A Feasibility Study of Personalized Prescription Schemes for Glioblastoma Patients Using a Proliferation and Invasion Glioma Model

Opportunities for improving brain cancer treatment outcomes through imaging-based mathematical modeling of the delivery of radiotherapy and immunotherapy

Immunotherapy has become a fourth pillar in the treatment of brain tumors and, when combined with radiation therapy, may improve patient outcomes and reduce the neurotoxicity. As with other combination therapies, the identification of a treatment schedule that maximizes the synergistic effect of radiation- and immune-therapy is a fundamental challenge. Mechanism-based mathematical modeling is one promising approach to systematically investigate therapeutic combinations to maximize positive outcomes within a rigorous framework. However, successful clinical translation of model-generated combinations of treatment requires patient-specific data to allow the models to be meaningfully initialized and parameterized. Quantitative imaging techniques have emerged as a promising source of high quality, spatially and temporally resolved data for the development and validation of mathematical models. In this review, we will present approaches to personalize mechanism-based modeling frameworks with patient data, and then discuss how these techniques could be leveraged to improve brain cancer outcomes through patient-specific modeling and optimization of treatment strategies.

Intermittent radiotherapy as alternative treatment for recurrent high grade glioma: a modeling study based on longitudinal tumor measurements

Recurrent high grade glioma patients face a poor prognosis for which no curative treatment option currently exists. In contrast to prescribing high dose hypofractionated stereotactic radiotherapy (HFSRT, [Formula: see text] Gy [Formula: see text] 5 in daily fractions) with debulking intent, we suggest a personalized treatment strategy to improve tumor control by delivering high dose intermittent radiation treatment (iRT, [Formula: see text] Gy [Formula: see text] 1 every 6 weeks). We performed a simulation analysis to compare HFSRT, iRT and iRT plus boost ([Formula: see text] Gy [Formula: see text] 3 in daily fractions at time of progression) based on a mathematical model of tumor growth, radiation response and patient-specific evolution of resistance to additional treatments (pembrolizumab and bevacizumab). Model parameters were fitted from tumor growth curves of 16 patients enrolled in the phase 1 NCT02313272 trial that combined HFSRT with bevacizumab and pembrolizumab. Then, iRT +/- boost treatments were simulated and compared to HFSRT based on time to tumor regrowth. The modeling results demonstrated that iRT + boost(- boost) treatment was equal or superior to HFSRT in 15(11) out of 16 cases and that patients that remained responsive to pembrolizumab and bevacizumab would benefit most from iRT. Time to progression could be prolonged through the application of additional, intermittently delivered fractions. iRT hence provides a promising treatment option for recurrent high grade glioma patients for prospective clinical evaluation.

Towards an Image-Informed Mathematical Model of In Vivo Response to Fractionated Radiation Therapy

Simple Summary

Using medical imaging data and computational models, we develop a modeling framework to provide personalized treatment response forecasts to fractionated radiation therapy for individual tumors. We evaluate this approach in an animal model of brain cancer and forecast changes in tumor cellularity and vasculature.

Abstract

Fractionated radiation therapy is central to the treatment of numerous malignancies, including high-grade gliomas where complete surgical resection is often impractical due to its highly invasive nature. Development of approaches to forecast response to fractionated radiation therapy may provide the ability to optimize or adapt treatment plans for radiotherapy. Towards this end, we have developed a family of 18 biologically-based mathematical models describing the response of both tumor and vasculature to fractionated radiation therapy. Importantly, these models can be personalized for individual tumors via quantitative imaging measurements. To evaluate this family of models, rats (n = 7) with U-87 glioblastomas were imaged with magnetic resonance imaging (MRI) before, during, and after treatment with fractionated radiotherapy (with doses of either 2 Gy/day or 4 Gy/day for up to 10 days). Estimates of tumor and blood volume fractions, provided by diffusion-weighted MRI and dynamic contrast-enhanced MRI, respectively, were used to calibrate tumor-specific model parameters. The Akaike Information Criterion was employed to select the most parsimonious model and determine an ensemble averaged model, and the resulting forecasts were evaluated at the global and local level. At the global level, the selected model’s forecast resulted in less than 16.2% error in tumor volume estimates. At the local (voxel) level, the median Pearson correlation coefficient across all prediction time points ranged from 0.57 to 0.87 for all animals. While the ensemble average forecast resulted in increased error (ranging from 4.0% to 1063%) in tumor volume predictions over the selected model, it increased the voxel wise correlation (by greater than 12.3%) for three of the animals. This study demonstrates the feasibility of calibrating a model of response by serial quantitative MRI data collected during fractionated radiotherapy to predict response at the conclusion of treatment.

Identification of 2-Fluoropalmitic Acid as a Potential Therapeutic Agent Against Glioblastoma

BACKGROUND

Glioblastomas (GBMs) are aggressive malignant brain tumors. Although chemotherapy with temozolomide (TMZ) can extend patient survival, most patients eventually demonstrate resistance. Therefore, novel therapeutic agents that overcome TMZ chemoresistance are required to improve patient outcomes.

PURPOSE

Drug screening is an efficient method to find new therapeutic agents from existing drugs. In this study, we explored a novel anti-glioma agent by drug screening and analyzed its function with respect to GBM treatment for future clinical applications.

METHODS

Drug libraries containing 1,301 diverse chemical compounds were screened against two glioma stem cell (GSC) lines for drug candidate selection. The effect of selected agents on GSCs and glioma was estimated through viability, proliferation, sphere formation, and invasion assays. Combination therapy was performed to assess its ability to enhance TMZ cytotoxicity against GBM. To clarify the mechanism of action, we performed methylation-specific polymerase chain reaction, gelatin zymography, and western blot analysis.

RESULTS

The acyl-CoA synthetase inhibitor 2-fluoropalmitic acid (2-FPA) was selected as a candidate anti-glioma agent. 2-FPA suppressed the viability and stem-like phenotype of GSCs. It also inhibited proliferation and invasion of glioma cell lines. Combination therapy of 2-FPA with TMZ synergistically enhanced the efficacy of TMZ. 2-FPA suppressed the expression of phosphor-ERK, CD133, and SOX-2; reduced MMP-2 activity; and increased methylation of the MGMT promoter.

CONCLUSION

2-FPA was identified as a potential therapeutic agent against GBM. To extend these findings, physiological studies are required to examine the efficacy of 2-FPA against GBM in vivo.

Disulfiram-copper activates chloride currents and induces apoptosis with tyrosine kinase in prostate cancer cells

AIM

To elucidates the mechanism that disulfiram/copper complex (DSF/Cu) treatment activates chloride channels and induces apoptosis in prostate cancer cells.

METHODS

Cellular membrane currents were measured by membrane clamp technique; western blot to detect protein expression; flow cytometry to detect apoptosis; immunofluorescence to detect target protein co-localization, and further validated by a combination of protein-protein interaction and mock protein molecular docking techniques.

RESULTS

DSF/Cu activated chloride channels and induced apoptosis in LNCaP (a type of androgen-dependent prostate cancer cells) cells. The chloride currents activated by DSF/Cu were significantly reduced after knockdown of CLC3 with siRNA. In addition, DSF/Cu-activated chloride currents were reduced to background current levels after perfusion with genistein, a highly specific tyrosine kinase inhibitor. Conversely, DSF/Cu failed to activate chloride currents in LNCaP cells after 30 minutes of pre-incubation with genistein. When genistein was removed, and DSF/Cu was added, the activated currents were small and unstable, and gradually decreased. Immunofluorescence in LNCaP cells also showed co-localization of the CLC3 protein with tyrosine kinase 2β (PTK2B).

CONCLUSION

DSF/Cu can activate chloride channels and induce apoptosis in LNCaP cells with the involvement of tyrosine kinase. These results provide new insights into the target therapy of prostate cancer.

Radial basis function-generated finite difference scheme for simulating the brain cancer growth model under radiotherapy in various types of computational domains

BACKGROUND AND OBJECTIVES

We extend the original mathematical model, i.e., Swanson's reaction-diffusion equation to the surfaces with no boundary, and we find a new numerical method based on a meshless approach for solving numerically Swanson's reaction-diffusion model in the square and on the sphere.

METHODS

To solve numerically the Swanson's reaction-diffusion model and its extension version, a collocation meshless technique, namely radial basis function-generated finite difference (RBF-FD) scheme is employed for approximating the spatial variables in the square domain and on the sphere, respectively. Also, to approximate the time variable of the studied models, a first-order semi-implicit backward Euler scheme is used. The resulting fully discrete scheme is a linear system of algebraic equations per time step that is solved via the biconjugate gradient stabilized (BiCGSTAB) iterative algorithm with a zero-fill incomplete lower-upper (ILU) preconditioner.

RESULTS

The numerical simulations show the growth of untreated and treated brain tumors with radiotherapy using estimated and clinical data (given from magnetic resonance imaging (MRI) scans of patients). Moreover, the results reported here can be used for improving the treatment strategies of the invasive brain tumor.

CONCLUSIONS

Using the developed numerical scheme in this paper, we can simulate the behavior of the invasive form of brain tumor response to radiotherapy. Also, we can see the effects of radiation response on the brain tumor cell concentration of individual patients. The proposed meshless technique, which is applied for solving numerically the studied model, does not depend on any background mesh or triangulation for approximation in comparison with mesh-dependent methods. Moreover, we apply this technique to the sphere via any set of distributed points easily.

Patient-specific parameter estimates of glioblastoma multiforme growth dynamics from a model with explicit birth and death rates

Glioblastoma multiforme (GBM) is an aggressive primary brain cancer with a grim prog-nosis. Its morphology is heterogeneous, but prototypically consists of an inner, largely necrotic core surrounded by an outer, contrast-enhancing rim, and often extensive tumor-associated edema beyond. This structure is usually demonstrated by magnetic resonance imaging (MRI). To help relate the three highly idealized components of GBMs (i.e., necrotic core, enhancing rim, and maximum edema ex-tent) to the underlying growth "laws," a mathematical model of GBM growth with explicit motility, birth, and death processes is proposed. This model generates a traveling-wave solution that mimics tumor progression. We develop several novel methods to approximate key characteristics of the wave profile, which can be compared with MRI data. Several simplified forms of growth and death terms and their parameter identifiability are studied. We use several test cases of MRI data of GBM patients to yield personalized parameterizations of the model, and the biological and clinical implications are discussed.

Sigma-2 receptor/TMEM97 agonist PB221 as an alternative drug for brain tumor

Background

There are limited effective drugs that can reach the brain to target brain tumors, in particular glioblastoma, which is one of the most difficult cancers to be cured from. Because the overexpression of the sigma-2 receptor is frequently reported in glioma clinical samples and associated with poor prognosis and malignancy, we herein studied the anti-tumor effect of the sigma-2 receptor agonist PB221 (4-cyclohexyl-1-[3-(5-methoxy-1,2,3,4-tetrahydronaphthalen-1-yl)propyl]piperidine) on an anaplastic astrocytoma tumor model based on previous encouraging results in pancreatic cancer and neuroblastoma SK-N-SH cells.

Methods

The expression of the sigma-2 receptor, transmembrane protein 97 (TMEM97), in ALTS1C1 and UN-KC6141 cell lines was measured by RT-PCR and quantitative RT-PCR. The binding of sigma-2 receptor fluorescent ligands PB385 (6-[5-[3-(4-cyclohexylpiperazin-1-yl)propyl]-5,6,7,8-tetrahydronaphthalen-5-yloxy]-N-(7-nitro-2,1,3-benzoxadiazol-4-yl)hexanamine) and NO1 (2-{6-[2-(3-(6,7-dimethoxy-3,4-dihydroisoquinolin-2(1H)-yl)propyl)-3,4-dihydroisoquinolin-1(2H)-one-5-yloxy]hexyl}-5-(dimethylamino)isoindoline-1,3-dione) was examined by flow cytometry and the fluorescent plate reader. The antitumor activity of PB221 was initially examined in the murine brain tumor cell line ALTS1C1 and then in the murine pancreatic cell line UN-KC6141. The potential therapeutic efficacy of PB221 for murine brain tumors was examined by in vitro migration and invasion assays and in vivo ectopic and orthotopic ALTS1C1 tumor models.

Results: The IC₅₀ of PB221 for ALTS1C1 and UN-KC6141 cell lines was 10.61 ± 0.96 and 13.13 ± 1.15 μM, respectively. A low dose of PB221 (1 μM) significantly repressed the migration and invasion of ALTS1C1 cells, and a high dose of PB221 (20 μM) resulted in the apoptotic cell death of ALTS1C1 cells. These effects were reduced by the lipid antioxidant α-tocopherol, but not by the hydrophilic N-acetylcysteine, suggesting mitochondrial oxidative stress is involved. The in vivo study revealed that PB221 effectively retarded tumor growth to 36% of the control tumor volume in the ectopic intramuscular tumor model and increased the overall survival time by 20% (from 26 to 31 days) in the orthotopic intracerebral tumor model.

Conclusions

This study demonstrates that the sigma-2 receptor agonist PB221 has the potential to be an alternative chemotherapeutic drug for brain tumors with comparable side effects as the current standard-of-care drug, temozolomide.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5700-7) contains supplementary material, which is available to authorized users.

Distinct Tumor Microenvironment at Tumor Edge as a Result of Astrocyte Activation Is Associated With Therapeutic Resistance for Brain Tumor

Tumor vasculatures and hypoxia are critical tumor micro-environmental factors associated with tumor response to the therapy and heterogeneous in both time- and location-dependent manner. Using a murine orthotopic anaplastic astrocytoma model, ALTS1C1, this study showed that brain tumor edge had a very unique microenvironment, having higher microvascular density (MVD) and better vessel function than the tumor core, but on the other hand was also positive for hypoxia markers, such as pimonidazole (PIMO), hypoxia inducible factor-1α (HIF-1α), and carbonic anhydrase IV (CAIX). The hypoxia at tumor edge was transient, named as peripheral hypoxia, and caused by different mechanisms from the chronic hypoxia in tumor core. The correlation of CAIX staining with astrocyte activation marker, glial fibrillary acid protein (GFAP), at the tumor edge indicated the involvement of astrocyte activation on the development of peripheral hypoxia. Peripheral hypoxia was a specific trait of orthotopic brain tumors at tumor edge, regardless of tumor origin. The hypoxic cells were resistant to the therapy, regardless of their location. Surviving cells, particularly those at the hypoxic region of tumor edge, are likely the cause of tumor recurrence after the therapy. New therapeutic platform that targets cells in tumor edge is likely to achieve better treatment outcomes.