The role of CD200-CD200R in tumor immune evasion

CD200R promotes high glucose-induced oxidative stress and damage in human retinal pigment epithelial cells by activating the mTOR signaling pathway

Diabetic retinopathy (DR) is established as the primary cause of visual impairment and preventable blindness, posing significant social and economic burdens on healthcare systems worldwide. Oxidative stress has been identified as a major contributor to DR, yet the precise role of the transmembrane glycoprotein CD200R in this context remains elusive. We studied human retinal pigment epithelia ARPE-19 cells to investigate the role of CD200R in high-glucose (HG) induced oxidative stress. Under HG conditions, we found a significant increase in CD200R expression in a time-dependent pattern. Conversely, knockdown of CD200R effectively alleviated oxidative stress and restored cell viability in HG-treated ARPE-19 cells, a phenomenon corroborated by the addition of a reactive oxygen species (ROS) scavenger. Exploration of the AKT/mTOR signaling pathway confirmed its mediating role regarding CD200R knockdown suppression of the expression of key proteins induced by HG conditions. Additionally, we found that the inhibition of mTOR signaling with Rapamycin effectively countered HG-induced oxidative stress in ARPE-19 cells, suggesting a promising therapeutic target against oxidative stress in the context of DR. This study establishes the crucial role of CD200R in HG-induced oxidative stress and identifies potential therapeutic avenues for the treatment of DR.

Translation of Data from Animal Models of Cancer to Immunotherapy of Breast Cancer and Chronic Lymphocytic Leukemia

The field of clinical oncology has been revolutionized over the past decade with the introduction of many new immunotherapies the existence of which have depended to a large extent on experimentation with both in vitro analysis and the use of various animal models, including gene-modified mice. The discussion below will review my own laboratory's studies, along with those of others in the field, on cancer immunotherapy. Our own studies have predominantly dwelt on two models of malignancy, namely a solid tumor model (breast cancer) and lymphoma. The data from our own laboratory, and that of other scientists, highlights the novel information so obtained, and the evidence that application of such information has already had an impact on immunotherapy of human oncologic diseases.

Different mechanisms of CD200-CD200R induce diverse outcomes in cancer treatment

The CD200 is a cell membrane protein expressed by tumor cells, and its receptor CD200 receptor (CD200R) is expressed by immune cells including macrophages and dendritic cells. The formation of CD200-CD200R inhibits the cellular functions of the targeted immune cells, so CD200 is one type of the immune checkpoint and blockade CD200-CD200R formation is a potential cancer treatment. However, the CD200 blockade has opposite treatment outcomes in different types of cancers. For instance, the CD200R deficient mice have a higher tumor load than the wild type (WT) mice in melanoma suggesting that CD200-CD200R inhibits melanoma. On the other hand, the antibody anti-CD200 treatment in pancreatic ductal adenocarcinoma (PDAC) and head and neck squamous cell carcinoma (HNSCC) significantly reduces the tumor load indicating that CD200-CD200R promotes PDAC and HNSCC. In this work, we hypothesize that different mechanisms of CD200-CD200R in tumor microenvironment could be one of the reasons for the diverse treatment outcomes of CD200 blockade in different types of cancers. We create one Ordinary Differential Equations (ODEs) model for melanoma including the inhibition of CCL8 and regulatory T cells and the switching from M2 to M1 macrophages by CD200-CD200R to capture the tumor inhibition by CD200-CD200R. We also create another ODEs model for PDAC and HNSCC including the promotion of the polarization and suppressive activities of M2 macrophages by CD200-CD200R to generate the tumor promotion by CD200-CD200R. Furthermore, we use these two models to investigate the treatment efficacy of the combination treatment between the CD200-CD200R blockade and the other immune checkpoint inhibitor, anti-PD-1. Our result shows that different mechanisms of CD200-CD200R can induce different treatment outcomes in combination treatments, namely, only the CD200-CD200R blockade reduces tumor load in melanoma and only the anti-PD-1 and CD200 knockout decrease tumor load in PDAC and HNSCC. Moreover, in melanoma, the CD200-CD200R mainly utilizes the inhibitions on M1 macrophages and dendritic cells to inhibit tumor growth, instead of M2 macrophages.

Emerging Immune Checkpoint Molecules on Cancer Cells: CD24 and CD200

Cancer immunotherapy strategies are based on the utilization of immune checkpoint inhibitors to instigate an antitumor immune response. The efficacy of immune checkpoint blockade, directed at adaptive immune checkpoints, has been demonstrated in select cancer types. However, only a limited subset of patients has exhibited definitive outcomes characterized by a sustained response after discontinuation of therapy. Recent investigations have highlighted the significance of immune checkpoint molecules that are overexpressed in cancer cells and inhibit myeloid lineage immune cells within a tumor microenvironment. These checkpoints are identified as potential targets for anticancer immune responses. Notably, the immune checkpoint molecules CD24 and CD200 have garnered attention owing to their involvement in tumor immune evasion. CD24 and CD200 are overexpressed across diverse cancer types and serve as signaling checkpoints by engaging their respective receptors, Siglec-10 and CD200 receptor, which are expressed on tumor-associated myeloid cells. In this review, we summarized and discussed the latest advancements and insights into CD24 and CD200 as emergent immune checkpoint moieties, further delving into their therapeutic potentials for cancer treatment.

Investigating the spatial interaction of immune cells in colon cancer

The intricate network of interactions between cells and molecules in the tumor microenvironment creates a heterogeneous ecosystem. The proximity of the cells and molecules to their activators and inhibitors is essential in the progression of tumors. Here, we develop a system of partial differential equations coupled with linear elasticity to investigate the effects of spatial interactions on the tumor microenvironment. We observe interesting cell and cytokine distribution patterns, which are heavily affected by macrophages. We also see that cytotoxic T cells get recruited and suppressed at the site of macrophages. Moreover, we observe that anti-tumor macrophages reorganize the patterns in favor of a more spatially restricted cancer and necrotic core. Furthermore, the adjoint-based sensitivity analysis indicates that the most sensitive model's parameters are directly related to macrophages. The results emphasize the widely acknowledged effect of macrophages in controlling cancer cells population and spatially arranging cells in the tumor microenvironment.

Bio-Mechanical Model of Osteosarcoma Tumor Microenvironment: A Porous Media Approach

Osteosarcoma is the most common malignant bone tumor in children and adolescents with a poor prognosis. To describe the progression of osteosarcoma, we expanded a system of data-driven ODE from a previous study into a system of Reaction-Diffusion-Advection (RDA) equations and coupled it with Biot equations of poroelasticity to form a bio-mechanical model. The RDA system includes the spatio-temporal information of the key components of the tumor microenvironment. The Biot equations are comprised of an equation for the solid phase, which governs the movement of the solid tumor, and an equation for the fluid phase, which relates to the motion of cells. The model predicts the total number of cells and cytokines of the tumor microenvironment and simulates the tumor's size growth. We simulated different scenarios using this model to investigate the impact of several biomedical settings on tumors' growth. The results indicate the importance of macrophages in tumors' growth. Particularly, we have observed a high co-localization of macrophages and cancer cells, and the concentration of tumor cells increases as the number of macrophages increases.

Current perspectives and trend of nanomedicine in cancer: A review and bibliometric analysis

The limitations of traditional cancer treatments are driving the creation and development of new nanomedicines. At present, with the rapid increase of research on nanomedicine in the field of cancer, there is a lack of intuitive analysis of the development trend, main authors and research hotspots of nanomedicine in the field of cancer, as well as detailed elaboration of possible research hotspots. In this review, data collected from the Web of Science Core Collection database between January 1st, 2000, and December 31st, 2021, were subjected to a bibliometric analysis. The co-authorship, co-citation, and co-occurrence of countries, institutions, authors, literature, and keywords in this subject were examined using VOSviewer, Citespace, and a well-known online bibliometrics platform. We collected 19,654 published papers, China produced the most publications (36.654%, 7204), followed by the United States (29.594%, 5777), and India (7.780%, 1529). An interesting fact is that, despite China having more publications than the United States, the United States still dominates this field, having the highest H-index and the most citations. Acs Nano, Nano Letters, and Biomaterials are the top three academic publications that publish articles on nanomedicine for cancer out of a total of 7580 academic journals. The most significant increases were shown for the keywords "cancer nanomedicine", "tumor microenvironment", "nanoparticles", "prodrug", "targeted nanomedicine", "combination", and "cancer immunotherapy" indicating the promising area of research. Meanwhile, the development prospects and challenges of nanomedicine in cancer are also discussed and provided some solutions to the major obstacles.

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.

Prediction of the atherosclerotic plaque development in carotid arteries; the effect of T-cells

The carotid artery disease is one of the leading causes of mortality worldwide, as it leads to the progressive arterial stenosis that may result to stroke. To address this issue, the scientific community is attempting not only to enrich our knowledge on the underlying atherosclerotic mechanisms, but also to enable the prediction of the atherosclerotic progression. This study investigates the role of T-cells in the atherosclerotic plaque growth process through the implementation of a computational model in realistic geometries of carotid arteries. T-cells mediate in the inflammatory process by secreting interferon-y that enhances the activation of macrophages. In this analysis, we used 5 realistic human carotid arterial segments as input to the model. In particular, magnetic resonance imaging data, as well as, clinical data were collected from the patients at two time points. Using the baseline data, plaque growth was predicted and correlated to the follow-up arterial geometries. The results exhibited a very good agreement between them, presenting a high coefficient of determination R²=0.64.

A PDE Model of Breast Tumor Progression in MMTV-PyMT Mice

The evolution of breast tumors greatly depends on the interaction network among different cell types, including immune cells and cancer cells in the tumor. This study takes advantage of newly collected rich spatio-temporal mouse data to develop a data-driven mathematical model of breast tumors that considers cells' location and key interactions in the tumor. The results show that cancer cells have a minor presence in the area with the most overall immune cells, and the number of activated immune cells in the tumor is depleted over time when there is no influx of immune cells. Interestingly, in the case of the influx of immune cells, the highest concentrations of both T cells and cancer cells are in the boundary of the tumor, as we use the Robin boundary condition to model the influx of immune cells. In other words, the influx of immune cells causes a dominant outward advection for cancer cells. We also investigate the effect of cells' diffusion and immune cells' influx rates in the dynamics of cells in the tumor micro-environment. Sensitivity analyses indicate that cancer cells and adipocytes' diffusion rates are the most sensitive parameters, followed by influx and diffusion rates of cytotoxic T cells, implying that targeting them is a possible treatment strategy for breast cancer.

Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model

The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven mathematical model to investigate the dynamics of key cell types and cytokines involved in breast cancer development. We use time-course gene expression profiles of a mouse model to estimate the relative abundance of cells and cytokines. We then employ a least-squares optimization method to evaluate the model’s parameters based on the mice data. The resulting dynamics of the cells and cytokines obtained from the optimal set of parameters exhibit a decent agreement between the data and predictions. We perform a sensitivity analysis to identify the crucial parameters of the model and then perform a local bifurcation on them. The results reveal a strong connection between adipocytes, IL6, and the cancer population, suggesting them as potential targets for therapies.

One of the outstanding challenges of the mathematical modeling of cancer progression is the existence of many unknown parameters. In this work, we develop a data-driven mathematical model of breast cancer progression by deriving a system of ordinary differential equations for the interaction networks of key cell types and molecules in breast tumors. To overcome the limitations of unknown parameters, we utilize a time course data of a PyMT mice model of breast cancer and estimate parameters using an optimization method. Although the predicted dynamics of cancer and necrotic cells using the obtained values of parameters are in good agreement with the data, the predicted values for a few other variables do not match the data. This might indicate that there are some other key interactions that have not been modeled, and/or there is a noise in the data. The sensitivity and bifurcation analyses show that the most important parameters in controlling the cancer cells population are the proliferation and death rates of cancer cells and adipocytes. These results are in agreement with some biological and clinical studies of breast cancer, which have reported a link between adipocytes and breast cancer progression.

CD200 expression in hematopoietic neoplasms: Beyond a marker for diagnosis of B-cell neoplasms

CD200 (OX-2) is expressed in myeloid cells, B cells, subsets of T cells and on other normal and neoplastic non-hematopoietic cells. It interacts with CD200R and has a suppressive effect on T cells immune mediated response. We aimed to review CD200 expression and its role in the immune evasion of non-B cell hematopoietic neoplasms. In acute myeloid leukemia, CD200 seems to be related to the worst outcome, even in diseases of good prognosis, possibly due to an immunosuppressive effect. In plasma cell myeloma studies, while some have associated CD200 expression with worst prognosis possibly due to its suppressive effect on monocyte and T cell-mediated immune response, in others CD200 appeared to be a marker of a better outcome, or even showed no impact in event-free survival (EFS). Few studies have evaluated CD200 expression in T cell neoplasms; however, it appears to be a good immunophenotypic marker for angioimmunoblastic T cell lymphoma. In conclusion, CD200 appears to be involved in the immune evasion of malignant cells, which could affect the survival of these patients.

Implications of immune-mediated metastatic growth on metastatic dormancy, blow-up, early detection, and treatment

Metastatic seeding of distant organs can occur in the very early stages of primary tumor development. Once seeded, these micrometastases may enter a dormant phase that can last decades. Curiously, the surgical removal of the primary tumor can stimulate the accelerated growth of distant metastases, a phenomenon known as metastatic blow-up. Recent clinical evidence has shown that the immune response can have strong tumor promoting effects. In this work, we investigate if the pro-tumor effects of the immune response can have a significant contribution to metastatic dormancy and metastatic blow-up. We develop an ordinary differential equation model of the immune-mediated theory of metastasis. We include both anti- and pro-tumor immune effects, in addition to the experimentally observed phenomenon of tumor-induced immune cell phenotypic plasticity. Using geometric singular perturbation analysis, we derive a rather simple model that captures the main processes and, at the same time, can be fully analyzed. Literature-derived parameter estimates are obtained, and model robustness is demonstrated through a time dependent sensitivity analysis. We determine conditions under which the parameterized model can successfully explain both metastatic dormancy and blow-up. The results confirm the significant active role of the immune system in the metastatic process. Numerical simulations suggest a novel measure to predict the occurrence of future metastatic blow-up in addition to new potential avenues for treatment of clinically undetectable micrometastases.

Functional and Phenotypic Characterization of Tumor-Infiltrating Leukocyte Subsets and Their Contribution to the Pathogenesis of Hepatocellular Carcinoma and Cholangiocarcinoma

Hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA) represent the most common primary liver malignancies whose outcome is influenced by the immune response. In the present study, we evaluated the tumor-infiltrating leukocyte (TIL) populations in 21 HCC patients and 8 CCA patients by flow cytometry immediately after the surgical procedure. Moreover, CD4⁺ T cells, CD8⁺ T cells, monocytes, and macrophages were purified by cell sorting for further analysis of gene expression by quantitative reverse-transcription polymerase chain reaction. Regarding tumor-infiltrating macrophages, we observed a significantly higher expression of markers associated with M2 phenotype and a higher expression of PD-L1 in patients with HCC in comparison to CCA. In addition, for HCC patients, we found a significant increase in the expression of CD200R in macrophages from tumors that were in grade G3-G4 as compared to tumors in grade G1-G2. Besides, a significantly higher frequency of tumor-infiltrating lymphocytes, CD8⁺CD56⁺ T cells, and natural killer cells was detected in HCC biopsies in comparison to CCA. In summary, this study has revealed functional and phenotypic differences in TIL cell subpopulations between CCA and HCC, as well as among different histopathological grades and tumor aggressiveness degrees, and it has provided evidence to better understand the tumor immune microenvironment of CCA and HCC.

Tumor-derived vaccines containing CD200 inhibit immune activation: implications for immunotherapy

There are over 400 ongoing clinical trials using tumor-derived vaccines. This approach is especially attractive for many types of brain tumors, including glioblastoma, yet so far the clinical response is highly variable. One contributor to poor response is CD200, which acts as a checkpoint blockade, inducing immune tolerance. We demonstrate that, in response to vaccination, glioma-derived CD200 suppresses the anti-tumor immune response. In contrast, a CD200 peptide inhibitor that activates antigen-presenting cells overcomes immune tolerance. The addition of the CD200 inhibitor significantly increased leukocyte infiltration into the vaccine site, cytokine and chemokine production, and cytolytic activity. Our data therefore suggest that CD200 suppresses the immune system's response to vaccines, and that blocking CD200 could improve the efficacy of cancer immunotherapy.

Delineation of an immunosuppressive gradient in hepatocellular carcinoma using high-dimensional proteomic and transcriptomic analyses

The recent development of immunotherapy as a cancer treatment has proved effective over recent years, but the precise dynamics between the tumor microenvironment (TME), nontumor microenvironment (NTME), and the systemic immune system remain elusive. Here, we interrogated these compartments in hepatocellular carcinoma (HCC) using high-dimensional proteomic and transcriptomic analyses. By time-of-flight mass cytometry, we found that the TME was enriched in regulatory T cells (Tregs), tissue resident memory CD8⁺ T cells (T_RMs), resident natural killer cells (NK_Rs), and tumor-associated macrophages (TAMs). This finding was also validated with immunofluorescence staining on Foxp3⁺CD4⁺ and PD-1⁺CD8⁺ T cells. Interestingly, Tregs and T_RMs isolated from the TME expressed multiple markers for T-cell exhaustion, including PD-1, Lag-3, and Tim-3 compared with Tregs and T_RMs isolated from the NTME. We found PD-1⁺ T_RMs were the predominant T-cell subset responsive to anti-PD-1 treatment and significantly reduced in number with increasing HCC tumor progression. Furthermore, T-bet was identified as a key transcription factor, negatively correlated with PD-1 expression on memory CD8⁺ T cells, and the PD-1:T-bet ratio increased upon exposure to tumor antigens. Finally, transcriptomic analysis of tumor and adjacent nontumor tissues identified a chemotactic gradient for recruitment of TAMs and NK_Rs via CXCR3/CXCL10 and CCR6/CCL20 pathways, respectively. Taken together, these data confirm the existence of an immunosuppressive gradient across the TME, NTME, and peripheral blood in primary HCC that manipulates the activation status of tumor-infiltrating leukocytes and renders them immunocompromised against tumor cells. By understanding the immunologic composition of this gradient, more effective immunotherapeutics for HCC may be designed.

Activation of Macrophages in Response to Biomaterials

Macrophages are the initial biologic responders to biomaterials. These highly plastic immune sentinels control and modulate responses to materials, foreign or natural. The responses may vary from immune stimulatory to immune suppressive. Several parameters have been identified that influence macrophage response to biomaterials, specifically size, geometry, surface topography, hydrophobicity, surface chemistry, material mechanics, and protein adsorption. In this review, the influence of these parameters is supported with examples of both synthetic and naturally derived materials and illustrates that a combination of these parameters ultimately influences macrophage responses to the biomaterial. Having an understanding of these properties may lead to highly efficient design of biomaterials with desirable biologic response properties.

Mathematical modeling of Interleukin-35 promoting tumor growth and angiogenesis

Interleukin-35 (IL-35), a cytokine from the Interleukin-12 cytokine family, has been considered as an anti-inflammatory cytokine which promotes tumor progression and tumor immune evasion. It has also been demonstrated that IL-35 is secreted by regulatory T cells. Recent mouse experiments have shown that IL-35 produced by cancer cells promotes tumor growth via enhancing myeloid cell accumulation and angiogenesis, and reducing the infiltration of activated CD8[Formula: see text] T cells into tumor microenvironment. In the present paper we develop a mathematical model based on these experimental results. We include in the model an anti-IL-35 drug as treatment. The extended model (with drug) is used to design protocols of anti-IL-35 injections for treatment of cancer. We find that with a fixed total amount of drug, continuous injection has better efficacy than intermittent injections in reducing the tumor load while the treatment is ongoing. We also find that the percentage of tumor reduction under anti-IL-35 treatment improves when the production of IL-35 by cancer is increased.

Mathematical modeling of interleukin-27 induction of anti-tumor T cells response

Interleukin-12 is a pro-inflammatory cytokine which promotes Th1 and cytotoxic T lymphocyte activities, such as Interferon- secretion. For this reason Interleukin-12 could be a powerful therapeutic agent for cancer treatment. However, Interleukin-12 is also excessively toxic. Interleukin-27 is an immunoregulatory cytokine from the Interleukin-12 family, but it is not as toxic as Interleukin-12. In recent years, Interleukin-27 has been considered as a potential anti-tumor agent. Recent experiments in vitro and in vivo have shown that cancer cells transfected with IL-27 activate CD8⁺ T cells to promote the secretion of anti-tumor cytokines Interleukin-10, although, at the same time, IL-27 inhibits the secretion of Interferon- by CD8⁺ T cells. In the present paper we develop a mathematical model based on these experimental results. The model involves a dynamic network which includes tumor cells, CD8⁺ T cells and cytokines Interleukin-27, Interleukin-10 and Interferon-. Simulations of the model show how Interleukin-27 promotes CD8⁺ T cells to secrete Interleukin-10 to inhibit tumor growth. On the other hand Interleukin-27 inhibits the secretion of Interferon- by CD8⁺ T cells which somewhat diminishes the inhibition of tumor growth. Our numerical results are in qualitative agreement with experimental data. We use the model to design protocols of IL-27 injections for the treatment of cancer and find that, for some special types of cancer, with a fixed total amount of drug, within a certain range, continuous injection has better efficacy than intermittent injections in reducing the tumor load while the treatment is ongoing, although the decrease in tumor load is only temporary.

The LDL-HDL profile determines the risk of atherosclerosis: a mathematical model

Atherosclerosis, the leading death in the United State, is a disease in which a plaque builds up inside the arteries. As the plaque continues to grow, the shear force of the blood flow through the decreasing cross section of the lumen increases. This force may eventually cause rupture of the plaque, resulting in the formation of thrombus, and possibly heart attack. It has long been recognized that the formation of a plaque relates to the cholesterol concentration in the blood. For example, individuals with LDL above 190 mg/dL and HDL below 40 mg/dL are at high risk, while individuals with LDL below 100 mg/dL and HDL above 50 mg/dL are at no risk. In this paper, we developed a mathematical model of the formation of a plaque, which includes the following key variables: LDL and HDL, free radicals and oxidized LDL, MMP and TIMP, cytockines: MCP-1, IFN-γ, IL-12 and PDGF, and cells: macrophages, foam cells, T cells and smooth muscle cells. The model is given by a system of partial differential equations with in evolving plaque. Simulations of the model show how the combination of the concentrations of LDL and HDL in the blood determine whether a plaque will grow or disappear. More precisely, we create a map, showing the risk of plaque development for any pair of values (LDL,HDL).