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A mathematical model for treatment using chemo-immunotherapy.

ABSTRACT: In this study, we investigated a mathematical model for chemoimmunotherapy (a combination of chemotherapy and immunotherapy) for brain cancer. In most cases, the standard protocol for cancer treatment is fixed in terms of treatment time intervals and dosages. We offer a wide range of non-fixed protocols, which essentially vary in terms of time intervals and dosages (i.e., personalised medicine). The functions that describe this treatment are explicit and analytical. Hence, the parameters of the function can be easily changed and a new protocol can be obtained. We compared different protocols and obtained an optimal solution. In addition, we applied the singular perturbed vector field (SPVF) method to determine the hierarchy of the system of equations, which enabled us to identify the equilibrium points of the mathematical model and investigate their stability.

SUBMITTER: Nave O

PROVIDER: S-EPMC9065634 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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A mathematical model for treatment using chemo-immunotherapy.

Nave Ophir O

Heliyon 20220426 4

In this study, we investigated a mathematical model for chemoimmunotherapy (a combination of chemotherapy and immunotherapy) for brain cancer. In most cases, the standard protocol for cancer treatment is fixed in terms of treatment time intervals and dosages. We offer a wide range of non-fixed protocols, which essentially vary in terms of time intervals and dosages (i.e., personalised medicine). The functions that describe this treatment are explicit and analytical. Hence, the parameters of the ...[more]

PMID: 35520602

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Project description:BackgroundMismatch Repair Deficiency (MMR-D)-related tumors are highly immunogenic and constitute ideal vaccination targets. In a proof-of-concept study delayed tumorigenesis and prolonged survival has been shown in a clinically-relevant mouse model for MMR-D-related diseases (=MLH1 knock out mice). To refine this approach, vaccination was combined with immune modulatory low-dose chemotherapy to polarize immune regulatory subtypes.MethodsMice (prophylactic: 8-10 weeks; therapeutic: > 36 weeks) received a single injection of cyclophosphamide (CPX, 120 mg/kg bw, i.p.) or gemcitabine (GEM, 100 mg/kg bw, i.p.) prior to vaccination (lysate of a gastrointestinal tumor allograft, 10 mg/kg bw, n = 9 mice/group). The vaccine was given repetitively (10 mg/kg bw, s.c., 4 x / once a week, followed by monthly boosts) until tumor formation or progression. Tumor growth ([18F] FDG PET/CT imaging) and immune responses were monitored (flow cytometry, IFNγ ELISpot). The microenvironment was analyzed by immunofluorescence.ResultsProphylactic application of GEM + lysate delayed tumorigenesis compared to lysate monotherapy and CPX-pre-treatment (median time of onset: 53 vs. 47 vs. 48 weeks). 33% of mice even remained tumor-free until the experimental endpoint (= 65 weeks). This was accompanied by long-term effect on cytokine plasma levels; splenic myeloid derived suppressor cells (MDSC) as well as regulatory T cell numbers. Assessment of tumor microenvironment from GEM + lysate treated mice revealed low numbers of MDSCs, but enhanced T cell infiltration, in some cases co-expressing PD-L1. Therapeutic chemo-immunotherapy (GEM + lysate) had minor impact on overall survival (median time: 12 (GEM + lysate) vs. 11.5 (lysate) vs. 3 weeks (control)), but induced complete remission in one case. Dendritic and T cell infiltrates increased in both treatment groups. Reactive T cells specifically recognized MLH1-/- tumor cells in IFNγ ELISpot, but lacked response towards NK cell targets YAC-1.ConclusionsCombined chemo-immunotherapy impairs tumor onset and growth likely attributable to modulation of immune responses. Depleting or 're-educating' immunosuppressive cell types, such as MDSC, may help moving a step closer to combat cancer.

Project description:Immunotherapy has gained great momentum with chimeric antigen receptor T cell (CAR-T) therapy, in which patient's T lymphocytes are genetically manipulated to recognize tumor-specific antigens, increasing tumor elimination efficiency. In recent years, CAR-T cell immunotherapy for hematological malignancies achieved a great response rate in patients and is a very promising therapy for several other malignancies. Each new CAR design requires a preclinical proof-of-concept experiment using immunodeficient mouse models. The absence of a functional immune system in these mice makes them simple and suitable for use as mathematical models. In this work, we develop a three-population mathematical model to describe tumor response to CAR-T cell immunotherapy in immunodeficient mouse models, encompassing interactions between a non-solid tumor and CAR-T cells (effector and long-term memory). We account for several phenomena, such as tumor-induced immunosuppression, memory pool formation, and conversion of memory into effector CAR-T cells in the presence of new tumor cells. Individual donor and tumor specificities are considered uncertainties in the model parameters. Our model is able to reproduce several CAR-T cell immunotherapy scenarios, with different CAR receptors and tumor targets reported in the literature. We found that therapy effectiveness mostly depends on specific parameters such as the differentiation of effector to memory CAR-T cells, CAR-T cytotoxic capacity, tumor growth rate, and tumor-induced immunosuppression. In summary, our model can contribute to reducing and optimizing the number of in vivo experiments with in silico tests to select specific scenarios that could be tested in experimental research. Such an in silico laboratory is an easy-to-run open-source simulator, built on a Shiny R-based platform called CARTmath. It contains the results of this manuscript as examples and documentation. The developed model together with the CARTmath platform have potential use in assessing different CAR-T cell immunotherapy protocols and its associated efficacy, becoming an accessory for in silico trials.

Dataset Information

A mathematical model for treatment using chemo-immunotherapy.

Publications

A mathematical model for treatment using chemo-immunotherapy.

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