Vittorio Cristini - US grants

A joint theoretical, numerical and experimental study of co-continuous polymer blends under processing flow conditions is performed. Co-continuous blends consist of distinct continuous phases that form under appropriate conditions of flow and mass compositions near the phase-inversion point. This co-continuous regime leads to synergistic properties of the materials after processing, such as high electrical conductivity coupled to light weight and optimal mechanical response. This study is aimed at the development of criteria for detection, conditions for production, and to a better understanding of the stability of co-continuous blends. The Newtonian flow regime is investigated and the effect of a third component, i.e. surfactants, is studied. To perform this study, novel, state-of-the-art numerical methods are developed and applied to perform large-scale simulations. In parallel, experiments are targeted to provide insight and validation of the mathematical models, simulations and theory.

A joint theoretical, computational and experimental study of co-continuous polymer blends is performed. Co-continuous polymer blends consist of distinct sponge-like phases where one of the phases plays the role of the sponge and the other its complement. Such blends offer an important route to materials with unique combinations of properties not available in
single polymers or in blends with traditional dispersed (non continuous) droplet morphology. These unique properties impact strongly applications in the areas of materials and manufacturing, and biotechnology. For example, mechanical properties such as impact strength and tensile strength can exceed those of either blend component. Another application of co-continuous polymer blends is products for mass transfer control. In particular, a water-permeable phase containing a desiccant can be used to remove moisture from moisture sensitive products such as food or pharmaceuticals while the other phase provides mechanical strength. The key to performance in these products is the control of pore size and volume. This fundamental study brings together state-of-the-art mathematical and numerical analysis, modeling and large-scale scientific computation with an innovative experimental program. The experiments are targeted to provide insight and validation of the mathematical models, simulations and theory. This research is aimed to provide guidelines for controlling pore size and volume of the blends and thus to optimize the blend properties. It is expected to lead to significant improvements in the industrial fabrication processes of co-continuous blends and in the properties of the final products.

The goal of this project, which lies at the interface between mathematics and biology, is to develop mathematical models of tumor growth that connect intra-tumor molecular and cellular properties with critical tumor behaviors, such as invasiveness, and experimentally observable properties such as morphology. The research group will (1) perform novel analytical and computational studies of important constituent processes, (2) incorporate experimental data into these studies, and (3) develop and apply state-of-the-art numerical algorithms to large-scale computations over multiple time and space scales. By integrating experimental data with sophisticated, multi-scale mathematical and computational models, the potential for breakthroughs that will significantly further the understanding of tumor biology are great, thereby addressing a pressing national and global need.

Solid tumors are complex micro-structured materials, where the three-dimensional tissue architecture (morphology) and dynamics are coupled in complex, nonlinear ways to cellular characteristics and to molecular composition and structure of the growth environment. This close connection between the tumor morphology and the underlying cellular/molecular dynamics has fundamental scientific importance in that the cellular dynamics that give rise to various tumor morphologies also control its ability to invade the host tissue. This allows observable properties of the tumor, such as its morphology, to be used to both understand the underlying cellular physiology and predict the tumors invasion potential. In particular, the conjecture that diverse morphologic patterns of invasion observed during tumor growth are the quantitatively predictable result of molecular inhomogeneity (of both composition and structure) in the tumors growth environment will be tested. Because tumor cells use similar or identical migration and proliferation mechanisms as normal cells, and because of the multi-scale nature of these processes, the mathematical modeling, analysis and simulation that will be conducted in this project will also have application in understanding normal functional processes during development, wound-healing, stem cell differentiation and tissue regeneration. This project will also establish a new collaboration among five institutions and broadens the participation of women and minorities in research as trainees in the investigators? groups, thereby addressing national needs. It will provide interdisciplinary training with theoreticians and experimentalists at the interface between mathematics and tumor cell biology. Finally, a month-long summer COSMOS (California State Summer School for Mathematics and Science) course at UC Irvine will be developed for high school students on these topics. This course enhances the participation of gifted high school students in research, and helps to recruit new math and science undergraduates, which addresses another national need.

Core 1 will provide an In silico framework (i) for modeling the systemic administration of therapeutic agents to solid tumors, their transport properties, and their efficacy in controlling tumor growth and (ii) for the 'rational design' of injectable nano-sized particulate systems (nPSs). The mathematical tools will be multi-scale and multi-physics spanning from the analysis of particulate transport within the vascular compartment (sovracellular level, > 10 um), to the adhesive interactions with the vascular walls and macrophages/Kuppfer cells within the liver sinusoids (cellular level, >1 um and <10 um); to the passive translocation across the vascular endothelium and Gl epithelial layers (sub-cellular level, < 1 um), down to the cellular internalization and intracellular transport (sub-cellular level, ¿ 1 um). This core is composed by modules, highly integrated one with the other the other core. Core 1 is co-lead by Drs. Cristini and Decuzzi with the collaboration of Dr. Ferrari and Dr. Macklin. Dr. Cristini (Ph.D. Chemical Engineering, FAAN) is an Associate Professor of Biomedical Engineering and Health Information Sciences at the University of Texas Health Science Center and provides multiscale modeling expertise. Dr. Decuzzi (Ph.D. Mechanical Engineering) is an Associate Professor of Mechanical and Biomedical Engineering at the University of Texas Health Science Center and the Center for Bio/Nanotechnology and Engineering for Medicine at the University of Magna Graecia (In Italy). Dr. Ferrari (Ph.D. Mechanical Engineering) is professor of Professor and Director of the Division of Nanomedicine and Professor of Internal Medicine in the Cardiology Division of The University of Texas Health Science Center, Deputy Chairman of the Department of Biomedical Engineering at the University of Texas. Dr. Macl

Overall, the project is designed to (1) add insights as to the biophysical mechanisms that link molecular- and cell-scale variations in the tumor and the microenvironment to the tumor's growth, (2) develop techniques that allow us to readily incorporate cutting-edge experimental measurements into the multi-scale model and thus more quickly determine their impact on overall tumor progression and response to therapy, (3) investigate and quantify the spatiotemporal dynamics of tumor response to therapy, (4) improve the in vivo-in silico development feedback loop that forms the backbone of true integrative modeling, and so (4) push the frontier of multi-scale, integrative cancer modeling. In order to quantify the relationships between complex cancer phenomena at different scales, we harness the advantages of both discrete and continuum modeling approaches by employing hybrid modeling. We implement hybrid, multi-scale algorithms as the next stage of cancer modeling in general, and lymphoma and leukemia modeling in particular. This involves dynamically coupling tumor-scale models and molecular/cell-scale models developed by Cristini, Macklin and coworkers with cell signaling and evolutionary/hereditary models developed by Research Project 2. This also requires integration with state of- the-art intravital time-course measurements of tumor growth, vascularization, and response to chemotherapy by Gambhir and co-workers. These experiments will (1) provide us with first-hand biological data that will shape the model development, (2) provide us with precise measurements of key model parameters that uniquely constrain the modeling framework, (3) provide additional, independent tests for model validation and testing, and (4) provide an opportunity for true integrative modeling, where our first round of investigating the calibrated model leads to follow-up experiments to test new cancer biology hypotheses and improve the multiscale model.

The structure of the developing mammary gland is regulated by stimulatory and inhibitory epithelial-epithelial and epithelial-stromal cell interactions (e.g., signaling, adhesion). While mammary developmental biologists have gathered a wealth of molecular and cellular data, fundamental questions remain. For example, it is still unknown how cells of various types become organized into a duct. How is the organization affected by system perturbations such as altered signaling processes? The answers to these questions rely on an understanding of signaling and behavioral "rules" governing normal ductal morphogenesis and maintenance. Experimental investigations of these interactions, complemented by mathematical models, can help facilitate the understanding and definition of these rules. In this project, the investigators employ a joint experimental and mathematical modeling approach to study mammary gland development with a focus on ductal morphogenesis. With respect to cellular and tissue level parameters, the investigators design specific experiments to measure model parameters and validate model results. Particular emphasis will be placed on the nature of the signaling vs. receiving cell type(s). In parallel, the complementary expertise will be leveraged and used to develop a multiscale mathematical and computational framework to bridge the gap between tissue scale models of ductal morphogenesis and cellular scale models with detailed cell arrangements. This integrative project will allow for predicting what occurs in response to system perturbations such as loss-of-function due to mutations or epigenetic events. This can provide insight on the emergence of abnormal development programs and the initiation of tumors. The methods developed here will be applicable to modeling other organs with branching architectures such as lung, salivary, olfactory epithelium and prostate glands. Beyond these applications, the new tools developed here will also impact other problems in the biological sciences including development of other tissues and organs, wound healing, and tissue regeneration that are characterized by processes occurring in concert over a wide range of space and time scales.

One of the fundamental questions in biology is how tissues and organs develop and become organized. Developmental processes are the result of complex mechanical and signaling processes occurring inside and outside cells, and between cells and the environment. Such complex processes are very difficult to understand by using conventional experiment-based approaches alone. Recently, it has been recognized that mathematical modeling can provide a unique and complementary tool to experimental investigations by generating experimentally testable hypotheses, and that an integrated experimental and computational approach can potentially be more powerful than solely using experimental investigation, in identifying mechanisms responsible for non-intuitive developmental behavior frequently observed in experiments. However, the developmental processes involve interactions across a wide range of spatial and temporal biological scales. Thus, new mathematical models describing biological behavior at different scales, and at different levels of complexity, should be developed, linked together, and experimentally validated to provide a theoretical predictive framework to complement current developmental biology research. This is precisely what this project will address in the context of the mammary gland, for which it is still unknown how the cells of various types become organized and how this organization is affected by perturbations to the system such as from mutations. Specifically, these questions will be addressed by drawing on the complementary expertise of the researchers in mathematical and computational modeling and in experimental techniques to create and analyze a multiscale modeling framework for mammary gland development. The parameters in the models will be measured, and the models will be validated, using specifically designed experiments. The integrative work presents a necessary first step towards further development of a comprehensive, multiscale computational framework capable of accurately predicting the development of normal and abnormal mammary gland morphologies.

The University of Texas Health Science Center at Houston (UTHSC-H), The University of Texas M.D. Anderson Cancer Center, Rice University and Albert Einstein College of Medicine have joined forces to form the Texas Center for Cancer Nanomedicine (TCCN). The TCCN brings together a multi-disciplinary, internationally recognized team of investigators to develop and translate nanotechnology-enabled innovation for improving the traditionally dismal outcome of ovarian and pancreatic cancers. The main research focus areas of the TCCN are: Multifunctional Nano-Therapeutics and Post-Therapy Monitoring Tools (Area 2 of the CCNE RFA), and Devices and Techniques for Cancer Prevention and Control (Area 3). By natural synergies of the underlying nano-platforms, the TCCN's investigations in focus areas 2 and 3 automatically provide a cadre of approaches for Area 1: Early Diagnosis Using In-Vitro Assays and Devices and In-Vivo Imaging Techniques. The TCCN has four projects and three cores. Projects 1 and 2 directly address ovarian cancer, and Projects 3 and 4 directly address pancreatic cancer. In each oncology focus area, one project involves multifunctional nanoplatforms for the delivery of bioactive agents to the tumors (Project 1- ovarian and Project 3- pancreatic), and the other, targeting approaches to the cancer-associated vascular endothelia (Project 2- ovarian and Project 4- pancreatic), for imaging and therapy. Both adenocarcinoma (Project 3) and endocrine pancreatic malignancies (Project 4) are considered in the TCCN. All Projects integrate fundamental investigations in cancer biology, nanotechnology platform development, and pharmaceutical sciences, albeit to different degrees. The cores are the Biomathematics Core, Targeting Core and Nanoengineering Core. All projects and Cores integrate with each other through the sharing of research results and nanotechnology platforms. This integration allows the TCCN to achieve clinical translation of its research breakthroughs, and aggressively manage the risks that are naturally associated with any highly innovative program at a rapid pace. To fuel translation to the clinic, several TCCN investigators have successfully developed spin-off companies based upon their research. Collectively, with a combination of synergistic projects supported by cores that provide services to each project and a track record of successful bench-to-bedside translation, the TCCN is uniquely positioned to bring forth highly effective nanotechnology platforms for prevention, therapy and monitoring of ovarian and pancreatic cancers.

The complexity of tumor growth, which involves interactions within cells, among cells, and between cells and their environment, calls for development of mathematical and computational models that can connect processes from the cell, and sub-cell scales, to tissue level scales. These methods are needed to help tumor biologists gain further insight into the underlying mechanisms of the processes (e.g., proliferation, differentiation, and migration) involved in tumor development, at the scales which influence their behavior. Because of this complexity, it has been challenging to functionally link cell and tissue scale processes, the knowledge of which is key to development of predictive multiscale tumor models. However, current models typically use ad-hoc rules to bridge between scales, which limits their predictive capability. This project will address this challenge by developing a new multiscale method where directly measurable quantities at the cell-scale inform the model parameters at the continuum tissue scale through rigorous, mathematical upscaling techniques. The multiscale model will be tested and validated by comparing simulation results against experimentally obtained information about the overall growth rates and spatiotemporal behaviors of the different cells and tumors. The new multiscale method will be used to study pancreatic tumors to elucidate the transition of pancreatic lesions into invasive pancreatic ductal adenocarcinoma (PDAC). By integrating patient data analysis with quantitative tumor modeling, the project will develop reliable methods that can predict the likelihood of pancreatic cyst progression to PDAC using relatively non-invasive approaches.

The project team will develop a new class of multiscale models that bridge these scales non-phenomenologically through application of rigorous upscaling techniques in order to close the continuum equations at the tissue scale and provide an accurate description of the processes across both cell and tissue scales. Specifically, stochastic agent-based models at the cell-scale and continuum partial differential equation models at the tissue-scale will be developed. Consistent functional relationships between the variables at the tissue-scale and measurements at the cell-scale will be found by upscaling the discrete models by using and extending the framework of dynamic density functional theory (DDFT) to obtain multi-cell scale continuum equations that account for correlations among cells as well as biological processes such cell birth and death. Further upscaling to the tissue scale will be done by identifying and deriving equations for slowly varying variables. The consistency of the different models in domains where the scales overlap will be tested and validated. The new multiscale method will be applied to model the progression of pancreatic neoplasms into invasive carcinomas in order to estimate the probability of this progression. Large-scale human patient datasets of pancreatic lesions, provided by our consultants through a separately funded project, will be used to validate and refine the models. The project will enhance the cross disciplinary training of students.

ABSTRACT Eight percent of patients diagnosed with prostate cancer progress to lethal metastatic disease. Development of resistance to androgen-deprivation therapy and eventually, to last line chemotherapeutics such as enzalutamide (ENZ), contribute to lethal, metastatic prostate cancer. While interest to identify tumor-specific molecular signatures, termed precision medicine, is gaining popular favor, it requires identification of physiologically accessible targets. By diverting the function of a molecular tumor target by conventional anti- cancer drugs, rates of tumor growth are expected to decrease; however, this does not take into account acquired drug resistance mechanisms which are dependent on systemic drug stability, solubility or toxicity. One method to stabilize poorly soluble and/or highly toxic drugs, and potentially overcome resistance, is to encapsulate drugs in nanoparticles (NPs) to prevent their degradation and enhance their circulation time. Moreover, accumulation of loaded NPs at the tumor site can be improved by adding tumor-specific targeting moieties that induce NP endocytosis, thereby improving the therapeutic index while minimizing collateral damage to healthy cells. A prostate tumor-specific biomarker, the 78 kDa glucose-regulated protein (GRP78), was identified by the Pasqualini and Arap team by screening antibodies from prostate cancer patient sera. GRP78 is a biomarker of disease progression and, crucial to our proposed research, we recently identified human recombinant anti-GRP78 antibodies with optimal in vivo tumor targeting. In this proposal, our objective is to generate GRP78-targeted NPs against ENZ-resistant prostate cancer. We will employ the novel, modular ?protocell? platform developed by the Brinker team. Protocells consist of a porous silica core, which can be engineered to accommodate varied and combination cargos, encapsulated within a supported lipid bilayer that protects and retains the cargo, and provides a biocompatible surface for conjugation to targeting and/or trafficking ligands. The Brinker team demonstrated exceptional stability of targeted, first-generation protocells in vivo with specific binding and cargo delivery to individual circulating leukemia cells. Instead of delivering chemotherapeutic drugs that work at the protein level, we propose to deliver small interfering RNAs (siRNAs) directed against the long non-coding RNA, PCA3. We showed that interfering with PCA3 inhibits growth of human prostate xenografts. Guided by predictive modeling conducted by the Cristini team, our modular GRP78-targeted protocells will be designed to package PCA3 siRNAs to selectively bind to GRP78-expressing prostate cancer cells, and deliver PCA3 siRNAs intracellularly to inhibit tumor growth. Our project is a first-in- field study that galvanizes our current combined expertise and technology. The dual prostate tumor ?centric? feature of these next generation NP prototype platforms increases their specificity and efficacy, and overcomes the limitation of conventional standard-of-care drugs, particularly in the case of acquired drug resistance.

The deregulation of miR-155, a highly oncogenic microRNA (miRNA), has been associated with a wide variety of malignancies including lung cancer. Non-small-cell lung cancer (NSCLC) is the leading cause of cancer- related death in the US with dismal clinical advances to improve patient?s survival, due to the development of drug-resistance. We have demonstrated that miR-155 plays a role in mediating resistance to chemotherapy in NSCLC. Treatment with anti-miR-155-DOPC significantly reduced tumor growth and resensitized NSCLC to standard of care platinum-based chemotherapeutics with no toxicity in an in vivo orthotopic mouse model. miR- 155 acts on a TP53-dependent mechanism, triggering a feedback loop leading to chemotherapy resistance. Tumor microenvironment (TME) plays an important role in the promotion of cancer, specifically via monocyte/macrophage cells that express high levels of miR-155 by exosomal transfer with cancer cells. We developed nanoliposomal-bound aptamers to specifically target the AXL receptor, significantly overexpressed by NSCLC tumor cells and expressed also by monocyte/macrophage cells, in addition to targeting miR-155. By complementing standard interventions that have life-threatening toxicities with anti-miR-155 in nanodelivery vehicles (like single-lipid nanoliposomal particles, SLNPs), which we anticipate to be safe and non-toxic, we expect our findings to change treatment regimens for NSCLC. The main goal of this MPI revised application is to perform preclinical safety and toxicity studies to test the efficacy and safety of adjuvant anti-miR-155 therapies, coupled with SLNP-anti-miR-155 or AXL-Apt-SLNP-anti-miR-155, alone or in combination with cisplatin and vinorelbin. These preclinical studies will pave the way to an Investigational New Drug (IND) application for the use of anti-miR-155 treatment in NSCLC, and other chemotherapeutic resistant tumors. We plan to: 1) target miR-155 both in cancer cells and in TME by using the two types of SLNPs in NSCLC; 2) determine the toxicity of anti-miR-155 therapies based on the delivery using biocompatible nanodelivery in animal studies; 3) identify the full spectrum of miR-155 targets that could be therapeutically exploited and used for reducing toxicity; 4) develop novel mathematical models to determine the therapeutic value of anti-miR-155 treatment, based on multiple parameters, including circadian administration; 5) determine the in vivo antitumor efficacy of tumor targeted dual-effect AXL-Apt-SLNP-anti-miR-155 nanotherapeutics alone and in combination with chemotherapy in orthotopic and patient-derived xenograft models and, finally, 6) to compile the results for the IND application. The final outcome of our proposal would be to establish the efficacy of anti-miR-155 to treat NSCLC by directly targeting miR-155 in the tumor and TME in combination with existing chemotherapeutic treatments. We expect anti-miR-155 to significantly reduce the mortality of NSCLC without any major side effects, and also improve overall survival. Such studies can be further expanded for targeted therapeutic strategies, such as checkpoint inhibition, if these become the standard of care.