referenced to (i) the percentage volume of a particular structure receiving at least 150 V/m (VE150), (ii) the magnitude of electric field strength encompassing 95% of a particular structure's volume (E95%), (iii) the magnitude of electric field strength encompassing 50% of a particular structure's volume (E50%), and (iv) the magnitude of electric field strength encompassing 20% of a particular structure's volume (E20%). Similarly, the comparison of the rate of energy absorbed in different specific absorption ratio-volume histogram models is referenced to (i) the percentage volume of a particular structure receiving at least 7.5 W/kg (VSAR7.5), (ii) the magnitude of specific absorption rate (SAR) encompassing 95% of a particular structure's volume (SAR95%), (iii) the magnitude of SAR encompassing 50% of a particular structure's volume (SAR50%), and (iv) the magnitude of SAR encompassing 20% of a particular structure's volume (SAR20%). Collectively, these parameters on the electric field-volume histogram and the specific absorption ratio-volume histogram can facility the comparison of the electric field strength and the amount of energy absorbed among patients [Figure 4].
|Figure 4: Volume histograms EVH and SARVH. (A–D) The EVH (A), SARVH (B), electric field map (C), and SAR map (D) were generated using a transducer array placement map. The highest EAUCwas found at the scalp and skull, whereas the lowest was detected at the orbits, bilateral ventricles, and brainstem. The highest SARAUCwas found at the skull, GTV, and the layer of cerebrospinal fluid between cortex and dura, whereas the lowest was found in the orbits, cerebellum, and the orbits. EVH: Electric field–volume histogram, SARVH: Specific absorption rate–volume histogram, SAR: Specific absorption rate, GTV: Gross tumor volume. (Reprinted from Lok et al. Cancer Med 2017;6:1286-300.)|
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Computer simulation can be a valuable tool to predict the results from changes in the delivery of TTFields. For example, the position of the arrays may affect the intensity and distribution of TTFields at the GTV depending on the location of the glioblastoma. Korshoej et al. identified optimal array positions for the majority of tumors located in the anterior-posterior direction but not in the left-right direction, except for a few that an oblique array layout, associated with TTFields oriented at 45° to the sagittal plane, was superior to the conventional anterior-posterior and left-right array positions. Furthermore, the removal of the craniotomy bone flap and the application of the arrays to the overlying scalp increased the effective electric field strength by 60%–70% at the GTV located at the cerebral hemisphere [Figure 5], but such craniectomy did not increase the field strength for a deep-seated tumor. Regardless, these data generated from computer simulation require confirmation of actual effectiveness in clinical situations.
|Figure 5: Effect of craniectomy with and without tumor resection. (A) Field strength distributions with and without craniectomy (coronal, axial and sagittal sections from left to right, color bar 0 ± 300 V/m). (B) Paired difference between craniectomy and no craniectomy scenarios. Craniectomy produced a marked and focal increase in electrical field strength in the regions of pathology underlying the craniectomy, while healthy tissues were largely spared. (C) Percentage of tissue exposed to field strengths above the corresponding value on the abscissa (craniectomy-stippled line; no craniectomy-solid line). Rows represent different tissues and columns the left/right (L/R) and anterior/posterior (A/P) electrode pairs, as indicated. Craniectomy significantly increased the electrical field strengths in tumor tissue and the peritumoral region compared to no craniectomy. The distributions of field strengths in healthy tissues were largely unaffected. WM: White matter, GM: Gray matter, ∣E∣: Absolute electric field in V/m (volts/meter). (Reprinted from Korshoej et al. PLoS One 2016;11:e0164051.)|
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| Adjuvant Tumor Treating Fields Prolong the Survival of Glioblastoma Patients|| |
EF-14 is the pivotal randomized phase III clinical trial (ClinicalTrials.gov: NCT00916409) that established a survival benefit when TTFields were added in the adjuvant setting to newly diagnosed glioblastoma patients. In the trial, individuals were randomized in a 2:1 fashion to receive TTFields plus adjuvant temozolomide or adjuvant temozolomide alone after completion of the initial involved-field cranial irradiation and concomitant daily temozolomide. The primary endpoint was progression-free survival (PFS) and second endpoints were overall survival (OS), PFS at 6 months, survival at 1 and 2 years, as well as the quality of life assessment. The findings from the prespecified interim analysis and the final analysis were essentially the same. The intent-to-treat cohort received TTFields plus temozolomide (n = 466) had a longer PFS than the cohort treated with temozolomide alone (n = 229), with a median PFS 6.7 versus 4.0 months, respectively (hazard ratio [HR] = 0.63, 95% confidence interval (CI) 0.52–0.76, log-rank P < 0.001) [Figure 6]; the PFS at 6 months was 56% (95%CI 51%–61%) versus 37% (95% CI 30%–44%), respectively. The median OS also favored the TTFields plus temozolomide over the temozolomide alone cohort, 20.9 versus 16.0 months respectively (HR = 0.63, 95% CI 0.53–0.76, log-rank P < 0.001) [Figure 6]. There were no unexpected adverse events and expected Grade 3 and 4 toxicities were similar between the two groups, including hematological side effects, gastrointestinal disorders, and convulsions. Scalp reaction was seen only in the device-treated cohort and not in the temozolomide-only group. Therefore, EF-14 provides a definite signal of survival benefit in the glioblastoma population when TTFields are applied.
|Figure 6: Kaplan-Meier survival curves for patients in the EF-14 trial. (A) Median progression-free survival from randomization for the tumor-treating fields plus temozolomide group was 6.7 months and was 4.0 months for the temozolomide-alone group (hazard ratio, 0.63; 95% confidence interval 0.52–0.76; P < 0.001). (B) Median survival from randomization was 20.9 for the tumor treating fields plus temozolomide group versus 16.0 months for the temozolomide-alone group (hazard ratio, 0.63; 95% confidence interval 0.53–0.76; P < 0.001). Median follow up was 44 months (range, 25–91 months) in both groups. (Reprinted with permission from Stupp et al. JAMA 2017;318:2306-16.)|
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EF-14 also included a robust health-related quality of life assessment. No significant difference was seen between the two cohorts except for scalp irritation in the TTFields-treated individuals. Measures for global health status, physical functioning, emotional functioning, pain, and leg weakness all favored the TTFields-treated group (P < 0.01), while role and social functioning were not affected by TTFields. Therefore, when added in the adjuvant setting, TTFields does not have a negative impact on patients with respect to their health-related quality of life except for scalp pruritus.
The treatment of glioblastoma patients using TTFields in the real world, clinical practice setting requires a number of important considerations [Figure 7]. First, usage compliance correlates with the efficacy of the device for controlling the tumor. In the EF-11 trial and the patient registry dataset for recurrent glioblastoma patients (ClinicalTrials.gov: NCT00379470), a threshold of 75% per day of usage was important, and this correlated with a longer OS. In contrast, the threshold was 50% for patients with newly diagnosed glioblastoma in the EF-14 trial. This lower threshold may be due to the application of TTFields in the newly diagnosed population, which may have a higher sensitivity to this treatment, and the combination with temozolomide in the adjuvant setting may also augment the efficacy of TTFields and therefore lower the threshold requirement. Second, the response pattern analysis from mathematical modeling of the EF-11 trial data suggests that tumor response develops slowly over time, with a median time to response of 5.2 months. However, responded patients have durable responses with a median duration of 12.9 months. Finally, supportive medication like dexamethasone that is frequently used in the glioblastoma population can have a negative impact on the efficacy of TTFields. The post hoc analysis of dexamethasone effect in the EF-11 cohorts demonstrated that patients taking ≤ 4.1 mg per day of dexamethasone lived more than twice as long as those used > 4.1 mg per day, with an OS of 11.0 versus 4.8 months, respectively (χ2= 34.6, P < 0.0001). Surprisingly, this superimposed dexamethasone effect was also seen in the chemotherapy-treated control cohort, and patient OS was 8.9 versus 6.0 months, respectively (χ2= 10.0, P < 0.0015). A similar dexamethasone effect superimposed negatively on patient survival was also seen in larger datasets from Memorial Sloan Kettering Cancer Center, the pivotal trial of the European Organization for Research and Treatment of Cancer/National Cancer Institute of Canada and the German Glioma Network. This survival disadvantage is likely a result of dexamethasone's immunosuppressive effect that weakens the already marginal antitumor immunity in these patients. Indeed, another immunosuppressant everolimus, which is also an inhibitor against the mammalian target of rapamycin, was evaluated in the glioblastoma population in a randomized study and patients taking this medication died sooner on average by 4.7 months. Therefore, patients undergoing TTFields treatment should avoid dexamethasone or other immunosuppressants.
|Figure 7: Factors influencing glioblastoma patient survival. A variety of factors may influence the separation of the experimental versus the control survival curves in clinical trials for glioblastoma. These factors include the number of individuals with intrinsic factors (IDH-1 mutations and MGMT methylation), extrinsic treatment factors (TTFields) and superimposed factors (dexamethasone and mTOR inhibitors). IDH-1: Isocitrate dehydrogenase 1, MGMT: O-6-methylguanine-DNA methyltransferase, TTFields: Tumor treating fields, mTOR: Mammalian target of rapamycin. (Adapted from Stupp et al. N Engl J Med 2005;352:987-96.)|
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| Conclusions|| |
The concept of treating malignancy using alternating electric fields at 150–200 kHz, also known as TTFields, has gained acceptance as a bona fide therapeutic modality for cancer. This is based on the observation of mitosis disruption in cell culture when dividing cells are exposed to these fields. Proteins with large dipole moments, including Tubulin and Septin, are major targets because they are critical for the proper progression of mitosis at metaphase and anaphase. In addition, TTFields affect cells in telophase due to increased DNA double-strand breaks. Furthermore, the geometry of dividing cells is relevant, particularly with the cytokinetic furrowing in telophase that can potentiate the anti-mitotic effect of these fields. From a clinical perspective, the treatment of newly diagnosed glioblastoma patients with TTFields plus temozolomide results in longer PFS and OS than standard temozolomide alone in the adjuvant setting, and this survival benefit is accompanied by improved measures in health-related quality of life. Furthermore, computer simulations offer an opportunity to quantify the amount of electric field applied to the tumor, but additional work is required to determine its correlation with clinical anti-tumor efficacy. Finally, adequate compliance and duration of usage, as well as avoidance of immunosuppressants, are also relevant factors in the treatment of glioblastoma patients with TTFields.
Financial support and sponsorship
Conflicts of interest
ETW receives sponsored research agreement and clinical trial support from Novocure; he also serves as a consultant for Zai Lab and Novocure.
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