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Hu2018 - Dynamics of tumor-CD4+-cytokine-host cells interactions with treatments

ABSTRACT: This is a proposed mathematical model describing interactions between tumor cells, CD4+ T cells, cytokines, and host cells within the context of CD4+ T cells inducing tumor regression. A platform is provided to assess the effectiveness of single or combination therapy with CD4+ T cells and/or cytokines.

SUBMITTER: Johannes Meyer

PROVIDER: BIOMD0000000797 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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			Action	DRS
	BIOMD0000000797?filename=Hu2018-biopax2.owl	Owl
	BIOMD0000000797?filename=Hu2018-biopax3.owl	Owl
	BIOMD0000000797?filename=Hu2018-matlab.m	Other
	BIOMD0000000797?filename=Hu2018-octave.m	Other
	BIOMD0000000797?filename=Hu2018.cps	Other

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Project description:Background: Despite current therapeutic treatments including surgery, chemotherapy, radiotherapy and recently immunotherapy, the mortality rate of lung cancer stays high. Regarding lung cancer, epigenetic modifications altering cell cycle, angiogenesis and programmed cancer cell death are therapeutic targets to combine with immunotherapy to improve treatment success. In a recent study, we uncovered a dual function of a molecule called QAPHA ((E)-3-(5-((2-cyanoquinolin-4-yl)(methyl)amino)-2-methoxyphenyl)-N-hydroxyacrylamide) as both a tubulin polymerization and HDAC inhibitors. Here, we investigate the impact of this novel dual inhibitor on the lung cancer immune response. Methods: To elucidate the mechanism of action of QAPHA, we conducted a chemical proteomics analysis. Using an in vivo mouse model of lung cancer (TC-1 tumor cells), we assessed the effects of QAPHA on tumor regression. Tumor infiltrating immune cells were characterize by flow cytometry. Results In this study, we first show that QAPHA can inhibit HDAC6, leading to upregulation of HSP90, cytochrome C and caspases, found by proteomic analysis. We also confirm that QAPHA induces immunogenic cell death (ICD) by upregulating HMGB1 in vitro and demonstrated its effectiveness as a vaccine in vivo. Remarkably, even at a low concentration (0.5mg/kg), QAPHA achieved complete tumor regression in approximately 60% of intratumorally treated mice, establishing a long-lasting anticancer immune response. Moreover, QAPHA treatment promoted infiltration of neutrophils in the treated mice, reflecting inflammatory cell death promoted. Very interestingly, we show that QAPHA is also able to upregulate MHC-II expression on TC-1 tumor cells in vitro and in vivo. This process participates to the recruitment of CD4+ NKG2D+ CRTAM+ Perforin+ T cells in tumor infiltrate, defined as cytotoxic CD4+ T cells (CD4+ CTL). Finally, we show that tumor regression is strongly correlated to MHC-II expression level on tumor cell and CD4+ CTL infiltrate. Conclusion Collectively, our findings shed light on the discovery of a new multi-target inhibitor able to induce ICD and MHC-II upregulation in TC-1 tumor cell. These two processes participate to enhance a specific CD4+ cytotoxic T cell-mediated anti-tumor response in vivo in our model of lung cancer. This breakthrough suggests the potential of QAPHA as a promising therapeutic agent for cancer treatment.

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.

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Hu2018 - Dynamics of tumor-CD4+-cytokine-host cells interactions with treatments

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