Workshop 3: Cancer and the Immune System

(November 17,2014 - November 21,2014 )

Organizers


Avner Friedman
Department of Mathematics, The Ohio State University
Gregory Lesinski
Molecular Virology Immunology and Medical Genetics, The Ohio State University
Ami Radunskaya
Mathematics, Pomona College

Cancer immunology is the study of the interactions between the immune system and cancer cells. The aim is to discover innovative therapies using the immune system to retard the progression of the disease. The immune system aims to identify and destroy pathogenic microorganisms that invade our body. Cancer cells, however, are cells of our body, so the immune system may not recognize them as "enemy." In fact, cancer cells often even exploit the immune cells to help them proliferate. Tumor associated macrophages, for instance, are known to influence cancer cells by modulating immune functions, and accelerating angiogenesis, but not much is known on the cytokine signaling network that regulate this process. Recent years have seen the development of cancer immunotherapy, that is, the use of the immune system to attack malignant tumor cells. This can be achieved either by immunization of the patient by a vaccine, or by administering a therapeutic antibody as a drug which will recruit the immune system to recognize and destroy tumor cells. Recent years have also seen the development of mathematical models that aim to represent, at least at the conceptual level, the cancer-immune interactions, as well as models that represent immunotherapy processes. These models are formulated by systems of ODEs or PDEs. The present workshop will bring together cancer biologists and mathematical modelers to review the state of present knowledge and explore future directions. It will also provide an environment that will encourage communication and new contacts among the biologists and mathematicians. Formal lecture and informal discussions will articulate future directions where mathematical models can significantly enhance understanding of the complex relations between tumor cells and the immune cells, and suggest novel approaches to therapy.

Accepted Speakers

Xue-Feng Bai
Experimental Pathology, The Ohio State University
Helen Byrne
Centre for Collaborative Applied Mathematics, University of Oxford
Duan Chen
Department of Mathematics, University of North Carolina, Charlotte
Lisette de Pillis
Mathematics, Harvey Mudd College
Raluca Eftimie
Division of Mathematics, University of Dundee
Tim Eubank
Internal Medicine/Pulmonary Medicine, The Ohio State University
Matthew Farren
The James Comprehensive Cancer Center, The Ohio State University
Thomas Hillen
Mathematical and Statistical Sciences, University of Alberta
Sarah Hook
School of Pharmacy, University of Otago
Karly Jacobsen
Mathematical Biosciences Institute, The Ohio State University
Jenny Jiang
Biomedical Engineering, The University of Texas at Austin
Balveen Kaur
Department of Neurological Surgery, The Ohio State University
Ilona Kryczek
Health Systems, University of Michigan Health Systems
Yang Kuang
Department of Mathematics and Statistics, Arizona State University
Urszula Ledzewicz
Department of Mathematics and Statistics, Southern Illinois University
Doron Levy
Department of Mathematics, University of Maryland
Kang-Ling Liao
mathematical biosciences institute, The Ohio State University
Michael Lotze
Surgery, Immunology, and Bioengineering, University of Pittsburgh Cancer Institute
Yoram Louzoun
Mathematics, bar ilan university
Pedro Lowenstein
Neurosurgery, Cell and Developmental Biology, University of Michigan
Shari Pilon-Thomas
Immunology Program, H. Lee Moffitt Cancer Center & Research Institute
Daniel Powell
Pathology & Laboratory Medicine, University of Pennsylvania
Mark Robertson Tessi
Integrated Mathematical Oncology, Moffitt Cancer Center
Ben Wendel
Biomedical Engineering, The University of Texas at Austin
Theresa Whiteside
Pathology, Immunology ans Otolaryngology, University of Pittsburgh School of Medicine
Chuan Xue
Department of Mathematics, The Ohio State University
Monday, November 17, 2014
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
08:45 AM

Breakfast

08:45 AM
09:00 AM

Introductions and Information - Marty Golubitsky

09:00 AM
09:45 AM
Avner Friedman - An Overview of Cancer and the Immune System

This is tutorial talk, in which I will introduce the main components of the immune system in the context of cancer. I will introduce the different phenotypes of macrophages, the four classes of CD4+ T cells, and the cytotoxic T cells (CTL) or CD8+ T cell. As will be explained, the tumor may be recognized by macrophages and dendritic cells, and these cells will then activate 'effective' T cells to kill cancer cells. However, the tumor can fight back against the immune system, and in fact it can even use the system to its own advantage, by "educating" macrophages so that they will actually enhance tumor growth by increasing VEGF production. Another factor that works in favor of a tumor are the T regulatory cells, enhanced by the tumor, which inhibit the activities of the effective T cells.

09:45 AM
10:30 AM
Ami Radunskaya - An overview of cancer immunotherapies: a modeling perspective.

Cancer immunotherapy was announced as the "Breakthrough of the Year 2013" by Science Magazine (December 2013), but there is still a lot of uncertainty in how to design and deliver therapies that boost the immune system€™s defense against cancer. In this talk, I will present a brief overview of cancer immunotherapies, including therapeutic cancer vaccines. I will briefly discuss nonspecific and specific immunotherapies, their uses and their drawbacks. I will also highlight how mathematical modeling has been used to understand the effects of immunotherapies, and to design treatment strategies. Most of these models address one of the two main treatment design questions: How Much? and How Often?

10:30 AM
11:00 AM

Break

11:00 AM
11:45 AM
Theresa Whiteside - Regulatory T cell networks in human cancer and immune therapies

Regulatory T Cells (Tregs) accumulating in the peripheral circulation and tumor sites of patients contribute to tumor escape from the host immune system. Tregs encompass subsets of immune cells with distinct phenotypic and functional properties. Whereas natural (n) or thymic-derived (t) Tregs regulate responses to self-antigens, inducible (i) or peripheral (p) Tregs generated and expanded in regulatory microenvironments control immune responses to a broad variety of antigens.


Human Tregs accumulating in cancer comprise €˜bad€™ subsets, which inhibit antitumor immunity, and €˜good€™ anti-inflammatory subsets, which maintain tolerance to self and benefit the host. Future therapeutic strategies targeting Tregs will need to discriminate between these Treg subsets and will need to consider reprogramming strategies instead of Treg elimination. Re-establishment of effective antitumor immune responses in cancer patients without disturbing a normal homeostatic T-cell balance will greatly benefit from insights into inhibitory pathways engaged by human tumors.

11:45 AM
12:30 PM
Ben Wendel - High-throughput Sequencing and Single Cell Analysis of the Immune Repertoire

The immune repertoire has incredible diversity generated through V(D)J recombination to recognize the universe of antigens. This diversity, while crucial for the immune system, makes immune repertoire sequencing (IR-seq) a challenging task. Current sequencing technologies lack the accuracy to delineate between the myriad of minor mutations and PCR/sequencing errors. Using a barcode-driven Molecular IDentifier clustering-based IR-Seq (MIDCIRS), we€™ve effectively lowered the error rate for high throughput IR-seq to ~1 in 30,000 nucleotides. With this unprecedented accuracy, we have the power to resolve finer properties of the immune repertoire to characterize responses to disease, treatments, vaccinations, and aging.


On the other end of the spectrum, single cell analysis is critical to elucidate heterogeneity that can be lost in bulk samples. Antigen-specific T cells can be extremely rare, as low as 1 per million T cells, and can have starkly difference phenotypic and functional properties than the bulk. Using a pMHC tetramer-based enrichment strategy, we can isolate the responders to particular diseases and employ our single cell analysis method to simultaneously measure the T cell receptor sequences and gene expression levels. Our single cell analysis technique can be used to investigate the clonal nature and functional capacity of tumor infiltrating lymphocytes €“ the groups of T cells that are sought to activate by many cancer immunotherapies. This can lead to pretreatment screening and post-treatment disease monitoring methods that can be utilized to provide the optimal treatment regimen for a given patient.

12:30 PM
02:00 PM

Lunch

02:00 PM
02:45 PM
Ilona Kryczek - Immune elements reshape cancer stemness and invasiveness

We have studied the cross-talk between immune cell subsets and tumor/stem cells in the tumor microenvironment, and its impact on tumor immunity and therapy. Our prior research efforts demonstrate that the tumor microenvironment is comprised of immune cells that have been reprogrammed by active tumor-mediated processes to defeat tumor-specific immunity and promote tumor growth in a highly effective manner. These studies have helped define the nature of immune responses in the tumor microenvironment, and provide new insights into designing novel immune therapies to target the immune suppressive mechanisms including Tregs and inhibitory B7 family members and treat patients with cancer.

In this talk we focus on the interaction between tumor cells and host immune system in the cancer microenvironment patients with cancer. We demonstrate that immune cells can alter cancer stem cell gene expression, sphere formation and cancer metastasis. This is associated with patient outcome. We will further discuss the cellular and molecular mechanisms by which immune cell subsets control cancer stemness and tumorigenesis. We suggest that targeting the interactive network between tumor and immune cells might be a valuable strategy to control cancer metastasis and reduce therapeutic resistance.

02:45 PM
03:30 PM
Michael Lotze - Innate Immune Responses to Mitochondrial Nuclear Mismatch-The Smoking Gun?

Mammalian cells contain hundreds to thousands of mitochondrial DNAs (mtDNA) encoding essential oxidative phosphorylation genes, and can encompass varying percentages of mutant and normal mtDNAs (heteroplasmy) associated with different clinical phenotypes. By generating a set of somatic cell cybrids harboring increasing levels of the pathogenic tRNA 3243A>G mutation [0% mutant (normal), 20-30% (autism & diabetes), 50-90% (neurodegenerative disease), and 100% (Leigh Syndrome)] and assessing changes in mtDNA and nuclear DNA (nDNA) transcriptome by RNA sequencing, Doug Wallace discovered that each clinically relevant mtDNA heteroplasmy level is associated with a unique gene expression profile. Hence, small mitochondrial physiological changes precipitate abrupt changes in cellular signal transduction and epigenomic systems resulting in distinct cellular and clinical phenotypes. Mutations in the 16.6 kilobase human mtDNA can cause a broad spectrum of multi-systemic diseases. Unlike chromosomal genes which are present in only two copies per cell, the mtDNA can be present in hundreds to thousands of copies. If a cell acquires a deleterious mtDNA mutation, this creates an intracellular mixture of mutant and normal mtDNAs, a state known as heteroplasmy. Surprisingly, relatively subtle changes in the heteroplasmic levels can have dramatic effects on a patient€™s phenotype. Similarly our group at the University of Pittsburgh has shown profound metabolic changes regulated by the central nuclear protein, HMGB1, evolutionarily ancient and present in all metazoans, driving mitochondrial quality control and serving as a damage associated molecular pattern (DAMP) molecule/target when released for innate and adaptive cell immunity but also promoting autophagy (programmed cell survival) within the cytosol. Nuclear-mitochondrial mismatch can be recognized by innate immune cells but not by adaptive (T and B) cells. Innate immune cells recognize stress ligands on the target cell surface which we hypothesize are promoted in part by important oxidation of critical cysteines in HMGB1.

03:30 PM
04:15 PM

Break

04:15 PM
05:00 PM
Gregory Lesinski - Interactions between pancreatic stroma and immune suppression.

Recent studies from our laboratory and others have demonstrated that populations of activated fibroblasts, termed pancreatic stellate cells (PSC) are instrumental in driving inflammation in the pancreas. Our data indicate that PSC isolated from patients with either pancreatic cancer or chronic pancreatitis produce abundant levels of interleukin-6 (IL-6) and other cytokines. These data identify a novel role for PSC as mediators of local and systemic inflammatory changes in pancreatic disease. Thus, these cells may represent a viable target for limiting inflammatory processes in the pancreatic microenvironment.

05:00 PM
07:00 PM

Reception and Poster Session

07:15 PM

Shuttle pick-up from MBI

Tuesday, November 18, 2014
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:45 AM
Daniel Powell - Genetically-engineered T cells for the adoptive immunotherapy for cancer

Adoptive transfer of tumor-reactive T cells can mediate potent and durable remissions in patients with advanced malignancy. While some patients do harbor tumor-reactive T cells that can be harvested and expanded to large numbers for autologous infusion, patients lacking detectable endogenous anti-tumor T cell responses may not benefit from adoptive immunotherapy. Recent advances in gene transfer technology and cell cultivation procedures now makes it possible to de novo generate tumor antigen specific T cells for passive autologous infusion. Primary human T cells genetically modified to express an antibody based chimeric immune receptor can be redirected against tumor antigens, bolstered for activity by incorporation of costimulatory domains and have resulted in dramatic tumor regressions in clinical trials, particularly when these receptors have been optimized for expression, affinity and potency. The opportunity now exists to build upon early clinical trials results and platform optimization to deliver effective therapy for cancer at a wide scale.

09:45 AM
10:30 AM
Shari Pilon-Thomas - Adoptive cell therapy using tumor infiltrating lymphocytes (TIL)

Adoptive cell therapy (ACT) with tumor-infiltrating lymphocytes (TIL) has emerged as a powerful therapy for metastatic melanoma. TIL preparation involves the surgical resection of melanoma tumors and in vitro expansion of TIL from tumor fragments. Upon adequate TIL generation, patients undergo lymphodepleting chemotherapy to ablate peripheral immune cells, and infusion of the expanded TIL. ACT depends upon the presence of TIL in tumors, successful expansion of TIL in the laboratory, and effective activation and persistence of T cells after infusion. In this presentation, I will discuss several strategies to improve TIL therapy. These will include interventions to improve T cell infiltration into tumors prior to surgical resection and targeting co-stimulatory receptors to improve the growth of T cells in the laboratory.

10:30 AM
11:00 AM

Break

11:00 AM
11:45 AM
Tim Eubank - Regulation of angiogenesis by Tie2-expressing monocytes/macrophages in breast cancer

Tumor-associated macrophages (TAMs) regulate tumor angiogenesis in women with breast cancer. In fact, increased numbers of TAMs portends a worse prognosis and reduced breast cancer survival. Unfortunately, current therapeutic strategies targeting TAMs to modulate function and reduce tumor angiogenesis have yielded disappointing results, clinically. Recent studies highlight the role of a unique subset of tumor macrophages that express the endothelial cell receptor, TIE2. This macrophage subset is termed "TIE2-expressing monocytes/macrophages" (TEMs), and are differentially-recruited to the tumor vasculature by conditions generated in the tumor microenvironment to drive tumor angiogenesis, critical for tumor growth and metastases. TEMs are important in regulating angiogenesis in mouse models and human breast cancer, underscoring the importance of understanding the molecular regulation of angiogenesis by these cells. To test hypotheses of a causal relationship of TEMs to breast cancer angiogenesis, we generated a unique transgenic mouse lacking myeloid-specific expression of the TIE2 receptor (TEM knock outs). By combining these mice with the well-studied MMTV-PyMT mouse breast cancer model which emulates human tumor staging, our goal is to investigate a causal role of TEMs in angiogenesis, tumor growth and metastasis, and translate these findings to designing interventions for human breast cancer. Here, we demonstrate alternate pathways which augment TEM subsets both in circulation and once monocytes reach the tumor proper.

11:45 AM
02:00 PM

Lunch provided at MBI

02:00 PM
02:45 PM
Sarah Hook - Timing is everything: getting the right therapies to the right place at the right time

Most cancer therapies are given systemically however we need them to act locally in either lymphoid tissues or in tumors. In this presentation I will discuss some strategies that can be used to turn weapons of mass destruction (or mass immune activation) into precision-guided munitions. Areas where mathematical modeling could aid in the optimal delivery of therapies will also be discussed.

02:45 PM
03:30 PM
Xue-Feng Bai - IL-27 as a potential therapeutic for cancer: lessons from animal studies

In the past decade, cancer immunotherapies based on checkpoint blockade or adoptive T cell transfer (ACT) has achieved significant success. However, the overall responding rates to check point blockade such as anti-PD-1 therapy remain low. ACT therapy involves lengthy procedures of in vitro culture of tumor infiltrating lymphocytes (TILs) or generation of chimeric antigen receptor (CAR)-redirected T cells, whose efficacies are often limited by the poor T cell survival and persistence in vivo and expansion of regulatory T cells. Thus, although the time of immunotherapy has finally arrived, additional approaches are needed to replace or improve current immunotherapies. IL-27 is an anti-inflammatory cytokine of the IL-12 cytokine family that down-regulates autoimmune Th17 response and induces IL-10 and PD-L1 expression in T cells. However, accumulating evidences from animal studies have indicated that both endogenous and exogenous IL-27 inhibit tumor growth. Recently, we have obtained compelling evidence that IL-27 can be used as a novel therapeutic for cancer. First, IL-27 induces a new subset of Th1/Tc1 effector stem cells that have potent anti-tumor activity. Second, IL-27 treatment of mice leads to the dramatic reduction of regulatory T cells. Third, we have found that IL-27 and anti-PD-1 antibody show significant synergy in inhibiting tumor growth. Our studies suggest that IL-27-based combinational immunotherapy has the potential for cancer treatment.

03:30 PM
04:00 PM

Break

04:00 PM
05:30 PM

Panel Discussion (Lesinski and Lotze)

05:45 PM

Shuttle pick-up from MBI

Wednesday, November 19, 2014
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:30 AM
Matthew Farren - STAT3 Signaling Dysregulates Myelopoeisis in Cancer

A major mechanism by which cancers escape control by the immune system is by blocking the differentiation of myeloid cells into dendritic cells (DCs), immunostimulatory cells that activate antitumor T cells. Tumor-dependent activation of signal transducer and activator of transcription 3 (STAT3) signaling in myeloid progenitor cells is thought to cause this block in their differentiation. In addition, a signaling pathway through protein kinase C βII (PKCβII) is essential for the differentiation of myeloid cells into DCs. We found in humans and mice that breast cancer cells substantially decreased the abundance of PKCβII in myeloid progenitor cells through a mechanism involving the enhanced activation of STAT3 signaling by soluble, tumor-derived factors (TDFs). STAT3 bound to previously undescribed negative regulatory elements within the promoter of PRKCB, which encodes PKCβII. We also found a previously undescribed counter-regulatory mechanism through which the activity of PKCβII inhibited tumor-dependent STAT3 signaling by decreasing the abundance of cell surface receptors, such as cytokine and growth factor receptors, that are activated by TDFs. Together, these data suggest that a previously unrecognized cross-talk mechanism between the STAT3 and PKCβII signaling pathways provides the molecular basis for the tumor-induced blockade in the differentiation of myeloid cells, and suggest that enhancing PKCβII activity may be a therapeutic strategy to alleviate cancer-mediated suppression of the immune system.

09:30 AM
10:00 AM
Yoram Louzoun - Bistability induced by tumor-immune system interactions.

Many tumors target the specific immune system cells raised to protect the host against tumor. This targeting can take two main shapes. Either the tumor cells attract immune cells to the tumor, enhancing the tumor growth, or they prevent the immune cells from killing existing tumor cells. In both cases a positive feedback loop emerges between the tumor and immune system cell concentrations.


Such a feedback loop may explain the equilibrium obtained between the host immune system and tumors, where tumors stop growing, or grow very slowly, but are not destroyed by the immune response. While tumor size can increase by a factor of 10 within a day, in most cases, this huge division rate is not obtained and in reality the tumor is almost in equilibrium. This equilibrium can be explained by a bi-stable solution of the tumor-immune system dynamics.


We here study a generic set of feedback loops between the immune system cells and their targets in tumors and show that a bi-stable solution can emerge. This solution can occur only if the tumor induces death or inactivation of macrophages. In such a case, a simple negative effect of the pathogens on the macrophages will suffice to induce bistability. The initial conditions then becomes crucial for the solution, given that, according to it, the solution tends to one or the other fixed point, which correspond to a healthy or a sick state.


We show that double inhibition positive feedback loops (immune system kills tumor, which in turn kill immune system cells) behave differently than double activation feedback loops (Tumor produce cytokines that attract immune cells, which in turn produce cytokines which induce tumor growth).Double inhibition feedback loops induce bi-stability in most parameter space, while double activation feedback loops induce such a bistability in very limited regions of parameter space.

10:00 AM
10:30 AM

Break

10:30 AM
11:00 AM
Helen Byrne - The Immune System and Cancer: Friends or Foe?

The relationship between the immune system and cancer is undoubtedly complex. Indeed it remains unclear when the presence of immune cells at a tumour site is beneficial to the patient and when it is not. Even so, considerable efforts are now being invested in exploiting and manipulating the immune system in order to deliver treatment tumours. While there have been some extremely promising results, many questions remain to be addressed. In this talk I will illustrate how mathematical modelling can help to interpret experimental results, generate experimentally testable predictions and gain mechanistic insight into the complex relationship between the immune system and cancer.

11:00 AM
11:30 AM
Lisette de Pillis - Modeling Cancer-Immune System Dynamics

We will present a variety of mathematical models of tumor-immune interactions that have resulted from interdisciplinary collaborations with practicing oncologists and experimentalists. We will discuss certain approaches to modeling cancer growth and immune system interactions, and treatment approaches that harness the power of the immune system to slow and sometimes stop cancer progression.

11:30 AM
02:00 PM

Lunch

02:00 PM
02:30 PM
Thomas Hillen, Andreas Buttenschoen - Macrophage-Cancer Cell Interactions drive Tumor Invasion Types

The interactions between cancer cells and immune cells is one of the hallmarks of cancer. In this talk we present an individual based model, including the interactions between macrophages and cancer cells at the tumor invasion front. The model is based on the Glazier-Graner-Hogeweg modeling approach (Cellular Potts Model). In this model the macrophages and cancer cells interact via adhesion modeled using the Differential Adhesion Hypothesis and a paracrine loop (Epidermal Growth Factor (EGF) and Colony Stimulating Factor (CSF)). We show that the paracrine loop drives invasion depth, whereas cellular adhesion drives invasion types (ie. individual, collective invasion).

02:30 PM
03:00 PM
Mark Robertson Tessi - The effect of T-cell homeostasis on solid and liquid tumors

T-cell populations are subject to homeostatic control from cytokines and microenvironmental signaling. Disruption of homeostasis can cause changes to the dynamics of the system that have implications for the progression of cancer. Here we present two mathematical models that examine the progression of tumors in the context of T-cell homeostasis. Model 1: During a chronic disease such as cancer, T cells often become tolerant to the antigens presented by the disease. This tolerant state effectively limits the response of the immune system to the tumor. Experimental evidence has shown that depletion of T-cells can lead to a loss of T-cell tolerance. During the homeostatic phase of T-cell compartment repopulation, there is a temporary window of opportunity during which T cells lose their tolerant state, allowing them to respond to tumor antigens. In addition, clonal expansion of the tumor-specific T-cell clone may be enhanced during the regrowth phase due to increased stimulation. We use an ordinary differential equation (ODE) model to explore the effect of T-cell depletion and homeostatic repopulation on the loss of tolerance in the T-cell compartment and subsequent effectiveness of immune-mediated tumor cytotoxicity. The model predicts different outcomes for the tumor and T-cell compartment, dependent on the strength and schedule of the depletion therapy. The optimal regimen can lead to tumor control in some cases, but T-cell exhaustion is also common dynamic predicted by the model. By understanding the effects of T-cell depletion, immune depleting therapies can be optimized to enhance immune potential. Model 2: Large Granular Lymphocytic Leukemia (LGLL) is a T-cell lymphoproliferative disorder that exhibits clonal expansion of a subset of T cells. Since there are no clinical biomarkers to predict the aggressiveness of the disease, treatment decisions are often made on a watch and wait approach. Using a set of ODEs, we develop a model of LGLL that uses clinical patient data from diagnosis to predict the timeframe for progression of the disease. Our experimental results have suggested that the disease is caused by a change in sensitivity to both positive and negative regulators of T-cell homeostasis. The model incorporates these cell-specific mechanisms to investigate their effect when placed in a homeostatic setting. The level of dysregulation as measured from patient-specific data determines the rate of outgrowth of the diseased T-cell clone, and therefore serve as a useful predictive tool for managing treatment decisions in the clinic.

03:00 PM
03:30 PM

Break

03:30 PM
04:45 PM

Poster Chalk Talks (5-10 Minutes Each)

04:45 PM
05:15 PM

Informal Discussion

05:15 PM

Shuttle pick-up from MBI

Thursday, November 20, 2014
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:30 AM
Balveen Kaur - Use of HSV-1 for Oncolytic Viral Therapy

Abstract not submitted.

09:30 AM
10:00 AM
Raluca Eftimie - Oncolytic viral therapies and the balance between the memory and effector immune responses

Over the past years, oncolytic viruses have generated much interest for cancer therapies, mainly due to the fact that once a virus is injected into the patient it can actively search for cancer cells and destroy them, without significant side effects. However, the anti-tumor effect of oncolytic viruses is greatly diminished by the anti-viral immune response. Experimental studies have shown that the sequential administration of two viruses that carry the same tumor antigen can overcome the anti-viral immune response by generating both anti-tumor effector and memory responses. However, the importance of memory versus effector immune responses in eliminating and controlling the tumors is still an open question.


Here, we introduce a mathematical model for cancer-immune-virus interactions, and use it to investigate the delicate balance between the anti-viral and anti-cancer immune responses. We also investigate the interplay between the effector and memory immune responses in improving the outcome of cancer therapies.

10:00 AM
10:30 AM

Break

10:30 AM
11:00 AM
Yang Kuang - A mathematical model for the immunotherapy of advanced prostate cancer

A mathematical model of advanced prostate cancer treatment is developed to examine the combined effects of androgen deprivation therapy and immunotherapy. Androgen deprivation therapy has been the primary form of treatment for advanced prostate cancer for the past 50 years. While initially successful, this therapy eventually results in a relapse after two to three years in the form of androgen-independent prostate cancer. Intermittent androgen deprivation therapy attempts to prevent relapse by cycling the patient on and off treatment. Over the past decade, dendritic cell vaccines have been used in clinical studies for the immunotherapy of prostate cancer with some success. Our model examines the efficacy of dendritic cell vaccines when used with continuous or intermittent androgen deprivation therapy schedules. Numerical simulations of the model suggest that immunotherapy can successfully stabilize the disease using both continuous and intermittent androgen deprivation.


11:00 AM
11:30 AM
Duan Chen - Involvement of tumor macrophage HIFs in chemotherapy effectiveness: Mathematical modeling of oxygen, pH, and glutathione.

The four variables, hypoxia, acidity, high glutathione (GSH) concentration and fast reducing rate (redox) are distinct and varied characteristics of solid tumors compared to normal tissue. These parameters are among the most significant factors underlying the metabolism and physiology of solid tumors, regardless of their type or origin. Low oxygen tension contributes to both inhibition of cancer cell proliferation and therapeutic resistance of tumors; low extracellular pH, the reverse of normal cells, mainly enhances tumor invasion; and dysregulated GSH and redox potential within cancer cells favor their proliferation. In fact, cancer cells under these microenvironmental conditions appreciably alter tumor response to cytotoxic anti- cancer treatments. Recent experiments measured the in vivo longitudinal data of these four parameters with tumor development and the corresponding presence and absence of tumor macrophage HIF-1α or HIF-2α in a mouse model of breast cancer. In the current paper, we present a mathematical model-based system of (ordinary and partial) differential equations to monitor tumor growth and susceptibility to standard chemotherapy with oxygen level, pH, and intracellular GSH concentration. We first show that our model simulations agree with the corresponding experiments, and then we use our model to suggest treatments of tumors by altering these four parameters in tumor microenvironment. For example, the model qualitatively predicts that GSH depletion can raise the level of reactive oxygen species (ROS) above a toxic threshold and result in inhibition of tumor growth.

11:30 AM
02:00 PM

Lunch

02:00 PM
02:30 PM
Urszula Ledzewicz - Dynamics and optimal control of tumor-immune interactions under metronomic chemotherapy

In this talk metronomic chemotherapy, an interesting alternative to MTD (maximum tolerated dose), will be introduced and its benefits discussed from the biomedical point of view, including not just cytotoxic effect on the tumor, but also anti-angiogenic and pro-immuno effects. The pro-immune action will be discussed in more details and its effect on regulatory T cells and dendritic cells will be addressed. Then a minimally parameterized model for metronomic chemotherapy will be presented where three main compartments are taken into account: tumor, vasculature and the immune system. The model comes from combining a model for anti-angiogenic signaling (Hahnfeldt et al) with a classical model for tumor-immune system interactions (Stepanova et al) and incorporating a single input control function that represents cytotoxic, anti-angiogenic and pro-immune action of low dose chemotherapy. The analysis of the model as a dynamical system actually indicates that it inherits the geometrical characteristics of the tumor-immune system interactions model like multi-stability with benign and malignant region of attractions. This gives a useful insight into the proper construction of the objective which would have as a goal to provide a maintenance program rather than to eradicate the tumor. An interesting relation between saddle-node bifurcations and immune-surveillance will be discussed. Partial results about the form of the optimal protocols, which relate to the metronomic chemotherapy as a biologically optimal dose BOD will be presented. Evidence from the medical trials and medical literature will be given.

02:30 PM
03:00 PM
Doron Levy - The Role of the Immune Response in CML

Chronic Myeloid Leukemia (CML) is a myeloproliferative disorder caused by the formation of the Philadelphia Chromosome, which produces the BCR-ABL gene that codes for a constitutively active tyrosine kinase. In this talk we will overview our recent results on mathematically modeling the role of the immune response in the progression of CML. This is a joint work with G. Clapp, T. Lepoutre, R. Cheikh, and F. Nicolini.

03:00 PM
03:15 PM

Break

03:15 PM
03:45 PM
Pedro Lowenstein - Mechanisms of glioma formation: computational and experimental studies on the role of pre-existing vessels vs. neoangionesis

(from Neoplasia 16:543-561, 2014): As glioma cells infiltrate the brain they become associated with various microanatomical brain structures such as blood vessels, white matter tracts, and brain parenchyma. How these distinct invasion patterns coordinate tumor growth and influence clinical outcomes remain poorly understood. We have investigated how perivascular growth affects glioma growth patterning and response to anti-angiogenic therapy within the highly vascularized brain. Orthotopically implanted rodent and human glioma cells are shown to commonly invade and proliferate within brain perivascular space. This form of brain tumor growth and invasion is also shown to characterize de-novo generated endogenous mouse brain tumors, biopsies of primary human glioblastoma, and peripheral cancer metastasis to the human brain. Perivascularly invading brain tumors become vascularized by normal brain microvessels as individual gliomas cells use perivascular space as a conduit for tumor invasion. Agent-based computational modeling recapitulated biological perivascular glioma growth without the need for neoangiogenesis. We tested the requirement for neoangiogenesis in perivascular glioma by treating animals with angiogenesis inhibitors bevacizumab and DC101. These inhibitors induced the expected vesselnormalization, yet failed to reduce tumor growth or improve survival of mice bearing orthotopic or endogenous gliomas while exacerbating brain tumor invasion. Our results provide compelling experimental evidence in support of the recently described failure of clinically used antiangiogenics to extend the survival of human glioma patients.

04:15 PM

Shuttle pick-up from MBI

05:30 PM
06:00 PM

Cash Bar - Crowne Plaza

06:00 PM
07:30 PM

Banquet at Crowne Plaza

Friday, November 21, 2014
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:30 AM
Kang-Ling Liao - Mathematical modeling of Interleukin-35 promoting tumor growth and angiogenesis

Interleukin-35 (IL-35), a cytokine from the Interleukin-12 cytokine family, has beenconsidered as an anti-inflammatory cytokine which promotes tumor progression andtumor immune evasion. It has also been demonstrated that IL-35 is secreted byregulatory T cells. Recent mouse experiments have shown that IL-35 produced bycancer cells promotes tumor growth via enhancing myeloid cell accumulation andangiogenesis, and reducing the infiltration of activated CD8+ T cells into tumormicroenvironment. 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.

09:30 AM
10:00 AM
Chuan Xue - A mathematical model for pancreatic cancer growth and treatments

Pancreatic cancer is one of the most deadly types of cancer and has extremely poor prognosis. This malignancy typically induces only limited cellular immune responses, the magnitude of which can increase with the number of encountered cancer cells. On the other hand, pancreatic cancer is highly effective at evading immune responses by inducing polarization of pro-inflammatory M1 macrophages into anti-inflammatory M2 macrophages, and promoting expansion of myeloid derived suppressor cells, which block the killing of cancer cells by cytotoxic T cells. These factors allow immune evasion to predominate, promoting metastasis and poor responsiveness to chemotherapies and immunotherapies. In this paper we develop a mathematical model of pancreatic cancer, and use it to qualitatively explain a variety of biomedical and clinical data. The model shows that drugs aimed at suppressing cancer growth are effective only if the immune induced cancer cell death lies within a specific range, that is, the immune system has a specific window of opportunity to effectively suppress cancer under treatment. The model results suggest that tumor growth rate is affected by complex feedback loops between the tumor cells, endothelial cells and the immune response. The relative strength of the different loops determines the cancer growth rate and its response to immunotherapy. The model could serve as a starting point to identify optimal nodes for intervention against pancreatic cancer.

10:00 AM
10:30 AM

Break

10:30 AM
11:00 AM
Karly Jacobsen - Modeling the effects of macrophage content and CCN1 on glioma virotherapy

Oncolytic virus (OV) is a genetically engineered virus that can selectively replicate in and kill tumor cells while not harming normal cells. OV therapy has been explored as a treatment for numerous cancers including glioblastoma, an aggressive and devastating brain tumor. Experiments show that extracellular matrix protein CCN1 limits OV therapy of glioma by orchestrating an antiviral response and enhancing the proinflammatory activation and migration of macrophages. Neutralizing CCN1 by antibody has been demonstrated to improve OV spread and tends to increase the time to disease progression. We develop a mathematical model to investigate the effects of CCN1 on the treatment of glioma with oncolytic herpes simplex virus. We show that numerical simulations of the model are in agreement with the experimental results and then use the model to explore the anti-tumor effects of combining antibodies with OV therapy. Model simulations suggest that the macrophage content of the tumor is a critical factor to the success of OV therapy and to the reduction in tumor volume gained with the CCN1 antibody.

11:00 AM
12:00 PM

Discussion

12:15 PM

Shuttle pick-up from MBI (One to airport and one back to hotel)

Name Email Affiliation
Aavani, Pooya pooya.aavani@ttu.edu Mathematics and Statistics, Texas Tech University
Abrham, Yorusaliem yorusaliem@gmail.com Decemhare Referal Hospital, Orotha school of Medicine
Aguda, Baltazar bdaguda@gmail.com Founder & CEO, Disease Pathways, LLC
Aminzare, Zahra aminzare@math.rutgers.edu Mathematics, Rutgers University
and Erica Rutter, Tracy Stepien School of Mathematical and Statistical Sciences, Arizona State University
and Lisette de Pillis, Elizabeth Sarapata
Bai, Xue-Feng Xue-feng.Bai@osumc.edu Experimental Pathology, The Ohio State University
Bates, Dan bates@math.colostate.edu Department of Mathematics, Colorado State University
Buttenschoen, Andreas andreas.buttenschoen@ualberta.ca Department of Mathematical and Statistical Sciences, University of Alberta
Byrne, Helen byrneh@maths.ox.ac.uk Centre for Collaborative Applied Mathematics, University of Oxford
Cebulla, Colleen colleen.cebulla@osumc.edu Ophthalmology and Visual Science, The Ohio State University
Chacon, Jessica jchacon@mail.med.upenn.edu Ovarian Cancer Research Center, University of Pennsylvania
Chen, Duan dchen10@uncc.edu Department of Mathematics, University of North Carolina, Charlotte
Curtin, Lee pmxlc1@exmail.nottingham.ac.uk School of Mathematical Sciences, University of Nottingham
Davis, Courtney courtney.davis2@pepperdine.edu Natural Science Division, Pepperdine University
de Pillis, Lisette depillis@hmc.edu Mathematics, Harvey Mudd College
Eftimie, Raluca reftimie@maths.dundee.ac.uk Division of Mathematics, University of Dundee
Eubank, Tim tim.eubank@osumc.edu Internal Medicine/Pulmonary Medicine, The Ohio State University
Everett, Rebecca rarodger@asu.edu Applied Mathematics, Arizona State University
Farren, Matthew Matthew.Farren@osumc.edu The James Comprehensive Cancer Center, The Ohio State University
Flores Castillo, Nicolas castillo.173@osu.edu Department of Statistics, Rice University
Friedman, Avner afriedman@math.ohio-state.edu Department of Mathematics, The Ohio State University
Gevertz, Jana gevertz@tcnj.edu Mathematics and Statistics, The College of New Jersey
Gulzar, Faisal mfaisalgul33@gmail.com Department of Pharmacology, Faculty of Pharmacy, University of Sargodha
Hartmann, Katherine katherine.hartmann@osumc.edu Pharmacology, The Ohio State University
Hillen, Thomas thillen@ualberta.ca Mathematical and Statistical Sciences, University of Alberta
Hook, Sarah sarah.hook@otago.ac.nz School of Pharmacy, University of Otago
Jacobsen, Karly jacobsen.50@mbi.osu.edu Mathematical Biosciences Institute, The Ohio State University
Jiang, Jenny Jenny.n.jiang@gmail.com Biomedical Engineering, The University of Texas at Austin
Kari, Suresh Suresh.Kari@osumc.edu MOLECULAR VIROLOGY IMMUNOLOGY AND MEDICAL GENETICS, Ohio State University
Kaur, Balveen kaur.11@osu.edu Department of Neurological Surgery, The Ohio State University
Kianercy, Ardeshir akianer1@jhmi.edu Urology, Johns Hopkins Hospital
Kim, Peter pkim@maths.usyd.edu.au School of Mathematics and Statistics, University of Sydney
Kong, Liang lkong9@uis.edu Mathematical Science, University of Illinois at Springfield
Kraj, Piotr peter_kraj@knology.net Dept. Biological Sciences, Old Dominion University
Kryczek, Ilona ilonak@med.umich.edu Health Systems, University of Michigan Health Systems
Kuang, Yang kuang@asu.edu Department of Mathematics and Statistics, Arizona State University
Lavi, Orit laviorit@gmail.com Laboratory of Cell Biology, National Cancer Institute, NIH
Ledzewicz, Urszula uledzew@siue.edu Department of Mathematics and Statistics, Southern Illinois University
Lee, Hyun Geun leeh@korea.ac.kr Department of Mathematics, Institute of Mathematical Sciences, Ewha W. University
Lesinski, Gregory Gregory.Lesinski@osumc.edu Molecular Virology Immunology and Medical Genetics, The Ohio State University
Levy, Doron dlevy@math.umd.edu Department of Mathematics, University of Maryland
Liao, Kang-Ling liao.92@mbi.osu.edu mathematical biosciences institute, The Ohio State University
Lim, Sookkyung sookkyung.lim@uc.edu Department of Mathematical Sciences, University of Cincinnati
Losic, Bojan bojan.losic@mssm.edu Genetics and Genomic Sciences, Mount Sinai School of Medicine
Lotze, Michael lotzemt@upmc.edu Surgery, Immunology, and Bioengineering, University of Pittsburgh Cancer Institute
Louzoun, Yoram louzouy@math.biu.ac.il Mathematics, bar ilan university
Lowenstein, Pedro pedrol@umich.edu Neurosurgery, Cell and Developmental Biology, University of Michigan
Mace, Thomas thomas.mace@osumc.edu Internal Medicine, The Ohio State University
Mahdipour Shirayeh, Ali ali.mahdipour@gmail.com Applied Mathematics, University of Waterloo, University of Waterloo
Moore, Helen helen.moore@bms.com Clinical Pharmacology and Pharmacometrics, Bristol-Myers Squibb
Perez-Castro, Antonio antonio.perez-castro@osumc.edu molecular virology, immunology and genetics, OSU
Pilon-Thomas, Shari Shari.Pilon-Thomas@moffitt.org Immunology Program, H. Lee Moffitt Cancer Center & Research Institute
Pohar, Kamal amy.filippi@osumc.edu College of Medicine - Department of Urology, The Ohio State University
Powell, Daniel poda@mail.med.upenn.edu Pathology & Laboratory Medicine, University of Pennsylvania
Radunskaya, Ami aradunskaya@pomona.edu Mathematics, Pomona College
Rambani, Komal komal.rambani@osumc.edu IBGP, OSU
Reynolds, Sara s-sreynol5@math.unl.edu Mathematics, University of Nebraska-Lincoln
Rezaei Yousefi, Mohammadmahdi rezaeiyousefi.1@osu.edu Electrical and Computer Engineering, The Ohio State University
Robertson Tessi, Mark Mark.Robertsontessi@moffitt.org Integrated Mathematical Oncology, Moffitt Cancer Center
Rutter, Erica Erica.Rutter@asu.edu School of Mathematical & Statistical Science, Arizona State University
Sarapata, Elizabeth esarapata@g.hmc.edu Mathematics, Claremont Graduate University
Shahriyari, Leili shahriyari.1@osu.edu Mathematical Biosciences Institute, Ohio State University
Sontag, Eduardo eduardo.sontag@gmail.com Mathematics, Rutgers University at New Brunswick
Stepien, Tracy tstepien@asu.edu School of Mathematical and Statistical Sciences, Arizona State University
Taslim, Cenny taslim.2@osu.edu Biomedical Informatics, The Ohio State University
Urbanska, Katarzyna katu@mail.med.upenn.edu Ovarian Cancer Research Center, UPENN
Wares, Joanna jwares@richmond.edu Math and Computer Science, University of Richmond
Wendel, Ben benwendel@utexas.edu Biomedical Engineering, The University of Texas at Austin
Whiteside, Theresa whitesidetl@upmc.edu Pathology, Immunology ans Otolaryngology, University of Pittsburgh School of Medicine
Xue, Chuan cxue@math.osu.edu Department of Mathematics, The Ohio State University
IL-27 as a potential therapeutic for cancer: lessons from animal studies

In the past decade, cancer immunotherapies based on checkpoint blockade or adoptive T cell transfer (ACT) has achieved significant success. However, the overall responding rates to check point blockade such as anti-PD-1 therapy remain low. ACT therapy involves lengthy procedures of in vitro culture of tumor infiltrating lymphocytes (TILs) or generation of chimeric antigen receptor (CAR)-redirected T cells, whose efficacies are often limited by the poor T cell survival and persistence in vivo and expansion of regulatory T cells. Thus, although the time of immunotherapy has finally arrived, additional approaches are needed to replace or improve current immunotherapies. IL-27 is an anti-inflammatory cytokine of the IL-12 cytokine family that down-regulates autoimmune Th17 response and induces IL-10 and PD-L1 expression in T cells. However, accumulating evidences from animal studies have indicated that both endogenous and exogenous IL-27 inhibit tumor growth. Recently, we have obtained compelling evidence that IL-27 can be used as a novel therapeutic for cancer. First, IL-27 induces a new subset of Th1/Tc1 effector stem cells that have potent anti-tumor activity. Second, IL-27 treatment of mice leads to the dramatic reduction of regulatory T cells. Third, we have found that IL-27 and anti-PD-1 antibody show significant synergy in inhibiting tumor growth. Our studies suggest that IL-27-based combinational immunotherapy has the potential for cancer treatment.

Macrophage-Cancer Cell Interactions drive Tumor Invasion Types

The interactions between cancer cells and immune cells is one of the hallmarks of cancer. In this talk we present an individual based model, including the interactions between macrophages and cancer cells at the tumor invasion front. The model is based on the Glazier-Graner-Hogeweg modeling approach (Cellular Potts Model). In this model the macrophages and cancer cells interact via adhesion modeled using the Differential Adhesion Hypothesis and a paracrine loop (Epidermal Growth Factor (EGF) and Colony Stimulating Factor (CSF)). We show that the paracrine loop drives invasion depth, whereas cellular adhesion drives invasion types (ie. individual, collective invasion).

The Immune System and Cancer: Friends or Foe?

The relationship between the immune system and cancer is undoubtedly complex. Indeed it remains unclear when the presence of immune cells at a tumour site is beneficial to the patient and when it is not. Even so, considerable efforts are now being invested in exploiting and manipulating the immune system in order to deliver treatment tumours. While there have been some extremely promising results, many questions remain to be addressed. In this talk I will illustrate how mathematical modelling can help to interpret experimental results, generate experimentally testable predictions and gain mechanistic insight into the complex relationship between the immune system and cancer.

Involvement of tumor macrophage HIFs in chemotherapy effectiveness: Mathematical modeling of oxygen, pH, and glutathione.

The four variables, hypoxia, acidity, high glutathione (GSH) concentration and fast reducing rate (redox) are distinct and varied characteristics of solid tumors compared to normal tissue. These parameters are among the most significant factors underlying the metabolism and physiology of solid tumors, regardless of their type or origin. Low oxygen tension contributes to both inhibition of cancer cell proliferation and therapeutic resistance of tumors; low extracellular pH, the reverse of normal cells, mainly enhances tumor invasion; and dysregulated GSH and redox potential within cancer cells favor their proliferation. In fact, cancer cells under these microenvironmental conditions appreciably alter tumor response to cytotoxic anti- cancer treatments. Recent experiments measured the in vivo longitudinal data of these four parameters with tumor development and the corresponding presence and absence of tumor macrophage HIF-1α or HIF-2α in a mouse model of breast cancer. In the current paper, we present a mathematical model-based system of (ordinary and partial) differential equations to monitor tumor growth and susceptibility to standard chemotherapy with oxygen level, pH, and intracellular GSH concentration. We first show that our model simulations agree with the corresponding experiments, and then we use our model to suggest treatments of tumors by altering these four parameters in tumor microenvironment. For example, the model qualitatively predicts that GSH depletion can raise the level of reactive oxygen species (ROS) above a toxic threshold and result in inhibition of tumor growth.

Modeling Cancer-Immune System Dynamics

We will present a variety of mathematical models of tumor-immune interactions that have resulted from interdisciplinary collaborations with practicing oncologists and experimentalists. We will discuss certain approaches to modeling cancer growth and immune system interactions, and treatment approaches that harness the power of the immune system to slow and sometimes stop cancer progression.

Oncolytic viral therapies and the balance between the memory and effector immune responses

Over the past years, oncolytic viruses have generated much interest for cancer therapies, mainly due to the fact that once a virus is injected into the patient it can actively search for cancer cells and destroy them, without significant side effects. However, the anti-tumor effect of oncolytic viruses is greatly diminished by the anti-viral immune response. Experimental studies have shown that the sequential administration of two viruses that carry the same tumor antigen can overcome the anti-viral immune response by generating both anti-tumor effector and memory responses. However, the importance of memory versus effector immune responses in eliminating and controlling the tumors is still an open question.


Here, we introduce a mathematical model for cancer-immune-virus interactions, and use it to investigate the delicate balance between the anti-viral and anti-cancer immune responses. We also investigate the interplay between the effector and memory immune responses in improving the outcome of cancer therapies.

Regulation of angiogenesis by Tie2-expressing monocytes/macrophages in breast cancer

Tumor-associated macrophages (TAMs) regulate tumor angiogenesis in women with breast cancer. In fact, increased numbers of TAMs portends a worse prognosis and reduced breast cancer survival. Unfortunately, current therapeutic strategies targeting TAMs to modulate function and reduce tumor angiogenesis have yielded disappointing results, clinically. Recent studies highlight the role of a unique subset of tumor macrophages that express the endothelial cell receptor, TIE2. This macrophage subset is termed "TIE2-expressing monocytes/macrophages" (TEMs), and are differentially-recruited to the tumor vasculature by conditions generated in the tumor microenvironment to drive tumor angiogenesis, critical for tumor growth and metastases. TEMs are important in regulating angiogenesis in mouse models and human breast cancer, underscoring the importance of understanding the molecular regulation of angiogenesis by these cells. To test hypotheses of a causal relationship of TEMs to breast cancer angiogenesis, we generated a unique transgenic mouse lacking myeloid-specific expression of the TIE2 receptor (TEM knock outs). By combining these mice with the well-studied MMTV-PyMT mouse breast cancer model which emulates human tumor staging, our goal is to investigate a causal role of TEMs in angiogenesis, tumor growth and metastasis, and translate these findings to designing interventions for human breast cancer. Here, we demonstrate alternate pathways which augment TEM subsets both in circulation and once monocytes reach the tumor proper.

STAT3 Signaling Dysregulates Myelopoeisis in Cancer

A major mechanism by which cancers escape control by the immune system is by blocking the differentiation of myeloid cells into dendritic cells (DCs), immunostimulatory cells that activate antitumor T cells. Tumor-dependent activation of signal transducer and activator of transcription 3 (STAT3) signaling in myeloid progenitor cells is thought to cause this block in their differentiation. In addition, a signaling pathway through protein kinase C βII (PKCβII) is essential for the differentiation of myeloid cells into DCs. We found in humans and mice that breast cancer cells substantially decreased the abundance of PKCβII in myeloid progenitor cells through a mechanism involving the enhanced activation of STAT3 signaling by soluble, tumor-derived factors (TDFs). STAT3 bound to previously undescribed negative regulatory elements within the promoter of PRKCB, which encodes PKCβII. We also found a previously undescribed counter-regulatory mechanism through which the activity of PKCβII inhibited tumor-dependent STAT3 signaling by decreasing the abundance of cell surface receptors, such as cytokine and growth factor receptors, that are activated by TDFs. Together, these data suggest that a previously unrecognized cross-talk mechanism between the STAT3 and PKCβII signaling pathways provides the molecular basis for the tumor-induced blockade in the differentiation of myeloid cells, and suggest that enhancing PKCβII activity may be a therapeutic strategy to alleviate cancer-mediated suppression of the immune system.

An Overview of Cancer and the Immune System

This is tutorial talk, in which I will introduce the main components of the immune system in the context of cancer. I will introduce the different phenotypes of macrophages, the four classes of CD4+ T cells, and the cytotoxic T cells (CTL) or CD8+ T cell. As will be explained, the tumor may be recognized by macrophages and dendritic cells, and these cells will then activate 'effective' T cells to kill cancer cells. However, the tumor can fight back against the immune system, and in fact it can even use the system to its own advantage, by "educating" macrophages so that they will actually enhance tumor growth by increasing VEGF production. Another factor that works in favor of a tumor are the T regulatory cells, enhanced by the tumor, which inhibit the activities of the effective T cells.

Macrophage-Cancer Cell Interactions drive Tumor Invasion Types

The interactions between cancer cells and immune cells is one of the hallmarks of cancer. In this talk we present an individual based model, including the interactions between macrophages and cancer cells at the tumor invasion front. The model is based on the Glazier-Graner-Hogeweg modeling approach (Cellular Potts Model). In this model the macrophages and cancer cells interact via adhesion modeled using the Differential Adhesion Hypothesis and a paracrine loop (Epidermal Growth Factor (EGF) and Colony Stimulating Factor (CSF)). We show that the paracrine loop drives invasion depth, whereas cellular adhesion drives invasion types (ie. individual, collective invasion).

Timing is everything: getting the right therapies to the right place at the right time

Most cancer therapies are given systemically however we need them to act locally in either lymphoid tissues or in tumors. In this presentation I will discuss some strategies that can be used to turn weapons of mass destruction (or mass immune activation) into precision-guided munitions. Areas where mathematical modeling could aid in the optimal delivery of therapies will also be discussed.

Modeling the effects of macrophage content and CCN1 on glioma virotherapy

Oncolytic virus (OV) is a genetically engineered virus that can selectively replicate in and kill tumor cells while not harming normal cells. OV therapy has been explored as a treatment for numerous cancers including glioblastoma, an aggressive and devastating brain tumor. Experiments show that extracellular matrix protein CCN1 limits OV therapy of glioma by orchestrating an antiviral response and enhancing the proinflammatory activation and migration of macrophages. Neutralizing CCN1 by antibody has been demonstrated to improve OV spread and tends to increase the time to disease progression. We develop a mathematical model to investigate the effects of CCN1 on the treatment of glioma with oncolytic herpes simplex virus. We show that numerical simulations of the model are in agreement with the experimental results and then use the model to explore the anti-tumor effects of combining antibodies with OV therapy. Model simulations suggest that the macrophage content of the tumor is a critical factor to the success of OV therapy and to the reduction in tumor volume gained with the CCN1 antibody.

Use of HSV-1 for Oncolytic Viral Therapy

Abstract not submitted.

Immune elements reshape cancer stemness and invasiveness

We have studied the cross-talk between immune cell subsets and tumor/stem cells in the tumor microenvironment, and its impact on tumor immunity and therapy. Our prior research efforts demonstrate that the tumor microenvironment is comprised of immune cells that have been reprogrammed by active tumor-mediated processes to defeat tumor-specific immunity and promote tumor growth in a highly effective manner. These studies have helped define the nature of immune responses in the tumor microenvironment, and provide new insights into designing novel immune therapies to target the immune suppressive mechanisms including Tregs and inhibitory B7 family members and treat patients with cancer.

In this talk we focus on the interaction between tumor cells and host immune system in the cancer microenvironment patients with cancer. We demonstrate that immune cells can alter cancer stem cell gene expression, sphere formation and cancer metastasis. This is associated with patient outcome. We will further discuss the cellular and molecular mechanisms by which immune cell subsets control cancer stemness and tumorigenesis. We suggest that targeting the interactive network between tumor and immune cells might be a valuable strategy to control cancer metastasis and reduce therapeutic resistance.

A mathematical model for the immunotherapy of advanced prostate cancer

A mathematical model of advanced prostate cancer treatment is developed to examine the combined effects of androgen deprivation therapy and immunotherapy. Androgen deprivation therapy has been the primary form of treatment for advanced prostate cancer for the past 50 years. While initially successful, this therapy eventually results in a relapse after two to three years in the form of androgen-independent prostate cancer. Intermittent androgen deprivation therapy attempts to prevent relapse by cycling the patient on and off treatment. Over the past decade, dendritic cell vaccines have been used in clinical studies for the immunotherapy of prostate cancer with some success. Our model examines the efficacy of dendritic cell vaccines when used with continuous or intermittent androgen deprivation therapy schedules. Numerical simulations of the model suggest that immunotherapy can successfully stabilize the disease using both continuous and intermittent androgen deprivation.


Dynamics and optimal control of tumor-immune interactions under metronomic chemotherapy

In this talk metronomic chemotherapy, an interesting alternative to MTD (maximum tolerated dose), will be introduced and its benefits discussed from the biomedical point of view, including not just cytotoxic effect on the tumor, but also anti-angiogenic and pro-immuno effects. The pro-immune action will be discussed in more details and its effect on regulatory T cells and dendritic cells will be addressed. Then a minimally parameterized model for metronomic chemotherapy will be presented where three main compartments are taken into account: tumor, vasculature and the immune system. The model comes from combining a model for anti-angiogenic signaling (Hahnfeldt et al) with a classical model for tumor-immune system interactions (Stepanova et al) and incorporating a single input control function that represents cytotoxic, anti-angiogenic and pro-immune action of low dose chemotherapy. The analysis of the model as a dynamical system actually indicates that it inherits the geometrical characteristics of the tumor-immune system interactions model like multi-stability with benign and malignant region of attractions. This gives a useful insight into the proper construction of the objective which would have as a goal to provide a maintenance program rather than to eradicate the tumor. An interesting relation between saddle-node bifurcations and immune-surveillance will be discussed. Partial results about the form of the optimal protocols, which relate to the metronomic chemotherapy as a biologically optimal dose BOD will be presented. Evidence from the medical trials and medical literature will be given.

Interactions between pancreatic stroma and immune suppression.

Recent studies from our laboratory and others have demonstrated that populations of activated fibroblasts, termed pancreatic stellate cells (PSC) are instrumental in driving inflammation in the pancreas. Our data indicate that PSC isolated from patients with either pancreatic cancer or chronic pancreatitis produce abundant levels of interleukin-6 (IL-6) and other cytokines. These data identify a novel role for PSC as mediators of local and systemic inflammatory changes in pancreatic disease. Thus, these cells may represent a viable target for limiting inflammatory processes in the pancreatic microenvironment.

The Role of the Immune Response in CML

Chronic Myeloid Leukemia (CML) is a myeloproliferative disorder caused by the formation of the Philadelphia Chromosome, which produces the BCR-ABL gene that codes for a constitutively active tyrosine kinase. In this talk we will overview our recent results on mathematically modeling the role of the immune response in the progression of CML. This is a joint work with G. Clapp, T. Lepoutre, R. Cheikh, and F. Nicolini.

Mathematical modeling of Interleukin-35 promoting tumor growth and angiogenesis

Interleukin-35 (IL-35), a cytokine from the Interleukin-12 cytokine family, has beenconsidered as an anti-inflammatory cytokine which promotes tumor progression andtumor immune evasion. It has also been demonstrated that IL-35 is secreted byregulatory T cells. Recent mouse experiments have shown that IL-35 produced bycancer cells promotes tumor growth via enhancing myeloid cell accumulation andangiogenesis, and reducing the infiltration of activated CD8+ T cells into tumormicroenvironment. 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.

Personalized Neoantigen Vaccination with Synthetic Long Peptides

Abstract not submitted.

Innate Immune Responses to Mitochondrial Nuclear Mismatch-The Smoking Gun?

Mammalian cells contain hundreds to thousands of mitochondrial DNAs (mtDNA) encoding essential oxidative phosphorylation genes, and can encompass varying percentages of mutant and normal mtDNAs (heteroplasmy) associated with different clinical phenotypes. By generating a set of somatic cell cybrids harboring increasing levels of the pathogenic tRNA 3243A>G mutation [0% mutant (normal), 20-30% (autism & diabetes), 50-90% (neurodegenerative disease), and 100% (Leigh Syndrome)] and assessing changes in mtDNA and nuclear DNA (nDNA) transcriptome by RNA sequencing, Doug Wallace discovered that each clinically relevant mtDNA heteroplasmy level is associated with a unique gene expression profile. Hence, small mitochondrial physiological changes precipitate abrupt changes in cellular signal transduction and epigenomic systems resulting in distinct cellular and clinical phenotypes. Mutations in the 16.6 kilobase human mtDNA can cause a broad spectrum of multi-systemic diseases. Unlike chromosomal genes which are present in only two copies per cell, the mtDNA can be present in hundreds to thousands of copies. If a cell acquires a deleterious mtDNA mutation, this creates an intracellular mixture of mutant and normal mtDNAs, a state known as heteroplasmy. Surprisingly, relatively subtle changes in the heteroplasmic levels can have dramatic effects on a patient’s phenotype. Similarly our group at the University of Pittsburgh has shown profound metabolic changes regulated by the central nuclear protein, HMGB1, evolutionarily ancient and present in all metazoans, driving mitochondrial quality control and serving as a damage associated molecular pattern (DAMP) molecule/target when released for innate and adaptive cell immunity but also promoting autophagy (programmed cell survival) within the cytosol. Nuclear-mitochondrial mismatch can be recognized by innate immune cells but not by adaptive (T and B) cells. Innate immune cells recognize stress ligands on the target cell surface which we hypothesize are promoted in part by important oxidation of critical cysteines in HMGB1.

Bistability induced by tumor-immune system interactions.

Many tumors target the specific immune system cells raised to protect the host against tumor. This targeting can take two main shapes. Either the tumor cells attract immune cells to the tumor, enhancing the tumor growth, or they prevent the immune cells from killing existing tumor cells. In both cases a positive feedback loop emerges between the tumor and immune system cell concentrations.


Such a feedback loop may explain the equilibrium obtained between the host immune system and tumors, where tumors stop growing, or grow very slowly, but are not destroyed by the immune response. While tumor size can increase by a factor of 10 within a day, in most cases, this huge division rate is not obtained and in reality the tumor is almost in equilibrium. This equilibrium can be explained by a bi-stable solution of the tumor-immune system dynamics.


We here study a generic set of feedback loops between the immune system cells and their targets in tumors and show that a bi-stable solution can emerge. This solution can occur only if the tumor induces death or inactivation of macrophages. In such a case, a simple negative effect of the pathogens on the macrophages will suffice to induce bistability. The initial conditions then becomes crucial for the solution, given that, according to it, the solution tends to one or the other fixed point, which correspond to a healthy or a sick state.


We show that double inhibition positive feedback loops (immune system kills tumor, which in turn kill immune system cells) behave differently than double activation feedback loops (Tumor produce cytokines that attract immune cells, which in turn produce cytokines which induce tumor growth).Double inhibition feedback loops induce bi-stability in most parameter space, while double activation feedback loops induce such a bistability in very limited regions of parameter space.

Mechanisms of glioma formation: computational and experimental studies on the role of pre-existing vessels vs. neoangionesis

(from Neoplasia 16:543-561, 2014): As glioma cells infiltrate the brain they become associated with various microanatomical brain structures such as blood vessels, white matter tracts, and brain parenchyma. How these distinct invasion patterns coordinate tumor growth and influence clinical outcomes remain poorly understood. We have investigated how perivascular growth affects glioma growth patterning and response to anti-angiogenic therapy within the highly vascularized brain. Orthotopically implanted rodent and human glioma cells are shown to commonly invade and proliferate within brain perivascular space. This form of brain tumor growth and invasion is also shown to characterize de-novo generated endogenous mouse brain tumors, biopsies of primary human glioblastoma, and peripheral cancer metastasis to the human brain. Perivascularly invading brain tumors become vascularized by normal brain microvessels as individual gliomas cells use perivascular space as a conduit for tumor invasion. Agent-based computational modeling recapitulated biological perivascular glioma growth without the need for neoangiogenesis. We tested the requirement for neoangiogenesis in perivascular glioma by treating animals with angiogenesis inhibitors bevacizumab and DC101. These inhibitors induced the expected vesselnormalization, yet failed to reduce tumor growth or improve survival of mice bearing orthotopic or endogenous gliomas while exacerbating brain tumor invasion. Our results provide compelling experimental evidence in support of the recently described failure of clinically used antiangiogenics to extend the survival of human glioma patients.

Adoptive cell therapy using tumor infiltrating lymphocytes (TIL)

Adoptive cell therapy (ACT) with tumor-infiltrating lymphocytes (TIL) has emerged as a powerful therapy for metastatic melanoma. TIL preparation involves the surgical resection of melanoma tumors and in vitro expansion of TIL from tumor fragments. Upon adequate TIL generation, patients undergo lymphodepleting chemotherapy to ablate peripheral immune cells, and infusion of the expanded TIL. ACT depends upon the presence of TIL in tumors, successful expansion of TIL in the laboratory, and effective activation and persistence of T cells after infusion. In this presentation, I will discuss several strategies to improve TIL therapy. These will include interventions to improve T cell infiltration into tumors prior to surgical resection and targeting co-stimulatory receptors to improve the growth of T cells in the laboratory.

Genetically-engineered T cells for the adoptive immunotherapy for cancer

Adoptive transfer of tumor-reactive T cells can mediate potent and durable remissions in patients with advanced malignancy. While some patients do harbor tumor-reactive T cells that can be harvested and expanded to large numbers for autologous infusion, patients lacking detectable endogenous anti-tumor T cell responses may not benefit from adoptive immunotherapy. Recent advances in gene transfer technology and cell cultivation procedures now makes it possible to de novo generate tumor antigen specific T cells for passive autologous infusion. Primary human T cells genetically modified to express an antibody based chimeric immune receptor can be redirected against tumor antigens, bolstered for activity by incorporation of costimulatory domains and have resulted in dramatic tumor regressions in clinical trials, particularly when these receptors have been optimized for expression, affinity and potency. The opportunity now exists to build upon early clinical trials results and platform optimization to deliver effective therapy for cancer at a wide scale.

An overview of cancer immunotherapies: a modeling perspective.

Cancer immunotherapy was announced as the "Breakthrough of the Year 2013" by Science Magazine (December 2013), but there is still a lot of uncertainty in how to design and deliver therapies that boost the immune system’s defense against cancer. In this talk, I will present a brief overview of cancer immunotherapies, including therapeutic cancer vaccines. I will briefly discuss nonspecific and specific immunotherapies, their uses and their drawbacks. I will also highlight how mathematical modeling has been used to understand the effects of immunotherapies, and to design treatment strategies. Most of these models address one of the two main treatment design questions: How Much? and How Often?

The effect of T-cell homeostasis on solid and liquid tumors

T-cell populations are subject to homeostatic control from cytokines and microenvironmental signaling. Disruption of homeostasis can cause changes to the dynamics of the system that have implications for the progression of cancer. Here we present two mathematical models that examine the progression of tumors in the context of T-cell homeostasis. Model 1: During a chronic disease such as cancer, T cells often become tolerant to the antigens presented by the disease. This tolerant state effectively limits the response of the immune system to the tumor. Experimental evidence has shown that depletion of T-cells can lead to a loss of T-cell tolerance. During the homeostatic phase of T-cell compartment repopulation, there is a temporary window of opportunity during which T cells lose their tolerant state, allowing them to respond to tumor antigens. In addition, clonal expansion of the tumor-specific T-cell clone may be enhanced during the regrowth phase due to increased stimulation. We use an ordinary differential equation (ODE) model to explore the effect of T-cell depletion and homeostatic repopulation on the loss of tolerance in the T-cell compartment and subsequent effectiveness of immune-mediated tumor cytotoxicity. The model predicts different outcomes for the tumor and T-cell compartment, dependent on the strength and schedule of the depletion therapy. The optimal regimen can lead to tumor control in some cases, but T-cell exhaustion is also common dynamic predicted by the model. By understanding the effects of T-cell depletion, immune depleting therapies can be optimized to enhance immune potential. Model 2: Large Granular Lymphocytic Leukemia (LGLL) is a T-cell lymphoproliferative disorder that exhibits clonal expansion of a subset of T cells. Since there are no clinical biomarkers to predict the aggressiveness of the disease, treatment decisions are often made on a watch and wait approach. Using a set of ODEs, we develop a model of LGLL that uses clinical patient data from diagnosis to predict the timeframe for progression of the disease. Our experimental results have suggested that the disease is caused by a change in sensitivity to both positive and negative regulators of T-cell homeostasis. The model incorporates these cell-specific mechanisms to investigate their effect when placed in a homeostatic setting. The level of dysregulation as measured from patient-specific data determines the rate of outgrowth of the diseased T-cell clone, and therefore serve as a useful predictive tool for managing treatment decisions in the clinic.

High-throughput Sequencing and Single Cell Analysis of the Immune Repertoire

The immune repertoire has incredible diversity generated through V(D)J recombination to recognize the universe of antigens. This diversity, while crucial for the immune system, makes immune repertoire sequencing (IR-seq) a challenging task. Current sequencing technologies lack the accuracy to delineate between the myriad of minor mutations and PCR/sequencing errors. Using a barcode-driven Molecular IDentifier clustering-based IR-Seq (MIDCIRS), we’ve effectively lowered the error rate for high throughput IR-seq to ~1 in 30,000 nucleotides. With this unprecedented accuracy, we have the power to resolve finer properties of the immune repertoire to characterize responses to disease, treatments, vaccinations, and aging.


On the other end of the spectrum, single cell analysis is critical to elucidate heterogeneity that can be lost in bulk samples. Antigen-specific T cells can be extremely rare, as low as 1 per million T cells, and can have starkly difference phenotypic and functional properties than the bulk. Using a pMHC tetramer-based enrichment strategy, we can isolate the responders to particular diseases and employ our single cell analysis method to simultaneously measure the T cell receptor sequences and gene expression levels. Our single cell analysis technique can be used to investigate the clonal nature and functional capacity of tumor infiltrating lymphocytes – the groups of T cells that are sought to activate by many cancer immunotherapies. This can lead to pretreatment screening and post-treatment disease monitoring methods that can be utilized to provide the optimal treatment regimen for a given patient.

Regulatory T cell networks in human cancer and immune therapies

Regulatory T Cells (Tregs) accumulating in the peripheral circulation and tumor sites of patients contribute to tumor escape from the host immune system. Tregs encompass subsets of immune cells with distinct phenotypic and functional properties. Whereas natural (n) or thymic-derived (t) Tregs regulate responses to self-antigens, inducible (i) or peripheral (p) Tregs generated and expanded in regulatory microenvironments control immune responses to a broad variety of antigens.


Human Tregs accumulating in cancer comprise ‘bad’ subsets, which inhibit antitumor immunity, and ‘good’ anti-inflammatory subsets, which maintain tolerance to self and benefit the host. Future therapeutic strategies targeting Tregs will need to discriminate between these Treg subsets and will need to consider reprogramming strategies instead of Treg elimination. Re-establishment of effective antitumor immune responses in cancer patients without disturbing a normal homeostatic T-cell balance will greatly benefit from insights into inhibitory pathways engaged by human tumors.

A mathematical model for pancreatic cancer growth and treatments

Pancreatic cancer is one of the most deadly types of cancer and has extremely poor prognosis. This malignancy typically induces only limited cellular immune responses, the magnitude of which can increase with the number of encountered cancer cells. On the other hand, pancreatic cancer is highly effective at evading immune responses by inducing polarization of pro-inflammatory M1 macrophages into anti-inflammatory M2 macrophages, and promoting expansion of myeloid derived suppressor cells, which block the killing of cancer cells by cytotoxic T cells. These factors allow immune evasion to predominate, promoting metastasis and poor responsiveness to chemotherapies and immunotherapies. In this paper we develop a mathematical model of pancreatic cancer, and use it to qualitatively explain a variety of biomedical and clinical data. The model shows that drugs aimed at suppressing cancer growth are effective only if the immune induced cancer cell death lies within a specific range, that is, the immune system has a specific window of opportunity to effectively suppress cancer under treatment. The model results suggest that tumor growth rate is affected by complex feedback loops between the tumor cells, endothelial cells and the immune response. The relative strength of the different loops determines the cancer growth rate and its response to immunotherapy. The model could serve as a starting point to identify optimal nodes for intervention against pancreatic cancer.

Posters

The Role of CD4 T Cells in Immune System Activation and Viral Reproduction in a Model for HIV Infection

CD4 T cells play a fundamental role in the adaptive immune response including activation of naive B cells and macrophages and recruitment of neutrophils and macrophages to the site of infection. Human immunodeficiency virus (HIV) which infects and kills CD4 T cells, causes progressive failure of the immune system. However, HIV particles are also reproduced by the infected CD4 T cells. Therefore, during HIV infection, infected and healthy CD4 T cells act in opposition to each other, reproducing virus particles and activating humoral and cellular immune responses, respectively. In this investigation, we develop and analyze a simple system of four ordinary differential equations that accounts for these two opposing roles of CD4 T cells. The model illustrates the importance of the adaptive immune response during the asymptomatic stage of HIV infection. In addition, the solution behavior exhibits the three stages of infection, acute, asymptotic and final AIDS stage.

A Data-Validated Density-Dependent Diffusion Model of Glioblastoma Growth

Glioblastoma multiforme is an aggressive brain cancer that is extremely fatal. It is characterized by both proliferation and large amounts of migration, which contributes to the difficulty of treatment. Previous models of this type of cancer growth often include two separate equations to model proliferation or migration. We propose a single equation which uses density-dependent diffusion to capture the behavior of both proliferation and migration. We analyze the model to determine the existence of traveling wave solutions. To prove the viability of the density-dependent diffusion function chosen, we compare our model with well-known in vitro experimental data.

A Model of Macrophage Dynamics in Cancer

Recent advances in cancer immunotherapy have enhanced the nonspecific immune system's ability to target and kill tumor cells. Treatment with CD47 monoclonal antibodies disables the protein on tumor cells which inhibits phagocytosis, causing macrophages to recognize tumor cells as invader instead of host cells.Preliminary numerical analysis indicates the presence of stable zero-level and high-level tumor equilibria.We propose a tumor-macrophage model with biologically verified parameters in order to theoretically analyze what makes this treatment effective.

A Clinically Parameterized Model of Shigella Immunity to Inform Vaccine Design

Shigella, a bacteria in the same family as E. coli, causes bacterial dysentery and kills 1.1 million people each year. No vaccine exists for Shigella despite decades of clinical research, in part because the immune components responsible for conferring immunity against Shigella are not known. We investigate which key immune mechanisms and bacterial components should be targeted to make a protective vaccine against Shigella.

We have developed ODE models of the humoral immune response against Shigella to search for promising vaccine targets. We use Latin hypercube sampling and Monte Carlo parameter estimation with vaccine clinical trial data to identify biologically grounded parameter value combinations. Sensitivity analysis enables us to predict which crucial parameters and parameter ranges correlate with disease prevention and clearance.

Dynamics of a Data-Validated Ovarian Tumor Growth Model

It is well-known that cancer is a world-wide major public health problem and that there is a need for new approaches in order to better understand cancer and improve treatment. One recent interdisciplinary approach is to apply a com-bination of mathematics and ecology to cancer biology since tumor cells live in an ecological setting; they interact with and compete against normal and other cancerous cells for space and nutrients. We present a stoichiometric tumor model using the Droop cell quota model to consider angiogenesis in ovarian cancer. We compare the model to data from a study that analyzed the role of vascular endothelial growth factor (VEGF) in tumor growth and progression of ovarian cancer. Immunode?cient mice were induced with tumors and then some received an antibody to inhibit VEGF. This model is able to capture the dynamics observed in both on-treatment and off-treatment data as well as predict the tumor growth.

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A mathematical model for the immunotherapy of advanced prostate cancer
Yang Kuang

A mathematical model of advanced prostate cancer treatment is developed to examine the combined effects of androgen deprivation therapy and immunotherapy. Androgen deprivation therapy has been the primary form of treatment for advanced prost

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The effect of T-cell homeostasis on solid and liquid tumors
Mark Robertson Tessi

T-cell populations are subject to homeostatic control from cytokines and microenvironmental signaling. Disruption of homeostasis can cause changes to the dynamics of the system that have implications for the progression of cancer. Here we pr

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Modeling Cancer-Immune System Dynamics
Lisette de Pillis

We will present a variety of mathematical models of tumor-immune interactions that have resulted from interdisciplinary collaborations with practicing oncologists and experimentalists. We will discuss certain approaches to modeling cancer gr

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Bistability induced by tumor-immune system interactions.
Yoram Louzoun

Many tumors target the specific immune system cells raised to protect the host against tumor. This targeting can take two main shapes. Either the tumor cells attract immune cells to the tumor, enhancing the tumor growth, or they prevent the

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STAT3 Signaling Dysregulates Myelopoeisis in Cancer
Matthew Farren

A major mechanism by which cancers escape control by the immune system is by blocking the differentiation of myeloid cells into dendritic cells (DCs), immunostimulatory cells that activate antitumor T cells. Tumor-dependent activation of sig

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Panel Discussion (Lesinski and Lotze)
Panel Discussion (Lesinski and Lotze)

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Timing is everything: getting the right therapies to the right place at the right time
Sarah Hook

Most cancer therapies are given systemically however we need them to act locally in either lymphoid tissues or in tumors. In this presentation I will discuss some strategies that can be used to turn weapons of mass destruction (or mass immun

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Innate Immune Responses to Mitochondrial Nuclear Mismatch-The Smoking Gun?
Michael Lotze

Mammalian cells contain hundreds to thousands of mitochondrial DNAs (mtDNA) encoding essential oxidative phosphorylation genes, and can encompass varying percentages of mutant and normal mtDNAs (heteroplasmy) associated with different clinic

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High-throughput Sequencing and Single Cell Analysis of the Immune Repertoire
Ben Wendel

The immune repertoire has incredible diversity generated through V(D)J recombination to recognize the universe of antigens. This diversity, while crucial for the immune system, makes immune repertoire sequencing (IR-seq) a challenging task.

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Regulatory T cell networks in human cancer and immune therapies
Theresa Whiteside

Regulatory T Cells (Tregs) accumulating in the peripheral circulation and tumor sites of patients contribute to tumor escape from the host immune system. Tregs encompass subsets of immune cells with distinct phenotypic a

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An Overview of Cancer and the Immune System
Avner Friedman

This is tutorial talk, in which I will introduce the main components of the immune system in the context of cancer. I will introduce the different phenotypes of macrophages, the four classes of CD4+ T cells, and the cytotoxic T cells (CTL) o

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An overview of cancer immunotherapies: a modeling perspective.
Ami Radunskaya

Cancer immunotherapy was announced as the "Breakthrough of the Year 2013" by Science Magazine (December 2013), but there is still a lot of uncertainty in how to design and deliver therapies that boost the immune system€