Multiscale model for the effects of adaptive immunity suppression on the viral therapy of cancer

Paiva, Leticia R.; Silva, Hallan S; Ferreira, Silvio C.; Martins, Marcelo L.

doi:10.1088/1478-3975/10/2/025005

Cited by 10 publications

(4 citation statements)

References 51 publications

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“…The PRAME gene was overexpressed in 84% of samples, allowing it to be a strong candidate for immunotherapy. Paiva et al (2013) published an article about oncolytic virotherapy showing its innovative and highly promising route for treating cancer. Authors proposed a multi-scale mathematical model to study how the immune response interferes with the viral oncolytic activity.…”

Section: Non-specific Therapiesmentioning

confidence: 99%

Immunological Processes in Cancer: A Link Between Inflammation and Immunity

Victorino¹

2014

American Journal of Immunology

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Cancer is a worldwide issue and one of the most relevant death causes in child and adults. There are several causes that can lead to cancer development. It is well known that inflammation is one known hallmark of cancer and it favors tumor cells growth. Several alterations in immunological and inflammatory processes are caused in response to tumor presence and both innate and adaptive immunity have effective mechanism to destroy tumor cells. Nevertheless, distinct tumor types developed mechanisms to evade anti-tumor immunological responses. Here, we revise researches regarding inflammation and immune response during cancer development, as well as cancer signaling pathways and immunotherapy that have been performed in Brazil. The better understanding of the mechanisms regarding cancer and immunological processes is of huge importance and it may support the development of new cancer targets.

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Section: Non-specific Therapiesmentioning

confidence: 99%

Immunological Processes in Cancer: A Link Between Inflammation and Immunity

Victorino¹

2014

American Journal of Immunology

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“…The great majority of these models are single-scale models, which focus on spatial tumour invasion [5,16,12], on tumour oncolytic therapies [11,14,13,17,21,28,42], or both [6,24,27,38,43]. More recently, various multi-scale mathematical models have been derived to reproduce and investigate biological processes that take place at different spatial scales [1,2,3,4,30,31,39,36]. For example, [39] introduced a multi-scale moving boundary model for cancer invasion, which focused on the local interactions between cancer cells and the ECM, via matrix degrading enzymes (MDEs) that act at the micro-scale level of the invading tumour boundary.…”

Section: Introductionmentioning

confidence: 99%

Nonlocal multiscale modelling of tumour-oncolytic viruses interactions within a heterogeneous fibrous/non-fibrous extracellular matrix

Alsisi¹,

Eftimie²,

Trucu³

2021

Preprint

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In this study we investigate computationally tumour-oncolytic virus (OV) interactions that take place within a heterogeneous ExtraCellular Matrix (ECM). The ECM is viewed as a mixture of two constitutive phases, namely a fibre phase and a non-fibre phase. The multiscale mathematical model presented here focuses on the nonlocal cell-cell and cell-ECM interactions, and how these interactions might be impacted by the infection of cancer cells with the OV. At macroscale we track the kinetics of cancer cells, virus particles and the ECM. At microscale we track (i) the degradation of ECM by matrix degrading enzymes (MDEs) produced by cancer cells, which further influences the movement of tumour boundary; (ii) the re-arrangement of the microfibres that influences the re-arrangement of macrofibres (i.e., fibres at macroscale). With the help of this new multiscale model, we investigate two questions: (i) whether the infected cancer cell fluxes are the result of local or non-local advection in response to ECM density; and (ii) what is the effect of ECM fibres on the the spatial spread of oncolytic viruses and the outcome of oncolytic virotherapy.

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“…The last two decades have seen the development of various mathematical models for multiscale cancer dynamics [1,34,39,48,49,50]. Nevertheless, there are not many multiscale mathematical models for oncolytic viral therapies and tumour-viral interactions; among the very few multiscale models we mention those in [3,4,37,38]. These models focus on local cancer cell dynamics and local interactions between cells, ECM and viruses.…”

Section: Introductionmentioning

confidence: 99%

Non-local multiscale approaches for tumour-oncolytic viruses interactions

Alsisi¹,

Eftimie²,

Trucu

2020

Math Appl Sci Eng

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Oncolytic virus (OV) therapy is a promising treatment for cancer due to the OVs selective ability to infect and replicate inside cancer cells, thus killing them, without harming healthy cells. In this work, we present a new non-local multiscale moving boundary model for the spatio-temporal cancer-OV interactions. This model explores an important double feedback loop that links the macro-scale dynamics of cancer-virus interactions and the micro-scale dynamics of proteolytic activity taking place at the tumour interface. The cancer cell-cell and cell-matrix interactions are assumed to be nonlocal, while the cell-virus interactions are assumed local. With the help of this model we investigate computationally various cancer treatment scenarios involving oncolytic viruses (i.e., the effect of injecting the OV inside the tumour, or outside it). Moreover, we investigate the effect of different cell-cell and cell-matrix interaction strengths on the success of OV spreading throughout the tumour, and the effect of constant or density-dependent virus diffusion coefficients on viral spread.

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Multiscale model for the effects of adaptive immunity suppression on the viral therapy of cancer

Cited by 10 publications

References 51 publications

Immunological Processes in Cancer: A Link Between Inflammation and Immunity

Immunological Processes in Cancer: A Link Between Inflammation and Immunity

Nonlocal multiscale modelling of tumour-oncolytic viruses interactions within a heterogeneous fibrous/non-fibrous extracellular matrix

Non-local multiscale approaches for tumour-oncolytic viruses interactions

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