Unraveling the intricacies of spatial organization of the ErbB receptors and downstream signaling pathways

Faced with the complexity of diseases such as cancer which has 1012 mutations, altering gene expression, and disrupting regulatory networks, there has been a paradigm shift in the biological sciences and what has emerged is a much more quantitative field of biology. Mathematical modeling can aid in biological discovery with the development of predictive models that provide future direction for experimentalist. In this work, I have contributed to the development of novel computational approaches which explore mechanisms of receptor aggregation and predict the effects of downstream signaling. The coupled spatial non-spatial simulation algorithm, CSNSA is a tool that I took part in developing, which implements a spatial kinetic Monte Carlo for capturing receptor interactions on the cell membrane with Gillespies stochastic simulation algorithm, SSA, for temporal cytosolic interactions. Using this framework we determine that receptor clustering significantly enhances downstream signaling. In the next study the goal was to understand mechanisms of clustering. Cytoskeletal interactions with mobile proteins are known to hinder diffusion. Using a Monte Carlo approach we simulate these interactions, determining at what cytoskeletal distribution and receptor concentration optimal clustering occurs and when it is inhibited. We investigate oligomerization induced trapping to determine mechanisms of clustering, and our results show that the cytoskeletal interactions lead to receptor clustering. After exploring the mechanisms of clustering we determine how receptor aggregation effects downstream signaling. We further proceed by implementing the adaptively coarse grained Monte Carlo, ACGMC to determine if \u27receptor-sharing\u27 occurs when receptors are clustered. In our proposed \u27receptor-sharing\u27 mechanism a cytosolic species binds with a receptor then disassociates and rebinds a neighboring receptor. We tested our hypothesis using a novel computational approach, the ACGMC, an algorithm which enables the spatial temporal evolution of the system in three dimensions by using a coarse graining approach. In this framework we are modeling EGFR reaction-diffusion events on the plasma membrane while capturing the spatial-temporal dynamics of proteins in the cytosol. From this framework we observe \u27receptor-sharing\u27 which may be an important mechanism in the regulation and overall efficiency of signal transduction. In summary, I have helped to develop predictive computational tools that take systems biology in a new direction.\u2

Localized immune surveillance of primary melanoma in the skin deciphered through executable modeling

While skin is a site of active immune surveillance, primary melanomas often escape detection. Here, we have developed an in silico model to determine the local cross-talk between melanomas and Langerhans cells (LCs), the primary antigen-presenting cells at the site of melanoma development. The model predicts that melanomas fail to activate LC migration to lymph nodes until tumors reach a critical size, which is determined by a positive TNF-α feedback loop within melanomas, in line with our observations of murine tumors. In silico drug screening, supported by subsequent experimental testing, shows that treatment of primary tumors with MAPK pathway inhibitors may further prevent LC migration. In addition, our in silico model predicts treatment combinations that bypass LC dysfunction. In conclusion, our combined approach of in silico and in vivo studies suggests a molecular mechanism that explains how early melanomas develop under the radar of immune surveillance by LC

Analysis of matrix metalloproteinases in cancer cell signaling and extracellular behavior

Despite the fact that over the past two decades the total death rate has declined up to twenty percent, cancer remains the second leading cause of death in the United States and accounts for nearly one in every four deaths. It is therefore of paramount importance that new strategies continue to develop in an effort to curb both incidence and treatment of disease. The current research landscape is focused on developing strategies to disrupt molecular signatures of cancer cell types, commonly known as targeted therapy. Of particular importance in the advancement of targeted therapies are matrix metalloproteinases (MMPs), a family of endopeptidases whose primary function lies in cleaving extracellular matrix (ECM) proteins and are frequently dysregulated in cancer. While research regarding MMPs is decades old, their significance in the signal transduction of several oncogenic pathways is yet to be fully explored. In addition, a dearth of quantitative data exists describing the action of MMPs in three dimensional (3D) networks, a configuration that causes cells to express vastly different behaviors compared to traditional two-dimensional (2D) in vitro culture methods. This dissertation aims to further elucidate the intimate relationships between MMPs, the ECM, cancer pathway signaling, and cell migration. First, the behavioral crosstalk between MMPs and the ECM is studied using quantitative methods in 3D matrices. Next, the role of MMPs in both Ras oncogenic and HER2 positive breast cancer is probed via extensive protein expression analysis. Finally, the behavioral aspects of MMPs in 3D are assessed marrying both in vitro data with a computational model to predict migration response. The results reveal that MMPs exhibit a bidirectional relationship with respect to matrix architecture, and the ability to regulate and be regulated by the ECM. In addition, it is concluded that MMPs play a significant role in both active Ras and HER2 upregulated cancer signaling. Finally, the data demonstrates the robustness and accuracy of our methods in manufacturing a model to predict migration in 3D matrices. The work described here promises to further enhance the knowledge of MMPs in cancer and potentially inform future drug development endeavors

Metabolic therapy and bioenergetic analysis: The missing piece of the puzzle.

Background Aberrant metabolism is recognized as a hallmark of cancer, a pillar necessary for cellular proliferation. Regarding bioenergetics (ATP generation), most cancers display a preference not only toward aerobic glycolysis (“Warburg effect”) and glutaminolysis (mitochondrial substrate level-phosphorylation) but also toward other metabolites such as lactate, pyruvate, and fat-derived sources. These secondary metabolites can assist in proliferation but cannot fully cover ATP demands. Scope of review The concept of a static metabolic profile is challenged by instances of heterogeneity and flexibility to meet fuel/anaplerotic demands. Although metabolic therapies are a promising tool to improve therapeutic outcomes, either via pharmacological targets or press-pulse interventions, metabolic plasticity is rarely considered. Lack of bioenergetic analysis in vitro and patient-derived models is hindering translational potential. Here, we review the bioenergetics of cancer and propose a simple analysis of major metabolic pathways, encompassing both affordable and advanced techniques. A comprehensive compendium of Seahorse XF bioenergetic measurements is presented for the first time. Major conclusions Standardization of principal readouts might help researchers to collect a complete metabolic picture of cancer using the most appropriate methods depending on the sample of interest.post-print3250 K

Cell Signaling Regulatory Mechanisms Controlling Epithelial-Mesenchymal Transition in Carcinoma

Epithelial-mesenchymal transition (EMT) is a cellular program normally engaged during development and wound healing that is hijacked in many cancers to drive metastasis and resistance to therapy. The clinical implications of EMT in cancer progression have driven efforts to understand the cellular processes controlling EMT induction. Transforming growth factor-beta (TGFβ) and expression of related transcription factors potentiate EMT induction through complex and incompletely understood mechanisms. In this thesis, we investigated specific intracellular signaling pathways controlling maintenance of mesenchymal characteristics and EMT induction in response to growth factors in lung and pancreatic carcinoma cells. In lung carcinoma cells, extracellular signal-regulated kinase-1/2 (ERK1/2) pathway activation, which promotes cell survival and proliferation, was required for complete EMT induction. Furthermore, chronic ERK1/2 inhibition reversed baseline mesenchymal traits while simultaneously augmenting cellular sensitivity to a clinically approved small molecule EGFR inhibitor in cell lines with multiple clinically relevant modes of therapy resistance. In both lung and pancreatic carcinoma cell lines, TGFβ-mediated EMT was enhanced by co-treatment with epidermal growth factor (EGF), as had been noted in other contexts. We demonstrated that the ability of EGF to enhance TGFβ-mediated EMT depended on SH2 domain-containing phosphatase-2 (SHP2) activation through tyrosine phosphorylated adapter binding, which is required for complete ERK1/2 activation. Though SHP2 was not directly engaged and activated by TGFβ, SHP2 was required for TGFβ-mediated effects. Incomplete or transient effects of ERK inhibition and SHP2 depletion motivated subsequent systematic evaluation of cell signaling processes engaged during EMT induction to identify other pathways that control mesenchymal dedifferentiation in pancreatic carcinoma cells. We thus developed a data-driven computational model to predict the relationships between multivariate signaling events and EMT-associated phenotypes in response to combinations of TGFβ, EGF, and hepatocyte growth factor (HGF). Signaling intermediates that co-varied most with mesenchymal traits provided novel potential targets to inhibit EMT phenotype acquisition or restore epithelial traits in carcinoma. Together, this thesis enhanced mechanistic understanding of EMT regulation by SHP2, identified novel strategies to reverse EMT phenotypes in carcinoma cells, and generated a quantitative model to understand mesenchymal dedifferentiation, which can be leveraged in the future to improve clinical outcomes for cancer patients

Systematic identification of MACC1-driven metabolic networks in colorectal cancer

MACC1 is a prognostic and predictive metastasis biomarker for more than 20 solid cancer entities. However, its role in cancer metabolism is not sufficiently explored. Here, we report on how MACC1 impacts the use of glucose, glutamine, lactate, pyruvate and fatty acids and show the comprehensive analysis of MACC1-driven metabolic networks. We analyzed concentration-dependent changes in nutrient use, nutrient depletion, metabolic tracing employing (13)C-labeled substrates, and in vivo studies. We found that MACC1 permits numerous effects on cancer metabolism. Most of those effects increased nutrient uptake. Furthermore, MACC1 alters metabolic pathways by affecting metabolite production or turnover from metabolic substrates. MACC1 supports use of glucose, glutamine and pyruvate via their increased depletion or altered distribution within metabolic pathways. In summary, we demonstrate that MACC1 is an important regulator of metabolism in cancer cells

Translational Research in Cancer

Translational research in oncology benefits from an abundance of knowledge resulting from genome-scale studies concerning the molecular pathways involved in tumorigenesis. Translational oncology represents a bridge between basic research and clinical practice in cancer medicine. The vast majority of cancer cases are due to environmental risk factors. Many of these environmental factors are controllable lifestyle choices. Experimental cancer treatments are studied in clinical trials to compare the proposed treatment to the best existing treatment through translational research. The key features of the book include: 1) New screening for the development of radioprotectors: radioprotection and anti-cancer effect of β-Glucan (Enterococcus faecalis) 2) Translational perspective on hepatocellular carcinoma 3) Brachytherapy for endometrial cancer 4) Discovery of small molecule inhibitors for histone methyltransferases in cance

Doctor of Philosophy

dissertationThermal ablation is widely used, first line local-regional therapy for unresectable hepatocellular carcinoma (HCC). Although high temperature delivered by thermal energy results in efficient coagulation necrosis in tumor cells, various factors including tumor size, shape, location, and cirrhosis can lead to un-uniform heat distribution and inefficient cell damage. As a result, the incomplete ablation causes high rates of tumor recurrence and poor survival for HCC patients. Cells that are not completely ablated can induce heat shock proteins (HSPs), which are cellular gatekeepers to protect tumor cells from thermal damage and prepare them for future neoplastic growth. Synchronous adjuvant chemotherapy targeting those cells can achieve more complete tumor abrogation and prevent future tumor recurrence. This dissertation describes a strategy to combat postablation recurrence by synchronous inhibition of heat shock protein 90 (HSP90) by thermo-responsive, elastin-like polypeptide (ELP)-based biopolymer conjugates. ELP copolymer carries high concentrations of a potent HSP90 inhibitor, geldanamycin (GA), which inhibit the induction of HSP90 and further destabilize numerous HSP90 client proteins critical for cell survival. It is hypothesized that combination of thermal ablation with concomitant inhibition of HSP90 via ELP-GA conjugates can achieve synergistic anticancer effect. Specifically, the ablation-created hyperthermia will sensitize tumor cells to be more vulnerable to the drug, which will be conjugated with high concentrations through thermally targeted, ELP-based biopolymer systems. The ELP conjugates, in turn, will reach and kill the remaining viable cells to prevent future recurrence. ELP-GA conjugates that ferry multiple GAs and rapidly respond to hyperthermia were synthesized, characterized, and evaluated for activity in HCC models. The cytotoxicity of ELP-GA conjugates was enhanced with hyperthermia treatment, and effective HSP90 inhibition was achieved in HCC cell lines. In a tumor-bearing mouse model, electrocautery-based thermal ablation offered effective destruction of tumor core and created a hyperthermia zone for targeted delivery and accumulation of ELP-GA conjugates. Results demonstrate that the combination of thermal ablation and targeted HSP90 inhibition can enhance the anticancer effect and cellular delivery of macromolecular chemotherapeutics to achieve safe, synergistic, and long-term anticancer effect with no tumor recurrence observed. The combination approach paves the way for developing molecular-targeted intervention to increase the efficacy of first-line local-regional therapies for HCC

Tumor-penetrating delivery of small interfering RNA therapeutics

Thesis (Ph. D. in Medical Engineering)--Harvard-MIT Program in Health Sciences and Technology, 2012.Vita. Cataloged from PDF version of thesis.Includes bibliographical references (p. 234-250).Efforts to sequence cancer genomes have begun to uncover comprehensive lists of genes altered in cancer. Unfortunately, the number and complexity of identified alterations has made dissecting the underlying biology of cancer difficult, as many genes are not amenable to manipulation by small molecules or antibodies. RNA interference (RNAi) provides a direct way to assess and act on putative cancer targets. However, the translation of RNAi into the clinic has been thwarted by the "delivery" challenge, as small interfering RNA (siRNA) therapeutics must overcome clearance mechanisms and penetrate into tumor tissues to access cancer cells. This thesis sought to develop nanotechnology-based platforms to rapidly discover and validate cancer targets in vivo. First, we developed versatile surface chemistries for nanoparticle tumor targeting. Leveraging new discoveries in amplified transvascular transport, we designed a siRNA delivery system that integrates the tumor specificity and tissue-penetrating ability of tumor-penetrating peptides with membrane penetration properties of protein transduction domains to direct siRNA to tumors in vivo. Second, we utilized this delivery system to bridge the gap between cancer genomic discovery and in vivo target validation. Comprehensive analysis of ovarian cancer genomes identified candidate targets that are undruggable by traditional approaches. Tumor-penetrating delivery of siRNA against these genes potently impeded the growth of ovarian tumors in mice and improved survival, thereby credentialing their roles in tumor initiation and maintenance. Lastly, we described efforts extending this platform for clinical translation. Mechanistic studies identified functional properties that favored receptor-specific siRNA delivery. We also explored a strategy to improve the microdistribution of successively dosed siRNA therapeutics through modulating the tumor microenvironment. Finally, we investigated the utility of the system in primary human tumors derived from patients with ovarian cancer. Together, these findings illustrate that the combination of cancer genomics with the engineering of siRNA delivery nanomaterials establishes a platform for discovering genes amenable to RNAi therapies. As efforts in genome sequencing accelerate, this platform illustrates a path to clinical translation in humans.by Yin Ren.Ph.D.in Medical Engineerin