Autonomy and Non-autonomy of Angiogenic Cell Movements Revealed by Experiment-Driven Mathematical Modeling

Sugihara, Kei; Nishiyama, Koichi; Fukuhara, Shigetomo; Arima, Satoshi; Kobayashi, Ryo; Köhn‐Luque, Alvaro; Mochizuki, Naoki; Suda, Toshio; Ogawa, Hisao; Kurihara, Hiroki

doi:10.1016/j.celrep.2015.10.051

Cited by 30 publications

(46 citation statements)

References 48 publications

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“…Cell motility. In experiments [?, 82,83], observed endothelial cell motility is much higher than in our simulations. 303 Real cells move in 3D and can climb past each other but our simulations are 2D.…”

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confidence: 46%

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Notch signaling and taxis mechanims regulate early stage angiogenesis: A mathematical and computational model

Vega

Carretero

Travasso

et al. 2019

Preprint

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During angiogenesis, new blood vessels sprout and grow from existing ones. This process plays a crucial role in organ development and repair, in wound healing and in numerous pathological processes such as cancer progression or diabetes. We present here a mathematical model of early stage angiogenesis that permits to explore the relative importance of mechanical, chemical and cellular cues. Endothelial cells proliferate and move over an extracellular matrix by following external gradients of Vessel Endothelial Growth Factor, adhesion and stiffness, which are incorporated to a Cellular Potts model with a finite element description of elasticity. The dynamics of Notch signaling involving Delta-4 and Jagged-1 ligands determines tip cell selection and vessel branching. Through their production rates, competing Jagged-Notch and Delta-Notch dynamics determine the influence of lateral inhibition and lateral induction on the selection of cellular phenotypes, branching of blood vessels, anastomosis (fusion of blood vessels) and angiogenesis velocity. Anastomosis may be favored or impeded depending on the mechanical configuration of strain vectors in the ECM near tip cells. Numerical simulations demonstrate that increasing Jagged production results in pathological vasculatures with thinner and more abundant vessels, which can be compensated by augmenting the production of Delta ligands. Author SummaryAngiogenesis is the process by which new blood vessels grow from existing ones. This process plays a crucial role in 1 organ development, in wound healing and in numerous pathological processes such as cancer growth or in diabetes. 2Angiogenesis is a complex, multi-step and well regulated process where biochemistry and physics are intertwined: 3 with signaling in vessel cells being driven by both chemical and mechanical mechanisms that result in vascular cell 4 movement, deformation and proliferation. Mathematical models have the ability to bring together these mechanisms 5 in order to explore their relative relevance in vessel growth. In this work, we present a mathematical model of early 6 stage angiogenesis that is able to explore the role of biochemical signaling and tissue mechanics. We use this model to 7 unravel the regulating role of Jagged, Notch and Delta dynamics in vascular cells. These membrane proteins have an 8 important part in determining the leading cell in each neo-vascular sprout. Numerical simulations demonstrate that 9 increasing Jagged production results in pathological vasculatures with thinner and more abundant vessels, which can 10 be compensated by augmenting the production of Delta ligands. 101The section Mathematical Model describes the CPM coupled with the Delta-Notch-Jagged dynamics. In the 102 section Results and Discussion, we present the results of the simulation and how Jagged-1 determines sprouting 103 dynamics. Finally, in the last section we draw the conclusions of the manuscript. 104 Mathematical model 105 The mathematical model consists of a CPM in which the dynamics of the Notch signali...

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confidence: 46%

“…To obtain the equivalence between the number of MCTS and the time measured in 123 experiments, we measured the pixel size in Fig. 1H of Ref [82], which is 0.9 µm. According to Fig.…”

mentioning

confidence: 99%

Notch signaling and taxis mechanims regulate early stage angiogenesis: A mathematical and computational model

Vega

Carretero

Travasso

et al. 2019

Preprint

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“…Blood vessels in gliomas are not stable, being continuously formed, occluded and destroyed. Neovascularisation takes place by different angiogenic and vasculogenic processes induced by complex signalling mechanisms that are not well understood [11,63,64]. For simplicity, we assume that tumour blood vessels are created when pro-angiogenic factors prevail anti-angiogenic stimuli, i.e.…”

Section: Density Of Functional Tumour Vasculaturementioning

confidence: 99%

Why one-size-fits-all vaso-modulatory interventions fail to control glioma invasion: in silico insights

Alfonso

Köhn‐Luque

Stylianopoulos

et al. 2016

Sci Rep

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Gliomas are highly invasive brain tumours characterised by poor prognosis and limited response to therapy. There is an ongoing debate on the therapeutic potential of vaso-modulatory interventions against glioma invasion. Prominent vasculature-targeting therapies involve tumour blood vessel deterioration and normalisation. The former aims at tumour infarction and nutrient deprivation induced by blood vessel occlusion/collapse. In contrast, the therapeutic intention of normalising the abnormal tumour vasculature is to improve the efficacy of conventional treatment modalities. Although these strategies have shown therapeutic potential, it remains unclear why they both often fail to control glioma growth. To shed some light on this issue, we propose a mathematical model based on the migration/proliferation dichotomy of glioma cells in order to investigate why vaso-modulatory interventions have shown limited success in terms of tumour clearance. We found the existence of a critical cell proliferation/diffusion ratio that separates glioma responses to vaso-modulatory interventions into two distinct regimes. While for tumours, belonging to one regime, vascular modulations reduce the front speed and increase the infiltration width, for those in the other regime, the invasion speed increases and infiltration width decreases. We discuss how these in silico findings can be used to guide individualised vaso-modulatory approaches to improve treatment success rates.

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“…Its argument, E N i , represents the number of ECs in a cell's local neighbourhood (red-coloured cells in Fig 4). The functional form of the neighbourhood function reflects the experimental observation that cells do not move when they lose contact with their neighbours [8]. Similarly, ECs are unlikely to migrate into regions with high EC density.…”

Section: Individual Cell System (1)mentioning

confidence: 74%

“…Angiogenesis, the process by which new blood vessels are generated from a pre-existing vascular network, has been extensively investigated in recent years [1][2][3][4][5][6][7][8][9][10]. However, understanding of the complex behaviour of endothelial cells (ECs) during angiogenesis remains incomplete.…”

Section: Introductionmentioning

confidence: 99%

A multiscale model of complex endothelial cell dynamics in early angiogenesis

Stepanova

Byrne

Maini

et al. 2020

Preprint

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We introduce a hybrid two-dimensional multiscale model of angiogenesis, the process by which endothelial cells (ECs) migrate from a pre-existing vascular bed in response to local environmental cues and cell-cell interactions, to create a new vascular network. Recent experimental studies have highlighted a central role of cell rearrangements in the formation of angiogenic networks. Our model accounts for this phenomenon via the heterogeneous response of ECs to their microenvironment. These cell rearrangements, in turn, dynamically remodel the local environment. The model reproduces characteristic features of angiogenic sprouting that include branching, chemotactic sensitivity, the brush border effect, and cell mixing. These properties, rather than being hardwired into the model, emerge naturally from the gene expression patterns of individual cells. After calibrating and validating our model against experimental data, we use it to predict how the structure of the vascular network changes as the baseline gene expression levels of the VEGF-Delta-Notch pathway, and the composition of the extracellular environment, vary. In order to investigate the impact of cell rearrangements on the vascular network structure, we introduce the mixing measure, a scalar metric that quantifies cell mixing as the vascular network grows. We calculate the mixing measure for the simulated vascular networks generated by ECs of different lineages (wild type cells and mutant cells with impaired expression of a specific receptor). Our results show that the time evolution of the mixing measure is directly correlated to the generic features of the vascular branching pattern, thus, supporting the hypothesis that cell rearrangements play an essential role in sprouting angiogenesis. Furthermore, we predict that lower cell rearrangement leads to an imbalance between branching and sprout elongation. Since the computation of this statistic requires only individual cell trajectories, it can be computed for networks generated in biological experiments, making it a potential biomarker for pathological angiogenesis. Author summaryAngiogenesis, the process by which new blood vessels are formed by sprouting from the pre-existing vascular bed, plays a key role in both physiological and pathological processes, including tumour growth. The structure of a growing vascular network is determined by the coordinated behaviour of endothelial cells in response to various signalling cues. Recent experimental studies have highlighted the importance of cell rearrangements as a driver for sprout elongation. However, the functional role of this phenomenon remains unclear. We formulate a new multiscale model of angiogenesis which, by accounting explicitly for the complex dynamics of endothelial cells within growing angiogenic sprouts, is able to produce generic features of angiogenic structures (branching, chemotactic sensitivity, cell mixing, etc.) as emergent properties of its dynamics. We validate our model against experimental data and then use it to quantify the pheno...

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Autonomy and Non-autonomy of Angiogenic Cell Movements Revealed by Experiment-Driven Mathematical Modeling

Cited by 30 publications

References 48 publications

Notch signaling and taxis mechanims regulate early stage angiogenesis: A mathematical and computational model

Notch signaling and taxis mechanims regulate early stage angiogenesis: A mathematical and computational model

Why one-size-fits-all vaso-modulatory interventions fail to control glioma invasion: in silico insights

A multiscale model of complex endothelial cell dynamics in early angiogenesis

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