Data-Driven Mathematical Model of Osteosarcoma

As the immune system has a significant role in tumor progression, in this paper, we develop a data-driven mathematical model to study the interactions between immune cells and the osteosarcoma microenvironment. Osteosarcoma tumors are divided into three clusters based on their relative abundance of immune cells as estimated from their gene expression profiles. We then analyze the tumor progression and effects of the immune system on cancer growth in each cluster. Cluster 3, which had approximately the same number of naive and M2 macrophages, had the slowest tumor growth, and cluster 2, with the highest population of naive macrophages, had the highest cancer population at the steady states. We also found that the fastest growth of cancer occurred when the anti-tumor immune cells and cytokines, including dendritic cells, helper T cells, cytotoxic cells, and IFN-γ, switched from increasing to decreasing, while the dynamics of regulatory T cells switched from decreasing to increasing. Importantly, the most impactful immune parameters on the number of cancer and total cells were the activation and decay rates of the macrophages and regulatory T cells for all clusters. This work presents the first osteosarcoma progression model, which can be later extended to investigate the effectiveness of various osteosarcoma treatments.

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A Comparison of Ex Vivo Expanded Human Regulatory T Cells Using Allogeneic Stimulated B Cells or Monocyte-Derived Dendritic Cells

Frontiers in Immunology ◽

10.3389/fimmu.2021.679675 ◽

2021 ◽

Vol 12 ◽

Author(s):

Linda M. Lee ◽

Hong Zhang ◽

Karim Lee ◽

Horace Liang ◽

Alexander Merleev ◽

...

Keyword(s):

T Cells ◽

Dendritic Cells ◽

B Cells ◽

Regulatory T Cells ◽

Ex Vivo ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Low Frequencies ◽

Almost All

Alloreactive regulatory T cells (arTregs) are more potent than polyclonal Tregs at suppressing immune responses to transplant antigens. Human arTregs can be expanded with allogeneic CD40L-stimulated B cells (sBcs) or stimulated-matured monocyte-derived dendritic cells (sDCs). Here, we compared the expansion efficiency and properties of arTregs stimulated ex vivo using these two types of antigen-presenting cells. Compared to sBcs, sDCs stimulated Tregs to expand two times more in number. The superior expansion-inducing capacity of sDCs correlated with their higher expression of CD80, CD86, and T cell-attracting chemokines. sBc- and sDC-arTregs expressed comparable levels of FOXP3, HELIOS, CD25, CD27, and CD62L, demethylated FOXP3 enhancer and in vitro suppressive function. sBc- and sDCs-arTregs had similar gene expression profiles that were distinct from primary Tregs. sBc- and sDC-arTregs exhibited similar low frequencies of IFN-γ, IL-4, and IL-17A-producing cells, and the cytokine-producing arTregs expressed high levels of FOXP3. Almost all sBc- and sDC-arTregs expressed CXCR3, which may enable them traffic to inflammatory sites. Thus, sDCs-arTregs that expand more readily, are phenotypically similar to sBc-arTregs, supporting sDCs as a viable alternative for arTreg production for clinical evaluation.

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The Multifaceted Role of Regulatory T Cells in Breast Cancer

Annual Review of Cancer Biology ◽

10.1146/annurev-cancerbio-042920-104912 ◽

2020 ◽

Vol 5 (1) ◽

Author(s):

Kevin Kos ◽

Karin E. de Visser

Keyword(s):

Breast Cancer ◽

T Cells ◽

Regulatory T Cells ◽

Tumor Progression ◽

Immune Cells ◽

Cancer Biology ◽

Immune Escape ◽

Breast Cancer Subtype ◽

Annual Review ◽

Publication Date

The microenvironment of breast cancer hosts a dynamic cross talk between diverse players of the immune system. While cytotoxic immune cells are equipped to control tumor growth and metastasis, tumor-corrupted immunosuppressive immune cells strive to impair effective immunity and promote tumor progression. Of these, regulatory T cells (Tregs), the gatekeepers of immune homeostasis, emerge as multifaceted players involved in breast cancer. Intriguingly, clinical observations suggest that blood and intratumoral Tregs can have strong prognostic value, dictated by breast cancer subtype. Accordingly, emerging preclinical evidence shows that Tregs occupy a central role in breast cancer initiation and progression and provide critical support to metastasis formation. Here, Tregs are not only important for immune escape but also promote tumor progression independent of their immune regulatory capacity. Combining insights into Treg biology with advances made across the rapidly growing field of immuno-oncology is expected to set the stage for the design of more effective immunotherapy strategies. Expected final online publication date for the Annual Review of Cancer Biology, Volume 5 is March 4, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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Data Driven Mathematical Model of Colon Cancer Progression

Journal of Clinical Medicine ◽

10.3390/jcm9123947 ◽

2020 ◽

Vol 9 (12) ◽

pp. 3947

Author(s):

Arkadz Kirshtein ◽

Shaya Akbarinejad ◽

Wenrui Hao ◽

Trang Le ◽

Sumeyye Su ◽

...

Keyword(s):

Mathematical Model ◽

Colon Cancer ◽

Cancer Progression ◽

Immune Cell ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Interaction Network ◽

Data Driven ◽

Colon Cancer Progression ◽

Negative Effect

Every colon cancer has its own unique characteristics, and therefore may respond differently to identical treatments. Here, we develop a data driven mathematical model for the interaction network of key components of immune microenvironment in colon cancer. We estimate the relative abundance of each immune cell from gene expression profiles of tumors, and group patients based on their immune patterns. Then we compare the tumor sensitivity and progression in each of these groups of patients, and observe differences in the patterns of tumor growth between the groups. For instance, in tumors with a smaller density of naive macrophages than activated macrophages, a higher activation rate of macrophages leads to an increase in cancer cell density, demonstrating a negative effect of macrophages. Other tumors however, exhibit an opposite trend, showing a positive effect of macrophages in controlling tumor size. Although the results indicate that for all patients the size of the tumor is sensitive to the parameters related to macrophages, such as their activation and death rate, this research demonstrates that no single biomarker could predict the dynamics of tumors.

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Immunology of pregnancy: cellular mechanisms allowing fetal survival within the maternal uterus

Expert Reviews in Molecular Medicine ◽

10.1017/s1462399407000294 ◽

2007 ◽

Vol 9 (10) ◽

pp. 1-14 ◽

Cited By ~ 32

Author(s):

Ana Claudia Zenclussen ◽

Anne Schumacher ◽

Maria Laura Zenclussen ◽

Paul Wafula ◽

Hans-Dieter Volk

Keyword(s):

T Cells ◽

Immune System ◽

Regulatory T Cells ◽

Immune Cells ◽

Heme Oxygenase 1 ◽

Tolerance Mechanisms ◽

Cellular Mechanisms ◽

Fetal Survival ◽

Maternal Immune System ◽

Natural Tolerance

AbstractPregnancy success remains a fascinating phenomenon to immunologists as it defies the immunological rules of rejection. Although it was previously thought that the maternal immune system does not see the fetus, it is now well documented that fetal cells reach the maternal body and encounter host immune cells. Natural tolerance mechanisms following this interaction remain to be fully elucidated. This article reviews the current literature on mechanisms of adaptive immunity, with emphasis on regulatory T cells and heme oxygenase 1 (HO-1). We propose a scenario in which regulatory T cells create a tolerant microenvironment at the fetal–maternal interface characterised by the presence of tolerance-associated molecules such as HO-1, which has been shown to be of vital importance for fetal survival.

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Identification and Validation of the Signatures of Infiltrating Immune Cells in the Eutopic Endometrium Endometria of Women With Endometriosis

Frontiers in Immunology ◽

10.3389/fimmu.2021.671201 ◽

2021 ◽

Vol 12 ◽

Author(s):

Xiang-Guang Wu ◽

Jin-Jiao Chen ◽

Hui-Ling Zhou ◽

Yu Wu ◽

Fei Lin ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

Nk Cells ◽

Immune Cells ◽

Expression Profiles ◽

Embryo Implantation ◽

Gene Expression Profiles ◽

Signalling Pathway ◽

Clinical Samples ◽

Normal Controls

Endometriosis is an oestrogen-dependent chronic inflammatory process with primary symptoms including dysmenorrhea, chronic pelvic pain, and infertility. The immune environment of the endometrium is essential for successful embryo implantation and ongoing pregnancy. In this study, we assessed the composition, density, and distribution of infiltrating immune cells in the endometria of women with endometriosis. Gene expression profiles of endometrial samples were downloaded from the Gene Expression Omnibus (GEO) database. We found that the TNF signalling pathway, the IL-17 signalling pathway, and the MAPK signalling pathway were significantly enriched in the eutopic endometria of women with endometriosis. The fractions and proportion of infiltrating immune cells were estimated by the CIBERSORT, MCP-counter, and ImmuCellAI methods. We found that the proportions of CD8+ T cells, activated NK cells, and follicular helper T cells were significantly higher in the endometria of women with endometriosis than in the endometria of normal controls, while the proportions of M2 macrophages and resting mast cells were significantly lower in the eutopic endometria. In GSE120103 (n = 36), we found that elevated CD8+ T cells in endometriosis increased the risk of infertility (P = 0.0019). The area under the receiver operating characteristic (ROC) curve (AUC) of CD8+ T cells to distinguish fertile and infertile endometriosis was 0.914. In clinical samples (n = 40), we found that the proportions of CD8+ T cells and CD56+ NK cells were significantly higher in the eutopic endometria of women with endometriosis than in the endometria of normal controls, while the proportion of CD163+ macrophages were lower in the eutopic endometria. The AUCs of CD8+ T cells and CD163+ macrophages were 0.727 and 0.833, respectively, which indicated that CD8 and CD163 were potential diagnostic markers for endometriosis. In conclusion, our results demonstrated that increased CD8+ T cells and CD56+ NK cells and decreased CD163+ macrophages within the eutopic endometria of women with endometriosis reveal a proinflammatory feature in the endometrial immune environment and that elevated CD8+ T cells increase the risk of infertility in women with the disease.

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Myeloid-derived suppressor cells at diagnosis may discriminate between benign and malignant ovarian tumors

International Journal of Gynecological Cancer ◽

10.1136/ijgc-2019-000521 ◽

2019 ◽

Vol 29 (9) ◽

pp. 1381-1388 ◽

Cited By ~ 4

Author(s):

An Coosemans ◽

Thaïs Baert ◽

Jolien Ceusters ◽

Pieter Busschaert ◽

Chiara Landolfo ◽

...

Keyword(s):

Ovarian Cancer ◽

T Cells ◽

Immune System ◽

Natural Killer Cells ◽

Regulatory T Cells ◽

Natural Killer ◽

Immune Cells ◽

Suppressor Cells ◽

Myeloid Derived Suppressor Cells ◽

Killer Cells

BackgroundThe behavior of the immune system as a driver in the progression of ovarian cancer has barely been studied. Our knowledge is mainly limited to the intra-tumoral adaptive immune system. Because of the widespread metastases of ovarian cancer, an assessment of the circulating immune system seems more accurate.To demonstrate the presence of immune cells in blood samples of patients with ovarian neoplasms.MethodsIn this exploratory prospective cohort study, peripheral blood mononuclear cells were collected at diagnosis from 143 women, including 62 patients with benign cysts, 13 with borderline tumor, 41 with invasive ovarian cancer, and 27 age-matched healthy controls. Immune profile analyses, based on the presence of CD4 (cluster of differentiation), CD8, natural killer cells, myeloid-derived suppressor cells, and regulatory T cells, were performed by fluorescence activated cell sorting.ResultsIn a multivariable analysis, six immune cells (activated regulatory T cells, natural killer cells, myeloid-derived suppressor cells, monocytic myeloid-derived suppressor cells, exhausted monocytic myeloid-derived suppressor cells, and total myeloid cells) were selected as independent predictors of malignancy, with an optimism-corrected area under the receiver operating characteristic curve (AUC) of 0.858. In contrast, a profile based on CD8 and regulatory T cells, the current standard in ovarian cancer immunology, resulted in an AUC of 0.639.ConclusionsOur immune profile in blood suggests an involvement of innate immunosuppression driven by myeloid-derived suppressor cells in the development of ovarian cancer. This finding could contribute to clinical management of patients and in selection of immunotherapy.

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Mathematical Modelling of the Inhibitory Role of Regulatory T Cells in Tumor Immune Response

Complexity ◽

10.1155/2020/4834165 ◽

2020 ◽

Vol 2020 ◽

pp. 1-21

Author(s):

Zhongtao Yang ◽

Cuihong Yang ◽

Yueping Dong ◽

Yasuhiro Takeuchi

Keyword(s):

T Cells ◽

Immune System ◽

Regulatory T Cells ◽

Immune Cells ◽

Immune Escape ◽

Critical Value ◽

Inhibitory Effect ◽

Tumor Escape ◽

Tumor Immune Escape ◽

Stimulation Rate

The immune system against tumors acts through a complex dynamical process showing a dual role. On the one hand, the immune system can activate some immune cells to kill tumor cells (TCs), such as cytotoxic T lymphocytes (CTLs) and natural killer cells (NKs), but on the other hand, more evidence shows that some immune cells can help tumor escape, such as regulatory T cells (Tregs). In this paper, we propose a tumor immune interaction model based on Tregs-mediated tumor immune escape mechanism. When helper T cells’ (HTCs) stimulation rate by the presence of identified tumor antigens is below critical value, the coexistence (tumor and immune) equilibrium is always stable in its existence region. When HTCs stimulation rate is higher than the critical value, the inhibition rate of effector cells (ECs) by Tregs can destabilize the coexistence equilibrium and cause Hopf bifurcations and produce a limit cycle. This model shows that Tregs might play a crucial role in triggering the tumor immune escape. Furthermore, we introduce the adoptive cellular immunotherapy (ACI) and monoclonal antibody immunotherapy (MAI) as the treatment to boost the immune system to fight against tumors. The numerical results show that ACI can control TCs more, while MAI can delay the inhibitory effect of Tregs on ECs. The result also shows that the combination of both immunotherapies can control TCs and reduce the inhibitory effect of Tregs better than a single immunotherapy can control.

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Data driven mathematical model of colon cancer progression

10.1101/2020.11.02.365668 ◽

2020 ◽

Author(s):

Arkadz Kirshtein ◽

Shaya Akbarinejad ◽

Wenrui Hao ◽

Trang Le ◽

Rachel A. Aronow ◽

...

Keyword(s):

Mathematical Model ◽

Colon Cancer ◽

Cancer Progression ◽

Immune Cell ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Interaction Network ◽

Data Driven ◽

Colon Cancer Progression ◽

Negative Effect

AbstractEvery colon cancer has its own unique characteristics, and therefore may respond differently to identical treatments. Here, we develop a data driven mathematical model for the interaction network of key components of immune microenvironment in colon cancer. We estimate the relative abundance of each immune cell from gene expression profiles of tumors, and group patients based on their immune patterns. Then we compare the tumor sensitivity and progression in each of these groups of patients, and observe differences in the patterns of tumor growth between the groups. For instance, in tumors with a smaller density of naive macrophages than activated macrophages, a higher activation rate of macrophages leads to an increase in cancer cell density, demonstrating a negative effect of macrophages. Other tumors however, exhibit an opposite trend, showing a positive effect of macrophages in controlling tumor size. Although the results indicate that for all patients, the size of the tumor is sensitive to the parameters related to macrophages such as their activation and death rate, this research demonstrates that no single biomarker could predict the dynamics of tumors.

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