Endothelial cell capture of heparin-binding growth factors under flow

A global method for fast simulations of molecular dynamics in multiscale agent-based models of biological tissues

Agent-based models (ABMs) are a natural platform for capturing the multiple time and spatial scales in biological processes. However, these models are computationally expensive, especially when including molecular-level effects. The traditional approach to simulating this type of multiscale ABM is to solve a system of ordinary differential equations for the molecular events per cell. This significantly adds to the computational cost of simulations as the number of agents grows, which contributes to many ABMs being limited to around10 5 cells. We propose an approach that requires the same computational time independent of the number of agents. This speeds up the entire simulation by orders of magnitude, allowing for more thorough explorations of ABMs with even larger numbers of agents. We use two systems to show that the new method strongly agrees with the traditionally used approach. This computational strategy can be applied to a wide range of biological investigations.

A validated mathematical model of FGFR3-mediated tumor growth reveals pathways to harness the benefits of combination targeted therapy and immunotherapy in bladder cancer

Bladder cancer is a common malignancy with over 80,000 estimated new cases and nearly 18,000 deaths per year in the United States alone. Therapeutic options for metastatic bladder cancer had not evolved much for nearly four decades, until recently, when five immune checkpoint inhibitors were approved by the U.S. Food and Drug Administration (FDA). Despite the activity of these drugs in some patients, the objective response rate for each is less than 25%. At the same time, fibroblast growth factor receptors (FGFRs) have been attractive drug targets for a variety of cancers, and in 2019 the FDA approved the first therapy targeted against FGFR3 for bladder cancer. Given the excitement around these new receptor tyrosine kinase and immune checkpoint targeted strategies, and the challenges they each may face on their own, emerging data suggest that combining these treatment options could lead to improved therapeutic outcomes. In this paper, we develop a mathematical model for FGFR3-mediated tumor growth and use it to investigate the impact of the combined administration of a small molecule inhibitor of FGFR3 and a monoclonal antibody against the PD-1/PD-L1 immune checkpoint. The model is carefully calibrated and validated with experimental data before survival benefits, and dosing schedules are explored. Predictions of the model suggest that FGFR3 mutation reduces the effectiveness of anti-PD-L1 therapy, that there are regions of parameter space where each monotherapy can outperform the other, and that pretreatment with anti-PD-L1 therapy always results in greater tumor reduction even when anti-FGFR3 therapy is the more effective monotherapy.

ERK and Akt exhibit distinct signaling responses following stimulation by pro-angiogenic factors

Background

Angiogenesis plays an important role in the survival of tissues, as blood vessels provide oxygen and nutrients required by the resident cells. Thus, targeting angiogenesis is a prominent strategy in many different settings, including both tissue engineering and cancer treatment. However, not all of the approaches that modulate angiogenesis lead to successful outcomes. Angiogenesis-based therapies primarily target pro-angiogenic factors such as vascular endothelial growth factor-A (VEGF) or fibroblast growth factor (FGF) in isolation, and there is a limited understanding of how these promoters combine together to stimulate angiogenesis. Targeting one pathway could be insufficient, as alternative pathways may compensate, diminishing the overall effect of the treatment strategy.

Methods

To gain mechanistic insight and identify novel therapeutic strategies, we have developed a detailed mathematical model to quantitatively characterize the crosstalk of FGF and VEGF intracellular signaling. The model focuses on FGF- and VEGF-induced mitogen-activated protein kinase (MAPK) signaling to promote cell proliferation and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) pathway, which promotes cell survival and migration. We fit the model to published experimental datasets that measure phosphorylated extracellular regulated kinase (pERK) and Akt (pAkt) upon FGF or VEGF stimulation. We validate the model with separate sets of data.

Results

We apply the trained and validated mathematical model to characterize the dynamics of pERK and pAkt in response to the mono- and co-stimulation by FGF and VEGF. The model predicts that for certain ranges of ligand concentrations, the maximum pERK level is more responsive to changes in ligand concentration compared to the maximum pAkt level. Also, the combination of FGF and VEGF indicates a greater effect in increasing the maximum pERK compared to the summation of individual effects, which is not seen for maximum pAkt levels. In addition, our model identifies the influential species and kinetic parameters that specifically modulate the pERK and pAkt responses, which represent potential targets for angiogenesis-based therapies.

Conclusions

Overall, the model predicts the combination effects of FGF and VEGF stimulation on ERK and Akt quantitatively and provides a framework to mechanistically explain experimental results and guide experimental design. Thus, this model can be utilized to study the effects of pro- and anti-angiogenic therapies that particularly target ERK and/or Akt activation upon stimulation with FGF and VEGF.

Exploring the Extracellular Regulation of the Tumor Angiogenic Interaction Network Using a Systems Biology Model

Tumor angiogenesis is regulated by pro- and anti-angiogenic factors. Anti-angiogenic agents target the interconnected network of angiogenic factors to inhibit neovascularization, which subsequently impedes tumor growth. Due to the complexity of this network, optimizing anti-angiogenic cancer treatments requires detailed knowledge at a systems level. In this study, we constructed a tumor tissue-based model to better understand how the angiogenic network is regulated by opposing mediators at the extracellular level. We consider the network comprised of two pro-angiogenic factors: vascular endothelial growth factor (VEGF) and basic fibroblast growth factor (FGF2), and two anti-angiogenic factors: thrombospondin-1 (TSP1) and platelet factor 4 (PF4). The model's prediction of angiogenic factors' distribution in tumor tissue reveals the localization of different factors and indicates the angiogenic state of the tumor. We explored how the distributions are affected by the secretion of the pro- and anti-angiogenic factors, illustrating how the angiogenic network is regulated in the extracellular space. Interestingly, we identified a counterintuitive result that the secretion of the anti-angiogenic factor PF4 can enhance pro-angiogenic signaling by elevating the levels of the interstitial and surface-level pro-angiogenic species. This counterintuitive situation is pertinent to the clinical setting, such as the release of anti-angiogenic factors in platelet activation or the administration of exogenous PF4 for anti-angiogenic therapy. Our study provides mechanistic insights into this counterintuitive result and highlights the role of heparan sulfate proteoglycans in regulating the interactions between angiogenic factors. This work complements previous studies aimed at understanding the formation of angiogenic complexes in tumor tissue and helps in the development of anti-cancer strategies targeting angiogenesis.

Fibroblast Growth Factor-2 Binding to Heparan Sulfate Proteoglycans Varies with Shear Stress in Flow-Adapted Cells

Fibroblast growth factor 2 (FGF2), an important regulator of angiogenesis, binds to endothelial cell (EC) surface FGF receptors (FGFRs) and heparan sulfate proteoglycans (HSPGs). FGF2 binding kinetics have been predominantly studied in static culture; however, the endothelium is constantly exposed to flow which may affect FGF2 binding. We therefore used experimental and computational techniques to study how EC FGF2 binding changes in flow. ECs adapted to 24 h of flow demonstrated biphasic FGF2-HSPG binding, with FGF2-HSPG complexes increasing up to 20 dynes/cm2 shear stress and then decreasing at higher shear stresses. To understand how adaptive EC surface remodeling in response to shear stress may affect FGF2 binding to FGFR and HSPG, we implemented a computational model to predict the relative effects of flow-induced surface receptor changes. We then fit the computational model to the experimental data using relationships between HSPG availability and FGF2-HSPG dissociation and flow that were developed from a basement membrane study, as well as including HSPG production. These studies suggest that FGF2 binding kinetics are altered in flow-adapted ECs due to changes in cell surface receptor quantity, availability, and binding kinetics, which may affect cell growth factor response.

Mechanistic insight into activation of MAPK signaling by pro-angiogenic factors

Background

Angiogenesis is important in physiological and pathological conditions, as blood vessels provide nutrients and oxygen needed for tissue growth and survival. Therefore, targeting angiogenesis is a prominent strategy in both tissue engineering and cancer treatment. However, not all of the approaches to promote or inhibit angiogenesis lead to successful outcomes. Angiogenesis-based therapies primarily target pro-angiogenic factors such as vascular endothelial growth factor-A (VEGF) or fibroblast growth factor (FGF) in isolation. However, pre-clinical and clinical evidence shows these therapies often have limited effects. To improve therapeutic strategies, including targeting FGF and VEGF in combination, we need a quantitative understanding of the how the promoters combine to stimulate angiogenesis.

Results

In this study, we trained and validated a detailed mathematical model to quantitatively characterize the crosstalk of FGF and VEGF intracellular signaling. This signaling is initiated by FGF binding to the FGF receptor 1 (FGFR1) and heparan sulfate glycosaminoglycans (HSGAGs) or VEGF binding to VEGF receptor 2 (VEGFR2) to promote downstream signaling. The model focuses on FGF- and VEGF-induced mitogen-activated protein kinase (MAPK) signaling and phosphorylation of extracellular regulated kinase (ERK), which promotes cell proliferation. We apply the model to predict the dynamics of phosphorylated ERK (pERK) in response to the stimulation by FGF and VEGF individually and in combination. The model predicts that FGF and VEGF have differential effects on pERK. Additionally, since VEGFR2 upregulation has been observed in pathological conditions, we apply the model to investigate the effects of VEGFR2 density and trafficking parameters. The model predictions show that these parameters significantly influence the response to VEGF stimulation.

Conclusions

The model agrees with experimental data and is a framework to synthesize and quantitatively explain experimental studies. Ultimately, the model provides mechanistic insight into FGF and VEGF interactions needed to identify potential targets for pro- or anti-angiogenic therapies.

Electronic supplementary material

The online version of this article (10.1186/s12918-018-0668-5) contains supplementary material, which is available to authorized users.

Hollow fiber bioreactor technology for tissue engineering applications

Hollow fiber bioreactors are the focus of scientific research aiming to mimic physiological vascular networks and engineer organs and tissues in vitro. The reason for this lies in the interesting features of this bioreactor type, including excellent mass transport properties. Indeed, hollow fiber bioreactors allow limitations to be overcome in nutrient transport by diffusion, which is often an obstacle to engineer sizable constructs in vitro. This work reviews the existing literature relevant to hollow fiber bioreactors in organ and tissue engineering applications. To this purpose, we first classify the hollow fiber bioreactors into 2 categories: cylindrical and rectangular. For each category, we summarize their main applications both at the tissue and at the organ level, focusing on experimental models and computational studies as predictive tools for designing innovative, dynamic culture systems. Finally, we discuss future perspectives on hollow fiber bioreactors as in vitro models for tissue and organ engineering applications.

Systems biology of the microvasculature

The vascular network carries blood throughout the body, delivering oxygen to tissues and providing a pathway for communication between distant organs. The network is hierarchical and structured, but also dynamic, especially at the smaller scales. Remodeling of the microvasculature occurs in response to local changes in oxygen, gene expression, cell-cell communication, and chemical and mechanical stimuli from the microenvironment. These local changes occur as a result of physiological processes such as growth and exercise, as well as acute and chronic diseases including stroke, cancer, and diabetes, and pharmacological intervention. While the vasculature is an important therapeutic target in many diseases, drugs designed to inhibit vascular growth have achieved only limited success, and no drug has yet been approved to promote therapeutic vascular remodeling. This highlights the challenges involved in identifying appropriate therapeutic targets in a system as complex as the vasculature. Systems biology approaches provide a means to bridge current understanding of the vascular system, from detailed signaling dynamics measured in vitro and pre-clinical animal models of vascular disease, to a more complete picture of vascular regulation in vivo. This will translate to an improved ability to identify multi-component biomarkers for diagnosis, prognosis, and monitoring of therapy that are easy to measure in vivo, as well as better drug targets for specific disease states. In this review, we summarize systems biology approaches that have advanced our understanding of vascular function and dysfunction in vivo, with a focus on computational modeling.

Mechanistic and biological significance of DNA methyltransferase 1 upregulated by growth factors in human hepatocellular carcinoma

Dysregulation of growth factor signaling plays a pivotal role in controlling the malignancy phenotype and progression of hepatocellular carcinoma (HCC). However, the precise oncogenic mechanisms underlying transcription regulation of certain tumor suppressor genes (TSGs) by growth factors are poorly understood. In the present study, we report a novel insulin-like growth factor 1 (IGF1) pathway that mediates de novo DNA methylation and TSG (such as DLC1 and CHD5) silencing by upregulation of the DNA methyltransferase 1 (DNMT1) via an AKT/β-transducin repeat-containing protein (βTrCP)-mediated ubiquitin-proteasome pathway in HCC. Analysis of DNA methylation in CpG islands of target genes revealed high co-localization of DNMT1 and DNMT3B on the promoters of TSGs associated with enhanced CpG hypermethylation. Our results point to a novel epigenetic mechanism for growth factor-mediated repression of TSG transcription that involves DNA methylation.

A computational model of fibroblast growth factor-2 binding to endothelial cells under fluid flow

Fibroblast growth factor-2 (FGF2) is an angiogenic growth factor that binds to cell surface receptors (FGFR) and heparan sulfate proteoglycans (HSPG), as well as HSPG in the basement membrane. FGF2 plays a critical role in angiogenesis, yet clinical FGF2 trials demonstrated limited success perhaps due to inadequate understanding of FGF2 binding in physiological conditions. We developed a computational model of FGF2 binding to isolated (HSPG or FGFR) or combined (HSPG and FGFR) binding sites under physiological fluid flow and predicted the effects of FGF2 concentration, binding site density, fluid flow rate, and delivery mode (continuous vs. bolus) on FGF2 complex formation. The isolated binding site models showed increased binding with FGF2 and binding site density. However, in the triad model, increasing FGF2 concentration decreased triads (FGF2-HSPG-FGFR) and increased FGF2-HSPG complexes. Fluid flow decreased time to equilibrium and dissociation in isolated binding site models, yet flow effect in the triad model depended on binding site density. Similarly, FGF2 capture and complex stability in bolus delivery depended on bolus size, flow rate, association and dissociation rate constants, as well as binding site density. This model shows the integrated effects of FGF2 binding stoichiometry, fluid flow, and delivery mode, and enhances our understanding of FGF2 complex formation under physiological conditions.