Quantitative analysis of perivascular antibody distribution in solid tumors

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, February 2013.Cataloged from PDF version of thesis. "September 2012."Includes bibliographical references.Monoclonal antibodies and proteins derived from them are an emerging class of anticancer therapeutics that have shown efficacy in a range of blood and solid tumors. Antibodies targeting solid tumors face considerable transport barriers in vivo, including blood clearance, extravasation, diffusion within the tumor interstitium, binding to antigen, endocytosis, and degradation. The unique pathology of the blood supply to solid tumors only serves to exacerbate these problems. A consequence of poor delivery of antibodies to solid tumors is a characteristic perivascular distribution of antibodies around tumor blood vessels. Often, antibodies bind only cells within a few cell layers of blood vessels, leaving large areas of tumor cells farther from perfused vessels completely untargeted. This phenomenon has been observed in multiple studies involving different antibodies, antigens, and tumor types, both in animal models and in clinical settings. In this thesis, the perivascular localization of antibodies is explored as a function of quantitative parameters of the antibody and associated antigen. A novel experimental system to quantitatively determine bound antibody levels, antigen levels, and blood vessel localization on a microscopic scale throughout entire tumor cross sections has been developed. This system has been used to quantitatively measure antibody and antigen distribution in tumor tissue under a variety of conditions. Effects of varying antibody dose, antibody affinity, and tumor type and site have been explored and quantitated using this model. To guide experimental design, we have developed a simplified mathematical model of the tumor vasculature. This model offers insights into the effects of antigen and antibody parameters, including dose, affinity, antigen density, and endocytosis rates, which are measurable in vivo and affect antibody penetration into tumor tissue. A simple scaling analysis further allows the quantitative determination of the minimum antibody dose required to saturate a tumor given the antigen turnover rate and density. Together, the mathematical model and quantitative experimental analysis allow conclusions to be made regarding antibody design and antigen selection for improved tumor penetration of therapeutic antibodies.by John J. Rhoden.Ph.D

Decitabine potentiates efficacy of doxorubicin in a preclinical trastuzumab-resistant HER2-positive breast cancer models

Acquired drug resistance and metastasis in breast cancer (BC) are coupled with epigenetic deregulation of gene expression. Epigenetic drugs, aiming to reverse these aberrant transcriptional patterns and sensitize cancer cells to other therapies, provide a new treatment strategy for drug-resistant tumors. Here we investigated the ability of DNA methyltransferase (DNMT) inhibitor decitabine (DAC) to increase the sensitivity of BC cells to anthracycline antibiotic doxorubicin (DOX). Three cell lines representing different molecular BC subtypes, JIMT-1, MDA-MB-231 and T-47D, were used to evaluate the synergy of sequential DAC + DOX treatment in vitro. The cytotoxicity, genotoxicity, apoptosis, and migration capacity were tested in 2D and 3D cultures. Moreover, genome-wide DNA methylation and transcriptomic analyses were employed to understand the differences underlying DAC responsiveness. The ability of DAC to sensitize trastuzumab-resistant HER2-positive JIMT-1 cells to DOX was examined in vivo in an orthotopic xenograft mouse model. DAC and DOX synergistic effect was identified in all tested cell lines, with JIMT-1 cells being most sensitive to DAC. Based on the whole-genome data, we assume that the aggressive behavior of JIMT-1 cells can be related to the enrichment of epithelial-to-mesenchymal transition and stemness-associated pathways in this cell line. The four-week DAC + DOX sequential administration significantly reduced the tumor growth, DNMT1 expression, and global DNA methylation in xenograft tissues. The efficacy of combination therapy was comparable to effect of pegylated liposomal DOX, used exclusively for the treatment of metastatic BC. This work demonstrates the potential of epigenetic drugs to modulate cancer cells' sensitivity to other forms of anticancer therapy.publishedVersio

Quantitative analysis of the focused ultrasound-induced blood-brain barrier opening with applications in neurodegenerative disorders

The blood-brain barrier poses a formidable impediment to the treatment of adult-onset neurodegenerative disorders, by prevention of most drugs from gaining access to the brain parenchyma. Focused ultrasound (FUS), in conjunction with systemically administered microbubbles, has been shown to open the blood-brain barrier (BBB) locally, reversibly and non invasively both in rodents and in non-human-primates. Initially, we demonstrate a monotonic increase of the BBB opening volume with close to normal incidence angle, detectable by diffusion tensor imaging; the employed contrast-free magnetic resonance protocol that revealed the anisotropic nature of the diffusion gradient. Implementation of this optimized BBB opening technique in Parkinsonian mice, coupled with the administration of trophic growth factors, induced restorative effects in the dopaminergic neurons, the main cellular target of the pathological process in Parkinson’s disease. The immune response initiated by the FUS-induced BBB disruption has been proven pivotal in reducing proteinaceous aggregates from the brain through the activation of a gliosis cascade. Therefore, we investigated this immunomodulatory effect in Alzheimer’s disease. The neuropathological hallmarks of Alzheimer’s disease include aggregation of amyloid beta into plaques and accumulation of tau protein into neurofibrillary tangles. Tau pathology correlates well with impaired neuronal activity and dementia and was found to be attenuated after the application of ultrasound that correlated with increased microglia activity. Given the beneficial effect of this methodology on the Alzheimer’s pathologies when studied separately, we explored the application of FUS in brains subjected concurrently to amyloidosis and tau phosphorylation. Our findings indicate the reduction of tau protein and decrease in the amyloid load from brains treated with ultrasound, accompanied by spatial memory improvement. Overall, in this dissertation, we established an optimized targeting and detection protocol, pre-clinical implementation of which confirmed its ameliorative effects as a drug-delivery adjuvant or an immune response stimulant. These preclinical findings support the immense potential of such a methodology that significantly contributes to the treatment of different neurodegenerative disorders curbing their progression

Resistance is Futile: Physical Science, Systems Biology and Single-Cell Analysis to Understanding the Plastic and Heterogeneous Nature of Melanoma and Their Role in Non-Genetic Drug Resistance

Melanoma is the most deadly form of skin cancer due to its great metastatic potential. Targeted therapy that inhibits the BRAF-V600E driver mutation has shown impressive initial responses in melanoma patients. However, drug resistance, as the universal phenomenon for any cancer therapy, always limits treatment efficacy and compromises outcomes. As the early-step of resistance development, non-genetic mechanisms enable cancer cells to transition into a drug-resistant state in as early as a few days after drug treatment without alteration of the genome. This early mechanism is, to a large extent, due to the heterogeneous and highly plastic nature of tumor cells. Therefore, it imperative to understand the plastic and heterogeneous nature of the melanoma cells in order to identify combination therapies that can overcome resistance. In this thesis, we investigate these two fundamental natures of non-genetic drug resistance using BRAF inhibition of BRAF-mutant melanomas as the model system. These melanoma cells undergo multi-step, reversible drug-induced cell-state transitions from the original sensitive phenotype to a drug-resistant one. We first conducted bulk analysis to characterize the detailed kinetics of the entire transition from drug-sensitive state towards drug-resistant state, revealing expression changes of thousands of genes and extensive chromatin remodeling. A 3-step computational biology approach greatly simplified the complexity and revealed that the whole cell-state transition was controlled by a gene module activated within just the first three days of drug treatment, with the RelA transcription factor driving chromatin remodeling to establish an epigenetic program encoding long-term phenotype changes towards resistance. From there, a detailed mechanism connecting tumor epigenetic plasticity with non-genetic drug resistance was resolved through in-depth molecular biology experiments. The mechanism was validated in clinical patient samples. We further investigated heterogeneity by moving from bulk cellular studies to single-cell analysis. The single-cell view further revealed that two driving forces from both cell-state interconversions and phenotype-specific drug selection control the cell-state transition dynamics. The single-cell studies also pinpointed the signaling network hub, RelA, as the driver molecule of the initiation of the adaptive transition. These two competing driving forces were further quantitatively modeled via a thermodynamic-inspired surprisal analysis and a modified Fokker-Planck-type kinetic model. Finally, using integrated single-cell proteomic and metabolic technology I developed to characterize the early-stage signaling and metabolic changes upon initial drug responses, we further identified two distinct paths connecting drug-sensitive and drug-tolerant states. Melanoma cells exclusively traverse one of the two paths depending on the level of MITF in the drug-naïve cells. The two trajectories are associated with distinct signaling and metabolic susceptibilities and are independently druggable. In total, this thesis combines and synergizes various physical science and systems biology approaches together with several unique single-cell technologies and analysis to obtain a deep and comprehensive understanding of non-genetic drug resistance in cancer. The findings from this thesis provide several novel insights into the rational design of effective combination therapy for overcoming the development of resistance in response to cancer treatments.</p

The impact on high-fat diet on skeletal muscle stem cell recruitment in CD36 deficient mice

The prevalence of obesity is a major risk factor for cardiovascular and metabolic diseases including impaired skeletal muscle regeneration. Given the importance of skeletal muscle function in the context of obesity, it is paramount to understand the underlying mechanisms of impaired muscle health. Since skeletal muscle regeneration is regulated by muscle stem cells, the so-called satellite cells (SC), this thesis aims to investigate the effects of diet-induced obesity (DIO) on SC function. This study provides evidence that SC function is impaired in obesity, possibly linked to ectopic lipid infiltration via the fatty acid translocase CD36. Ectopic lipid infiltration was further linked to altered gene expression involved in skeletal muscle redox homeostasis and lipid metabolism. The CD36-deficient mouse model (CD36 KO) used for this study provides, for the first time, evidence of improved redox signalling and decreased oxidative stress in skeletal muscle under high-fat diet conditions, potentially linked to an altered mitochondrial bioenergetic profile. CD36 KO mice showed improved skeletal muscle lipid metabolism but interestingly developed signs of hepatic steatosis when exposed to a high-fat diet. Furthermore, the observed impairment of SC function in WT animals on a high-fat diet was attenuated in CD36 deficiency. However, CD36 was also identified as a key regulator of SC terminal differentiation. CD36 KO mice showed impaired regeneration after acute skeletal muscle injury, possibly linked to the decreased SC differentiation capacity. Additionally, this study reports a decrease in macrophage infiltration in CD36 KO mice following skeletal muscle injury, possibly due to inefficient inflammation resolution, subsequently resulting in impaired regeneration.This demonstrates that CD36 deficiency protects against DIO, intramuscular lipid deposition and oxidative stress but results in impaired SC differentiation, delayed muscle regeneration and hepatic steatosis. CD36 is a key mediator of fatty acid uptake in skeletal muscle, linking obesity with SC function and muscle regeneration

Towards Accurate and Efficient Cell Tracking During Fly Wing Development

Understanding the development, organization, and function of tissues is a central goal in developmental biology. With modern time-lapse microscopy, it is now possible to image entire tissues during development and thereby localize subcellular proteins. A particularly productive area of research is the study of single layer epithelial tissues, which can be simply described as a 2D manifold. For example, the apical band of cell adhesions in epithelial cell layers actually forms a 2D manifold within the tissue and provides a 2D outline of each cell. The Drosophila melanogaster wing has become an important model system, because its 2D cell organization has the potential to reveal mechanisms that create the final fly wing shape. Other examples include structures that naturally localize at the surface of the tissue, such as the ciliary components of planarians. Data from these time-lapse movies typically consists of mosaics of overlapping 3D stacks. This is necessary because the surface of interest exceeds the field of view of todays microscopes. To quantify cellular tissue dynamics, these mosaics need to be processed in three main steps: (a) Extracting, correcting, and stitching individ- ual stacks into a single, seamless 2D projection per time point, (b) obtaining cell characteristics that occur at individual time points, and (c) determine cell dynamics over time. It is therefore necessary that the applied methods are capable of handling large amounts of data efficiently, while still producing accurate results. This task is made especially difficult by the low signal to noise ratios that are typical in live-cell imaging. In this PhD thesis, I develop algorithms that cover all three processing tasks men- tioned above and apply them in the analysis of polarity and tissue dynamics in large epithelial cell layers, namely the Drosophila wing and the planarian epithelium. First, I introduce an efficient pipeline that preprocesses raw image mosaics. This pipeline accurately extracts the stained surface of interest from each raw image stack and projects it onto a single 2D plane. It then corrects uneven illumination, aligns all mosaic planes, and adjusts brightness and contrast before finally stitching the processed images together. This preprocessing does not only significantly reduce the data quantity, but also simplifies downstream data analyses. Here, I apply this pipeline to datasets of the developing fly wing as well as a planarian epithelium. I additionally address the problem of determining cell polarities in chemically fixed samples of planarians. Here, I introduce a method that automatically estimates cell polarities by computing the orientation of rootlets in motile cilia. With this technique one can for the first time routinely measure and visualize how tissue polarities are established and maintained in entire planarian epithelia. Finally, I analyze cell migration patterns in the entire developing wing tissue in Drosophila. At each time point, cells are segmented using a progressive merging ap- proach with merging criteria that take typical cell shape characteristics into account. The method enforces biologically relevant constraints to improve the quality of the resulting segmentations. For cases where a full cell tracking is desired, I introduce a pipeline using a tracking-by-assignment approach. This allows me to link cells over time while considering critical events such as cell divisions or cell death. This work presents a very accurate large-scale cell tracking pipeline and opens up many avenues for further study including several in-vivo perturbation experiments as well as biophysical modeling. The methods introduced in this thesis are examples for computational pipelines that catalyze biological insights by enabling the quantification of tissue scale phenomena and dynamics. I provide not only detailed descriptions of the methods, but also show how they perform on concrete biological research projects

Noise Propagation and Information Transmission in the Tumor Necrosis Factor Signaling Pathway

Biological noise is generally defined as the non-genetic variability that arises in populations. For instance, identical twins, although very similar in appearance, will commonly display slightly different phenotypes. Likewise, daughter cells sharing the same genetic material may differentiate along divergent paths. In the past decade, there have been considerable advances in understanding the genetic mechanisms underpinning this variability; however, there still remain unanswered questions surrounding how signaling networks contribute to biological noise and how this noise sets limitations on intracellular information transmission. In the first half of this thesis, we demonstrate that a linear relationship between signal transduction responses allows one to quantify and map the propagation of noise along different parts of a signaling network, even if the network is complex and partially defined. We discover that the JNK pathway generates higher noise than the NF-κB pathway while the activation of c-Jun adds a greater amount of noise than the activation of ATF-2. In addition, by analyzing the negative feedback mechanisms mediated by the protein A20, we find that A20 can suppress noise in the activation of ATF-2 by separately inhibiting the tumor necrosis factor (TNF) receptor complex and JNK pathway. In the second half of this thesis, we will describe an integrative theoretical and experimental framework, based on the formalism of information theory, to quantitatively predict and measure the amount of information transduced by molecular and cellular networks. Analyzing TNF signaling, we find that individual TNF signaling pathways transduce information only sufficient for accurate binary decisions, and an upstream bottleneck limits the information gained via multiple integrated pathways. In this dissertation, we demonstrate that the application of engineering concepts proves to be of great utility in uncovering novel characteristics of biological noise. We anticipate that these contributions will help move biology closer towards a more predictable and rule-based engineering discipline allowing us to design de novo biological solutions to pressing issues