A multiscale systems perspective on cancer, immunotherapy, and Interleukin-12

Monoclonal antibodies represent some of the most promising molecular targeted immunotherapies. However, understanding mechanisms by which tumors evade elimination by the immune system of the host presents a significant challenge for developing effective cancer immunotherapies. The interaction of cancer cells with the host is a complex process that is distributed across a variety of time and length scales. The time scales range from the dynamics of protein refolding (i.e., microseconds) to the dynamics of disease progression (i.e., years). The length scales span the farthest reaches of the human body (i.e., meters) down to the range of molecular interactions (i.e., nanometers). Limited ranges of time and length scales are used experimentally to observe and quantify changes in physiology due to cancer. Translating knowledge obtained from the limited scales observed experimentally to predict patient response is an essential prerequisite for the rational design of cancer immunotherapies that improve clinical outcomes. In studying multiscale systems, engineers use systems analysis and design to identify important components in a complex system and to test conceptual understanding of the integrated system behavior using simulation. The objective of this review is to summarize interactions between the tumor and cell-mediated immunity from a multiscale perspective. Interleukin-12 and its role in coordinating antibody-dependent cell-mediated cytotoxicity is used illustrate the different time and length scale that underpin cancer immunoediting. An underlying theme in this review is the potential role that simulation can play in translating knowledge across scales

Unraveling the Complex Regulatory Relationships between Metabolism and Signal Transduction in Breast Cancer.

Almost all cancer cells exhibit a metabolic phenotype characterized by high rates of glucose uptake known as the Warburg effect. Metabolic changes that are representative of distinct stages of breast cancer may suggest dependence by cancer cells on certain metabolic processes that are not relevant to normal cells. Importantly, these differences may help identify therapeutic targets that are non-lethal to normal cells. In this thesis, I present a set of models and methodologies developed using both experimental and theoretical approaches to investigate the complex intracellular signaling and metabolic networks associated with distinct stages of breast cancer. First, a detailed literature search was used to construct a logic network model of the PI3K signaling pathway, which is known to play an important regulatory role in glucose metabolism. Comparisons of experimental and simulated results suggest that the network model is well constructed but some regulatory crosstalk with MAPK requires additional refinement. Targeted therapeutic inhibitors frequently induce off-target effects. This thesis also explored the role of retroactivity in generating off-target effects in signaling networks using a computational model. The simulation results suggest that the kinetics governing covalently modified cycles in a cascade are more important for propagating an upstream off-target effect via retroactivity than the binding affinity of a drug to a targeted protein, which is a commonly optimized property in drug development. Finally, 13C tracer experiments were used to infer relative glucose and glutamine derived flux in cell lines representing distinct stages of breast cancer. Steady state metabolic flux analysis was also used to computationally fit the absolute TCA cycle flux in these cell lines. Variations in acetyl-CoA, citrate, pyruvate, and alpha-ketoglutarate flux were identified. A particularly important finding was a large reductive carboxylation flux from alpha-ketoglutarate to citrate in SUM-149 cells. Together, the models presented in this thesis provide a framework for identifying mechanistic drivers of the Warburg effect, which may represent important therapeutic targets for modulating cancer proliferation and progression.PHDBioinformaticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/98062/1/mlwynn_1.pd

Unravelling cell migration: defining movement from the cell surface

Cell motility is essential for life and development. Unfortunately, cell migration is also linked to several pathological processes, such as cancer metastasis. Cells’ ability to migrate relies on many actors. Cells change their migratory strategy based on their phenotype and the properties of the surrounding microenvironment. Cell migration is, therefore, an extremely complex phenomenon. Researchers have investigated cell motility for more than a century. Recent discoveries have uncovered some of the mysteries associated with the mechanisms involved in cell migration, such as intracellular signaling and cell mechanics. These findings involve different players, including transmembrane receptors, adhesive complexes, cytoskeletal components , the nucleus, and the extracellular matrix. This review aims to give a global overview of our current understanding of cell migration

Oncogene and Cancer

This book describes a course of cancer growth starting from normal cells to cancerous form and the genomic instability, the cancer treatment as well as its prevention in form of the invention of a vaccine. Some diseases are also discussed in detail, such as breast cancer, leucaemia, cervical cancer, and glioma. Understanding cancer through its molecular mechanism is needed to reduce the cancer incidence. How to treat cancer more effectively and the problems like drug resistance and metastasis are very clearly illustrated in this publication as well as some research result that could be used to treat the cancer patients in the very near future. The book was divided into six main sections: 1. HER2 Carcinogenesis: Etiology, Treatment and Prevention; 2. DNA Repair Mechanism and Cancer; 3. New Approach to Cancer Mechanism; 4. New Role of Oncogenes and Tumor Suppressor Genes; 5. Non Coding RNA and Micro RNA in Tumorigenesis; 6. Oncogenes for Transcription Factor

Interactions of EGFR/IGF-1R Signaling in NSCLC - A Systems Biology Approach

Lung cancer is the leading cause of cancer‐related deaths worldwide with 50,000 new cases per year in Germany and 220,000 in the USA. Non‐small cell lung cancer (NSCLC) is the most prevalent variant, with the majority of cases classifying as the adenocarcinoma subtype. Advances in molecular diagnostics have revealed driving mutations in some tyrosine kinase receptors (TKRs), such as the EGF receptor (EGFR). Other TKRs like the IGF‐I receptor (IGF‐1R) have been implied in NSCLC carcinogenesis. Consequently, treatment strategies have evolved to include inhibitors against these TRKs (tyrosine kinase inhibitors, TKIs), but only with temporal benefit for the patient. Evidence pointing towards an important role of IGF‐1 signaling in the evasion of inhibition of EGFR lead to double inhibition of EGFR and IGF‐1R being tested in the clinics. Phase I and II trials were promising, but a phase III study failed to demonstrate benefit for the primary end point of progression‐free survival after 12 weeks. My project used a systems biology approach to investigate the role of the dynamic crosstalk between the signaling from EGFR and IGF‐1R on NSCLC cells to better define the effects of pathway interaction and find causes for the failure of clinical combination treatment. To generate meaningful quantitative data for the phenotypical modeling of cell behavior, I established partly novel evaluation algorithms for 2D migration (in cooperation with the group of Dr. F. Matthäus) and 3D invasion (in cooperation with the group of Dr. D. Drasdo). In cooperation with the group of Prof. T. Höfer I could successfully establish a first unified ODE model of EGFR and IGF‐1R signaling in NSCLC cells from quantitative time resolved pathway activation data. Even though microarray analysis of EGF stimulated NSCLC cells revealed upregulation of migration associated genes, phenotypical assays showed that NSCLC cell migration was dependent on a more complex signaling environment than double stimulation with EGF and IGF‐1. On the other hand, I was able to show rescue of the NSCLC migratory behavior by IGF‐1 stimulation after EGFR inhibition in a full medium setting, further corroborating the important role of the interaction between these two growth factors for the early spread of NSCLC. The migration data I generated is currently used in the development of an agentbased model of NSCLC migration by the group of Dr. F. Matthäus. The data presented here and the associated computational evaluation algorithms and models will serve as the basis for the integrated multiscale modeling of the complex conditions governing NSCLC migration and the relevant cell signaling. Thus my work constitutes an important contribution towards understanding the intricate signaling responsible for the early spread of NSCLC and resistance against inhibition of particular TRKs

EMPLOYING QUANTITATIVE SYSTEMS PHARMACOLOGY TO CHARACTERIZE DIFFERENCES IN IGF1 AND INSULIN SIGNALING PATHWAYS IN BREAST CANCER

Insulin and insulin-like growth factor I (IGF1) have been shown to influence cancer risk and progression through poorly understood mechanisms. Here, new insights on the mechanisms of differential MAPK and Akt activation are revealed by an iterative quantitative systems pharmacology approach. In the first iteration, I combined proteomic screening with computational network inference to uncover differences in IGF1 and insulin induced signaling. Using reverse phase protein array of 21 breast cancer cell lines treated with a time course of IGF1 and insulin, I constructed directed protein expression networks using three separate methods: (i) lasso regression, (ii) conventional matrix inversion, and (iii) entropy maximization. These networks, named here as the time translation models, were analyzed and the inferred interactions were ranked by differential magnitude to identify pathway differences. The two top candidates, chosen for experimental validation, were shown to regulate IGF1/insulin induced phosphorylation events. Both of the knock-down perturbations caused phosphorylation responses stronger in IGF1 stimulated cells compared with insulin. Overall, the time-translation modeling coupled to wet-lab experiments has proven to be powerful in inferring differential interactions downstream of IGF1 and insulin signaling, in vitro. In the second iteration, mechanistic representation of IGF1 and insulin dual signaling cascades by a set of ODEs is generated by rule-based modeling. The mechanistic network modeling provided a framework to elucidate experimental targets downstream of two receptors, which were treated as indistinguishable in previous models. The model included cascades of both mitogen-activated protein kinase (MAPK) and Akt signaling, as well as the crosstalk and feedback loops in between. The parameter perturbation scanning employed for seven different models of seven cell lines yielded new experimental hypotheses on how differential responses of MAPK and Akt originate. Complementary to the first iteration, the results in this part suggested that regulation of insulin receptor substrate 1 (IRS1) is critical in inducing differential MAPK or Akt activation. Compensation and activating feedback mechanisms collectively depressed the efficacy of anti-IGF1R/InsR therapies. With the quantitative systems pharmacologic approach, the networks of signal transduction constructed in this thesis are aimed to discern novel downstream components of the IGF1R/InsR system, and to direct patients with suitable tumor subclasses to efficient personalized clinical interventions

Bioengineering strategies for cancer therapy and modelling

Tese de doutoramento em Engenharia de Tecidos, Medicina Regenerativa e Células EstaminaisCancer is a global pandemic with a high incidence among the world population and effective treatments are for the most part elusive. The tumor microenvironment is a highly complex and heterotypic mixture of cells that interact to regulate central control mechanisms, driving immunosuppression and promoting both survival and invasion of cancer cells into surrounding tissues. It has been this complexity that has made finding effective therapeutics such a demanding task and therefore cancer still remains a burden worldwide in health as well as in economic terms. While the progression in the field of cancer research has been clear over the years, there are still several challenges that need to be addressed. Herein, two different sides to this disease are explored: treatment and in vitro models. Adoptive T cell therapy has shown impressive results, however not without its limitations. The use of the T cell mitogen IL-2 within culture systems is known to lead to early exhaustion of T cell subsets while high density of co-stimulating molecules has been linked to undesired immune responses. As an alternative, a nanoparticle system based on the natural polymer gellan-gum was proposed, with tailorable surface functionalization with co-stimulatory molecules. High levels of T cell expansion were observed over the studied period, with secreted IL-2 levels overcoming those of commercial alternatives. With this system, increased expression of cytotoxic molecules Granzyme B and Perforin were also detected in vitro. On the other spectrum, 3D cancer models have sustained a great number of developments observed by an increase in similarity towards native tissues; however, a requirement for even more complex architectures capable of better mimicking cellular interactions is still present. Therefore, an assembloid-based approach was proposed to develop a 3D in vitro melanoma model to further study cellular interactions. These heterotypic tumor assembloids presented a complex architecture capable of sustaining endothelial cell function as well as a high expression of stemness-related markers. These models were subjected to functionality assays where they showed a capacity for “cooperative invasion” which was coincident with an observed increased production of MMP-2. To further unravel the role of stromal cells in the invasive potential of cancer cells a 3D chemotaxis chamber was developed to study cellular interactions observed in the tumor microenvironment, where stem cells and fibroblasts showed to have a crucial role. Ultimately, this thesis allowed to explore biomedical engineering approaches to further contribute to the knowledge in the field opening new doors to be explored in the future.O cancro é uma pandemia global com uma elevada incidência e cujo desenvolvimento de tratamentos eficazes continua a ser difícil. O microambiente tumoral é uma mistura altamente complexa e heterotípica de células que interagem para regular mecanismos centrais que provocam imunossupressão promovendo a sobrevivência e invasão de células tumorais para os tecidos circundantes. É esta complexidade que tem tornado desafiante encontrar terapias eficazes, tornando esta doença um fardo a nível global em termos de saúde e economia. Enquanto a progressão na área da investigação oncológica tem sido clara ao longo dos anos, existem ainda vários desafios que precisam de serem encarados para permitir futuros desenvolvimentos. Aqui, foram exploradas duas vertentes diferentes desta doença: o tratamento e os modelos in vitro. A terapia celular adotiva tem demonstrado resultados impressionantes, no entanto não sem as suas limitações. O uso do mitogénio IL-2 nestes sistemas de cultura é conhecido por levar rapidamente à exaustão das células T, enquanto o uso de moléculas co-estimulatórias em elevadas densidades está associado a respostas imunes não desejadas. Como alternativa, foi proposto um sistema de nanopartículas baseado no polímero natural goma gelana e funcionalizado com moléculas co estimulatórias. Foram observados elevados níveis de expansão de células T e quantidade de IL-2 secretada superior à de alternativas comerciais. Foi ainda verificado in vitro um aumento de expressão das moléculas citotóxicas Grazima B e Perforina. No outro espectro, têm sido desenvolvidos modelos tumorais 3D com uma cada vez maior similaridade para tecidos nativos; no entanto, a necessidade de arquiteturas ainda mais complexas capazes de melhor representar interações celulares persiste. Assim, foi proposta uma abordagem baseada em “assemblóides” para obter modelos 3D in vitro de melanoma para estudar interações celulares. Estes “assemblóides” tumorais heterotípicos apresentaram uma arquitetura complexa capaz de suportar a função de células endoteliais, bem como a elevada expressão de marcadores de pluripotência. Estes modelos foram sujeitos a ensaios de funcionalidade onde mostraram a capacidade de “invasão cooperativa” que foi coincidente com uma produção aumentada de MMP-2. Para tornar mais claro o papel das células estaminais no potencial invasivo de células tumorais, uma câmara 3D de quimiotaxia foi desenvolvida para estudar as interações celulares observadas no microambiente tumoral onde as células estaminais e fibroblastos mostraram ter um papel determinante. Em última análise, esta tese permitiu explorar abordagens da engenharia biomédica de forma a contribuir para o conhecimento da área e abrir novas portas a serem exploradas no futuro

The inflammatory infiltrate of high-grade serous carcinoma omental metastasis

PhDThe aim of this thesis is to investigate the role of inflammatory infiltrates and chemokines in metastasis of high-grade serous ovarian cancer, HGSC, to the omentum using human tissue biopsies and a 3- dimensional (3D) cell culture model. In ten patients with metastatic HGSC, omental tumour deposits contained a prominent leukocyte infiltrate of CD3+ T cells (9% of total cells) and CD68+ macrophages (11% of total cells). The presence of CD68+ macrophages showed a significant positive correlation with tumour cell proliferation analysed by Ki67 expression. Four ovarian cancer cell lines were co-cultured on a 3D model mimicking the microenvironment of the omentum for two weeks. The model was composed of collagen embedded human fibroblasts covered in a confluent layer of human primary mesothelial cells. The mesothelial cells in the 3D model significantly increased the growth (p = 0.002) and invasion (p = 0.0004) of the ovarian cancer cells. CXCL12 is the macrophage chemoattractant and ligand for the major chemokine receptor expressed on ovarian cancer cells. An association between CXCL12 and extracellular matrix remodelling was identified in two independent gene expression microarrays of ovarian cancer biopsies. The expression of CXCL12 in the HGSC omental metastases measured by quantitative Real Time-PCR positively correlated with decorin expression. Antibody mediated neutralisation of CXCL12 reduced growth (p = 0.012) and invasion (p = 0.029) in the 3D model. Mimicking an infiltrate of CD68+ macrophages in this multicellular 3D in vitro system also produced measurable changes in inflammatory cytokine and chemokine expression. There is currently a demand for more accurate models of HGSC and a necessity to study its metastasis that presents itself as the major clinical problem in patients. Therefore the development of this 3D model to mimic tumour-promoting inflammation in HGSC metastasis will provide researchers with an essential tool for testing novel therapeutic strategies.This work was supported by the BBSRC (Biotechnology and Biological Sciences Research Council) and AstraZeneca in an Industrial Case Studentship, grant number BB/G017867/1