A mathematical model of tumour growth with Beddington–DeAngelis functional response: a case of cancer without disease

Wei, Hao-Ji

doi:10.1080/17513758.2017.1418028

Cited by 9 publications

(5 citation statements)

References 41 publications

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“…The main biological characteristics of tumor cells are uncontrolled proliferation and high migration ability (25,26). The proliferation of MC-4 cells was reduced in a concentration-dependent manner by MD4-EPS.…”

Section: Discussionmentioning

confidence: 99%

Exopolysaccharides from an Ophiopogon japonicus endophyte inhibit proliferation and migration in MC-4 human gastric cancer cells

Xu¹,

Yang²,

Yang³

et al. 2018

Transl. Cancer Res

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Background: Recently, natural products have gained increasing attention. Endophytic bacteria represent a source of natural anticancer products, and are well-known for producing diverse bioactive anti-cancer compounds. Herein, we investigated the antitumor activity of exopolysaccharides (EPSs) extracted from endophytes in Ophiopogon japonicus.Methods: The endophyte bacterium MD4 was isolated from O. japonicus. To identify MD4, a partial sequence of 16S rDNA was analyzed. The phenol-sulfuric acid method was used to measure the EPSs concentration. Cell viability was tested by the MTT assay to quantify the EPS cytotoxicity effect. Wounding healing, gelatin zymography, and ELISA were used to measure cell migration ability.Results: MD4 was identified as a Staphylococcus sp. with 99% similarity. The results of the phenol sulfuric acid method showed that the purified EPS concentration from MD4 was 28.068 μg/μL. There was a concentration-dependent cytotoxic effect of MD4-EPS on MC-4 cells, with IC50 values of 0.891 μg/μL.The results of the MTT assay showed that MD4-EPS effectively inhibited the migration of MC-4 cells as the concentration increased. The gelatin zymography analysis showed that the enzymatic activities of the migration-related MMP2 and MMP9 proteins decreased after EPS treatment. Furthermore, the protein secretion levels of MMP2 and MMP9 after MD4-EPS treatment were significantly lower than those in the control and PBS groups.Conclusions: Our results demonstrate that the EPSs derived from the MD4 endophyte of O. japonicus acted as natural antitumor agents to inhibit the migration of gastric cancer cells.

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Section: Discussionmentioning

confidence: 99%

Exopolysaccharides from an Ophiopogon japonicus endophyte inhibit proliferation and migration in MC-4 human gastric cancer cells

Xu¹,

Yang²,

Yang³

et al. 2018

Transl. Cancer Res

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“…We also consider the concentration of chemotherapy and radiotherapy denoted by M ( t ) and R ( t ), respectively. To control breast cancer progression, an equation with chemotherapy treatment is included as adapted in [15, 23, 29, 30]. The interaction between chemotherapy and all cells is found to follow an exponential saturation kinetics model, and this saturation have been validated by [33] for a reasonable number of chemotherapeutic drugs.…”

Section: Methodsmentioning

confidence: 99%

Dynamics of Breast Cancer under Different Rates of Chemoradiotherapy

Mkango

Shaban

Mureithi

et al. 2019

Computational and Mathematical Methods in Medicine

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A type of cancer which originates from the breast tissue is referred to as breast cancer. Globally, it is the most common cause of death in women. Treatments such as radiotherapy, chemotherapy, hormone therapy, immunotherapy, and gene therapy are the main strategies in the fight against breast cancer. The present study aims at investigating the effects of the combined radiotherapy and chemotherapy as a way to treat breast cancer, and different treatment approaches are incorporated into the model. Also, the model is fitted to data on patients with breast cancer in Tanzania. We determine new treatment strategies, and finally, we show that when sufficient amount of chemotherapy and radiotherapy with a low decay rate is used, the drug will be significantly more effective in combating the disease while health cells remain above the threshold.

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“…Although the healthy tissue and tumor cells compete for available resources, the immune and tumor cells compete in a predator‐prey fashion. This model then became a base for a big cluster of models ( Figure ) where it was expanded to include CD8+ T‐cells, NK cells, circulating T‐lymphocytes, and dendritic cells to investigate mono and combinations of several immune modulating agents, such as chemotherapy, IL‐2, IL‐12, INF‐α, IL‐21, DC vaccine, and TIL 22–32 …”

Section: Legacy Models Of Cancer Immunobiologymentioning

confidence: 99%

“…This model then became a base for a big cluster of models ( Figure 3) where it was expanded to include CD8+ T-cells, NK cells, circulating T-lymphocytes, and dendritic cells to investigate mono and combinations of several immune modulating agents, such as chemotherapy, IL-2, IL-12, INF-α, IL-21, DC vaccine, and TIL. [22][23][24][25][26][27][28][29][30][31][32] Models taking into account immune suppression by regulatory T cells…”

Section: Confidence Buildingmentioning

confidence: 99%

Quantitative Systems Pharmacology Approaches for Immuno‐Oncology: Adding Virtual Patients to the Development Paradigm

Chelliah¹,

Lazarou²,

Bhatnagar

et al. 2020

Clin Pharma and Therapeutics

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Drug development in oncology commonly exploits the tools of molecular biology to gain therapeutic benefit through reprograming of cellular responses. In immuno‐oncology (IO) the aim is to direct the patient’s own immune system to fight cancer. After remarkable successes of antibodies targeting PD1/PD‐L1 and CTLA4 receptors in targeted patient populations, the focus of further development has shifted toward combination therapies. However, the current drug‐development approach of exploiting a vast number of possible combination targets and dosing regimens has proven to be challenging and is arguably inefficient. In particular, the unprecedented number of clinical trials testing different combinations may no longer be sustainable by the population of available patients. Further development in IO requires a step change in selection and validation of candidate therapies to decrease development attrition rate and limit the number of clinical trials. Quantitative systems pharmacology (QSP) proposes to tackle this challenge through mechanistic modeling and simulation. Compounds’ pharmacokinetics, target binding, and mechanisms of action as well as existing knowledge on the underlying tumor and immune system biology are described by quantitative, dynamic models aiming to predict clinical results for novel combinations. Here, we review the current QSP approaches, the legacy of mathematical models available to quantitative clinical pharmacologists describing interaction between tumor and immune system, and the recent development of IO QSP platform models. We argue that QSP and virtual patients can be integrated as a new tool in existing IO drug development approaches to increase the efficiency and effectiveness of the search for novel combination therapies.

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A mathematical model of tumour growth with Beddington–DeAngelis functional response: a case of cancer without disease

Cited by 9 publications

References 41 publications

Exopolysaccharides from an Ophiopogon japonicus endophyte inhibit proliferation and migration in MC-4 human gastric cancer cells

Exopolysaccharides from an Ophiopogon japonicus endophyte inhibit proliferation and migration in MC-4 human gastric cancer cells

Dynamics of Breast Cancer under Different Rates of Chemoradiotherapy

Quantitative Systems Pharmacology Approaches for Immuno‐Oncology: Adding Virtual Patients to the Development Paradigm

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