scholarly journals An Agent-Based Model of Combination Oncolytic Viral Therapy and Anti-PD-1 Immunotherapy Reveals the Importance of Spatial Location When Treating Glioblastoma

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5314
Author(s):  
Kathleen M. Storey ◽  
Trachette L. Jackson

Oncolytic viral therapies and immunotherapies are of growing clinical interest due to their selectivity for tumor cells over healthy cells and their immunostimulatory properties. These treatment modalities provide promising alternatives to the standard of care, particularly for cancers with poor prognoses, such as the lethal brain tumor glioblastoma (GBM). However, uncertainty remains regarding optimal dosing strategies, including how the spatial location of viral doses impacts therapeutic efficacy and tumor landscape characteristics that are most conducive to producing an effective immune response. We develop a three-dimensional agent-based model (ABM) of GBM undergoing treatment with a combination of an oncolytic Herpes Simplex Virus and an anti-PD-1 immunotherapy. We use a mechanistic approach to model the interactions between distinct populations of immune cells, incorporating both innate and adaptive immune responses to oncolytic viral therapy and including a mechanism of adaptive immune suppression via the PD-1/PD-L1 checkpoint pathway. We utilize the spatially explicit nature of the ABM to determine optimal viral dosing in both the temporal and spatial contexts. After proposing an adaptive viral dosing strategy that chooses to dose sites at the location of highest tumor cell density, we find that, in most cases, this adaptive strategy produces a more effective treatment outcome than repeatedly dosing in the center of the tumor.

Biosystems ◽  
2010 ◽  
Vol 100 (3) ◽  
pp. 225-230 ◽  
Author(s):  
Viviane Galvão ◽  
José Garcia Vivas Miranda

2017 ◽  
Vol 14 (134) ◽  
pp. 20170320 ◽  
Author(s):  
Chang Gong ◽  
Oleg Milberg ◽  
Bing Wang ◽  
Paolo Vicini ◽  
Rajesh Narwal ◽  
...  

When the immune system responds to tumour development, patterns of immune infiltrates emerge, highlighted by the expression of immune checkpoint-related molecules such as PDL1 on the surface of cancer cells. Such spatial heterogeneity carries information on intrinsic characteristics of the tumour lesion for individual patients, and thus is a potential source for biomarkers for anti-tumour therapeutics. We developed a systems biology multiscale agent-based model to capture the interactions between immune cells and cancer cells, and analysed the emergent global behaviour during tumour development and immunotherapy. Using this model, we are able to reproduce temporal dynamics of cytotoxic T cells and cancer cells during tumour progression, as well as three-dimensional spatial distributions of these cells. By varying the characteristics of the neoantigen profile of individual patients, such as mutational burden and antigen strength, a spectrum of pretreatment spatial patterns of PDL1 expression is generated in our simulations, resembling immuno-architectures obtained via immunohistochemistry from patient biopsies. By correlating these spatial characteristics with in silico treatment results using immune checkpoint inhibitors, the model provides a framework for use to predict treatment/biomarker combinations in different cancer types based on cancer-specific experimental data.


2017 ◽  
Vol 31 (10) ◽  
pp. 1742002
Author(s):  
Alexandra Westley ◽  
Nicholas De Meglio ◽  
Rebecca Hager ◽  
Jorge Wu Mok ◽  
Linda Shanahan ◽  
...  

In this paper, we expand upon our recent studies of an agent-based model of a battle between an intelligent army and an insurgent army to explore the role of modifying strategy according to the state of the battle (adaptive strategy) on battle outcomes. This model leads to surprising complexity and rich possibilities in battle outcomes, especially in battles between two well-matched sides. We contend that the use of adaptive strategies may be effective in winning battles.


2019 ◽  
Vol 16 (160) ◽  
pp. 20190264
Author(s):  
Asaf Liberman ◽  
Matan Mussel ◽  
Danny Kario ◽  
David Sprinzak ◽  
Uri Nevo

Predictive modelling of complex biological systems and biophysical interactions requires the inclusion of multiple nano- and micro-scale events. In many scenarios, however, numerical solutions alone do not necessarily enhance the understanding of the system. Instead, this work explores the use of an agent-based model with visualization capabilities to elucidate interactions between single cells. We present a model of juxtacrine signalling, using Cell Studio, an agent-based modelling system, based on gaming and three-dimensional visualization tools. The main advantages of the system are its ability to apply any cell geometry and to dynamically visualize the diffusion and interactions of the molecules within the cells in real time. These provide an excellent tool for obtaining insight about different biological scenarios, as the user may view the dynamics of a system and observe its emergent behaviour as it unfolds. The agent-based model was validated against the results of a mean-field model of Notch receptors and ligands in two neighbouring cells. The conversion to an agent-based model is described in detail. To demonstrate the advantages of the model, we further created a filopodium-mediated signalling model. Our model revealed that diffusion and endocytosis alone are insufficient to produce significant signalling in a filopodia scenario. This is due to the bottleneck at the cell–filopodium contact region and the long distance to the end of the filopodium. However, allowing active transport of ligands into filopodia enhances the signalling significantly compared with a face-to-face scenario. We conclude that the agent-based approach can provide insights into mechanisms underlying cell signalling. The open-source model can be found in the Internet hosting service GitHub.


2001 ◽  
Author(s):  
Minoru Tabata ◽  
Akira Ide ◽  
Nobuoki Eshima ◽  
Kyushu Takagi ◽  
Yasuhiro Takei ◽  
...  

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