Dataset Information

Phan2017 - innate immune in oncolytic virotherapy

ABSTRACT: The paper describes a model on the key components for tumor–immune dynamics in multiple myeloma. Created by COPASI 4.25 (Build 207) This model is described in the article: The Role of the Innate Immune System in Oncolytic Virotherapy Tuan Anh Phan and Jianjun Paul Tian Computational and Mathematical Methods in Medicine (2017) 6587258 Abstract: The complexity of the immune responses is a major challenge in current virotherapy. This study incorporates the innate immune response into our basic model for virotherapy and investigates how the innate immunity affects the outcome of virotherapy. The viral therapeutic dynamics is largely determined by the viral burst size, relative innate immune killing rate, and relative innate immunity decay rate. The innate immunity may complicate virotherapy in the way of creating more equilibria when the viral burst size is not too big, while the dynamics is similar to the system without innate immunity when the viral burst size is big. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

SUBMITTER: Jinghao Men

PROVIDER: BIOMD0000000748 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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	BIOMD0000000748?filename=Fig.2.png	Other
	BIOMD0000000748?filename=Phan2017-biopax2.owl	Owl
	BIOMD0000000748?filename=Phan2017-biopax3.owl	Owl
	BIOMD0000000748?filename=Phan2017-matlab.m	Other
	BIOMD0000000748?filename=Phan2017-octave.m	Other

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The Role of the Innate Immune System in Oncolytic Virotherapy.

Phan Tuan Anh TA Tian Jianjun Paul JP

Computational and mathematical methods in medicine 20171212

The complexity of the immune responses is a major challenge in current virotherapy. This study incorporates the innate immune response into our basic model for virotherapy and investigates how the innate immunity affects the outcome of virotherapy. The viral therapeutic dynamics is largely determined by the viral burst size, relative innate immune killing rate, and relative innate immunity decay rate. The innate immunity may complicate virotherapy in the way of creating more equilibria when the ...[more]

PMID: 29379572

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Project description:This mathematical model of the role of the innate immune responses generated by macrophages in the context of anti-tumour oncolytic viral therapies is described in the publication: Nada Almuallem, Dumitru Trucu, Raluca Eftimie. "Oncolytic viral therapies and the delicate balance between virus-macrophage-tumour interactions: A mathematical approach". Mathematical Biosciences and Engineering, 2021, 18(1): 764-799. doi: 10.3934/mbe.2021041 Comment: This model is represented by Equations 2.1a-f of the publication manuscript. Abstract: The success of oncolytic virotherapies depends on the tumour microenvironment, which contains a large number of infiltrating immune cells. In this theoretical study, we derive an ODE model to investigate the interactions between breast cancer tumour cells, an oncolytic virus (Vesicular Stomatitis Virus), and tumour-infiltrating macrophages with different phenotypes which can impact the dynamics of oncolytic viruses. The complexity of the model requires a combined analytical-numerical approach to understand the transient and asymptotic dynamics of this model. We use this model to propose new biological hypotheses regarding the impact on tumour elimination/relapse/persistence of: (i) different macrophage polarisation/re-polarisation rates; (ii) different infection rates of macrophages and tumour cells with the oncolytic virus; (iii) different viral burst sizes for macrophages and tumour cells. We show that increasing the rate at which the oncolytic virus infects the tumour cells can delay tumour relapse and even eliminate tumour. Increasing the rate at which the oncolytic virus particles infect the macrophages can trigger transitions between steady-state dynamics and oscillatory dynamics, but it does not lead to tumour elimination unless the tumour infection rate is also very large. Moreover, we confirm numerically that a large tumour-induced M1→M2 polarisation leads to fast tumour growth and fast relapse (if the tumour was reduced before by a strong anti-tumour immune and viral response). The increase in viral-induced M2→M1 re-polarisation reduces temporarily the tumour size, but does not lead to tumour elimination. Finally, we show numerically that the tumour size is more sensitive to the production of viruses by the infected macrophages.

Project description:Baris Hancioglu, David Swigon & Gilles Clermont. A dynamical model of human immune response to influenza A virus infection. Journal of Theoretical Biology 246, 1 (2007). We present a simplified dynamical model of immune response to uncomplicated influenza A virus (IAV) infection, which focuses on the control of the infection by the innate and adaptive immunity. Innate immunity is represented by interferon-induced resistance to infection of respiratory epithelial cells and by removal of infected cells by effector cells (cytotoxic T-cells and natural killer cells). Adaptive immunity is represented by virus-specific antibodies. Similar in spirit to the recent model of Bocharov and Romanyukha [1994. Mathematical model of antiviral immune response. III. Influenza A virus infection. J. Theor. Biol. 167, 323-360], the model is constructed as a system of 10 ordinary differential equations with 27 parameters characterizing the rates of various processes contributing to the course of disease. The parameters are derived from published experimental data or estimated so as to reproduce available data about the time course of IAV infection in a naïve host. We explore the effect of initial viral load on the severity and duration of the disease, construct a phase diagram that sheds insight into the dynamics of the disease, and perform sensitivity analysis on the model parameters to explore which ones influence the most the onset, duration and severity of infection. To account for the variability and speed of adaptation of the adaptive response to a particular virus strain, we introduce a variable that quantifies the antigenic compatibility between the virus and the antibodies currently produced by the organism. We find that for small initial viral load the disease progresses through an asymptomatic course, for intermediate value it takes a typical course with constant duration and severity of infection but variable onset, and for large initial viral load the disease becomes severe. This behavior is robust to a wide range of parameter values. The absence of antibody response leads to recurrence of disease and appearance of a chronic state with nontrivial constant viral load.

Project description:Fribourg2014 - Dynamics of viral antagonism and innate immune response (H1N1 influenza A virus - NC/99) The dynamics of the interplay between the viral antagonism and the innate immune response has been studied using modelling approaches. The responses of human monocyte-derived dendritic cells infected by two influenza A H1N1 strains (the pandemic swine-origin A/California/4/2009 (Cal/09) and the seasonal A/New Caledonia/20/1999 (NC/99)) that have different clinical outcomes have been modelled. From the time course gene expression measurements of a set of selected genes, the dynamic features of viral antagonism and innate immune response are extracted. It is found that the strength and the time scale of action of viral antagonism is significantly different between the two viruses. This model describes the viral infection by seasonal NC/99. This model is described in the article: Model of influenza A virus infection: Dynamics of viral antagonism and innate immune response. Fribourg M, Hartmann B, Schmolke M, Marjanovic N, Albrecht RA, García-Sastre A, Sealfon SC, Jayaprakash C, Hayot F. J Theor Biol. 2014 Mar 2;351C:47-57. Abstract: Viral antagonism of host responses is an essential component of virus pathogenicity. The study of the interplay between immune response and viral antagonism is challenging due to the involvement of many processes acting at multiple time scales. Here we develop an ordinary differential equation model to investigate the early, experimentally measured, responses of human monocyte-derived dendritic cells to infection by two H1N1 influenza A viruses of different clinical outcomes: pandemic A/California/4/2009 and seasonal A/New Caledonia/20/1999. Our results reveal how the strength of virus antagonism, and the time scale over which it acts to thwart the innate immune response, differs significantly between the two viruses, as is made clear by their impact on the temporal behavior of a number of measured genes. The model thus sheds light on the mechanisms that underlie the variability of innate immune responses to different H1N1 viruses. This model is hosted on BioModels Database and identified by: MODEL1403310001. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Fribourg2014 - Dynamics of viral antagonism and innate immune response (H1N1 influenza A virus - Cal/09) The dynamics of the interplay between the viral antagonism and the innate immune response has been studied using modelling approaches. The responses of human monocyte-derived dendritic cells infected by two influenza A H1N1 strains (the pandemic swine-origin A/California/4/2009 (Cal/09) and the seasonal A/New Caledonia/20/1999 (NC/99)) that have different clinical outcomes have been modelled. From the time course gene expression measurements of a set of selected genes, the dynamic features of viral antagonism and innate immune response are extracted. It is found that the strength and the time scale of action of viral antagonism is significantly different between the two viruses. This model describes the viral infection by seasonal Cal/09. This model is described in the article: Model of influenza A virus infection: Dynamics of viral antagonism and innate immune response. Fribourg M, Hartmann B, Schmolke M, Marjanovic N, Albrecht RA, García-Sastre A, Sealfon SC, Jayaprakash C, Hayot F. J Theor Biol. 2014 Mar 2;351C:47-57. Abstract: Viral antagonism of host responses is an essential component of virus pathogenicity. The study of the interplay between immune response and viral antagonism is challenging due to the involvement of many processes acting at multiple time scales. Here we develop an ordinary differential equation model to investigate the early, experimentally measured, responses of human monocyte-derived dendritic cells to infection by two H1N1 influenza A viruses of different clinical outcomes: pandemic A/California/4/2009 and seasonal A/New Caledonia/20/1999. Our results reveal how the strength of virus antagonism, and the time scale over which it acts to thwart the innate immune response, differs significantly between the two viruses, as is made clear by their impact on the temporal behavior of a number of measured genes. The model thus sheds light on the mechanisms that underlie the variability of innate immune responses to different H1N1 viruses. This model is hosted on BioModels Database and identified by: MODEL1403310002. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.