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:The paper describes a model of interaction of Th cells and macrophage in melanoma. Created by COPASI 4.25 (Build 207) This model is described in the article: Modelling and investigation of the CD4 T cells – Macrophages paradox in melanoma immunotherapies Raluca Eftimie, Haneen Hamam Journal of Theoretical Biology 420 (2017) 82–104 Abstract: It is generally accepted that tumour cells can be eliminated by M1 anti-tumour macrophages and CD8+ T cells. However, experimental results over the past 10–15 years have shown that B16 mouse melanoma cells can be eliminated by the CD4+ T cells alone (either Th1 or Th2 sub-types), in the absence of CD8+ T cells. In some studies, elimination of B16 melanoma was associated with a Th1 immune response (i.e., elimination occurred in the presence of cytokines produced by Th1 cells), while in other studies melanoma elimination was associated with a Th2 immune response (i.e., elimination occurred in the presence of cytokines produced by Th2 cells). Moreover, macrophages have been shown to be present inside the tumours, during both Th1 and Th2 immune responses. To investigate the possible biological mechanisms behind these apparently contradictory results, we develop a class of mathematical models for the dynamics of Th1 and Th2 cells, and M1 and M2 macrophages in the presence/absence of tumour cells. Using this mathematical model, we show that depending on the re- polarisation rates between M1 and M2 macrophages, we obtain tumour elimination in the presence of a type-I immune response (i.e., more Th1 and M1 cells, compared to the Th2 and M2 cells), or in the presence of a type- II immune response (i.e., more Th2 and M2 cells). Moreover, tumour elimination is also possible in the presence of a mixed type-I/type-II immune response. Tumour growth always occurs in the presence of a type-II immune response, as observed experimentally. Finally, tumour dormancy is the result of a delicate balance between the pro-tumour effects of M2 cells and the anti-tumour effects of M1 and Th1 cells. 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:The paper describes a model of oncolytic virotherapy. Created by COPASI 4.26 (Build 213) This model is described in the article: Mathematical Modelling of the Interaction Between Cancer Cells and an Oncolytic Virus: Insights into the Effects of Treatment Protocols Adrianne L. Jenner, Chae-Ok Yun, Peter S. Kim, Adelle C. F. Coster Bull Math Biol (2018) 80:1615–1629 Abstract: Oncolyticvirotherapyisanexperimentalcancertreatmentthatusesgenet- ically engineered viruses to target and kill cancer cells. One major limitation of this treatment is that virus particles are rapidly cleared by the immune system, preventing them from arriving at the tumour site. To improve virus survival and infectivity Kim et al. (Biomaterials 32(9):2314–2326, 2011) modified virus particles with the polymer polyethylene glycol (PEG) and the monoclonal antibody herceptin. Whilst PEG mod- ification appeared to improve plasma retention and initial infectivity, it also increased the virus particle arrival time. We derive a mathematical model that describes the inter- action between tumour cells and an oncolytic virus. We tune our model to represent the experimental data by Kim et al. (2011) and obtain optimised parameters. Our model provides a platform from which predictions may be made about the response of cancer growth to other treatment protocols beyond those in the experiments. Through model simulations, we find that the treatment protocol affects the outcome dramatically. We quantify the effects of dosage strategy as a function of tumour cell replication and tumour carrying capacity on the outcome of oncolytic virotherapy as a treatment. The relative significance of the modification of the virus and the crucial role it plays in optimising treatment efficacy are explored. 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.

			Action	DRS
	BIOMD0000000806?filename=Eftimie2019-Macrophages%20Plasticity.cps	Other
	BIOMD0000000806?filename=Macrophages%20Plasticity%20a.sedml	Other
	BIOMD0000000806?filename=Macrophages%20Plasticity%20b.sedml	Other
	BIOMD0000000806?filename=curation_image.png	Other
	BIOMD0000000806?filename=curation_notes.txt	Txt

Dataset Information

Eftimie2019-Macrophages Plasticity

Dataset's files

Publications

Investigating Macrophages Plasticity Following Tumour-Immune Interactions During Oncolytic Therapies.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets