Strategies of eradicating glioma cells: a multi-scale mathematical model with MiR-451-AMPK-mTOR control

Tumour growth: An approach to calibrate parameters of a multiphase porous media model based on in vitro observations of Neuroblastoma spheroid growth in a hydrogel microenvironment

To unravel processes that lead to the growth of solid tumours, it is necessary to link knowledge of cancer biology with the physical properties of the tumour and its interaction with the surrounding microenvironment. Our understanding of the underlying mechanisms is however still imprecise. We therefore developed computational physics-based models, which incorporate the interaction of the tumour with its surroundings based on the theory of porous media. However, the experimental validation of such models represents a challenge to its clinical use as a prognostic tool. This study combines a physics-based model with in vitro experiments based on microfluidic devices used to mimic a three-dimensional tumour microenvironment. By conducting a global sensitivity analysis, we identify the most influential input parameters and infer their posterior distribution based on Bayesian calibration. The resulting probability density is in agreement with the scattering of the experimental data and thus validates the proposed workflow. This study demonstrates the huge challenges associated with determining precise parameters with usually only limited data for such complex processes and models, but also demonstrates in general how to indirectly characterise the mechanical properties of neuroblastoma spheroids that cannot feasibly be measured experimentally.

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.

Role of senescent tumor cells in building a cytokine shield in the tumor microenvironment: mathematical modeling

Cellular senescence can induce dual effects (promotion or inhibition) on cancer progression. While immune cells naturally respond and migrate toward various chemotactic sources from the tumor mass, various factors including senescent tumor cells (STCs) in the tumor microenvironment may affect this chemotactic movement. In this work, we investigate the mutual interactions between the tumor cells and the immune cells that either inhibit or facilitate tumor growth by developing a mathematical model that consists of taxis-reaction-diffusion equations and receptor kinetics for the key players in the interaction network. We apply a mathematical model to a transwell Boyden chamber invasion assay used in the experiments to illustrate that STCs can play a pivotal role in negating immune attack through tight regulation of intra- and extra-cellular signaling molecules. In particular, we show that senescent tumor cells in cell cycle arrest can block intratumoral infiltration of CD8+ T cells by secreting a high level of CXCL12, which leads to significant reduction its receptors, CXCR4, on T cells, and thus impaired chemotaxis. The predictions of nonlinear responses to CXCL12 were in good agreement with experimental data. We tested several hypotheses on immune-tumor interactions under various biochemical conditions in the tumor microenvironment and developed new concepts for anti-tumor strategies targeting senescence induced immune impairment.

Optimal regulation of tumour-associated neutrophils in cancer progression

In a tumour microenvironment, tumour-associated neutrophils could display two opposing differential phenotypes: anti-tumour (N1) and pro-tumour (N2) effector cells. Converting N2 to N1 neutrophils provides innovative therapies for cancer treatment. In this study, a mathematical model for N1-N2 dynamics describing the cancer survival and immune inhibition in response to TGF-β and IFN-β is considered. The effects of exogenous intervention of TGF-β inhibitor and IFN-β are examined in order to enhance N1 recruitment to combat tumour progression. Our approach employs optimal control theory to determine drug infusion protocols that could minimize tumour volume with least administration cost possible. Four optimal control scenarios corresponding to different therapeutic strategies are explored, namely, TGF-β inhibitor control only, IFN-β control only, concomitant TGF-β inhibitor and IFN-β controls, and alternating TGF-β inhibitor and IFN-β controls. For each scheme, different initial conditions are varied to depict different pathophysiological condition of a cancer patient, leading to adaptive treatment schedule. TGF-β inhibitor and IFN-β drug dosages, total drug amount, infusion times and relative cost of drug administrations are obtained under various circumstances. The control strategies achieved could guide in designing individualized therapeutic protocols.

Atorvastatin-mediated rescue of cancer-related cognitive changes in combined anticancer therapies

Acute administration of trastuzumab (TZB) may induce various forms of cognitive impairment. These cancer-related cognitive changes (CRCC) are regulated by an adverse biological process involving cancer stem cells (CSCs) and IL-6. Recent studies have reported that atorvastatin (ATV) may change the dynamic of cognitive impairment in a combination (TZB+ATV) therapy. In this study, we investigate the mutual interactions between cancer stem cells and the tumor cells that facilitate cognitive impairment during long term TZB therapy by developing a mathematical model that involves IL-6 and the key apoptotic regulation. These include the densities of tumor cells and CSCs, and the concentrations of intracellular signaling molecules (NFκB, Bcl-2, BAX). We apply the mathematical model to a single or combination (ATV+TZB) therapy used in the experiments to demonstrate that the CSCs can enhance CRCC by secreting IL-6 and ATV may interfere the whole regulation. We show that the model can both reproduce the major experimental observation on onset and prevention of CRCC, and suggest several important predictions to guide future experiments with the goal of the development of new anti-tumor and anti-CRCC strategies. Moreover, using this model, we investigate the fundamental mechanism of onset of cognitive impairment in TZB-treated patients and the impact of alternating therapies on the anti-tumor efficacy and intracellular response to different treatment schedules.

A conventional drug, trastuzumab (TZB), was shown to be an effective weapon in killing cancer cells in brain. However, long term treatment of TZB increases the proportion of cancer stem cells (CSCs) in the tumour microenvironment (TME) and induces up-regulation of pro-tumoral molecules such as IL-6 in TME. These cancer cells then become more resistant to this chemotherapy through the IL-mediated up-regulation of NFκB and CSCs. More importantly, these changes in TME result in a serious side effect, cognitive impairment called cancer-related cognitive changes (CRCC). The detailed mechanism of CRCC is still poorly understood. However, cancer patients with chemotherapy-induced cognitive impairment can have long-term or delayed mental changes. In this study, we investigated the fundamental mechanism of CRCC in cancer patients based on experiments and a mathematical model that describes how tumor cells interact with CSCs in response to chemo drugs. In particular, we investigate how TZB-induced CSCs with modified IL-6 landscapes shape the cognitive functions in cancer patients. We showed that the combination treatment with another drug, atorvastatin (ATV), can abrogate the TZB-induced CRCC and enhance the survival probability of cancer patients by synergistic anti-tumor effect. We demonstrate that the cognitive functions and survival rates in cancer patients depend on the apoptotic signaling pathways via the critical communication and IL-6 landscapes of stimulated CTCs.

Neutrophil Extracellular Traps (NETs) in Cancer Invasion, Evasion and Metastasis

Simple Summary

This review focuses on the pro-tumorigenic action of neutrophil extracellular traps (NETs). NETs were found in various samples of human and animal tumors. The role of the NETs in tumor development increasingly includes cancer immunoediting and interactions between immune system and cancer cells. NETs awake dormant cancer cells, play a key regulatory role in the tumor microenvironment, and exacerbate tumor aggressiveness by enhancing cancer migration and invasion capacity. Furthermore, NETs induce the epithelial to mesenchymal transition in tumor cells. NET proteinases can also degrade the extracellular matrix, promoting cancer cell extravasation. Moreover, NETs can entrap circulating cancer cells and, in that way, facilitate metastasis. A better understanding of the crosstalk between cancer and NETs can help to devise novel approaches to the therapeutic interventions that block cancer evasion mechanisms and prevent metastatic spread.

Abstract

The present review highlights the complex interactions between cancer and neutrophil extracellular traps (NETs). Neutrophils constitute the first line of defense against foreign invaders using major effector mechanisms: phagocytosis, degranulation, and NETs formation. NETs are composed from decondensed nuclear or mitochondrial DNA decorated with proteases and various inflammatory mediators. Although NETs play a crucial role in defense against systemic infections, they also participate in non-infectious conditions, such as inflammation, autoimmune disorders, and cancer. Cancer cells recruit neutrophils (tumor-associated neutrophils, TANs), releasing NETs to the tumor microenvironment. NETs were found in various samples of human and animal tumors, such as pancreatic, breast, liver, and gastric cancers and around metastatic tumors. The role of the NETs in tumor development increasingly includes cancer immunoediting and interactions between the immune system and cancer cells. According to the accumulated evidence, NETs awake dormant cancer cells, causing tumor relapse, as well as its unconstrained growth and spread. NETs play a key regulatory role in the tumor microenvironment, such as the development of distant metastases through the secretion of proteases, i.e., matrix metalloproteinases and proinflammatory cytokines. NETs, furthermore, directly exacerbate tumor aggressiveness by enhancing cancer migration and invasion capacity. The collected evidence also states that through the induction of the high-mobility group box 1, NETs induce the epithelial to mesenchymal transition in tumor cells and, thereby, potentiate their invasiveness. NET proteinases can also degrade the extracellular matrix, promoting cancer cell extravasation. Moreover, NETs can entrap circulating cancer cells and, in that way, facilitate metastasis. NETs directly trigger tumor cell proliferation through their proteases or activating signals. This review focused on the pro-tumorigenic action of NETs, in spite of its potential to also exhibit an antitumor effect. NET components, such as myeloperoxidase or histones, have been shown to directly kill cancer cells. A better understanding of the crosstalk between cancer and NETs can help to devise novel approaches to the therapeutic interventions that block cancer evasion mechanisms and prevent metastatic spread. This review sought to provide the most recent knowledge on the crosstalk between NETs and cancer, and bring more profound ideas for future scientists exploring this field.

Mathematical model of STAT signalling pathways in cancer development and optimal control approaches

In various diseases, the STAT family display various cellular controls over various challenges faced by the immune system and cell death programs. In this study, we investigate how an intracellular signalling network (STAT1, STAT3, Bcl-2 and BAX) regulates important cellular states, either anti-apoptosis or apoptosis of cancer cells. We adapt a mathematical framework to illustrate how the signalling network can generate a bi-stability condition so that it will induce either apoptosis or anti-apoptosis status of tumour cells. Then, we use this model to develop several anti-tumour strategies including IFN-β infusion. The roles of JAK-STATs signalling in regulation of the cell death program in cancer cells and tumour growth are poorly understood. The mathematical model unveils the structure and functions of the intracellular signalling and cellular outcomes of the anti-tumour drugs in the presence of IFN-β and JAK stimuli. We identify the best injection order of IFN-β and DDP among many possible combinations, which may suggest better infusion strategies of multiple anti-cancer agents at clinics. We finally use an optimal control theory in order to maximize anti-tumour efficacy and minimize administrative costs. In particular, we minimize tumour volume and maximize the apoptotic potential by minimizing the Bcl-2 concentration and maximizing the BAX level while minimizing total injection amount of both IFN-β and JAK2 inhibitors (DDP).

Role of neutrophil extracellular traps in regulation of lung cancer invasion and metastasis: Structural insights from a computational model

Lung cancer is one of the leading causes of cancer-related deaths worldwide and is characterized by hijacking immune system for active growth and aggressive metastasis. Neutrophils, which in their original form should establish immune activities to the tumor as a first line of defense, are undermined by tumor cells to promote tumor invasion in several ways. In this study, we investigate the mutual interactions between the tumor cells and the neutrophils that facilitate tumor invasion by developing a mathematical model that involves taxis-reaction-diffusion equations for the critical components in the interaction. These include the densities of tumor and neutrophils, and the concentrations of signaling molecules and structure such as neutrophil extracellular traps (NETs). We apply the mathematical model to a Boyden invasion assay used in the experiments to demonstrate that the tumor-associated neutrophils can enhance tumor cell invasion by secreting the neutrophil elastase. We show that the model can both reproduce the major experimental observation on NET-mediated cancer invasion and make several important predictions to guide future experiments with the goal of the development of new anti-tumor strategies. Moreover, using this model, we investigate the fundamental mechanism of NET-mediated invasion of cancer cells and the impact of internal and external heterogeneity on the migration patterning of tumour cells and their response to different treatment schedules.

miR-451a suppression of IL-6R can inhibit proliferation and increase apoptosis through the JAK2/STAT3 pathway in multiple myeloma

The IL-6R/JAK2/STAT3 pathway mediated by interleukin-6 (IL-6) plays an important role in the occurrence and development of multiple myeloma (MM), which is associated with decreased microRNA-451a. However, the biological function of microRNA-451a in MM remains unclear. The bone marrow (BM) of patients with MM was sampled, and the plasma cells were enriched. BM miR-451a, IL-6 and IL-6R levels and Ki-67 expression intensity were evaluated using reverse transcription-quantitative PCR, ELISA and flow cytometry, respectively. U266 cell proliferation, viability and apoptosis were measured using BrdU, CCK-8 and Annexin V/propidium iodide assays, respectively. Total and phospo-(p-)JAK2 and p-STAT3 levels were measured by western blotting. Dual-luciferase reporter assays were performed to validate the predicted target binding sites. miR-451a expression was low in patients with MM and was associated with the Revised International Staging System (R-ISS) stage. IL-6 concentrations were significantly higher in patients with MM than in normal controls and were inversely associated with miR-451a levels (r=-0.96, P<0.0001). IL-6R levels were positively correlated with the R-ISS stage. miR-451a was downregulated, and IL-6R was upregulated in myeloma cell lines. Treatment with an miR-451a mimic inhibited viability and induced apoptosis in U266 cells. p-JAK2 and p-STAT3 levels were significantly lower in mimic-treated U266 cells than in control cells. Thus, miR-451a was shown to regulate myeloma cell proliferation and apoptosis via the IL-6R/JAK2/STAT3 pathway and may be used to predict patient prognosis.

Circulating miR-451a levels as a potential biomarker to predict the prognosis of patients with multiple myeloma

The natural course of multiple myeloma (MM) varies greatly between patients. The Revised MM International Staging System (R-ISS) identifies high-risk patients, but it is unsuitable for assessing minimal residual disease (MRD). Furthermore, the focal location of myeloma cells and clonal evolution often produce false negative results in flow cytometry. Extracellular microRNA (miRNA/miR) expression levels are stable in bodily fluids, and are retrievable and measurable from fresh or archived serum or plasma samples. Therefore, the present study aimed to investigate the clinical utility of circulating miRNA levels in patients with MM, particularly miR-451a, which is commonly downregulated in MM, and whether it could predict the prognosis and relapse of patients with MM. In total, 66 patients with MM, stratified using the R-ISS criteria, were recruited, while 10 healthy subjects (transplantation donors) were enrolled as controls. Reverse transcription-quantitative PCR was used to evaluate miR-451a expression in bone marrow (BM) and in the circulation. IL-6 levels were measured using ELISA, while western blotting was conducted to analyze the protein expression levels of the IL-6 receptor (IL-6R). During follow-up, MRD was assessed via multiparameter flow cytometry (MFC). miR-451a was identified to target IL-6R using a dual-luciferase reporter assay. Circulating miR-451a levels were low in patients with MM, and was found to be 0.39 times that of the control group (U=4.00; P<0.001). Among the 66 patients with MM, the median level of miR-451a was 0.73 and 0.41 times that of the control group in R-ISS stage I MM (15 patients) and R-ISS stage II stage (17 patients), respectively; patients with R-ISS stage III MM (34 patients) had the lowest level, at 0.24 times the value of the control group. Circulating miR-451a levels had a strong positive correlation with miR-451a levels in BM, but negatively correlated with IL-6 and IL-6R levels. After two courses of consolidation chemotherapy, 19 patients achieved complete remission, 10 of whom presented steady circulating miR-451a levels during follow-up; the other nine patients had an abrupt decrease in circulating miR-451a levels. The turning points in the trend appeared 4–8 weeks before positive results were obtained via MFC, and 4–16 weeks before clinical relapse. Moreover, miR-451a overexpression notably downregulated the expression of the IL-6R mRNA and protein. Collectively, circulating miR-451a levels potentially represent a novel biomarker to monitor MRD and predict relapse.

Collective invasion of glioma cells through OCT1 signalling and interaction with reactive astrocytes after surgery

Glioblastoma multiforme (GBM) is the most aggressive form of brain cancer with a short median survival time. GBM is characterized by the hallmarks of aggressive proliferation and cellular infiltration of normal brain tissue. miR-451 and its downstream molecules are known to play a pivotal role in regulation of the balance of proliferation and aggressive invasion in response to metabolic stress in the tumour microenvironment (TME). Surgery-induced transition in reactive astrocyte populations can play a significant role in tumour dynamics. In this work, we develop a multi-scale mathematical model of miR-451-LKB1-AMPK-OCT1-mTOR pathway signalling and individual cell dynamics of the tumour and reactive astrocytes after surgery. We show how the effects of fluctuating glucose on tumour cells need to be reprogrammed by taking into account the recent history of glucose variations and an AMPK/miR-451 reciprocal feedback loop. The model shows how variations in glucose availability significantly affect the activity of signalling molecules and, in turn, lead to critical cell migration. The model also predicts that microsurgery of a primary tumour induces phenotypical changes in reactive astrocytes and stem cell-like astrocytes promoting tumour cell proliferation and migration by Cxcl5. Finally, we investigated a new anti-tumour strategy by Cxcl5-targeting drugs. This article is part of the theme issue 'Multi-scale analysis and modelling of collective migration in biological systems'.

ADP is the dominant controller of AMP-activated protein kinase activity dynamics in skeletal muscle during exercise

Exercise training elicits profound metabolic adaptations in skeletal muscle cells. A key molecule in coordinating these adaptations is AMP-activated protein kinase (AMPK), whose activity increases in response to cellular energy demand. AMPK activity dynamics are primarily controlled by the adenine nucleotides ADP and AMP, but how each contributes to its control in skeletal muscle during exercise is unclear. We developed and validated a mathematical model of AMPK signaling dynamics, and then applied global parameter sensitivity analyses with data-informed constraints to predict that AMPK activity dynamics are determined principally by ADP and not AMP. We then used the model to predict the effects of two additional direct-binding activators of AMPK, ZMP and Compound 991, further validating the model and demonstrating its applicability to understanding AMPK pharmacology. The relative effects of direct-binding activators can be understood in terms of four properties, namely their concentrations, binding affinities for AMPK, abilities to enhance AMPK phosphorylation, and the magnitudes of their allosteric activation of AMPK. Despite AMP's favorable values in three of these four properties, ADP is the dominant controller of AMPK activity dynamics in skeletal muscle during exercise by virtue of its higher concentration compared to that of AMP.

Dynamic modeling of signal transduction by mTOR complexes in cancer

Signal integration has a crucial role in the cell fate decision and dysregulation of the cellular signaling pathways is a primary characteristic of cancer. As a signal integrator, mTOR shows a complex dynamical behavior which determines the cell fate at different cellular processes levels, including cell cycle progression, cell survival, cell death, metabolic reprogramming, and aging. The dynamics of the complex responses to rapamycin in cancer cells have been attributed to its differential time-dependent inhibitory effects on mTORC1 and mTORC2, the two main complexes of mTOR. Two explanations were previously provided for this phenomenon: 1-Rapamycin does not inhibit mTORC2 directly, whereas it prevents mTORC2 formation by sequestering free mTOR protein (Le Chatelier's principle). 2-Components like Phosphatidic Acid (PA) further stabilize mTORC2 compared with mTORC1. To understand the mechanism by which rapamycin differentially inhibits the mTOR complexes in the cancer cells, we present a mathematical model of rapamycin mode of action based on the first explanation, i.e., Le Chatelier's principle. Translating the interactions among components of mTORC1 and mTORC2 into a mathematical model revealed the dynamics of rapamycin action in different doses and time-intervals of rapamycin treatment. This model shows that rapamycin has stronger effects on mTORC1 compared with mTORC2, simply due to its direct interaction with free mTOR and mTORC1, but not mTORC2, without the need to consider other components that might further stabilize mTORC2. Based on our results, even when mTORC2 is less stable compared with mTORC1, it can be less inhibited by rapamycin.

Hybrid modeling frameworks of tumor development and treatment

Tumors are complex multicellular heterogeneous systems comprised of components that interact with and modify one another. Tumor development depends on multiple factors: intrinsic, such as genetic mutations, altered signaling pathways, or variable receptor expression; and extrinsic, such as differences in nutrient supply, crosstalk with stromal or immune cells, or variable composition of the surrounding extracellular matrix. Tumors are also characterized by high cellular heterogeneity and dynamically changing tumor microenvironments. The complexity increases when this multiscale, multicomponent system is perturbed by anticancer treatments. Modeling such complex systems and predicting how tumors will respond to therapies require mathematical models that can handle various types of information and combine diverse theoretical methods on multiple temporal and spatial scales, that is, hybrid models. In this update, we discuss the progress that has been achieved during the last 10 years in the area of the hybrid modeling of tumors. The classical definition of hybrid models refers to the coupling of discrete descriptions of cells with continuous descriptions of microenvironmental factors. To reflect on the direction that the modeling field has taken, we propose extending the definition of hybrid models to include of coupling two or more different mathematical frameworks. Thus, in addition to discussing recent advances in discrete/continuous modeling, we also discuss how these two mathematical descriptions can be coupled with theoretical frameworks of optimal control, optimization, fluid dynamics, game theory, and machine learning. All these methods will be illustrated with applications to tumor development and various anticancer treatments.

This article is characterized under:

Analytical and Computational Methods > Computational Methods

Translational, Genomic, and Systems Medicine > Therapeutic Methods

Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models

Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues

A main goal of mathematical and computational oncology is to develop quantitative tools to determine the most effective therapies for each individual patient. This involves predicting the right drug to be administered at the right time and at the right dose. Such an approach is known as precision medicine. Mathematical modelling can play an invaluable role in the development of such therapeutic strategies, since it allows for relatively fast, efficient and inexpensive simulations of a large number of treatment schedules in order to find the most effective. This review is a survey of mathematical models that explicitly take into account the spatial architecture of three-dimensional tumours and address tumour development, progression and response to treatments. In particular, we discuss models of epithelial acini, multicellular spheroids, normal and tumour spheroids and organoids, and multi-component tissues. Our intent is to showcase how these in silico models can be applied to patient-specific data to assess which therapeutic strategies will be the most efficient. We also present the concept of virtual clinical trials that integrate standard-of-care patient data, medical imaging, organ-on-chip experiments and computational models to determine personalized medical treatment strategies.

Strategies in regulating glioblastoma signaling pathways and anti-invasion therapy

Glioblastoma multiforme is one of the most invasive type of glial tumors, which rapidly grows and commonly spreads into nearby brain tissue. It is a devastating brain cancer that often results in death within approximately 12 to 15 months after diagnosis. In this work, optimal control theory was applied to regulate intracellular signaling pathways of miR-451–AMPK–mTOR–cell cycle dynamics via glucose and drug intravenous administration infusions. Glucose level is controlled to activate miR-451 in the up-stream pathway of the model. A potential drug blocking the inhibitory pathway of mTOR by AMPK complex is incorporated to explore regulation of the down-stream pathway to the cell cycle. Both miR-451 and mTOR levels are up-regulated inducing cell proliferation and reducing invasion in the neighboring tissues. Concomitant and alternating glucose and drug infusions are explored under various circumstances to predict best clinical outcomes with least administration costs.

MicroRNA-451 Inhibits Migration of Glioblastoma while Making It More Susceptible to Conventional Therapy

Malignant glioblastoma (GBM, glioma) is the most common and aggressive primary adult brain tumor. The prognosis of GBM patients remains poor, despite surgery, radiation and chemotherapy. The major obstacles for successful remedy are invasiveness and therapy resistance of GBM cells. Invasive glioma cells leave primary tumor core and infiltrate surrounding normal brain leading to inevitable recurrence, even after surgical resection, radiation and chemotherapy. Therapy resistance allowing for selection of more aggressive and resistant sub-populations including GBM stem-like cells (GSCs) upon treatment is another serious impediment to successful treatment. Through their regulation of multiple genes, microRNAs can orchestrate complex programs of gene expression and act as master regulators of cellular processes. MicroRNA-based therapeutics could thus impact broad cellular programs, leading to inhibition of invasion and sensitization to radio/chemotherapy. Our data show that miR-451 attenuates glioma cell migration in vitro and invasion in vivo. In addition, we have found that miR-451 sensitizes glioma cells to conventional chemo- and radio-therapy. Our data also show that miR-451 is regulated in vivo by AMPK pathway and that AMPK/miR-451 loop has the ability to switch between proliferative and migratory pattern of glioma cells behavior. We therefore postulate that AMPK/miR-451 negative reciprocal feedback loop allows GBM cells/GSCs to adapt to tumor “ecosystem” by metabolic and behavioral flexibility, and that disruption of such a loop reduces invasiveness and diminishes therapy resistance.

Synergistic Effects of Bortezomib-OV Therapy and Anti-Invasive Strategies in Glioblastoma: A Mathematical Model

It is well-known that the tumor microenvironment (TME) plays an important role in the regulation of tumor growth and the efficacy of anti-tumor therapies. Recent studies have demonstrated the potential of combination therapies, using oncolytic viruses (OVs) in conjunction with proteosome inhibitors for the treatment of glioblastoma, but the role of the TME in such therapies has not been studied. In this paper, we develop a mathematical model for combination therapies based on the proteosome inhibitor bortezomib and the oncolytic herpes simplex virus (oHSV), with the goal of understanding their roles in bortezomib-induced endoplasmic reticulum (ER) stress, and how the balance between apoptosis and necroptosis is affected by the treatment protocol. We show that the TME plays a significant role in anti-tumor efficacy in OV combination therapy, and illustrate the effect of different spatial patterns of OV injection. The results illustrate a possible phenotypic switch within tumor populations in a given microenvironment, and suggest new anti-invasion therapies.

Role of tumor-associated neutrophils in regulation of tumor growth in lung cancer development: A mathematical model

Neutrophils display rapid and potent innate immune responses in various diseases. Tumor-associated neutrophils (TANs) however either induce or overcome immunosuppressive functions of the tumor microenvironment through complex tumor-stroma crosstalk. We developed a mathematical model to address the question of how phenotypic alterations between tumor suppressive N1 TANS, and tumor promoting N2 TANs affect nonlinear tumor growth in a complex tumor microenvironment. The model provides a visual display of the complex behavior of populations of TANs and tumors in response to various TGF-β and IFN-β stimuli. In addition, the effect of anti-tumor drug administration is incorporated in the model in an effort to achieve optimal anti-tumor efficacy. The simulation results from the mathematical model were in good agreement with experimental data. We found that the N2-to-N1 ratio (N21R) index is positively correlated with aggressive tumor growth, suggesting that this may be a good prognostic factor. We also found that the antitumor efficacy increases when the relative ratio (Dap) of delayed apoptotic cell death of N1 and N2 TANs is either very small or relatively large, providing a basis for therapeutically targeting prometastatic N2 TANs.

Mechanistic Computational Models of MicroRNA-Mediated Signaling Networks in Human Diseases

MicroRNAs (miRs) are endogenous non-coding RNA molecules that play important roles in human health and disease by regulating gene expression and cellular processes. In recent years, with the increasing scientific knowledge and new discovery of miRs and their gene targets, as well as the plentiful experimental evidence that shows dysregulation of miRs in a wide variety of human diseases, the computational modeling approach has emerged as an effective tool to help researchers identify novel functional associations between differential miR expression and diseases, dissect the phenotypic expression patterns of miRs in gene regulatory networks, and elucidate the critical roles of miRs in the modulation of disease pathways from mechanistic and quantitative perspectives. Here we will review the recent systems biology studies that employed different kinetic modeling techniques to provide mechanistic insights relating to the regulatory function and therapeutic potential of miRs in human diseases. Some of the key computational aspects to be discussed in detail in this review include (i) models of miR-mediated network motifs in the regulation of gene expression, (ii) models of miR biogenesis and miR–target interactions, and (iii) the incorporation of such models into complex disease pathways in order to generate mechanistic, molecular- and systems-level understanding of pathophysiology. Other related bioinformatics tools such as computational platforms that predict miR-disease associations will also be discussed, and we will provide perspectives on the challenges and opportunities in the future development and translational application of data-driven systems biology models that involve miRs and their regulatory pathways in human diseases.

Role of extracellular matrix and microenvironment in regulation of tumor growth and LAR-mediated invasion in glioblastoma

The cellular dispersion and therapeutic control of glioblastoma, the most aggressive type of primary brain cancer, depends critically on the migration patterns after surgery and intracellular responses of the individual cancer cells in response to external biochemical cues in the microenvironment. Recent studies have shown that miR-451 regulates downstream molecules including AMPK/CAB39/MARK and mTOR to determine the balance between rapid proliferation and invasion in response to metabolic stress in the harsh tumor microenvironment. Surgical removal of the main tumor is inevitably followed by recurrence of the tumor due to inaccessibility of dispersed tumor cells in normal brain tissue. In order to address this complex process of cell proliferation and invasion and its response to conventional treatment, we propose a mathematical model that analyzes the intracellular dynamics of the miR-451-AMPK- mTOR-cell cycle signaling pathway within a cell. The model identifies a key mechanism underlying the molecular switches between proliferative phase and migratory phase in response to metabolic stress in response to fluctuating glucose levels. We show how up- or down-regulation of components in these pathways affects the key cellular decision to infiltrate or proliferate in a complex microenvironment in the absence and presence of time delays and stochastic noise. Glycosylated chondroitin sulfate proteoglycans (CSPGs), a major component of the extracellular matrix (ECM) in the brain, contribute to the physical structure of the local brain microenvironment but also induce or inhibit glioma invasion by regulating the dynamics of the CSPG receptor LAR as well as the spatiotemporal activation status of resident astrocytes and tumor-associated microglia. Using a multi-scale mathematical model, we investigate a CSPG-induced switch between invasive and non-invasive tumors through the coordination of ECM-cell adhesion and dynamic changes in stromal cells. We show that the CSPG-rich microenvironment is associated with non-invasive tumor lesions through LAR-CSGAG binding while the absence of glycosylated CSPGs induce the critical glioma invasion. We illustrate how high molecular weight CSPGs can regulate the exodus of local reactive astrocytes from the main tumor lesion, leading to encapsulation of non-invasive tumor and inhibition of tumor invasion. These different CSPG conditions also change the spatial profiles of ramified and activated microglia. The complex distribution of CSPGs in the tumor microenvironment can determine the nonlinear invasion behaviors of glioma cells, which suggests the need for careful therapeutic strategies.

Potential Role of miRNAs as Theranostic Biomarkers of Epilepsy

Epilepsy includes a group of disorders of the brain characterized by an enduring predisposition to generate epileptic seizures. Although familial epilepsy has a genetic component and heritability, the etiology of the majority of non-familial epilepsies has no known associated genetic mutations. In epilepsy, recent epigenetic profiles have highlighted a possible role of microRNAs in its pathophysiology. In particular, molecular profiling identifies a significant number of microRNAs (miRNAs) altered in epileptic hippocampus of both animal models and human tissues. In this review, analyzing molecular profiles of different animal models of epilepsy, we identified a group of 20 miRNAs commonly altered in different epilepsy-animal models. As emerging evidences highlighted the poor overlap between signatures of animal model tissues and human samples, we focused our analysis on miRNAs, circulating in human biofluids, with a principal role in epilepsy hallmarks, and we identified a group of 8 diagnostic circulating miRNAs. We discussed the functional role of these 8 miRNAs in the epilepsy hallmarks. A few of them have also been proposed as therapeutic molecules for epilepsy treatment, revealing a great potential for miRNAs as theranostic molecules in epilepsy.

AMPK: Potential Therapeutic Target for Ischemic Stroke

5'-AMP-activated protein kinase (AMPK), a member of the serine/threonine (Ser/Thr) kinase group, is universally distributed in various cells and organs. It is a significant endogenous defensive molecule that responds to harmful stimuli, such as cerebral ischemia, cerebral hemorrhage, and, neurodegenerative diseases (NDD). Cerebral ischemia, which results from insufficient blood flow or the blockage of blood vessels, is a major cause of ischemic stroke. Ischemic stroke has received increased attention due to its '3H' effects, namely high mortality, high morbidity, and high disability. Numerous studies have revealed that activation of AMPK plays a protective role in the brain, whereas its action in ischemic stroke remains elusive and poorly understood. Based on existing evidence, we introduce the basic structure, upstream regulators, and biological roles of AMPK. Second, we analyze the relationship between AMPK and the neurovascular unit (NVU). Third, the actions of AMPK in different phases of ischemia and current therapeutic methods are discussed. Finally, we evaluate existing controversy and provide a detailed analysis, followed by ethical issues, potential directions, and further prospects of AMPK. The information complied here may aid in clinical and basic research of AMPK, which may be a potent drug candidate for ischemic stroke treatment in the future.

A simple and accurate rule-based modeling framework for simulation of autocrine/paracrine stimulation of glioblastoma cell motility and proliferation by L1CAM in 2-D culture

Background

Glioblastoma multiforme (GBM) is a devastating brain cancer for which there is no known cure. Its malignancy is due to rapid cell division along with high motility and invasiveness of cells into the brain tissue. Simple 2-dimensional laboratory assays (e.g., a scratch assay) commonly are used to measure the effects of various experimental perturbations, such as treatment with chemical inhibitors. Several mathematical models have been developed to aid the understanding of the motile behavior and proliferation of GBM cells. However, many are mathematically complicated, look at multiple interdependent phenomena, and/or use modeling software not freely available to the research community. These attributes make the adoption of models and simulations of even simple 2-dimensional cell behavior an uncommon practice by cancer cell biologists.

Results

Herein, we developed an accurate, yet simple, rule-based modeling framework to describe the in vitro behavior of GBM cells that are stimulated by the L1CAM protein using freely available NetLogo software. In our model L1CAM is released by cells to act through two cell surface receptors and a point of signaling convergence to increase cell motility and proliferation. A simple graphical interface is provided so that changes can be made easily to several parameters controlling cell behavior, and behavior of the cells is viewed both pictorially and with dedicated graphs. We fully describe the hierarchical rule-based modeling framework, show simulation results under several settings, describe the accuracy compared to experimental data, and discuss the potential usefulness for predicting future experimental outcomes and for use as a teaching tool for cell biology students.

Conclusions

It is concluded that this simple modeling framework and its simulations accurately reflect much of the GBM cell motility behavior observed experimentally in vitro in the laboratory. Our framework can be modified easily to suit the needs of investigators interested in other similar intrinsic or extrinsic stimuli that influence cancer or other cell behavior. This modeling framework of a commonly used experimental motility assay (scratch assay) should be useful to both researchers of cell motility and students in a cell biology teaching laboratory.

Electronic supplementary material

The online version of this article (10.1186/s12918-017-0516-z) contains supplementary material, which is available to authorized users.

Large-scale genome-wide screening of circulating microRNAs in clear cell renal cell carcinoma reveals specific signatures in late-stage disease

Circulating miRNAs have shown great promises as noninvasive diagnostic and predictive biomarkers in several solid tumors. While the miRNA profiles of renal tumors have been extensively explored, knowledge of their circulating counterparts is limited. Our study aimed to provide a large-scale genome-wide profiling of plasma circulating miRNA in clear-cell renal cell carcinoma (ccRCC). Plasma samples from 94 ccRCC cases and 100 controls were screened for 754 circulating micro-RNAs (miRNA) by TaqMan arrays. Analyses including known risk factors for renal cancer-namely, age, sex, hypertension, obesity, diabetes, tobacco smoking and alcohol consumption-highlighted that circulating miRNA profiles were tightly correlated with the stage of the disease. Advanced tumors, characterized as stage III and IV, were associated with specific miRNA signatures that significantly differ from both controls and earlier stage ccRCC cases. Molecular pathway enrichment analyses of their gene targets showed high similarities with alterations observed in renal tumors. Plasma circulating levels of miR-150 were significantly associated with RCC-specific survival and could marginally improve the predictive accuracy of clinical parameters in our series, including age at diagnosis, sex and conventional staging. In summary, our results suggest that circulating miRNAs may provide insights into renal cell carcinoma progression.

The role of myosin II in glioma invasion: A mathematical model

Gliomas are malignant tumors that are commonly observed in primary brain cancer. Glioma cells migrate through a dense network of normal cells in microenvironment and spread long distances within brain. In this paper we present a two-dimensional multiscale model in which a glioma cell is surrounded by normal cells and its migration is controlled by cell-mechanical components in the microenvironment via the regulation of myosin II in response to chemoattractants. Our simulation results show that the myosin II plays a key role in the deformation of the cell nucleus as the glioma cell passes through the narrow intercellular space smaller than its nuclear diameter. We also demonstrate that the coordination of biochemical and mechanical components within the cell enables a glioma cell to take the mode of amoeboid migration. This study sheds lights on the understanding of glioma infiltration through the narrow intercellular spaces and may provide a potential approach for the development of anti-invasion strategies via the injection of chemoattractants for localization.

Quantitative analysis of the proliferative-to-invasive transition of hypoxic glioma cells

Impact of the proliferative-to-invasive transformation of glioma cells on the global growth kinetics of the tumor.

The Role of the Tumor Microenvironment in Glioblastoma: A Mathematical Model

Glioblastoma multiforme is one of the deadliest human cancers and is characterized by tumor cells that hijack immune system cells in a deadly symbiotic relationship. Microglia and glioma infiltrating macrophages, which in principle should mount an immune response to the tumor, are subverted by tumor cells to facilitate growth in several ways. In this study, we seek to understand the interactions between the tumor cells and the microglia that enhance tumor growth, and for this purpose, we develop a mathematical and computational model that involves reaction-diffusion equations for the important components in the interaction. These include the densities of tumor and microglial cells, and the concentrations of growth factors and other signaling molecules. We apply this model to a transwell assay used in the laboratory to demonstrate that microglia can stimulate tumor cell invasion by secreting the growth factor TGF- β. We show that the model can both replicate the major components of the experimental findings and make new predictions to guide future experiments aimed at the development of new therapeutic approaches. Sensitivity analysis is used to identify the most important parameters as an aid to future experimental work. This study is the first step in a program that involves development of detailed 3-D models of the mechanical and biochemical interactions between a glioblastoma and the tumor microenvironment.

Multi-scale Modeling in Clinical Oncology: Opportunities and Barriers to Success

Hierarchical processes spanning several orders of magnitude of both space and time underlie nearly all cancers. Multi-scale statistical, mathematical, and computational modeling methods are central to designing, implementing and assessing treatment strategies that account for these hierarchies. The basic science underlying these modeling efforts is maturing into a new discipline that is close to influencing and facilitating clinical successes. The purpose of this review is to capture the state-of-the-art as well as the key barriers to success for multi-scale modeling in clinical oncology. We begin with a summary of the long-envisioned promise of multi-scale modeling in clinical oncology, including the synthesis of disparate data types into models that reveal underlying mechanisms and allow for experimental testing of hypotheses. We then evaluate the mathematical techniques employed most widely and present several examples illustrating their application as well as the current gap between pre-clinical and clinical applications. We conclude with a discussion of what we view to be the key challenges and opportunities for multi-scale modeling in clinical oncology.

Metformin and Ara-a Effectively Suppress Brain Cancer by Targeting Cancer Stem/Progenitor Cells

Background: Gliomas and neuroblastomas pose a great health burden worldwide with a poor and moderate prognosis, respectively. Many studies have tried to find effective treatments for these primary malignant brain tumors. Of interest, the AMP-activated protein kinase (AMPK) pathway was found to be associated with tumorigenesis and tumor survival, leading to many studies on AMPK drugs, especially Metformin, and their potential role as anti-cancer treatments. Cancer stem cells (CSCs) are a small population of slowly-dividing, treatment-resistant, undifferentiated cancer cells that are being discovered in a multitude of cancers. They are thought to be responsible for replenishing the tumor with highly proliferative cells and increasing the risk of recurrence.

Methods: Metformin and 9-β-d-Arabinofuranosyl Adenine (Ara-a) were used to study the role of the AMPK pathway in vitro on U251 (glioblastoma) and SH-SY5Y (neuroblastoma) cell lines.

Results: We found that both drugs are able to decrease the survival of U251 and SH-SY5Y cell lines in a 2D as well as a 3D culture model. Metformin and Ara-a significantly decreased the invasive ability of these cancer cell lines. Treatment with these drugs decreased the sphere-forming units (SFU) of U251 cells, with Ara-a being more efficient, signifying the extinction of the CSC population. However, if treatment is withdrawn before all SFUs are extinguished, the CSCs regain some of their sphere-forming capabilities in the case of Metformin but not Ara-a treatment.

Conclusion: Metformin and Ara-a have proved to be effective in the treatment of glioblastomas and neuroblastomas, in vitro, by targeting their cancer stem/progenitor cell population, which prevents recurrence.

Computational Model of MicroRNA Control of HIF-VEGF Pathway: Insights into the Pathophysiology of Ischemic Vascular Disease and Cancer

HRMs (hypoxia-responsive miRNAs) are a specific group of microRNAs that are regulated by hypoxia. Recent studies revealed that several HRMs including let-7 family miRNAs were highly induced in response to HIF (hypoxia-inducible factor) stabilization in hypoxia, and they potently participated in angiogenesis by targeting AGO1 (argonaute 1) and upregulating VEGF (vascular endothelial growth factor). Here we constructed a novel computational model of microRNA control of HIF-VEGF pathway in endothelial cells to quantitatively investigate the role of HRMs in modulating the cellular adaptation to hypoxia. The model parameters were optimized and the simulations based on these parameters were validated against several published in vitro experimental data. To advance the mechanistic understanding of oxygen sensing in hypoxia, we demonstrated that the rate of HIF-1α nuclear import substantially influences its stabilization and the formation of HIF-1 transcription factor complex. We described the biological feedback loops involving let-7 and AGO1 in which the impact of external perturbations were minimized; as a pair of master regulators when low oxygen tension was sensed, they coordinated the critical process of VEGF desuppression in a controlled manner. Prompted by the model-motivated discoveries, we proposed and assessed novel pathway-specific therapeutics that modulate angiogenesis by adjusting VEGF synthesis in tumor and ischemic cardiovascular disease. Through simulations that capture the complex interactions between miRNAs and miRNA-processing molecules, this model explores an innovative perspective about the distinctive yet integrated roles of different miRNAs in angiogenesis, and it will help future research to elucidate the dysregulated miRNA profiles found in cancer and various cardiovascular diseases.

Cells living in a hypoxic environment secrete signals to stimulate new blood vessel growth, a process termed angiogenesis, to acquire more oxygen and nutrients. Hypoxia-inducible factor 1 (HIF-1) accumulates in hypoxia and expedites the release of pro-angiogenic cytokines such as vascular endothelial growth factor (VEGF), a prime inducer of angiogenesis. The intermediate signaling events connecting HIF-1 and VEGF are tightly controlled by microRNAs (miRs), which are endogenous, non-coding RNA molecules and powerful regulators in cancer and cardiovascular disease. Given the importance of angiogenesis in tumor development and post-ischemia reperfusion, it holds great basic research and therapeutic value to investigate how miRs modulate intracellular VEGF synthesis to control angiogenesis in hypoxia. We present a computational model that details the interactions between miRs and other key molecules which make up different hierarchies in HIF-miR-VEGF pathway. Based on simulation analysis, new potential therapies are introduced and tested in silico, from which the strategies that most effectively reduce VEGF synthesis in cancer, or enhance VEGF release in ischemic vascular disease are identified. We conclude that in hypoxia different miRs work consonantly to fine-tune the cellular adaptations; when a master miR alters its expression, dynamics of other miRs vary accordingly which together contribute to aberrant RNA/protein profiles observed in the pathophysiology of multiple diseases.