Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2009. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 118-127). / Adipose tissue serves two main functions in the body: (1) it is the body's primary energy depot; and (2) it also serves as an important endocrine organ, producing and secreting various enzymes, growth factors, cytokines, and hormones. Both of these functions require ample access to circulating blood. Many aspects of angiogenesis during adipose tissue expansion remain poorly understood. Adipocytes produce a large variety of molecules involved in angiogenesis, and obesity is associated with elevated circulating levels of Vascular Endothelial Growth Factor (VEGF). Our lab has previously shown that angiogenesis and adipogenesis are mutually dependent via a VEGF receptor 2 (VEGFR2)-mediated mechanism. Since then several other studies have reinforced a role for the VEGF-VEGFR system in energy metabolism. For example, genetically obese mice treated with anti-VEGF antibody had lower fat pad weights, but the VEGF receptor responsible for this observation is not known. There is also disagreement on the cell type(s) responsible for fat tissue's angiogenic capability, with some studies supporting a dominant role for adipocytes, while others attribute most of the angiogenic capacity to the adipose tissue stromal cells (ASC). This thesis project aimed to fill some of these gaps by examining the angiogenic capacity of adipose tissue relative to other tissues, the effects of VEGFR-1 and R-2 blockade in mouse models of adipogenesis and diet-induced obesity, the respective angiogenic capabilities of adipocytes and ASC, and the possibility of harnessing the angiogenic potential of adipose tissue for vascular tissue engineering. / (cont.) In addition, a physiologically-based mathematical model was developed to simulate the regulatory effects of the leptin pathway on murine energy homeostasis. / by Joshua Tam. / Ph.D.

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2009. / "May 2009." Cataloged from PDF version of thesis. / Includes bibliographical references (p. 133-147). / Tau protein is the primary constituent of protein aggregates known as neurofibrillary tangles, a pathological hallmark of Alzheimer's disease (AD). Previous studies suggest that tau protein may play a contributing role in neurodegenerative diseases such as AD. Thus characterizing the structural properties of tau is critical to understanding disease pathogenesis. However, obtaining a detailed structural description of tau protein has been difficult because it belongs to a class of heteropolymers known as intrinsically disordered proteins (IDPs). Unlike most proteins, IDPs adopt many distinct conformations under physiological conditions. In spite of their disordered nature, evidence exists that such proteins may exhibit residual structural preferences. In this work, models of tau are constructed to characterize these structural preferences. We begin by performing molecular dynamics simulations to study the inherent conformational preferences of the minimal tau subsequence required for in vitro aggregation. To model residual structure in larger regions of tau, we developed a novel method called Energy-minima Mapping and Weighting (EMW). The method samples energetically favorable / (cont.) conformations within an IDP and uses these structures to construct ensembles that are consistent with experimental data. This method is tested on a region of another IDP, p21 Wafl/Cipl/Sdil(14 5 -164 ), for which crystal structures of substrate-bound conformations are available. Residual conformational preferences identified using EMW were found to be comparable to crystal structures from substrate-bound conformations of p21 Wafl/Cipl/Sdil( 14 5 -164 ). By applying EMW to tau, we find disease-associated forms of tau exhibit a conformational preference for extended conformations near the aggregation-initiating region. Since an increased preference for extended states may facilitate the propagation of cross-[beta] conformation associated with aggregated forms of tau, these results help to explain how local conformational preferences in disease-associated states can promote the formation of tau aggregates. Finally, we examine limitations of the current methods for characterizing IDPs such as tau and discuss future directions in the modeling of these proteins. / by Austin Huang. / Ph.D.

Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2010. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 68-74). / Background: The commoditization of high-throughput gene expression sequencing and microarrays has led to a proliferation in both the amount of genomic and clinical data that is available. Descriptive textual information deposited with gene expression data in the Gene Expression Omnibus (GEO) is an underutilized resource because the textual information is unstructured and difficult to query. Rendering this information in a structured format utilizing standard medical terms would facilitate better searching and data reuse. Such a procedure would significantly increase the clinical utility of biomedical data repositories. Methods: The thesis is divided into two sections. The first section compares how well four medical terminologies were able to represent textual information deposited in GEO. The second section implements free-text search and faceted search and evaluates how well they are able to answer clinical queries with varying levels of complexity. Part I: 120 samples were randomly extracted from samples deposited in the GEO database from six clinical domains-breast cancer, colon cancer, rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type I diabetes mellitus (IDDM), and asthma. These samples were previously annotated manually and structured textual information was obtained in a tag:value format. Data was mapped to four different controlled terminologies: NCI Thesaurus, MeSH, SNOMED-CT, and ICD- 10. The samples were assigned a score on a three-point scale that was based on how well the terminology was able to represent descriptive textual information. Part II: Faceted and free-text search tools were implemented, with 300 GEO samples included for querying. Eight natural language search questions were selected randomly from scientific journals. Academic researchers were recruited and asked to use the faceted and free-text search tools to locate samples matching the question criteria. Precision, recall, F-score, and search time were compared and analyzed for both free-text and faceted search. Results: The results show that the NCI Thesaurus consistently ranked as the most comprehensive terminology across all domains while ICD-10 consistently ranked as the least comprehensive. Using NCI Thesaurus to augment the faceted search tool, each researcher was able to reach 100% precision and recall (F-score 1.0) for each of the eight search questions. Using free-text search, test users averaged 22.8% precision, 60.7% recall, and an F-score of 0.282. The mean search time per question using faceted search and free-text search were 116.7 seconds, and 138.4 seconds, respectively. The difference between search time was not statistically significant (p=0. 734). However, paired t-test analysis showed a statistically signficant difference between the two search strategies with respect to precision (p=O.001), recall (p=O.042), and F-score (p<0. 001). Conclusion: This work demonstrates that biomedical terms included in a gene expression database can be adequately expressed using the NCI Thesaurus. It also shows that faceted searching using a controlled terminology is superior to conventional free-text searching when answering queries of varying levels of complexity. / S.M.

Thesis: Ph. D., Harvard-MIT Program in Health Sciences and Technology, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 111-117). / Triple negative breast cancer (TNBC) is an aggressive form of cancer that represents 20% of invasive breast cancers, and about 15% are locally advanced at time of presentation. TNBC is negative for estrogen and progesterone receptor, as well as for HER2, and hence it is not treatable with common endocrine treatment such as tamoxifen or Herceptin. Systemic neoadjuvant therapy has been established as the preferred therapeutic approach for locally advanced breast cancer, downstaging the disease and preventing mastectomy. However, complications of systemic chemotherapy are devastating. Local therapy would prevent high concentrations of circulating drug and reduce off-target tissue retention. Yet, the means to attain ideal release kinetics and selective uptake remain elusive. I developed a novel class of biocompatible and biodegradable adhesive materials based on dendrimer and dextran that can coat the tumor and locally release doxorubicin in a controlled manner. Doxorubicin was conjugated to the dendritic component of the adhesive hydrogel to form a pro-drug capable of being released over time as the hydrogel degrades at a pre-programmed rate. The pro-drug was further modified with a ligand capable of sensing and discerning between healthy and cancer cells and facilitating uptake through receptor-mediated endocytosis (RME). The platform developed herein provides a paradigm shift in the way we treat cancer, in a local, selective and targeted manner, to impart optimal clinical outcome. / by Nuria Oliva Jorge. / Ph. D.

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 Engineering

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2010. / Page 84 blank. Cataloged from PDF version of thesis. / Includes bibliographical references. / The innate immune system is the first line of host defense, and its ability to propagate antimicrobial and inflammatory signals from the cellular microenvironment to the tissue at-large is critical for survival. In a remarkably complex microenvironment, cells are constantly processing external cues, initiating convoluted intracellular signaling cascades, and interacting with neighboring cells to generate a global, unified response. At the onset of infection or sterile injury, individual cells sense danger or damage signals and elicit innate immune responses that spread from the challenged cells to surrounding cells, thereby establishing an overall inflammatory state. However, little is known about how these dynamic spatiotemporal responses unfold. Through the use GFP reporters, in vitro transplant coculture systems, and in vivo models of infection and sterile injury, this thesis describes identification of a gap junction intercellular communication pathway for amplifying immune and inflammatory responses, and demonstrates its importance in host innate immunity. The first section describes development of stable GFP reporters to study the spatiotemporal activation patterns of two key transcription factors in inflammation and innate immunity: Nuclear factor-KappaB (NFKB) and Interferon regulatory factor 3 (IRF3). Stimulation of NFKB-GFP reporters resulted in a spatially homogeneous pattern of activation, found to be largely mediated by paracrine action of the pro-inflammatory cytokine TNFa. In contrast, the activation of IRF3 was spatially heterogeneous, resulting in the formation of multicellular colonies of activated cells in an otherwise latent background. This pattern of activation was demonstrated to be dependent on cell-cell contact mediated communication between neighboring cells, and not on paracrine signaling. The second section describes the discovery of a gap junction intercellular communication pathway responsible for the formation of IRF3 active colonies in response to immune activation. Cell sorting and gene expression profiling revealed that the activated reporter colonies, collectively, serve as the major source of critical antimicrobial and inflammatory cytokines. Using in vitro transplant coculture systems, colony formation was found to be dependent on gap junction communication. Blocking gap junctions with genetic specificity severely compromised the innate immune system's ability to mount antiviral and inflammatory responses. The third section illustrates an application of the gap junction-induced amplification of innate immunity phenomenon in an animal model of sterile injury. Drug-induced liver injury was shown to be dependent on gap junction communication for amplifying sterile inflammatory signals. Mice deficient in hepatic gap junction protein connexin 32 (Cx32) were protected against liver damage, inflammation, and death in response to hepatotoxic drugs. Co-administration of a selective pharmacologic Cx32 inhibitor with hepatotoxic drugs significantly limited hepatocyte damage and sterile inflammation, and completely abrogated mortality. These finds suggests that co-formulation of gap junction inhibitors with hepatotoxic drugs may prevent liver failure in humans, and potentially limit other forms of sterile injury. In summary, this thesis demonstrates the development of novel tools for investigating the spatiotemporal dynamics of cellular responses, describes how these tools were utilized to discover a basic gap junction communication pathway critical in innate immunity, and provides evidence for the clinical relevance of this pathway in sterile inflammatory injury. / by Suraj Jagdish Patel. / Ph.D.

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2009. / Cataloged from PDF version of thesis. / Includes bibliographical references. / The integrated network of biochemical reactions known collectively as metabolism is essential for life, and dysfunction in parts of this network causes human disease - both rare, inherited disorders and common diseases such as diabetes mellitus. The study of metabolic disease depends upon quantitative methods which are traditionally custom-tailored to a given compound. Recent advances in technologies such as mass spectrometry now enable the simultaneous measurement of a diverse metabolite collection spanning multiple biological pathways, an approach known as metabolic profiling or metabolomics. This dissertation describes the development of one such metabolic profiling system and its application to the study of two major topics in human energy metabolism: the fasting:feeding transition and mitochondrial disease. In the first study, we profile human plasma in response to glucose ingestion, detecting dozens of metabolite changes and identifying several distinct effects of insulin. Based on these observations, we propose a multivariate view of insulin sensitivity, and show that individuals at risk for developing diabetes mellitus can differ in their insulin response profile, a concept of potential value for estimating disease risk and progression. In the second study, we elucidate a metabolic signature of human mitochondrial disease that reflects substrate oxidation, biosynthesis and energy charge. / (cont.) We demonstrate that the culture media profile of a cellular disease model of mitochondrial dysfunction reflects the plasma profile of human patients, an approach that could be applicable to other diseases as well. In addition, we show that a combination of metabolites distinguishes individuals with mitochondrial disease from healthy individuals better than the currently used diagnostic markers. Our findings provide insight into human disorders of energy metabolism, and demonstrate the utility of a profiling approach for the understanding of metabolic disease. / by Oded Shaham. / Ph.D.

Thesis: Ph. D. in Bioinformatics, Harvard-MIT Program in Health Sciences and Technology, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 83-94). / The clinical course of infection is ultimately determined by a series of cellular interactions between invading pathogens and host immune cells. It has long been understood that these interactions, even when they occur in tissue culture models, give rise to a wide variety of different outcomes, some beneficial to the host, others to the pathogen. These cellular interactions, however, are typically studied at a bulk level; masking this cell-to-cell variation, losing important information about the full range of possible host-pathogen interactions, and leaving the mechanistic basis for these different outcomes largely unexplored. Here, we present a system that combines single-cell RNA sequencing with fluorescent markers of infection outcome to directly correlate host transcription signatures with infection outcome at the single cell level. Applying this system to the well-characterized model of Salmonella enterica infection of mouse macrophages, we found: 1) Unique transcription signatures associated with bacterial exposure and bacterial infection, 2) Sustained high levels of heterogeneity in immune pathways in infected macrophages, and 3) A novel subpopulation of macrophages characterized by high expression of the Type I Interferon response after infection. Upon further investigation we found that this heterogeneity in the host Type I Interferon response was the result of heterogeneity in the population of infecting bacteria, namely in the extent of PhoPQ-mediated LPS modifications. This work highlights the importance of heterogeneity as a characteristic of bacterial populations that can influence the host immune response. It also demonstrates the benefits of examining infection with single-cell resolution. / by Nathan Scott Haseley. / Ph. D. in Bioinformatics

Thesis: Ph. D., Harvard-MIT Program in Health Sciences and Technology, February 2014. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 128-144). / Cancer is a complex disease of the genome exhibiting myriad somatic mutations, from single nucleotide changes to various chromosomal rearrangements. The technological advances of next-generation sequencing enable high-throughput identification and characterization of these events genome-wide using computational algorithms. Retrotransposons comprise 42% of the human genome and have the capacity to "jump" across the genome in a copy-and-paste manner. Recent studies have identified families of retrotransposable elements that are currently active. In fact, retrotransposons constitute a major source of human genetic variation, and somatic retrotransposon insertions have been implicated in several cancers, including an insertion into the APC tumor suppressor in a colorectal tumor. Because of the highly repetitive nature of these elements, however, the full extent of somatic retrotransposon movement across cancer remains largely unexplored. To this end, we developed TranspoSeq, a computational framework that identifies retrotransposon insertions from paired-end whole genome sequencing data, and TranspoSeq- Exome, a tool that localizes these insertions from whole-exome data. TranspoSeq identifies novel somatic retrotransposon insertions with high sensitivity and specificity in simulated data and with a 94% validation rate via site-specific PCR. Next, we applied these methods to wholegenomes from 200 tumor/normal pairs and whole-exomes from 767 tumor/normal pairs across 11 tumor types as part of The Cancer Genome Atlas (TCGA) Pan-Cancer Project. We discover more than 800 somatic retrotransposon insertions primarily in lung squamous, head and neck, colorectal and endometrial carcinomas, while glioblastoma multiforme and acute myeloid leukemia show no evidence of somatic retrotransposition. Moreover, many somatic retrotransposon insertions occur in known cancer genes. TranspoSeq-Exome uncovers 35 additional somatic retrotransposon insertions into exonic regions, including an insertion into an exon of the PTEN tumor suppressor in endometrial cancer. Finally, we integrate orthogonal genomic and clinical data to characterize features of retrotransposon insertion and samples that exhibit extensive somatic retrotransposition. We present a large-scale, comprehensive analysis of retrotransposon movement across tumor types using next-generation sequencing data. Our results suggest that somatic retrotransposon insertions may represent an important class of tumor-specific structural variation in cancer and future studies should incorporate this form of somatic genome aberration. / by Elena Helman. / Ph. D.

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2011. / Cataloged from PDF version of thesis. / Includes bibliographical references. / Aneuploidy, an abnormal complement of chromosomes, is present in approximately 90% of human malignancies. Despite over 100 years of research, many questions remain regarding the contribution of aneuploidy to the cancer phenotype. In this thesis, we develop computational methods to infer the presence and specific patterns of aneuploidy across thousands of primary cancer tissue specimens. We then combine these inferences with clinical and genomic features of the cancer samples to refine our understanding of both the clinical implications of aneuploidy, and how it evolves in various human cancers. We identified a signature of chromosomal instability from specific genes whose expression was consistently correlated with aneuploidy in several cancer types, and which was predictive of poor clinical outcome multiple cancer types. Current genomic characterization techniques measure somatic alterations in a cancer sample in units of genomes (DNA mass). The meaning of such measurements is highly dependent on the tumors purity and its overall ploidy; they are hence complicated to interpret and compare across samples. Ideally, copy-number should be measured in copies-per-cancer-cell. Such measurements are straightforward to interpret and, for alterations that are fixed in the cancer cell population, are simple integer values. We develop two computational methods to infer tumor purity and malignant cell ploidy directly from allelic analysis of DNA. First we describe HAPSEG, a probabilistic method to interpret bi-allelic marker data in cancer samples in order to produce genome-wide estimates of homologue specific copy-ratios. Second, we describe ABSOLUTE, a method that infers purity, ploidy, and absolute copy-numbers from the estimates produced by HAPSEG. In addition, ABSOLUTE can analyze point mutations to detect subclonal heterogeneity and somatic homozygosity. We used ABSOLUTE to analyze ovarian cancer data and discovered that 54% of somatic point mutations were, in fact, subclonal. In contrast, mutations occurring in key tumor suppressor genes, TP53 and NF1 were predominantly clonal and homozygous. Analysis of absolute allelic copy-number profiles from 3,155 cancer specimens revealed that genome-doubling events are common in human cancer, and likely occur in already aneuploid cells in many cancer types. By correlating genome-doubling status with mutation data, we found that homozygous mutations in NF1 occurred predominantly in non-doubled samples. This finding suggests that genome doubling influences the pathways of tumor progression, with recessive inactivation being less common after genome doubling. / by Scott L. Carter. / Ph.D.