Al-Tuwairqi2020 - Dynamics of cancer virotherapy with immune response
Ontology highlight
ABSTRACT:
DISEASE(S): Cancer
SUBMITTER: 
Emilia Chen
PROVIDER: BIOMD0000001035 | BioModels | 2021-08-19
REPOSITORIES: BioModels
Similar Datasets
Project description:This ordinary differential equation model of cancer virotherapy dynamics is described in the publication:
Salma M. Al-Tuwairqi, Najwa O. Al-Johani, Eman A. Simbawa,
"Modeling dynamics of cancer radiovirotherapy",
Journal of Theoretical Biology, Volume 506, 2020, 110405, ISSN 0022-5193,
DOI: 10.1016/j.jtbi.2020.110405.
Comment:
This model is represented by the equations in system (2) of the publication manuscript and describes the cancer-virus interactions for the Phase I virotherapy treatment.
Abstract:
Advances in genetic engineering have paved the way for a new therapy for cancer, which is called virotherapy. This treatment uses genetically engineered viruses which selectively infect, replicate in, and destroy cancer cells without damaging normal cells. Furthermore, current research and clinical trials have indicated that these viruses can be delivered as single agents or in combination with other therapies. In this paper, we propose systems of ordinary differential equations for modeling the dynamics of aggressive tumor growth under radiovirotherapy treatment. We divide the treatment period into two phases; consequently, we present two mathematical models. First, we formulate the virotherapy model as Phase I of the treatment. Then we extend the model to include radiotherapy in combination with virotherapy as Phase II of the treatment. Comprehensive qualitative analyses of both models are conducted. Furthermore, numerical experiments are performed in order to support the analytical results. An analysis of the parameters is also carried out to investigate their effects on the outcome of the treatment. Overall, the analytical results reveal that radiovirotherapy is more effective than, and a good alternative to, virotherapy, as it is capable of eradicating tumors completely.
2021-08-16 | BIOMD0000001031 | BioModels
Project description:This ordinary differential equation model of cancer radiovirotherapy dynamics is described in the publication:
Salma M. Al-Tuwairqi, Najwa O. Al-Johani, Eman A. Simbawa,
"Modeling dynamics of cancer radiovirotherapy",
Journal of Theoretical Biology, Volume 506, 2020, 110405, ISSN 0022-5193,
DOI: 10.1016/j.jtbi.2020.110405.
Comment:
This model is represented by the equations in system (14) of the publication manuscript and describes the cancer-virus interactions for the Phase II radiovirotherapy treatment.
Abstract:
Advances in genetic engineering have paved the way for a new therapy for cancer, which is called virotherapy. This treatment uses genetically engineered viruses which selectively infect, replicate in, and destroy cancer cells without damaging normal cells. Furthermore, current research and clinical trials have indicated that these viruses can be delivered as single agents or in combination with other therapies. In this paper, we propose systems of ordinary differential equations for modeling the dynamics of aggressive tumor growth under radiovirotherapy treatment. We divide the treatment period into two phases; consequently, we present two mathematical models. First, we formulate the virotherapy model as Phase I of the treatment. Then we extend the model to include radiotherapy in combination with virotherapy as Phase II of the treatment. Comprehensive qualitative analyses of both models are conducted. Furthermore, numerical experiments are performed in order to support the analytical results. An analysis of the parameters is also carried out to investigate their effects on the outcome of the treatment. Overall, the analytical results reveal that radiovirotherapy is more effective than, and a good alternative to, virotherapy, as it is capable of eradicating tumors completely.
2021-08-17 | BIOMD0000001032 | BioModels
Project description:This ordinary differential equation model of tumor cell growth, called the normal-tumor-immune-unhealthy diet model (NTIUNHDM), is described by the publication:
Alharbi, S.A.; Rambely, A.S.
"A New ODE-Based Model for Tumor Cells and Immune System Competition"
Mathematics 2020, 8, 1285.
doi:10.3390/math8081285
Abstract:
Changes in diet are heavily associated with high mortality rates in several types of cancer. In this paper, a new mathematical model of tumor cells growth is established to dynamically demonstrate the effects of abnormal cell progression on the cells affected by the tumor in terms of the immune system’s functionality and normal cells’ dynamic growth. This model is called the normal-tumor-immune-unhealthy diet model (NTIUNHDM) and governed by a system of ordinary differential equations. In the NTIUNHDM, there are three main populations normal cells, tumor cell and immune cells. The model is discussed analytically and numerically by utilizing a fourth-order Runge–Kutta method. The dynamic behavior of the NTIUNHDM is discussed by analyzing the stability of the system at various equilibrium points and the Mathematica software is used to simulate the model. From analysis and simulation of the NTIUNHDM, it can be deduced that instability of the response stage, due to a weak immune system, is classified as one of the main reasons for the coexistence of abnormal cells and normal cells. Additionally, it is obvious that the NTIUNHDM has only one stable case when abnormal cells begin progressing into early stages of tumor cells such that the immune cells are generated once. Thus, early boosting of the immune system might contribute to reducing the risk of cancer.
2021-07-29 | BIOMD0000001023 | BioModels
Project description:This ordinary differential equation model simulating the interactions between tumor and immune cells is detailed in the publication:
Ahmed M. Makhlouf, Lamiaa El-Shennawy, Hesham A. Elkaranshawy, "Mathematical Modelling for the Role of CD4+T Cells in Tumor-Immune Interactions", Comput Math Methods Med. 2020 Feb 19;2020:7187602.
doi: 10.1155/2020/7187602
Comment:
This no treatment model is described by equations 1-7 of the publication manuscript.
Abstract:
Mathematical modelling has been used to study tumor-immune cell interaction. Some models were proposed to examine the effect of circulating lymphocytes, natural killer cells, and CD8+T cells, but they neglected the role of CD4+T cells. Other models were constructed to study the role of CD4+T cells but did not consider the role of other immune cells. In this study, we propose a mathematical model, in the form of a system of nonlinear ordinary differential equations, that predicts the interaction between tumor cells and natural killer cells, CD4+T cells, CD8+T cells, and circulating lymphocytes with or without immunotherapy and/or chemotherapy. This system is stiff, and the Runge–Kutta method failed to solve it. Consequently, the “Adams predictor-corrector” method is used. The results reveal that the patient’s immune system can overcome small tumors; however, if the tumor is large, adoptive therapy with CD4+T cells can be an alternative to both CD8+T cell therapy and cytokines in some cases. Moreover, CD4+T cell therapy could replace chemotherapy depending upon tumor size. Even if a combination of chemotherapy and immunotherapy is necessary, using CD4+T cell therapy can better reduce the dose of the associated chemotherapy compared to using combined CD8+T cells and cytokine therapy. Stability analysis is performed for the studied patients. It has been found that all equilibrium points are unstable, and a condition for preventing tumor recurrence after treatment has been deduced. Finally, a bifurcation analysis is performed to study the effect of varying system parameters on the stability, and bifurcation points are specified. New equilibrium points are created or demolished at some bifurcation points, and stability is changed at some others. Hence, for systems turning to be stable, tumors can be eradicated without the possibility of recurrence. The proposed mathematical model provides a valuable tool for designing patients’ treatment intervention strategies.
2021-09-06 | BIOMD0000001042 | BioModels
Project description:This ordinary differential equation model, simulating the tumor-immune interactions involved in BCG immunotherapy to treat superficial bladder cancer, is described by the publication:
Bunimovich-Mendrazitsky, S., Shochat, E., Stone, L. "Mathematical Model of BCG Immunotherapy in Superficial Bladder Cancer". Bull. Math. Biol. 69, 1847–1870 (2007). DOI: 10.1007/s11538-007-9195-z
Comment:
This model is based on the system of ODEs given in Equation 4 of the publication manuscript.
Reproduction of Figure 4 was achieved by setting p4 = 0.085.
Abstract:
Immunotherapy with Bacillus Calmette-Guérin (BCG)-an attenuated strain of Mycobacterium bovis (M. bovis) used for anti tuberculosis immunization-is a clinically established procedure for the treatment of superficial bladder cancer. However, the mode of action has not yet been fully elucidated, despite much extensive biological experience. The purpose of this paper is to develop a first mathematical model that describes tumor-immune interactions in the bladder as a result of BCG therapy. A mathematical analysis of the ODE model identifies multiple equilibrium points, their stability properties, and bifurcation points. Intriguing regimes of bistability are identified in which treatment has potential to result in a tumor-free equilibrium or a full-blown tumor depending only on initial conditions. Attention is given to estimating parameters and validating the model using published data taken from in vitro, mouse and human studies. The model makes clear that intensity of immunotherapy must be kept in limited bounds. While small treatment levels may fail to clear the tumor, a treatment that is too large can lead to an over-stimulated immune system having dangerous side effects for the patient.
2021-08-19 | BIOMD0000001034 | BioModels
Project description:Mathematical Modeling, Analysis, and Simulation of Tumor Dynamics with Drug Interventions
Pranav Unni 1 and Padmanabhan Seshaiyer
Abstract
Over the last few decades, there have been significant developments in theoretical, experimental, and clinical approaches to understand the dynamics of cancer cells and their interactions with the immune system. These have led to the development of important methods for cancer therapy including virotherapy, immunotherapy, chemotherapy, targeted drug therapy, and many others. Along with this, there have also been some developments on analytical and computational models to help provide insights into clinical observations. This work develops a new mathematical model that combines important interactions between tumor cells and cells in the immune systems including natural killer cells, dendritic cells, and cytotoxic CD8+ T cells combined with drug delivery to these cell sites. These interactions are described via a system of ordinary differential equations that are solved numerically. A stability analysis of this model is also performed to determine conditions for tumor-free equilibrium to be stable. We also study the influence of proliferation rates and drug interventions in the dynamics of all the cells involved. Another contribution is the development of a novel parameter estimation methodology to determine optimal parameters in the model that can reproduce a given dataset. Our results seem to suggest that the model employed is a robust candidate for studying the dynamics of tumor cells and it helps to provide the dynamic interactions between the tumor cells, immune system, and drug-response systems.
2019-12-10 | BIOMD0000000888 | BioModels
Project description:The oncolytic effect of virotherapy derives from the intrinsic capability of the applied virus in selectively infecting and killing tumor cells. Although oncolytic viruses of various constructions have been shown to efficiently infect and kill tumor cells in vitro, the efficiency of these viruses to exert the same effect on tumor cells within tumor tissues in vivo has not been extensively investigated. Here we report our studies using single-cell RNA sequencing to comprehensively analyze the gene expression profile of tumor tissues following herpes simplex virus 2-based oncolytic virotherapy. Our data revealed the extent and cell types within the tumor microenvironment that could be infected by the virus. Moreover, we observed changes in the expression of cellular genes, including antiviral genes, in response to viral infection. One notable gene found to be upregulated significantly in oncolytic virus-infected tumor cells was Gadd45g, which is desirable for optimal virus replication. These results not only help reveal the precise infection status of the oncolytic virus in vivo, but also provide insight that may lead to the development of new strategies to further enhance the therapeutic efficacy of oncolytic virotherapy.
2021-10-31 | GSE186753 | GEO
Project description:Replicating viruses have broad applications in biomedicine, notably in cancer virotherapy and in the design of attenuated vaccines, however uncontrolled virus replication in vulnerable tissues can give pathology and often restricts the use of potent strains. Increased knowledge of tissue-selective microRNA expression now affords the possibility of engineering replicating viruses that are attenuated at the RNA level in sites of potential pathology, but retain wild type replication activity at sites not expressing the relevant microRNA. To assess the usefulness of this approach for the DNA virus, adenovirus, we have engineered a hepatocyte-safe wild type adenovirus 5 (Ad5), which normally mediates significant toxicity and is potentially lethal in mice. To do this we have included binding sites for hepatocyte-selective microRNA122a within the 3' UTR of the E1A transcription cassette. Imaging versions of these viruses, produced by fusing E1A with luciferase, showed that inclusion of microRNA122a binding sites caused up to 80 fold decreased hepatic expression of E1A following intravenous delivery to mice. Animals administered a ten-times lethal dose of wild type Ad5 (5 x 1010 viral particles/mouse) showed substantial hepatic genome replication and extensive liver pathology, while inclusion of 4 microRNA binding sites decreased replication 50-fold and virtually abrogated liver toxicity. This modified wild type virus retained full activity within cancer cells and provides a potent, liver-safe oncolytic virus. In addition to providing many potent new viruses for cancer virotherapy, microRNA-control of virus replication should provide a new strategy for designing safe attenuated vaccines applied across a broad range of viral diseases. four groups which we had were: WT: RNA extracted from livers of mice treated with wild type Ad5, 3 Replicates miR: RNA extracted from livers of mice treated with wild type Ad5 bearing mir122-binding sites in the 3'UTR of E1A (3 Replicates) Luc: RNA extracted from livers of mice treated with non-replicating Ad5 (3 Replicates) PBS: RNA extracted from livers of mice treated with PBS only (3 Replicates)
2011-08-19 | E-GEOD-23854 | biostudies-arrayexpress
Project description:Replicating viruses have broad applications in biomedicine, notably in cancer virotherapy and in the design of attenuated vaccines, however uncontrolled virus replication in vulnerable tissues can give pathology and often restricts the use of potent strains. Increased knowledge of tissue-selective microRNA expression now affords the possibility of engineering replicating viruses that are attenuated at the RNA level in sites of potential pathology, but retain wild type replication activity at sites not expressing the relevant microRNA. To assess the usefulness of this approach for the DNA virus, adenovirus, we have engineered a hepatocyte-safe wild type adenovirus 5 (Ad5), which normally mediates significant toxicity and is potentially lethal in mice. To do this we have included binding sites for hepatocyte-selective microRNA122a within the 3’ UTR of the E1A transcription cassette. Imaging versions of these viruses, produced by fusing E1A with luciferase, showed that inclusion of microRNA122a binding sites caused up to 80 fold decreased hepatic expression of E1A following intravenous delivery to mice. Animals administered a ten-times lethal dose of wild type Ad5 (5 x 1010 viral particles/mouse) showed substantial hepatic genome replication and extensive liver pathology, while inclusion of 4 microRNA binding sites decreased replication 50-fold and virtually abrogated liver toxicity. This modified wild type virus retained full activity within cancer cells and provides a potent, liver-safe oncolytic virus. In addition to providing many potent new viruses for cancer virotherapy, microRNA-control of virus replication should provide a new strategy for designing safe attenuated vaccines applied across a broad range of viral diseases.
2011-08-20 | GSE23854 | GEO
Project description:Targeting the PD-1/PD-L1 axis has transformed the field of immune-oncology. While conventional wisdom initially postulated that PD-L1 serves as the inert ligand for PD-1, an emerging body of literature suggests that PD-L1 has cell‑intrinsic functions in immune and cancer cells. In line with these studies, here we show that PD-L1 potently inhibits the type I interferon pathway in cancer cells. Hampered type I interferon responses in PD-L1-expressing cells resulted in enhanced infection with oncolytic viruses in cancer cells in vitro and in vivo. PD-L1 expression marks tumor explants from cancer patients that are best infected by oncolytic viruses. Agonistic antibodies targeting PD-L1 further reduced type I IFN responses and enhanced oncolytic virus infection. Mechanistically, PD-L1 suppressed type I interferon by promoting Warburg metabolism, characterized by enhanced glucose uptake and glycolysis rate. Lactate generated from glycolysis was the key metabolite responsible for inhibiting type I interferon responses and enhancing oncolytic virus infection in PD‑L1‑expressing cells. In addition to adding mechanistic insight into PD-L1 intrinsic function and showing that PD-L1 has a broader impact on immunity and cancer biology besides acting as a ligand for PD-1, our results will also help guide the numerous efforts currently ongoing to combine PD-L1 antibodies with oncolytic virotherapy in clinical trials.
2023-06-28 | GSE210884 | GEO