Modeling Macrophage Polarization and Its Effect on Cancer Treatment Success

Modelling the Tumour Microenvironment, but What Exactly Do We Mean by "Model"?

The Oxford English Dictionary includes 17 definitions for the word "model" as a noun and another 11 as a verb. Therefore, context is necessary to understand the meaning of the word model. For instance, "model railways" refer to replicas of railways and trains at a smaller scale and a "model student" refers to an exemplary individual. In some cases, a specific context, like cancer research, may not be sufficient to provide one specific meaning for model. Even if the context is narrowed, specifically, to research related to the tumour microenvironment, "model" can be understood in a wide variety of ways, from an animal model to a mathematical expression. This paper presents a review of different "models" of the tumour microenvironment, as grouped by different definitions of the word into four categories: model organisms, in vitro models, mathematical models and computational models. Then, the frequencies of different meanings of the word "model" related to the tumour microenvironment are measured from numbers of entries in the MEDLINE database of the United States National Library of Medicine at the National Institutes of Health. The frequencies of the main components of the microenvironment and the organ-related cancers modelled are also assessed quantitatively with specific keywords. Whilst animal models, particularly xenografts and mouse models, are the most commonly used "models", the number of these entries has been slowly decreasing. Mathematical models, as well as prognostic and risk models, follow in frequency, and these have been growing in use.

CAXII inhibitors: Potential sensitizers for immune checkpoint inhibitors in HCC treatment

Hepatocellular carcinoma (HCC) is a lethal malignancy with a lack of effective treatments particularly for the disease at an advanced stage. Even though immune checkpoint inhibitors (ICIs) have made great progress in the treatment of HCC, durable and ideal clinical benefits still cannot be achieved in plenty of patients with HCC. Therefore, novel and refined ICI-based combination therapies are still needed to enhance the therapeutic effect. The latest study has reported that the carbonic anhydrase XII inhibitor (CAXIIi), a novel type of anticancer drug, can modify the tumor immunosuppression microenvironment by affecting hypoxic/acidic metabolism and alter the functions of monocytes and macrophages by regulating the expression of C-C motif chemokine ligand 8 (CCL8). These observations shine a light on improving programmed cell death protein 1 (PD-1)/programmed cell death ligand-1 (PD-L1) immunotherapy in combination with CAXIIis. This mini-review aims to ignite enthusiasm to explore the potential application of CAXIIis in combination with immunotherapy for HCC.

Betulinic Acid Inhibits the Stemness of Gastric Cancer Cells by Regulating the GRP78-TGF-β1 Signaling Pathway and Macrophage Polarization

Cancer stemness is the process by which cancer cells acquire chemoresistance and self-renewal in the tumor microenvironment. Glucose-regulated protein 78 (GRP78) is a biomarker for gastric cancer and is involved in cancer stemness. By inducing cancer stemness in various types of cancer, the polarization of macrophages into tumor-associated macrophages (TAMs) controls tumor progression. Betulinic acid (BA) is a bioactive natural compound with anticancer properties. However, whether GRP78 regulates TAM-mediated cancer stemness in the tumor microenvironment and whether BA inhibits GRP78-mediated cancer stemness in gastric cancer remain unknown. In this study, we investigated the role of GRP78 in gastric cancer stemness in a tumor microenvironment regulated by BA. The results indicated that BA inhibited not only GRP78-mediated stemness-related protein expression and GRP78-TGF-β-mediated macrophage polarization into TAMs, but also TAM-mediated cancer stemness. Therefore, BA is a promising candidate for clinical application in combination-chemotherapy targeting cancer stemness.

Mathematical Modeling and Analysis of CD200-CD200R in Cancer Treatment

CD200 is a cell membrane protein that binds to its receptor, CD200 receptor (CD200R). The CD200 positive tumor cells inhibit the cellular functions of M1 and M2 macrophages and dendritic cells (DCs) through the CD200-CD200R complex, resulting in downregulation of Interleukin-10 and Interleukin-12 productions and affecting the activation of cytotoxic T lymphocytes. In this work, we provide two ordinary differential equation models, one complete model and one simplified model, to investigate how the binding affinities of CD200R and the populations of M1 and M2 macrophages affect the functions of the CD200-CD200R complex in tumor growth. Our simulations demonstrate that (i) the impact of the CD200-CD200R complex on tumor promotion or inhibition highly depends on the binding affinity of the CD200R on M2 macrophages and DCs to the CD200 on tumor cells, and (ii) a stronger binding affinity of the CD200R on M1 macrophages or DCs to the CD200 on tumor cells induces a higher tumor cell density in the CD200 positive tumor. Thus, the CD200 blockade would be an efficient treatment method in this case. Moreover, the simplified model shows that the binding affinity of CD200R on macrophages is the major factor to determine the treatment efficacy of CD200 blockade when the binding affinities of CD200R on M1 and M2 macrophages are significantly different to each other. On the other hand, both the binding affinity of CD200R and the population of macrophages are the major factors to determine the treatment efficacy of CD200 blockade when the binding affinities of CD200R on M1 and M2 macrophages are close to each other. We also analyze the simplified model to investigate the dynamics of the positive and trivial equilibria of the CD200 positive tumor case and the CD200 deficient tumor case. The bifurcation diagrams show that when M1 macrophages dominate the population, the tumor cell density of the CD200 positive tumor is higher than the one of CD200 deficient tumor. Moreover, the dynamics of tumor cell density change from tumor elimination to tumor persistence to oscillation, as the maximal proliferation rate of tumor cells increases.

Mathematical investigation into the role of macrophage heterogeneity on the temporal and spatio-temporal dynamics of non-small cell lung cancers

Non Small Cell Lung Cancer (NSCLC) is the most common type of lung cancer, and represents the leading cause of cancer-related deaths worldwide. Experimental studies have shown that these solid cancers are heavily infiltrated with macrophages: anti-tumour M1 macrophages, pro-tumour M2 macrophages, and macrophage subtypes sharing both M1 and M2 properties. In this study we aim to investigate qualitatively the role of macrophages with different functional phenotypes (especially those with mixed phenotypes) on cancer dynamics and the success of different immunotherapies for cancer. To this end, we start with two time-evolving mathematical models for cancer-immune interactions that consider: (i) the effect of the two extreme phenotypes, M1 and M2 cells; (ii) the effect of M1 and M2 cells, as well as a macrophage sub-population with a mixed phenotype (throughout this theoretical study we call these cells "M12 cells"). We compare the dynamics of the two models using computational approaches, paying particular attention to the effect of different anti-cancer immunotherapies that focus on macrophages. Since data available for NSCLC and macrophage interactions are incomplete, we perform a global sensitivity analysis to see the influence of input parameters on model outcomes. Finally, we consider extensions of the previous two models to include also the spatial movement of cells, and investigate the role of macrophages with extreme phenotypes and with mixed phenotypes, on the invasion of cancer cells into the surrounding extracellular matrix (ECM). We use numerical simulations to investigate the macrophages phenotypes at the tumour center versus the invasive margin. Again, we examine the impact of immunotherapies for cancer on the spatial dynamics of cancers and immune cells, and observe a shift in the phenotype of macrophages distributed at the tumour center and invasive margin.

A NEW MATHEMATICAL MODELING AND SUB-OPTIMAL CHEMOTHERAPY OF CANCER

The development of more accurate cancer mathematical models leads to present more realistic treatment protocols, especially in model-based treatment protocol design. Hence, a cancer mathematical model is presented by considering tumor cells, immune cells, interleukins, macrophages polarization, and chemotherapy based on biological concepts. Both local and global sensitivity analyses are done to examine the effect of changing the parameters on the final tumor population. Then, the tumor-free equilibrium points of the system are derived, and their stabilities are studied. The main target of chemotherapy is to eliminate the tumor while limiting drug toxicity. The SDRE method is used to construct a sub-optimal control strategy by using the developed nonlinear cancer model. For simulation, three patients are considered: a young patient, an old patient, and a pregnant patient. These cases have different immune system strengths. Also, three initial tumor sizes are regarded for each case. So, different treatment strategies are suggested. Eradication of tumor cells in a finite duration with a desired amount of chemo-drug is shown in the simulation results. The results confirmed that the immune system’s ability plays an important role in treatment success. It is shown that there are different treatment protocols for different patients, and the SDRE method is more flexible and effective than the others.

Bifurcation and sensitivity analysis reveal key drivers of multistability in a model of macrophage polarization

In this paper, we present and analyze a mathematical model for polarization of a single macrophage which, despite its simplicity, exhibits complex dynamics in terms of multistability. In particular, we demonstrate that an asymmetry in the regulatory mechanisms and parameter values is important for observing multiple phenotypes. Bifurcation and sensitivity analyses show that external signaling cues are necessary for macrophage commitment and emergence to a phenotype, but that the intrinsic macrophage pathways are equally important. Based on our numerical results, we formulate hypotheses that could be further investigated by laboratory experiments to deepen our understanding of macrophage polarization.

Recombinant Newcastle disease virus expressing human IFN-λ1 (rL-hIFN-λ1) inhibits lung cancer migration through repolarizating macrophage from M2 to M1 phenotype

BACKGROUND

Tumor-associated macrophages (TAMs) are frequently infiltrated in tumor microenvironment and promote tumor progression. Lung cancer development largely depends upon the essential contributions from the TAMs which generally polarize into M2 TAMs and produce abundant anti-inflammatory factors and facilitate tumor development. The recombinant Newcastle disease virus expressing human IFN-λ1 (rL-hIFN-λ1) could regulate Th1/Th2 immune response to produce anti-tumor microenvironment. However, the interaction between rL-hIFN-λ1 and macrophages polarization remains unclear.

METHODS

The THP-1 cells were used to construct the THP-1-M0, THP-1-M1, THP-1-M2 and THP-1-rL-hIFN-λ1 macrophage models. qRT-PCR and Immunofluorescence were used to detect the polarization phenotype of macrophage polarized by rL-hIFN-λ1. The inhibitory properties of THP-rL-hIFN-λ1 on A549 cells and H446 cells were determined by a Clonogenic assay, as well as scratch migration assays and Transwell were used to explore the capability of migration. Furthermore, the M1/M2 infiltration density in different clinical stages of lung cancer tissues were examined.

RESULTS

It was showed that rL-hIFN-λ1 could induce normal macrophages to differentiate into THP-1-M1 macrophages. Meanwhile, rL-hIFN-λ1 could also direct THP-1-M2 macrophages polarization into THP-1-M1 macrophages. Supernatants from rL-hIFN-λl induced macrophages inhibited colony formation, migration and invasion of lung cancer cells in vitro which was similar to THP-1-M1 macrophages. Moreover, analysis of clinical tumor tissues indicated that M1-type macrophages decreased gradually with the development of the clinical stage of lung cancer.

CONCLUSIONS

Therefore, rL-hIFN-λl induced significant suppression of primary lung tumor growth and spontaneous lung metastases through regulating macrophages function, and it was expected to become a new biological therapy for lung cancer.