Hypofractionated radiotherapy for glioblastoma: A large institutional retrospective assessment of 2 approaches.

Background: Glioblastoma (GBM) poses therapeutic challenges due to its aggressive nature, particularly for patients with poor functional status and/or advanced disease. Hypofractionated radiotherapy (RT) regimens have demonstrated comparable disease outcomes for this population while allowing treatment to be completed more quickly. Here, we report our institutional outcomes of patients treated with 2 hypofractionated RT regimens: 40 Gy/15fx (3w-RT) and 50 Gy/20fx (4w-RT). Methods: A single-institution retrospective analysis was conducted of 127 GBM patients who underwent 3w-RT or 4w-RT. Patient characteristics, treatment regimens, and outcomes were analyzed. Univariate and multivariable Cox regression models were used to estimate progression-free survival (PFS) and overall survival (OS). The impact of chemotherapy and RT schedule was explored through subgroup analyses. Results: Median OS for the entire cohort was 7.7 months. There were no significant differences in PFS or OS between 3w-RT and 4w-RT groups overall. Receipt and timing of temozolomide (TMZ) emerged as the variable most strongly associated with survival, with patients receiving adjuvant-only or concurrent and adjuvant TMZ having significantly improved PFS and OS (P < .001). In a subgroup analysis of patients that did not receive TMZ, patients in the 4w-RT group demonstrated a trend toward improved OS as compared to the 3w-RT group (P = .12). Conclusions: This study demonstrates comparable survival outcomes between 3w-RT and 4w-RT regimens in GBM patients. Receipt and timing of TMZ were strongly associated with survival outcomes. The potential benefit of dose-escalated hypofractionation for patients not receiving chemotherapy warrants further investigation and emphasizes the importance of personalized treatment approaches.

Arterial Spin-Labeling and DSC Perfusion Metrics Improve Agreement in Neuroradiologists' Clinical Interpretations of Posttreatment High-Grade Glioma Surveillance MR Imaging-An Institutional Experience.

BACKGROUND AND PURPOSE: MR perfusion has shown value in the evaluation of posttreatment high-grade gliomas, but few studies have shown its impact on the consistency and confidence of neuroradiologists' interpretation in routine clinical practice. We evaluated the impact of adding MR perfusion metrics to conventional contrast-enhanced MR imaging in posttreatment high-grade glioma surveillance imaging. MATERIALS AND METHODS: This retrospective study included 45 adults with high-grade gliomas who had posttreatment perfusion MR imaging. Four neuroradiologists assigned Brain Tumor Reporting and Data System scores for each examination on the basis of the interpretation of contrast-enhanced MR imaging and then after the addition of arterial spin-labeling-CBF, DSC-relative CBV, and DSC-fractional tumor burden. Interrater agreement and rater agreement with a multidisciplinary consensus group were assessed with κ statistics. Raters used a 5-point Likert scale to report confidence scores. The frequency of clinically meaningful score changes resulting from the addition of each perfusion metric was determined. RESULTS: Interrater agreement was moderate for contrast-enhanced MR imaging alone (κ = 0.63) and higher with perfusion metrics (arterial spin-labeling-CBF, κ = 0.67; DSC-relative CBV, κ = 0.66; DSC-fractional tumor burden, κ = 0.70). Agreement between raters and consensus was highest with DSC-fractional tumor burden (κ = 0.66-0.80). Confidence scores were highest with DSC-fractional tumor burden. Across all raters, the addition of perfusion resulted in clinically meaningful interpretation changes in 2%-20% of patients compared with contrast-enhanced MR imaging alone. CONCLUSIONS: Adding perfusion to contrast-enhanced MR imaging improved interrater agreement, rater agreement with consensus, and rater confidence in the interpretation of posttreatment high-grade glioma MR imaging, with the highest agreement and confidence scores seen with DSC-fractional tumor burden. Perfusion MR imaging also resulted in interpretation changes that could change therapeutic management in up to 20% of patients.

Tumor treating fields suppress tumor cell growth and neurologic decline in models of spinal metastases.

Spinal metastases can result in severe neurologic compromise and decreased overall survival. Despite treatment advances, local disease progression is frequent, highlighting the need for novel therapies. Tumor treating fields (TTFields) impair tumor cell replication and are influenced by properties of surrounding tissue. We hypothesized that bone's dielectric properties will enhance TTFields-mediated suppression of tumor growth in spinal metastasis models. Computational modeling of TTFields intensity was performed following surgical resection of a spinal metastasis and demonstrated enhanced TTFields intensity within the resected vertebral body. Additionally, luciferase-tagged human KRIB osteosarcoma and A549 lung adenocarcinoma cell lines were cultured in demineralized bone grafts and exposed to TTFields. Following TTFields exposure, the bioluminescence imaging (BLI) signal decreased to 10%-80% of baseline, while control cultures displayed a 4.48- to 9.36-fold increase in signal. Lastly, TTFields were applied in an orthotopic murine model of spinal metastasis. After 21 days of treatment, control mice demonstrated a 5-fold increase in BLI signal compared with TTFields-treated mice. TTFields similarly prevented tumor invasion into the spinal canal and development of neurologic symptoms. Our data suggest that TTFields can be leveraged as a local therapy within minimally conductive bone of spinal metastases. This provides the groundwork for future studies investigating TTFields for patients with treatment-refractory spinal metastases.

Impact of glioma peritumoral edema, tumor size, and tumor location on alternating electric fields (AEF) therapy in realistic 3D rat glioma models: a computational study.

Objective.Alternating electric fields (AEF) therapy is a treatment modality for patients with glioblastoma. Tumor characteristics such as size, location, and extent of peritumoral edema may affect the AEF strength and distribution. We evaluated the sensitivity of the AEFs in a realistic 3D rat glioma model with respect to these properties.Approach.The electric properties of the peritumoral edema were varied based on calculated and literature-reported values. Models with different tumor composition, size, and location were created. The resulting AEFs were evaluated in 3D rat glioma models.Main results.In all cases, a pair of 5 mm diameter electrodes induced an average field strength >1 V cm-1. The simulation results showed that a negative relationship between edema conductivity and field strength was found. As the tumor core size was increased, the average field strength increased while the fraction of the shell achieving >1.5 V cm-1decreased. Increasing peritumoral edema thickness decreased the shell's mean field strength. Compared to rostrally/caudally, shifting the tumor location laterally/medially and ventrally (with respect to the electrodes) caused higher deviation in field strength.Significance.This study identifies tumor properties that are key drivers influencing AEF strength and distribution. The findings might be potential preclinical implications.

The genomic alterations in glioblastoma influence the levels of CSF metabolites.

Cerebrospinal fluid (CSF) analysis is underutilized in patients with glioblastoma (GBM), partly due to a lack of studies demonstrating the clinical utility of CSF biomarkers. While some studies show the utility of CSF cell-free DNA analysis, studies analyzing CSF metabolites in patients with glioblastoma are limited. Diffuse gliomas have altered cellular metabolism. For example, mutations in isocitrate dehydrogenase enzymes (e.g., IDH1 and IDH2) are common in diffuse gliomas and lead to increased levels of D-2-hydroxyglutarate in CSF. However, there is a poor understanding of changes CSF metabolites in GBM patients. In this study, we performed targeted metabolomic analysis of CSF from n = 31 patients with GBM and n = 13 individuals with non-neoplastic conditions (controls), by mass spectrometry. Hierarchical clustering and sparse partial least square-discriminant analysis (sPLS-DA) revealed differences in CSF metabolites between GBM and control CSF, including metabolites associated with fatty acid oxidation and the gut microbiome (i.e., carnitine, 2-methylbutyrylcarnitine, shikimate, aminobutanal, uridine, N-acetylputrescine, and farnesyl diphosphate). In addition, we identified differences in CSF metabolites in GBM patients based on the presence/absence of TP53 or PTEN mutations, consistent with the idea that different mutations have different effects on tumor metabolism. In summary, our results increase the understanding of CSF metabolites in patients with diffuse gliomas and highlight several metabolites that could be informative biomarkers in patients with GBM.

Tumor treating fields increases blood-brain barrier permeability and relative cerebral blood volume in patients with glioblastoma.

BACKGROUND AND OBJECTIVE: 200 kHz tumor treating fields (TTFields) is clinically approved for newly-diagnosed glioblastoma (nGBM). Because its effects on conventional surveillance MRI brain scans are equivocal, we investigated its effects on perfusion MRI (pMRI) brain scans. METHODS: Each patient underwent institutional standard pMRI: dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) pMRI at three time points: baseline, 2-, and 6-months on-adjuvant therapy. At each timepoint, the difference between T1 pre- versus post-contrast tumor volume (ΔT1) and these pMRI metrics were evaluated: normalized and standardized relative cerebral blood volume (nRCBV, sRCBV); fractional plasma volume (Vp), volume of extravascular extracellular space (EES) per volume of tissue (Ve), blood-brain barrier (BBB) permeability (Ktrans), and time constant for gadolinium reflux from EES back into the vascular system (Kep). Between-group comparisons were performed using rank-sum analysis, and bootstrapping evaluated likely reproducibility of the results. RESULTS: Among 13 pMRI datasets (11 nGBM, 2 recurrent GBM), therapies included temozolomide-only (n = 9) and temozolomide + TTFields (n = 4). No significant differences were found in patient or tumor characteristics. Compared to temozolomide-only, temozolomide + TTFields did not significantly affect the percent-change in pMRI metrics from baseline to 2 months. But during the 2- to 6-month period, temozolomide + TTFields significantly increased the percent-change in nRCBV (+26.9% [interquartile range 55.1%] vs -39.1% [37.0%], p = 0.049), sRCBV (+9.5% [39.7%] vs -30.5% [39.4%], p = 0.049), Ktrans (+54.6% [1768.4%] vs -26.9% [61.2%], p = 0.024), Ve (+111.0% [518.1%] vs -13.0% [22.5%], p = 0.048), and Vp (+98.8% [2172.4%] vs -24.6% [53.3%], p = 0.024) compared to temozolomide-only. CONCLUSION: Using pMRI, we provide initial in-human validation of pre-clinical studies regarding the effects of TTFields on tumor blood volume and BBB permeability in GBM.

Electric field distributions in realistic 3D rat head models during alternating electric field (AEF) therapy: a computational study.

Objective.Application of alternating electrical fields (AEFs) in the kHz range is an established treatment modality for primary and recurrent glioblastoma. Preclinical studies would enable innovations in treatment monitoring and efficacy, which could then be translated to benefit patients. We present a practical translational process converting image-based data into 3D rat head models for AEF simulations and study its sensitivity to parameter choices.Approach.Five rat head models composed of up to 7 different tissue types were created, and relative permittivity and conductivity of individual tissues obtained from the literature were assigned. Finite element analysis was used to model the AEF strength and distribution in the models with different combinations of head tissues, a virtual tumor, and an electrode pair.Main results.The simulations allowed for a sensitivity analysis of the AEF distribution with respect to different tissue combinations and tissue parameter values.Significance.For a single pair of 5 mm diameter electrodes, an average AEF strength inside the tumor exceeded 1.5 V cm-1, expected to be sufficient for a relevant therapeutic outcome. This study illustrates a robust and flexible approach for simulating AEF in different tissue types, suitable for preclinical studies in rodents and translatable to clinical use.

Current status of the preclinical evaluation of alternating electric fields as a form of cancer therapy.

Exposing cancer cells to alternating electric fields of 100-300 kHz frequency and 1-4 V/cm strength has been shown to significantly reduce cancer growth in cell culture and in human patients. This form of anti-cancer therapy is more commonly referred to as tumor treating fields (TTFields), a novel treatment modality that has been approved by the U.S. Food and Drug Administration for use in patients with glioblastoma and malignant pleural mesothelioma. Pivotal trials in other solid organ cancer trials are underway. In regards to overall survival, TTFields alone is comparable to chemotherapy alone in recurrent glioblastoma. However, when combined with adjuvant chemotherapy, TTFields prolong median survival by 4.9 months in newly-diagnosed glioblastoma. TTFields hold promise as a therapeutic approach to numerous solid organ cancers. This review summarizes the current status of TTFields research at the preclinical level, highlighting recent aspects of a relatively complex working hypothesis. In addition, we point out the gaps between limited preclinical in vivo studies and the available clinical data. To date, no customized system for TTFields delivery in rodent models of glioblastoma has been presented. We aim to motivate the expansion of TTFields preclinical research and facilitate the availability of suitable hardware, to ultimately improve outcomes in patients with cancer.

Low rates of structured advance care planning documentation in electronic health records: results of a single-center observational study.

BACKGROUND: Proper advance care planning (ACP) documentation both improves patient care and is increasingly seen as a marker of high quality by governmental payers. The transition of most medical documentation to electronic health records (EHR) allows for ACP documents to be rapidly disseminated across diverse ambulatory practice settings. At the same time, the complexity and heterogeneity of the EHR, as well as the multiple potential storage locations for documentation, may lead to confusion and inaccessibility. There has been movement to promote structured ACP (S-ACP) documentation within the EHR. METHODS: We performed a retrospective cohort study at a single, large university medical center in California to analyze rates of S-ACP documentation. S-ACP was defined as ACP documentation contained in standardized locations, auditable, and not in free-text format. The analytic cohort composed of all patients 65 and older with at least one ambulatory encounter at Stanford Health Care between 2012 and 2020, and without concurrent hospice care. We then analyzed clinic-level, provider-level, insurance, and temporal factors associated with S-ACP documentation rate. RESULTS: Of 187,316 unique outpatient encounters between 2012 and 2020, only 7,902 (4.2%) contained S-ACP documentation in the EHR. The most common methods of S-ACP documentation were through problem list diagnoses (3,802; 40.3%) and scanned documents (3,791; 40.0%). At the clinic level, marked variability in S-ACP documentation was observed, with Senior Care (46.6%) and Palliative Care (25.0%) demonstrating highest rates. There was a temporal trend toward increased S-ACP documentation rate (p < 0.001). CONCLUSION: This retrospective, single-center study reveals a low rate of S-ACP documentation irrespective of clinic and specialty. While S-ACP documentation rate should not be construed as a proxy for ACP documentation rate, it nonetheless serves as an important quality metric which may be reported to payers. This study highlights the need to both centralize and standardize reporting of ACP documentation in complex EHR systems.

TNTdetect.AI: A Deep Learning Model for Automated Detection and Counting of Tunneling Nanotubes in Microscopy Images.

BACKGROUND: Tunneling nanotubes (TNTs) are cellular structures connecting cell membranes and mediating intercellular communication. TNTs are manually identified and counted by a trained investigator; however, this process is time-intensive. We therefore sought to develop an automated approach for quantitative analysis of TNTs. METHODS: We used a convolutional neural network (U-Net) deep learning model to segment phase contrast microscopy images of both cancer and non-cancer cells. Our method was composed of preprocessing and model development. We developed a new preprocessing method to label TNTs on a pixel-wise basis. Two sequential models were employed to detect TNTs. First, we identified the regions of images with TNTs by implementing a classification algorithm. Second, we fed parts of the image classified as TNT-containing into a modified U-Net model to estimate TNTs on a pixel-wise basis. RESULTS: The algorithm detected 49.9% of human expert-identified TNTs, counted TNTs, and calculated the number of TNTs per cell, or TNT-to-cell ratio (TCR); it detected TNTs that were not originally detected by the experts. The model had 0.41 precision, 0.26 recall, and 0.32 f-1 score on a test dataset. The predicted and true TCRs were not significantly different across the training and test datasets (p = 0.78). CONCLUSIONS: Our automated approach labeled and detected TNTs and cells imaged in culture, resulting in comparable TCRs to those determined by human experts. Future studies will aim to improve on the accuracy, precision, and recall of the algorithm.

Biomimetic Hydrogels in the Study of Cancer Mechanobiology: Overview, Biomedical Applications, and Future Perspectives.

Hydrogels are biocompatible polymers that are tunable to the system under study, allowing them to be widely used in medicine, bioprinting, tissue engineering, and biomechanics. Hydrogels are used to mimic the three-dimensional microenvironment of tissues, which is essential to understanding cell-cell interactions and intracellular signaling pathways (e.g., proliferation, apoptosis, growth, and survival). Emerging evidence suggests that the malignant properties of cancer cells depend on mechanical cues that arise from changes in their microenvironment. These mechanobiological cues include stiffness, shear stress, and pressure, and have an impact on cancer proliferation and invasion. The hydrogels can be tuned to simulate these mechanobiological tissue properties. Although interest in and research on the biomedical applications of hydrogels has increased in the past 25 years, there is still much to learn about the development of biomimetic hydrogels and their potential applications in biomedical and clinical settings. This review highlights the application of hydrogels in developing pre-clinical cancer models and their potential for translation to human disease with a focus on reviewing the utility of such models in studying glioblastoma progression.

Remotely controlled near-infrared-triggered photothermal treatment of brain tumours in freely behaving mice using gold nanostars.

Current clinical brain tumour therapy practices are based on tumour resection and post-operative chemotherapy or X-ray radiation. Resection requires technically challenging open-skull surgeries that can lead to major neurological deficits and, in some cases, death. Treatments with X-ray and chemotherapy, on the other hand, cause major side-effects such as damage to surrounding normal brain tissues and other organs. Here we report the development of an integrated nanomedicine-bioelectronics brain-machine interface that enables continuous and on-demand treatment of brain tumours, without open-skull surgery and toxicological side-effects on other organs. Near-infrared surface plasmon characteristics of our gold nanostars enabled the precise treatment of deep brain tumours in freely behaving mice. Moreover, the nanostars' surface coating enabled their selective diffusion in tumour tissues after intratumoral administration, leading to the exclusive heating of tumours for treatment. This versatile remotely controlled and wireless method allows the adjustment of nanoparticles' photothermal strength, as well as power and wavelength of the therapeutic light, to target tumours in different anatomical locations within the brain.

Anti-cancer mechanisms of action of therapeutic alternating electric fields (tumor treating fields [TTFields]).

Despite improved survival outcomes across many cancer types, the prognosis remains grim for certain solid organ cancers including glioblastoma and pancreatic cancer. Invariably in these cancers, the control achieved by time-limited interventions such as traditional surgical resection, radiation therapy, and chemotherapy is short-lived. A new form of anti-cancer therapy called therapeutic alternating electric fields (AEFs) or tumor treating fields (TTFields) has been shown, either by itself or in combination with chemotherapy, to have anti-cancer effects that translate to improved survival outcomes in patients. Although the pre-clinical and clinical data are promising, the mechanisms of TTFields are not fully elucidated. Many investigations are underway to better understand how and why TTFields is able to selectively kill cancer cells and impede their proliferation. The purpose of this review is to summarize and discuss the reported mechanisms of action of TTFields from pre-clinical studies (both in vitro and in vivo). An improved understanding of how TTFields works will guide strategies focused on the timing and combination of TTFields with other therapies, to further improve survival outcomes in patients with solid organ cancers.

The Mechanisms of Action of Tumor Treating Fields.

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.

Recurrent Status Epilepticus in the Setting of Chimeric Antigen Receptor (CAR)-T Cell Therapy.

Axicabtagene ciloleucel (AC) is an FDA-approved anti-CD19 autologous chimeric antigen receptor T-cell (CAR-T) therapy for refractory diffuse large B cell lymphoma (DLBCL). While its efficacy in DLBCL has been promising, neurotoxicity remains a significant concern. We present a case of a 22-year-old woman with chemotherapy-refractory DLBCL who exhibited Grade IV neurotoxicity in the setting of sepsis, after undergoing AC infusion. Despite prophylactic levetiracetam given per guidelines,1,2 she experienced a precipitous mental status decline on post-infusion day 8 (D8) followed by hypoxic respiratory failure in the setting of clinical status epilepticus on D11 and nonconvulsive status epilepticus (NCSE) on D18. While neuroimaging was unremarkable, EEG demonstrated diffuse slowing and 2.5-3 Hz generalized periodic discharges consistent with NCSE. Seizures were initially refractory to lorazepam, increasing doses of levetiracetam, and phenobarbital, requiring a midazolam drip titrated to 50-70% burst suppression for resolution. Methylprednisolone and tocilizumab were used to treat neurotoxicity and cytokine release syndrome, respectively. Empiric antibiotics were used for sepsis. After cessation of sedatives on D19, mental status improved to near baseline. PET/CT just prior to discharge showed a complete response of the DLBCL (Deauville 3). She was discharged on D37 with no further seizure activity. Unfortunately, a 3-month interval PET/CT demonstrated disease progression which continued through salvage pembrolizumab eventually leading to death 1.2 years post-CAR-T infusion. This case illustrates the clinical management challenges of a complex and rare neurotoxic side effect of CAR-T cell therapy, namely NCSE following status epilepticus.

A Clinical PET Imaging Tracer ([18F]DASA-23) to Monitor Pyruvate Kinase M2-Induced Glycolytic Reprogramming in Glioblastoma.

PURPOSE: Pyruvate kinase M2 (PKM2) catalyzes the final step in glycolysis, a key process of cancer metabolism. PKM2 is preferentially expressed by glioblastoma (GBM) cells with minimal expression in healthy brain. We describe the development, validation, and translation of a novel PET tracer to study PKM2 in GBM. We evaluated 1-((2-fluoro-6-[18F]fluorophenyl)sulfonyl)-4-((4-methoxyphenyl)sulfonyl)piperazine ([18F]DASA-23) in cell culture, mouse models of GBM, healthy human volunteers, and patients with GBM. EXPERIMENTAL DESIGN: [18F]DASA-23 was synthesized with a molar activity of 100.47 ± 29.58 GBq/µmol and radiochemical purity >95%. We performed initial testing of [18F]DASA-23 in GBM cell culture and human GBM xenografts implanted orthotopically into mice. Next, we produced [18F]DASA-23 under FDA oversight, and evaluated it in healthy volunteers and a pilot cohort of patients with glioma. RESULTS: In mouse imaging studies, [18F]DASA-23 clearly delineated the U87 GBM from surrounding healthy brain tissue and had a tumor-to-brain ratio of 3.6 ± 0.5. In human volunteers, [18F]DASA-23 crossed the intact blood-brain barrier and was rapidly cleared. In patients with GBM, [18F]DASA-23 successfully outlined tumors visible on contrast-enhanced MRI. The uptake of [18F]DASA-23 was markedly elevated in GBMs compared with normal brain, and it identified a metabolic nonresponder within 1 week of treatment initiation. CONCLUSIONS: We developed and translated [18F]DASA-23 as a new tracer that demonstrated the visualization of aberrantly expressed PKM2 for the first time in human subjects. These results warrant further clinical evaluation of [18F]DASA-23 to assess its utility for imaging therapy-induced normalization of aberrant cancer metabolism.

Palliative Care Service Utilization and Advance Care Planning for Adult Glioblastoma Patients: A Systematic Review.

Glioblastoma (GBM) has a median overall survival of 16-21 months. As patients with GBM suffer concurrently from terminal cancer and a disease with progressive neurocognitive decline, advance care planning (ACP) and palliative care (PC) are critical. We conducted a systematic review exploring published literature on the prevalence of ACP, end-of-life (EOL) services utilization (including PC services), and experiences among adults with GBM. We searched from database inception until 20 December 2020. Preferred reporting items for systematic reviews guidelines were followed. Included studies were assessed for quality using the Newcastle-Ottawa Scale. The 16 articles were all nonrandomized studies conducted in six countries with all but two published in 2014 or later. ACP documentation varied from 4-55%, PC referral was pursued in 39-40% of cases, and hospice referrals were made for 66-76% of patients. Hospitalizations frequently occurred at the EOL with 20-56% of patients spending over 25% of their overall survival time hospitalized. Many GBM patients do not pursue ACP or have access to PC. There is a dearth of focused and high-quality studies on ACP, PC, and hospice use among adults with GBM. Prospective studies that address these and additional aspects related to EOL care, such as healthcare costs and inpatient supportive care needs, are needed.

Permeabilizing Cell Membranes with Electric Fields.

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.

PTEN mutations predict benefit from tumor treating fields (TTFields) therapy in patients with recurrent glioblastoma.

INTRODUCTION: Optimal treatment for recurrent glioblastoma isocitrate dehydrogenase 1 and 2 wild-type (rGBM IDH-WT) is not standardized, resulting in multiple therapeutic approaches. A phase III clinical trial showed that tumor treating fields (TTFields) monotherapy provided comparable survival benefits to physician's chemotherapy choice in rGBM. However, patients did not equally benefit from TTFields, highlighting the importance of identifying predictive biomarkers of TTFields efficacy. METHODS: A retrospective review of an institutional database with 530 patients with infiltrating gliomas was performed. Patients with IDH-WT rGBM receiving TTFields at first recurrence were included. Tumors were evaluated by next-generation sequencing for mutations in 205 cancer-related genes. Post-progression survival (PPS) was examined using the log-rank test and multivariate Cox-regression analysis. RESULTS: 149 rGBM patients were identified of which 29 (19%) were treated with TTFields. No significant difference in median PPS was observed between rGBM patients who received versus did not receive TTFields (13.9 versus 10.9 months, p = 0.068). However, within the TTFields-treated group (n = 29), PPS was improved in PTEN-mutant (n = 14) versus PTEN-WT (n = 15) rGBM, (22.2 versus 11.6 months, p = 0.017). Within the PTEN-mutant group (n = 70, 47%), patients treated with TTFields (n = 14) had longer median PPS (22.2 versus 9.3 months, p = 0.005). No PPS benefit was observed in PTEN-WT patients receiving TTFields (n = 79, 53%). CONCLUSIONS: TTFields therapy conferred a significant PPS benefit in PTEN-mutant rGBM. Understanding the molecular mechanisms underpinning the differences in response to TTFields therapy could help elucidate the mechanism of action of TTFields and identify the rGBM patients most likely to benefit from this therapeutic option.