A multiscale model for glioma spread including cell-tissue interactions and proliferation

Targeting MAGI2-AS3-modulated Akt-dependent ATP-binding cassette transporters as a possible strategy to reverse temozolomide resistance in temozolomide-resistant glioblastoma cells

Drug resistance is a major impediment to the successful treatment of glioma. This study aimed to elucidate the effects and mechanisms of the long noncoding RNA membrane-associated guanylate kinase inverted-2 antisense RNA 3 (MAGI2-AS3) on temozolomide (TMZ) resistance in glioma cells. MAGI2-AS3 expression in TMZ-resistant glioblastoma (GBM) cells was analyzed using the Gene Expression Omnibus data set GSE113510 and quantitative real-time PCR (qRT-PCR). Cell viability and TMZ half-maximal inhibitory concentration values were determined using the MTT assay. Apoptosis and cell cycle distribution were evaluated using flow cytometry. The expression of multidrug resistance 1 (MDR1), ATP-binding cassette superfamily G member 2 (ABCG2), protein kinase B (Akt), and phosphorylated Akt was detected using qRT-PCR and/or western blot analysis. MAGI2-AS3 was expressed at low levels in TMZ-resistant GBM cells relative to that in their parental cells. MAGI2-AS3 re-expression alleviated TMZ resistance in TMZ-resistant GBM cells. MAGI2-AS3 overexpression also accelerated TMZ-induced apoptosis and G2/M phase arrest. Mechanistically, MAGI2-AS3 overexpression reduced MDR1 and ABCG2 expression and inhibited the Akt pathway, whereas Akt overexpression abrogated the reduction in MDR1 and ABCG2 expression induced by MAGI2-AS3. Moreover, activation of the Akt pathway inhibited the effects of MAGI2-AS3 on TMZ resistance. MAGI2-AS3 inhibited tumor growth and enhanced the suppressive effect of TMZ on glioma tumorigenesis in vivo. In conclusion, MAGI2-AS3 reverses TMZ resistance in glioma cells by inactivating the Akt pathway.

Data driven modeling of pseudopalisade pattern formation

Pseudopalisading is an interesting phenomenon where cancer cells arrange themselves to form a dense garland-like pattern. Unlike the palisade structure, a similar type of pattern first observed in schwannomas by pathologist J.J. Verocay (Wippold et al. in AJNR Am J Neuroradiol 27(10):2037-2041, 2006), pseudopalisades are less organized and associated with a necrotic region at their core. These structures are mainly found in glioblastoma (GBM), a grade IV brain tumor, and provide a way to assess the aggressiveness of the tumor. Identification of the exact bio-mechanism responsible for the formation of pseudopalisades is a difficult task, mainly because pseudopalisades seem to be a consequence of complex nonlinear dynamics within the tumor. In this paper we propose a data-driven methodology to gain insight into the formation of different types of pseudopalisade structures. To this end, we start from a state of the art macroscopic model for the dynamics of GBM, that is coupled with the dynamics of extracellular pH, and formulate a terminal value optimal control problem. Thus, given a specific, observed pseudopalisade pattern, we determine the evolution of parameters (bio-mechanisms) that are responsible for its emergence. Random histological images exhibiting pseudopalisade-like structures are chosen to serve as target pattern. Having identified the optimal model parameters that generate the specified target pattern, we then formulate two different types of pattern counteracting ansatzes in order to determine possible ways to impair or obstruct the process of pseudopalisade formation. This provides the basis for designing active or live control of malignant GBM. Furthermore, we also provide a simple, yet insightful, mechanism to synthesize new pseudopalisade patterns by linearly combining the optimal model parameters responsible for generating different known target patterns. This particularly provides a hint that complex pseudopalisade patterns could be synthesized by a linear combination of parameters responsible for generating simple patterns. Going even further, we ask ourselves if complex therapy approaches can be conceived, such that some linear combination thereof is able to reverse or disrupt simple pseudopalisade patterns; this is investigated with the help of numerical simulations.

A stochastic hierarchical model for low grade glioma evolution

A stochastic hierarchical model for the evolution of low grade gliomas is proposed. Starting with the description of cell motion using a piecewise diffusion Markov process (PDifMP) at the cellular level, we derive an equation for the density of the transition probability of this Markov process based on the generalised Fokker-Planck equation. Then, a macroscopic model is derived via parabolic limit and Hilbert expansions in the moment equations. After setting up the model, we perform several numerical tests to study the role of the local characteristics and the extended generator of the PDifMP in the process of tumour progression. The main aim focuses on understanding how the variations of the jump rate function of this process at the microscopic scale and the diffusion coefficient at the macroscopic scale are related to the diffusive behaviour of the glioma cells and to the onset of malignancy, i.e., the transition from low-grade to high-grade gliomas.

EZH2-Myc driven glioblastoma elicited by cytomegalovirus infection of human astrocytes

Mounting evidence is identifying human cytomegalovirus (HCMV) as a potential oncogenic virus. HCMV has been detected in malignant gliomas. EZH2 and Myc play a potential oncogenic role, correlating with the glioma grade. Herewith, we present the first experimental evidence for HCMV as a reprogramming vector, straight through the dedifferentiation of mature human astrocytes, and generation of CMV-Elicited Glioblastoma Cells (CEGBCs) possessing glioblastoma-like traits. HCMV counterparts the progression of the perceived cellular and molecular mechanisms succeeding the transformation and invasion processes with CEGBCs involved in spheroid formation and invasiveness. Glioblastoma multiforme (GBM) biopsies were characterized by an elevated EZH2 and Myc expression, possessing a strong positive correlation between the aforementioned markers in the presence of HCMV. From GBM tissues, we isolated HCMV clinical strains that transformed HAs toward CEGBCs exhibiting upregulated EZH2 and Myc. Spheroids generated from CEGBCs possessed invasion potential and were sensitive to EZH2 inhibitor, ganciclovir, and temozolomide triple therapy. HCMV clinical strains transform HAs and fit with an HCMV-induced glioblastoma model of oncogenesis, and supports the tumorigenic properties of Myc and EZH2 which might be highly pertinent in the pathophysiology of astrocytic brain tumors and thereby paving the way for new therapeutic strategies.

Data-driven spatio-temporal modelling of glioblastoma

Mathematical oncology provides unique and invaluable insights into tumour growth on both the microscopic and macroscopic levels. This review presents state-of-the-art modelling techniques and focuses on their role in understanding glioblastoma, a malignant form of brain cancer. For each approach, we summarize the scope, drawbacks and assets. We highlight the potential clinical applications of each modelling technique and discuss the connections between the mathematical models and the molecular and imaging data used to inform them. By doing so, we aim to prime cancer researchers with current and emerging computational tools for understanding tumour progression. By providing an in-depth picture of the different modelling techniques, we also aim to assist researchers who seek to build and develop their own models and the associated inference frameworks. Our article thus strikes a unique balance. On the one hand, we provide a comprehensive overview of the available modelling techniques and their applications, including key mathematical expressions. On the other hand, the content is accessible to mathematicians and biomedical scientists alike to accommodate the interdisciplinary nature of cancer research.

Correlation of Diffusion Tensor Imaging Parameters with the Pathological Grade of Brain Glioma and Expression of Vascular Endothelial Growth Factor and Ki-67

Background: Most brain gliomas are high-grade and likely to spread locally. Consequently, these patients commonly have a poor prognosis. Accurate identification of the malignancy grade of brain glioma before treatment is of great clinical significance. Objectives: This study aimed to explore the correlation of diffusion tensor imaging (DTI) parameters, fractional anisotropy (FA), and apparent diffusion coefficient (ADC) with the pathological grade of brain glioma and expression of vascular endothelial growth factor (VEGF) and Ki-67. Patients and Methods: A total of 116 patients were selected for this study from January 2018 to December 2019. All the participants underwent magnetic resonance imaging (MRI) and DTI before surgery, and the FA and ADC values were measured for the regions of interest. Surgically resected tumor specimens were collected for immunohistochemical assay. Finally, the FA and ADC values and positive expression rates of VEGF and Ki-67 were compared. Results: A significantly higher FA, besides the positive expression of VEGF and Ki-67, was reported in the high-grade group, whereas a lower ADC was found in this group compared to the low-grade group (P < 0.05). Areas of normal white matter and peritumoral edema had higher FA values, whereas lower ADCs were measured in these areas compared to the cerebrospinal fluid (P < 0.05). The FA of tumor parenchymal area was positively correlated with the World Health Organization (WHO) WHO class of tumors (r = 0.588, P = 0.028), and the expression of VEGF and Ki-67 was positively correlated with the WHO grade (r = 0.843, P = 0.002 and r = 0.743, P = 0.006, respectively). The FA of tumor parenchymal area was positively correlated with the expression of VEGF and Ki-67 (r = 0.654, P = 0.008 and r = 0.567, P = 0.012, respectively). However, the ADC of tumor parenchymal area was not significantly correlated with the WHO grade, VEGF expression, or Ki-67 expression (r = 0.143, P = 0.156, r = 0.232, P = 0.116, and r = 0.054, P = 0.179, respectively). Conclusion: The FA value, as a DTI parameter, is valuable for assessing the malignancy grade of tumor cells and can provide a proper reference for formulating treatment regimens for brain gliomas.

Mesoscience in cell biology and cancer research

Mesoscale characteristics and their interdimensional correlation are the focus of contemporary interdisciplinary research. Mesoscience is a discipline that has the potential to radically update the existing knowledge structure, which differs from the conventional unit-scale and system-scale research models, revealing a previously untouchable area for scientific research. Integrative biology research aims to dissect the complex problems of life systems by conducting comprehensive research and integrating various disciplines from all biological levels of the living organism. However, the mesoscientific issues between different research units are neglected and challenging. Mesoscale research in biology requires the integration of research theories and methods from other disciplines (mathematics, physics, engineering, and even visual imaging) to investigate theoretical and frontier questions of biological processes through experiments, computations, and modeling. We reviewed  integrative paradigms and methods for the biological mesoscale problems (focusing on oncology research) and prospected the potential of their multiple dimensions and upcoming challenges. We expect to establish an interactive and collaborative theoretical platform for further expanding the depth and width of our understanding on the nature of biology.

Multi-Cue Kinetic Model with Non-Local Sensing for Cell Migration on a Fiber Network with Chemotaxis

Cells perform directed motion in response to external stimuli that they detect by sensing the environment with their membrane protrusions. Precisely, several biochemical and biophysical cues give rise to tactic migration in the direction of their specific targets. Thus, this defines a multi-cue environment in which cells have to sort and combine different, and potentially competitive, stimuli. We propose a non-local kinetic model for cell migration in which cell polarization is influenced simultaneously by two external factors: contact guidance and chemotaxis. We propose two different sensing strategies, and we analyze the two resulting transport kinetic models by recovering the appropriate macroscopic limit in different regimes, in order to observe how the cell size, with respect to the variation of both external fields, influences the overall behavior. This analysis shows the importance of dealing with hyperbolic models, rather than drift-diffusion ones. Moreover, we numerically integrate the kinetic transport equations in a two-dimensional setting in order to investigate qualitatively various scenarios. Finally, we show how our setting is able to reproduce some experimental results concerning the influence of topographical and chemical cues in directing cell motility.

Inducing Biomechanical Heterogeneity in Brain Tumor Modeling by MR Elastography: Effects on Tumor Growth, Vascular Density and Delivery of Therapeutics

Simple Summary

Biomechanical forces aggravate brain tumor progression. In this study, magnetic resonance elastography (MRE) is employed to extract tissue biomechanical properties from five glioblastoma patients and a healthy subject, and data are incorporated in a mathematical model that simulates tumor growth. Mathematical modeling enables further understanding of glioblastoma development and allows patient-specific predictions for tumor vascularity and delivery of drugs. Incorporating MRE data results in a more realistic intratumoral distribution of mechanical stress and anisotropic tumor growth and a better description of subsequent events that are closely related to the development of stresses, including heterogeneity of the tumor vasculature and intrapatient variations in tumor perfusion and delivery of drugs.

Abstract

The purpose of this study is to develop a methodology that incorporates a more accurate assessment of tissue mechanical properties compared to current mathematical modeling by use of biomechanical data from magnetic resonance elastography. The elastography data were derived from five glioblastoma patients and a healthy subject and used in a model that simulates tumor growth, vascular changes due to mechanical stresses and delivery of therapeutic agents. The model investigates the effect of tumor-specific biomechanical properties on tumor anisotropic growth, vascular density heterogeneity and chemotherapy delivery. The results showed that including elastography data provides a more realistic distribution of the mechanical stresses in the tumor and induces anisotropic tumor growth. Solid stress distribution differs among patients, which, in turn, induces a distinct functional vascular density distribution—owing to the compression of tumor vessels—and intratumoral drug distribution for each patient. In conclusion, incorporating elastography data results in a more accurate calculation of intratumoral mechanical stresses and enables a better mathematical description of subsequent events, such as the heterogeneous development of the tumor vasculature and intrapatient variations in tumor perfusion and delivery of drugs.

Multi-scale modeling of hippo signaling identifies homeostatic control by YAP-LATS negative feedback

The Hippo signaling primarily includes LATS1/2 and YAP1. Recent work has demonstrated a novel negative feedback between YAP1 and LATS1/2. However, how YAP-LATS negative feedback regulates cancer progression remains elusive. We constructed a multi-scale model which integrates angiogenesis, spatiotemporal variation of microenvironmental factors and phenotypic switch of tumor cells. Our simulation replicated the findings that YAP overexpression markedly attenuated cell proliferation owing to elevated negative feedback strength. After disruption of YAP-LATS negative feedback loop, however, YAP overexpression would promote cell proliferation. Consistently, LATS overexpression inhibited cell growth and lowered the proliferation potential. We also employed a putative LATS agonist and identified its dose-dependent tumor suppressive effects. Furthermore, targeted delivery could more effectively inhibit tumor growth. Our model has reconciled experimental findings and implied that reconstruction of functional and/or hyperactivated YAP-LATS negative feedback might be a promising strategy to homeostatic maintenance and tumor suppression.

Feasibility and clinical usefulness of modelling glioblastoma migration in adjuvant radiotherapy

Glioblastoma (GBM) is one of the most common primary brain tumours in adults, with a dismal prognosis despite aggressive multimodality treatment by a combination of surgery and adjuvant radiochemotherapy. A detailed knowledge of the spreading of glioma cells in the brain might allow for more targeted escalated radiotherapy, aiming to reduce locoregional relapse. Recent years have seen the development of a large variety of mathematical modelling approaches to predict glioma migration. The aim of this study is hence to evaluate the clinical applicability of a detailed micro- and meso-scale mathematical model in radiotherapy. First and foremost, a clinical workflow is established, in which the tumour is automatically segmented as input data and then followed in time mathematically based on the diffusion tensor imaging data. The influence of several free model parameters is individually evaluated, then the full model is retrospectively validated for a collective of 3 GBM patients treated at our institution by varying the most important model parameters to achieve optimum agreement with the tumour development during follow-up. Agreement of the model predictions with the real tumour growth as defined by manual contouring based on the follow-up MRI images is analyzed using the dice coefficient. The tumour evolution over 103-212 days follow-up could be predicted by the model with a dice coefficient better than 60% for all three patients. In all cases, the final tumour volume was overestimated by the model by a factor between 1.05 and 1.47. To evaluate the quality of the agreement between the model predictions and the ground truth, we must keep in mind that our gold standard relies on a single observer's (CB) manually-delineated tumour contours. We therefore decided to add a short validation of the stability and reliability of these contours by an inter-observer analysis including three other experienced radiation oncologists from our department. In total, a dice coefficient between 63% and 89% is achieved between the four different observers. Compared with this value, the model predictions (62-66%) perform reasonably well, given the fact that these tumour volumes were created based on the pre-operative segmentation and DTI.

Multiscale modeling of glioma pseudopalisades: contributions from the tumor microenvironment

Gliomas are primary brain tumors with a high invasive potential and infiltrative spread. Among them, glioblastoma multiforme (GBM) exhibits microvascular hyperplasia and pronounced necrosis triggered by hypoxia. Histological samples showing garland-like hypercellular structures (so-called pseudopalisades) centered around the occlusion site of a capillary are typical for GBM and hint on poor prognosis of patient survival. We propose a multiscale modeling approach in the kinetic theory of active particles framework and deduce by an upscaling process a reaction-diffusion model with repellent pH-taxis. We prove existence of a unique global bounded classical solution for a version of the obtained macroscopic system and investigate the asymptotic behavior of the solution. Moreover, we study two different types of scaling and compare the behavior of the obtained macroscopic PDEs by way of simulations. These show that patterns (not necessarily of Turing type), including pseudopalisades, can be formed for some parameter ranges, in accordance with the tumor grade. This is true when the PDEs are obtained via parabolic scaling (undirected tissue), while no such patterns are observed for the PDEs arising by a hyperbolic limit (directed tissue). This suggests that brain tissue might be undirected - at least as far as glioma migration is concerned. We also investigate two different ways of including cell level descriptions of response to hypoxia and the way they are related .

Tumor ablation due to inhomogeneous anisotropic diffusion in generic three-dimensional topologies

In recent decades computer-aided technologies have become prevalent in medicine, however, cancer drugs are often only tested on in vitro cell lines from biopsies. We derive a full three-dimensional model of inhomogeneous -anisotropic diffusion in a tumor region coupled to a binary population model, which simulates in vivo scenarios faster than traditional cell-line tests. The diffusion tensors are acquired using diffusion tensor magnetic resonance imaging from a patient diagnosed with glioblastoma multiform. Then we numerically simulate the full model with finite element methods and produce drug concentration heat maps, apoptosis hotspots, and dose-response curves. Finally, predictions are made about optimal injection locations and volumes, which are presented in a form that can be employed by doctors and oncologists.

A Flux-Limited Model for Glioma Patterning with Hypoxia-Induced Angiogenesis

We propose a model for glioma patterns in a microlocal tumor environment under the influence of acidity, angiogenesis, and tissue anisotropy. The bottom-up model deduction eventually leads to a system of reaction–diffusion–taxis equations for glioma and endothelial cell population densities, of which the former infers flux limitation both in the self-diffusion and taxis terms. The model extends a recently introduced (Kumar, Li and Surulescu, 2020) description of glioma pseudopalisade formation with the aim of studying the effect of hypoxia-induced tumor vascularization on the establishment and maintenance of these histological patterns which are typical for high-grade brain cancer. Numerical simulations of the population level dynamics are performed to investigate several model scenarios containing this and further effects.

Cell-Scale Degradation of Peritumoural Extracellular Matrix Fibre Network and Its Role Within Tissue-Scale Cancer Invasion

Local cancer invasion of tissue is a complex, multiscale process which plays an essential role in tumour progression. During the complex interaction between cancer cell population and the extracellular matrix (ECM), of key importance is the role played by both bulk two-scale dynamics of ECM fibres within collective movement of the tumour cells and the multiscale leading edge dynamics driven by proteolytic activity of the matrix-degrading enzymes (MDEs) that are secreted by the cancer cells. As these two multiscale subsystems share and contribute to the same tumour macro-dynamics, in this work we develop further the model introduced in Shuttleworth and Trucu (Bull Math Biol 81:2176–2219, 2019. 10.1007/s11538-019-00598-w) by exploring a new aspect of their interaction that occurs at the cell scale. Specifically, here we will focus on understanding the cell-scale cross talk between the micro-scale parts of these two multiscale subsystems which get to interact directly in the peritumoural region, with immediate consequences both for MDE micro-dynamics occurring at the leading edge of the tumour and for the cell-scale rearrangement of the naturally oriented ECM fibres in the peritumoural region, ultimately influencing the way tumour progresses in the surrounding tissue. To that end, we will propose a new modelling that captures the ECM fibres degradation not only at macro-scale in the bulk of the tumour but also explicitly in the micro-scale neighbourhood of the tumour interface as a consequence of the interactions with molecular fluxes of MDEs that exercise their spatial dynamics at the invasive edge of the tumour.

Lcn2-derived Circular RNA (hsa_circ_0088732) Inhibits Cell Apoptosis and Promotes EMT in Glioma via the miR-661/RAB3D Axis

Background: Glioma is the most common malignant tumor of the central nervous system, and often displays invasive growth. Recently, circular RNA (circRNA), which is a novel non-coding type of RNA, has been shown to play a vital role in glioma tumorigenesis. However, the functions and mechanism of lipocalin-2 (Lcn2)-derived circular RNA (hsa_circ_0088732) in glioma progression remain unclear.

Methods: We evaluated hsa_circ_0088732 expression by fluorescence in situ hybridization (FISH), Sanger sequencing, and PCR assays. Cell apoptosis was evaluated by flow cytometry and Hoechst 33258 staining. Transwell migration and invasion assays were performed to measure cell metastasis and viability. In addition, the target miRNA of hsa_circ_0088732 and the target gene of miR-661 were predicted by a bioinformatics analysis, and the interactions were verified by dual-luciferase reporter assays. RAB3D expression was analyzed by an immunochemistry assay, and E-cadherin, N-cadherin, and vimentin protein expression were examined by western blot assays. A mouse xenograft model was developed and used to analyze the effects of hsa_circ_0088732 on glioma growth in vivo.

Results: We verified that hsa_circ_0088732 is circular and highly expressed in glioma tissues. Knockdown of hsa_circ_0088732 induced glioma cell apoptosis and inhibited glioma cell migration, invasion, and epithelial-mesenchymal transition (EMT). We found that hsa_circ_0088732 negatively regulated miR-661 by targeting miR-661, and RAB3D was a target gene of miR-661. In addition, inhibition of miR-661 promoted glioma cell metastasis and suppressed cell apoptosis. Knockdown of RAB3D induced cell apoptosis and suppressed cell metastasis. Moreover, hsa_circ_0088732 accelerated glioma progression through its effects on the miR-661/RAB3D axis. Finally, results from a mouse xenograft model confirmed that knockdown of hsa_circ_0088732 induced miR-661 expression, resulting in suppression of RAB3D expression and inhibition of tumor growth in vivo.

Conclusion: We demonstrated that hsa_circ_0088732 facilitated glioma progression by sponging miR-661 to increase RAB3D expression. This study provides a theoretical basis for understanding the development and occurrence of glioma, as well as for the development of targeted drugs.

Exosomes derived from microRNA-199a-overexpressing mesenchymal stem cells inhibit glioma progression by down-regulating AGAP2

Accumulating evidence has implied that microRNAs (miRNAs) are implicated in glioma progression, and genetically engineered mesenchymal stem cells can help to inhibit tumor growth of glioma. Herein we hypothesized that miR-199a could be delivered by mesenchymal stem cells to glioma cells through exosomes and thus prevent the glioma development by down-regulating ArfGAP with GTPase domain, ankyrin repeat and PH domain 2 (AGAP2). The expression pattern of miR-199a and AGAP2 was characterized in glioma tissues and cells using RNA polymerase chain reaction quantification, immunohistochemical staining and Western blot assays. Mesenchymal stem cells transfected with miR-199a mimic or their derived exosomes were co-cultured with U251 cells. The biological behaviors as well as chemosensitivity of U251 cells were assessed to explore the involvement of miR-199a/AGAP2 in glioma. MiR-199a was poorly expressed in glioma tissue and cells while AGAP2 was highly expressed. Mesenchymal stem cells delivered miR-199a to the glioma cells via the exosomes, which resulted in the suppression of the proliferation, invasion and migration of glioma cells. Besides, mesenchymal stem cells over-expressing miR-199a enhanced the chemosensitivity to temozolomide and inhibited the tumor growth in vivo. Taken together, mesenchymal stem cell-derived exosomal miR-199a can inhibit the progression of glioma by down-regulating AGAP2.

Kinetic models with non-local sensing determining cell polarization and speed according to independent cues

Cells move by run and tumble, a kind of dynamics in which the cell alternates runs over straight lines and re-orientations. This erratic motion may be influenced by external factors, like chemicals, nutrients, the extra-cellular matrix, in the sense that the cell measures the external field and elaborates the signal eventually adapting its dynamics. We propose a kinetic transport equation implementing a velocity-jump process in which the transition probability takes into account a double bias, which acts, respectively, on the choice of the direction of motion and of the speed. The double bias depends on two different non-local sensing cues coming from the external environment. We analyze how the size of the cell and the way of sensing the environment with respect to the variation of the external fields affect the cell population dynamics by recovering an appropriate macroscopic limit and directly integrating the kinetic transport equation. A comparison between the solutions of the transport equation and of the proper macroscopic limit is also performed.

Resveratrol restores sensitivity of glioma cells to temozolamide through inhibiting the activation of Wnt signaling pathway

Malignant gliomas are aggressive primary neoplasms that originate in the glial cells of the brain or the spine with notable resistance to standard treatment options. We carried out the study with the aim to shed light on the sensitization of resveratrol to temozolomide (TMZ) against glioma through the Wnt signaling pathway. Initially, glioma cell lines with strong resistance to TMZ were selected by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Then, the glioma cells were subjected to resveratrol, TMZ, Wnt signaling pathway inhibitors, and activators. Cell survival rate and inhibitory concentration at half maximum value were detected by MTT, apoptosis by flow cytometry, and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling staining, in vitro proliferation by hanging drop method and β-catenin translocation into nuclei by TOP/FOP-FLASH assay. The expressions of the Wnt signaling pathway-related and apoptosis-related factors were determined by western blot analysis. Nude mice with glioma xenograft were established to detect tumorigenic ability. Glioma cell lines T98G and U138 which were highly resistant to TMZ were selected for subsequent experiments. Resveratrol increased the efficacy of TMZ by restraining cell proliferation, tumor growth, and promoting cell apoptosis in glioma cells. Resveratrol inhibited Wnt2 and β-catenin expressions yet elevated GSK-3β expression. Moreover, the Wnt signaling pathway participates in the sensitivity enhancing of resveratrol to TMZ via regulating O ⁶ -methylguanine-DNA methyltransferase (MGMT) expression. Resveratrol sensitized TMZ-induced glioma cell apoptosis by repressing the activation of the Wnt signaling pathway and downregulating MGMT expression, which may confer new thoughts to the chemotherapy of glioma.

MCL1 gene silencing promotes senescence and apoptosis of glioma cells via inhibition of the PI3K/Akt signaling pathway

Glioma is known to be the most prevalent primary brain tumor. In recent years, there has been evidence indicating myeloid cell leukemia-1 (MCL1) plays a role in brain glioblastoma. Therefore, the present study was conducted with aims of exploring the ability of MCL1 silencing to influence glioma cell senescence and apoptosis through the mediation of the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt) signaling pathway. Glioma and tumor-adjacent tissues were collected in order to detect the presence of higher levels of MCL1 protein expression. Next, the mRNA and protein expression of MCL1, PI3K, Akt, B cell lymphoma 2 (Bcl2), Bcl2-associated X (Bax), B lymphoma Mo-MLV insertion region 1 homolog (Bmi-1), and phosphatase and tensin homolog (PTEN) were determined. Cell counting kit-8 assay was applied to detect cell proliferation, β-galactosidase staining for cell senescence, and flow cytometry for cell cycle entry and apoptosis. Initially, the results revealed higher positive expression rate of MCL1 protein, increased mRNA and protein expression of MCL1, PI3K, Akt, Bmi-1, and Bcl-2 and decreased that of Bax and PTEN in human glioma tissues. The silencing of MCL1 resulted in a decrease in mRNA and protein expression of PI3K, Akt, Bmi-1, and Bcl-2 and an increase in Bax and PTEN expressions in glioma cells. Moreover, silencing of MCL1 also inhibited cell proliferation and cell cycle entry in glioma cells, and promoted glioma cell senescence and apoptosis. In conclusion, the aforementioned results collectively suggested that the silencing of MCL1 promotes senescence and apoptosis in glioma cells through inhibiting the PI3K/Akt signaling pathway. Thus, decreasing the expression of MCL1 might have therapeutic functions in glioma. © 2018 IUBMB Life, 71(1):81-92, 2019.

Towards patient-specific modeling of brain tumor growth and formation of secondary nodes guided by DTI-MRI

Previous studies to simulate brain tumor progression, often investigate either temporal changes in cancer cell density or the overall tissue-level growth of the tumor mass. Here, we developed a computational model to bridge these two approaches. The model incorporates the tumor biomechanical response at the tissue level and accounts for cellular events by modeling cancer cell proliferation, infiltration to surrounding tissues, and invasion to distant locations. Moreover, acquisition of high resolution human data from anatomical magnetic resonance imaging, diffusion tensor imaging and perfusion imaging was employed within the simulations towards a realistic and patient specific model. The model predicted the intratumoral mechanical stresses to range from 20 to 34 kPa, which caused an up to 4.5 mm displacement to the adjacent healthy tissue. Furthermore, the model predicted plausible cancer cell invasion patterns within the brain along the white matter fiber tracts. Finally, by varying the tumor vascular density and its invasive outer ring thickness, our model showed the potential of these parameters for guiding the timing (83–90 days) of cancer cell distant invasion as well as the number (0–2 sites) and location (temportal and/or parietal lobe) of the invasion sites.

In silico modeling for tumor growth visualization

BACKGROUND

Cancer is a complex disease. Fundamental cellular based studies as well as modeling provides insight into cancer biology and strategies to treatment of the disease. In silico models complement in vivo models. Research on tumor growth involves a plethora of models each emphasizing isolated aspects of benign and malignant neoplasms. Biologists and clinical scientists are often overwhelmed by the mathematical background knowledge necessary to grasp and to apply a model to their own research.

RESULTS

We aim to provide a comprehensive and expandable simulation tool to visualizing tumor growth. This novel Web-based application offers the advantage of a user-friendly graphical interface with several manipulable input variables to correlate different aspects of tumor growth. By refining model parameters we highlight the significance of heterogeneous intercellular interactions on tumor progression. Within this paper we present the implementation of the Cellular Potts Model graphically presented through Cytoscape.js within a Web application. The tool is available under the MIT license at https://github.com/davcem/cpm-cytoscape and http://styx.cgv.tugraz.at:8080/cpm-cytoscape/ .

CONCLUSION

In-silico methods overcome the lack of wet experimental possibilities and as dry method succeed in terms of reduction, refinement and replacement of animal experimentation, also known as the 3R principles. Our visualization approach to simulation allows for more flexible usage and easy extension to facilitate understanding and gain novel insight. We believe that biomedical research in general and research on tumor growth in particular will benefit from the systems biology perspective.