Tumour associated macrophages in Diffuse Large B cell lymphoma

Tumour associated macrophages (TAMs) have been associated with prognosis in a wide variety of tumours with most studies showing a high number of macrophages equating with poor prognosis. This is postulated to be due to TAMs providing support to the tumour through a wide variety of mechanisms including suppression of the immune response, promotion of angiogenesis and provision of growth supporting signals. Previous work within the group has characterised some of the mechanisms by which Burkitt lymphoma cells attract macrophages to the tumour and some of the mechanisms by which these macrophages support tumour cell growth. This thesis extends some of the work carried out in Burkitt lymphoma to Diffuse Large B cell lymphoma (DLBCL) and examines TAMs in this tumour type. Diffuse Large B cell lymphoma is the commonest high grade lymphoma in the Western world. Like Burkitt lymphoma it is characterised by diffuse sheets of lymphoid blasts. In contrast to Burkitt lymphoma, it represents a less well-defined entity that encompasses tumours with variable morphology, genetic abnormalities and outcome. Rates of proliferation and apoptosis vary between individual tumours, and unlike Burkitt lymphoma not all cases are characterised by a prominent macrophage infiltrate. Previous work within the group has shown a relationship in Burkitt lymphoma between apoptosis, macrophage infiltration and proliferation suggesting that apoptosis recruits macrophages to provide support to the tumour cells. This relationship was studied here in a large cohort of patients with DLBCL and the same relationship shown to exist in this tumour also. Following this observation, a bioinformatic approach was taken to define a gene expression signature of the TAM in DLBCL in situ in an unbiased way. Using large publicly available human tumour gene expression datasets, a graph clustering approach using the tool Biolayout Express 3D was used to explore the transcriptome of DLCBL and other human tumours. Signatures of immune cells and stromal cells, functional pathways and tumour specific signatures were defined from individual tumour type transcriptomes by study of clusters of co-expressed genes. Further work used a novel graph clustering approach based on mean Pearson correlations to define a ‘core’ transcriptome signature shared across many unrelated tumour types and in which elements of the tumour stroma were prominent. To validate the TAM signature derived from the DLBCL dataset, protein expression of selected elements of the signature were analysed at the protein level by immunohistochemistry in an unrelated cohort of DLBCL. Selected markers from the DLBCL TAM signature were then assessed for relationship to outcome in a cohort of patients treated with CHOP chemotherapy. Of the proteins studied, a significant difference in outcome was demonstrated only for leukocyte associated immunoglobulin receptor 1 (LAIR1) expression by TAMs, where low intensity staining for LAIR1 in TAMs was associated with better overall survival. LAIR1 is a collagen-binding inhibitory receptor expressed only in cells of haemopoetic lineage whose role is little studied in macrophages. The final results chapter presents some preliminary data from co-culture experiments in which the expression of LAIR-1 on the ‘macrophage-like’ cell line THP-1 is studied in various polarisation states and the ability of these cells to support or constrain tumour cell growth studied in the presence or absence of collagen

Protocols to capture the functional plasticity of protein domain superfamilies

Most proteins comprise several domains, segments that are clearly discernable in protein structure and sequence. Over the last two decades, it has become increasingly clear that domains are often also functional modules that can be duplicated and recombined in the course of evolution. This gives rise to novel protein functions. Traditionally, protein domains are grouped into homologous domain superfamilies in resources such as SCOP and CATH. This is done primarily on the basis of similarities in their three-dimensional structures. A biologically sound subdivision of the domain superfamilies into families of sequences with conserved function has so far been missing. Such families form the ideal framework to study the evolutionary and functional plasticity of individual superfamilies. In the few existing resources that aim to classify domain families, a considerable amount of manual curation is involved. Whilst immensely valuable, the latter is inherently slow and expensive. It can thus impede large-scale application. This work describes the development and application of a fully-automatic pipeline for identifying functional families within superfamilies of protein domains. This pipeline is built around a method for clustering large-scale sequence datasets in distributed computing environments. In addition, it implements two different protocols for identifying families on the basis of the clustering results: a supervised and an unsupervised protocol. These are used depending on whether or not high-quality protein function annotation data are associated with a given superfamily. The results attained for more than 1,500 domain superfamilies are discussed in both a qualitative and quantitative manner. The use of domain sequence data in conjunction with Gene Ontology protein function annotations and a set of rules and concepts to derive families is a novel approach to large-scale domain sequence classification. Importantly, the focus lies on domain, not whole-protein function

COMPUTATIONAL FRAMEWORKS FOR THE IDENTIFICATION OF SOMATIC AND GERMLINE VARIANTS CONTRIBUTING TO CANCER PREDISPOSITION AND DEVELOPMENT

The most recent cancer classification from NIH includes ~200 types of tumor that originates from several tissue types (http://www.cancer.gov/types). Although macroscopic and microscopic characteristics varies significantly across subtypes, the starting point of every cancer is believed to be a single cell that acquires DNA somatic alterations that increases its fitness over the surrounding cells and makes it behave abnormally and proliferate uncontrollably. Somatic mutations are the consequence of many possible defective processes such as replication deficiencies, exposure to carcinogens, or DNA repair machinery faults. Mutation development is a random and mostly natural process that frequently happens in every cell of an individual. Only the acquisition of a series of subtype-specific alterations, including also larger aberrations such as translocations or deletions, can lead to the development of the disease and this is a long process for the majority of adult tumor types. However, genetic predisposition for certain cancer types is epidemiologically well established. In fact, several cancer predisposing genes where identified in the last 30 years with various technologies but they characterize only a small fraction of familial cases. This work will therefore cover two main steps of cancer genetics and genomics: the identification of the genes that somatically changes the behavior of a normal human cell to a cancer cell and the genetic variants that increase risk of cancer development. The use of publicly available datasets is common to all the three results sections that compose this work. In particular, we took advantage of several whole exome sequencing databases (WES) for the identification of both driver mutations and driver variants. In particular, the use of WES in cancer predisposition analysis represents one of the few attempts of performing such analysis on genome-wide sequencing germline data

Identification of biomarkers of metastatic disease in uveal melanoma using proteomic analyses

Uveal melanoma (UM) is the most common intraocular malignancy in adults. Despite successful ocular treatment, about 50% of patients succumb to metastatic dissemination, which occurs haematogenously and mainly affects the liver. On the basis of clinical, histopathological and genetic features of the primary tumour it is possible to predict if the individual patient is at high risk (HR) or low risk (LR) of developing metastases. However, the mechanisms responsible for the development of metastatic disease in UM are still largely unknown; therefore no adjuvant treatment is currently offered to HR patients to prevent development of fatal disease. As the time to discovery of clinically detectable metastases can range from months to decades, a secreted biomarker(s) that could be routinely tested in blood is much needed. The scope of the work presented in this thesis was to use proteomics as a tool to identify potential novel, UM-specific biomarkers. Moreover, the proteomic data acquired would complement genomic and transcriptomic information already generated by the Liverpool Ocular Oncology Research Group, with the ultimate aim of increasing our understanding of UM development and dissemination. The aim of Chapter 2’s project was to compare the proteome of UM tissue samples at HR versus LR of developing metastatic disease using isobaric tags for relative and absolute quantitation (iTRAQ) labelling and mass spectrometry (MS). The quantification of proteins in our samples, proteomic analysis and further validation by immunohistochemistry has led to the identification of two novel prognostic and potentially therapeutic target, S100A6 and the tumour suppressor PDCD4. In Chapter 3 we focused on proteins released in the conditioned medium (secretome) of short-term cultures of HR and LR UM cells, as well as normal melanocytes. Using a label-free quantitative proteomic approach, almost 2000 proteins were identified and quantified, with more than 30% of these identified as secreted and/or previously described in exosomes. Using these data, an 18-protein signature able to discriminate between HR and LR UM was identified. Further validation will be necessary in secretome samples and in the peripheral blood of UM patients, but this has the potential of being translated into a clinically useful assay to detect early development of metastatic disease. As reported in Chapter 4, we also conducted a pilot clinical study on circulating tumour cells (CTC) in UM, using the CellSearch® platform with the novel melanoma kit to enumerate CTC in the peripheral blood of UM patients at LR, HR or with overt metastatic disease. CTC were detected in metastatic and HR tumours and were not present in LR UM, however, the number of CTC detected varied widely, calling into question the clinical value of using this platform in UM patients. The research detailed in Chapter 5 had a direct clinical value, as it addressed the procedures undertaken during the acquisition and processing of prognostic biopsies from UM tumours treated conservatively. The modifications introduced led to a significant improvement of the success rate of such prognostic biopsies for risk stratification, which is essential for clinical management, follow-up and research purposes. In conclusion, the work conducted throughout this PhD has provided further insight into the molecular characteristics that can differentiate between HR and LR UM, identifying novel potential biomarkers that will need validation in the clinical setting

Large-scale phylogenomic visualization and analysis of functional traits in bacteria

The growth of genomic information in public databases has dramatically improved our view of the tree of life and at the same time expanded our knowledge of protein diversity. Through the use of automated annotation pipelines, researchers can predict many of the functional capabilities of organisms directly from their genome sequence. Although there exist numerous phylogenetic and protein databases, there have been fewer attempts to combine these data, which is essential for the study of protein evolution. The web application AnnoTree (annotree.uwaterloo.ca) was developed as part of this thesis to facilitate the exploration and visualization of protein families (Pfams) and KEGG orthologs (KOs) on a phylogeny composed of nearly 24,000 bacterial genomes. The visualization includes an interactive tree of life, a summary of the taxonomic distribution of the query, basic taxonomic information, and annotation confidence scores. All protein sequences, visualizations, and summary information can be downloaded directly from the interface. The AnnoTree framework is open-source and can be modified to incorporate any custom tree, taxonomy, and proteome dataset. AnnoTree allows users to visualize the phylogenetic distribution of a Pfam of interest, which, in combination with obtained gain/loss data, promotes hypothesis-generation in the context of protein evolution. To identify functions that are more tightly associated with evolutionary mechanisms such as horizontal gene transfer and evolutionary conservation, the pre-computed annotation data were combined with the bacterial tree of life in a phylogenomics analysis. The phyletic patchiness of all Pfam and KO annotations was measured using the normalized consistency index (CI), a measure of disagreement between the presence/absence states of traits across the tree and the tree topology. Pfams and KOs with the highest normalized CI represent functions known to be associated with mobile genetic elements and viral defence. These annotations were most commonly found within the genomes of symbiotic and pathogenic bacteria. The most highly conserved Pfams and KOs were functions related to core processes such as transcription, DNA replication, and protein synthesis as well as those required for oxygenic photosynthesis and sporulation. Lineage-specific Pfams and KOs were classified in many bacterial taxa, revealing many clade-defining functions in the Baccilus_A genus, the Oxyphotobacteria class, and the Actinobacteria class, among others. An additional phylogenomics analysis was performed to identify branches of a phylogeny encompassing representatives from all three domains of life undergoing the most Pfam gain and loss events. The branches dividing the three taxonomic domains had the highest density of gain events, all of which were associated with well-known clade-defining functions. Missing data influenced the frequency of Pfam losses in lower taxonomic levels, but some characterized genome streamlining events within Eukaryotes were uncovered. Ultimately, the development of AnnoTree and accompanying analyses provide new insights into large-scale bacterial phylogenomics and the evolution and distributions of bacterial protein domains and gene families

Investigation of the mechanisms underlying the regulation of macrophage activation and glomerular inflammation by JunD

Macrophages are the predominant immune effector cell found in one of the most severe causes of renal failure in humans, crescentic glomerulonephritis (Crgn). The Wistar Kyoto (WLY) rat is uniquely susceptible among rat strains to Crgn and susceptibility genes have previously been mapped to seven quantitative trait loci (Crgn1-7). The AP-1 transcription factor JunD is markedly overexpressed in WKY macrophages and was identified as a major determinant of macrophage activation associated with Crgn susceptibility at Crgn2. The work presented in this thesis aimed to investigate mechanisms underlying the regulation of macrophage activation and glomerular inflammation by JunD in the NTN-susceptible WKY rat strain and in patients with Crgn. Genomic-based approaches, including microarray analysis of bone marrow-derived macrophage transcriptomes, RNA interference and cistrome analysis using ChIP-Seq, along with histological techniques and genotyping studies, were used to identify key genes and pathways underlying JunD-mediated activation of macrophages. Transcriptome analyses showed that the Crgn2 locus regulates expression of over 800 genes in WKY macrophage responses to lipopolysaccharide (LPS). Acute changes in Jund expression by RNA interference also modulated gene expression in WKY macrophages, including effector genes for the macrophage LPS response. Cistrome analysis revealed that genetically determined differences in Jund expression alter its genome binding pattern and the increased numbers of JunD-bound genes in WKY macrophages were functionally linked with signalling pathways and cell activation. Integration of the data identified 47 genes, that were associated with JunD binding peaks and whose expression was both regulated by Crgn2 and altered by siRNA knockdown of Jund, as the key candidates through which JunD determines macrophage activation. Overall, this work provides the basis for understanding genes and pathways through which JunD regulates macrophage activation and has identified novel gene targets for modulation of macrophage phenotypes in WKY rat and human macrophages

Insights into vector control through the modulation of An. gambiae G protein-coupled receptors

Thesis advisor: Marc A.T. MuskavitchMalaria is a life-threatening infectious disease caused by inoculation of the apicomplexan Plasmodium parasite into vertebrate hosts. Transmission of the parasite is mediated by the Anopheles mosquito, which has the capacity to efficiently transmit the parasite from host to host, as the disease vector. There are many factors that make anopheline mosquitoes competent vectors for disease transmission. The hematophagous (blood-feeding) behavior of the female mosquito is one of most fundamental factors in physical transmission of parasites, because the ingestion of blood from an infected host allows parasite entry into the mosquito and the completion of parasite sexual reproduction. In addition to this blood-feeding behavior, there are a host of biological (i.e., parasite replication) and behavioral factors (i.e., mosquito chemosensation, host preference) that contribute to the high vectorial capacity of these vector species. There are over four hundred Anopheles species worldwide, approximately forty of which are considered epidemiologically critical human malaria vectors. Anopheles gambiae, the primary vector in malaria-endemic sub-Saharan Africa, is responsible for the largest number of malaria cases in the world and is therefore one of the most important vectors to study and target with control measures. Currently, vector-targeted control strategies remain our most effective tools for reduction of malaria transmission and incidence. Although control efforts based on the deployment of insecticides have proven successful in the past and are still widely used, the threat and continuing increases of insecticide resistance motivate the discovery of novel insecticides. In this thesis, I provide evidence that G protein-coupled receptors (GPCRs) may serve as “druggable” targets for the development of new insecticides, through the modulation of developmental and sensory processes. In Chapter II, “A critical role for the Drosophila dopamine 1-like receptor Dop1R2 at the onset of metamorphosis,” I provide evidence supporting an essential role for this receptor in Drosophila melanogaster metamorphosis via transgenic RNA interference and pharmacological methods. In An. gambiae, we find that the receptor encoded by the mosquito ortholog GPRDOP2 can be inhibited in vitro using pharmacological antagonists, and that in vivo inhibition with such antagonists produces pre-adult lethality. These findings support the inference that this An. gambiae dopamine receptor may serve as a novel target for the development of vector-targeted larvicides. In Chapter III, “RNAi trigger delivery into Anopheles gambiae pupae,” I describe the development of a method for injection directly into the hemolymph of double strand RNA (dsRNA) during the pupal stage, and I demonstrate that knockdown of the translational product of the SRPN2 gene occurs efficiently, based on reductions in the levels of SRPN2 protein and formation of melanized pseudo-tumors, in SRPN2 knockdown mosquitoes. This method was developed for rapid knockdown of target genes, using a dye-labeled injection technique that allows for easy visualization of injection quality. This technique is further utilized in Chapter IV, “Uncovering the Role of an Anopheles gambiae G Protein-Coupled Receptor, GPRGR2, in the Detection of Noxious Compounds,” where the role for GPRGR2 in the detection of multiple noxious compounds is elucidated. We find that pupal stage knockdown of this receptor decreases the ability of adult Anopheles gambiae to identify multiple noxious compounds. While these findings provide a strong link between GPRGR2 and a very interesting mosquito behavior, they may also provide opportunities to develop better field-based strategies (i.e., insecticides baited traps) for vector control. The goal of this thesis is to understand the functional roles of selected mosquito GPCRs that may serve as targets for the development of new vector-targeted control strategies. Exploiting these GPCRs genetically and pharmacologically may provide insights into novel vector control targets that can be manipulated so as to decrease the vectorial capacity of An. gambiae and other malaria vectors in the field, and thereby decrease the burden of human malaria.Thesis (PhD) — Boston College, 2015.Submitted to: Boston College. Graduate School of Arts and Sciences.Discipline: Biology

Genetics and genomics of aortic form and function

The thoracic aorta is a dynamic organ which adapts and remodels throughout life. Thoracic aortic size, shape and function are important contributors to both cardiovascular health and disease and risk of aortic disease. A complex interaction of environmental, genetic and haemodynamic factors is mediated by cells of the aortic wall. This thesis presents aortic phenotyping, genotyping and genome-wide associations of aortic traits in a large healthy cohort of 1218 volunteers. This is the largest study to report normal parameters for healthy thoracic aortic size, shape and function derived from cardiovascular magnetic resonance imaging. Anthropometric and cardiovascular risk factors such as age, gender, body fat mass and lipid profile are identified as significant determinants of aortic phenotype. The work suggests that cardiovascular risk factors could impair normal adaptive aortic remodelling with age. Genome-wide association studies of aortic dimensions and function identify new common variants, genes and pathways which could be important in aortic biology and cardiovascular risk. These include genes involved in cardiovascular development (eg PCDH7 and SON associated with aortic root diameter), autonomic cardiovascular responses (eg GABA receptor genes associated with aortic root diameter), fibrosis (eg ACTC1, AGTR1 associated with ascending aortic distensibility, BAMBI and MYOD associated with descending aortic distensibility) and obesity (eg ARID5B and IRX3 associated with aortic pulse wave velocity and ascending aortic area respectively). Multiple regulatory pathways including TGF-ß and IGF signalling (IGF1R, IGF2R), are identified which are associated with aortic dimensions and function. Joint trait analysis of aortic root dimensions identifies a new genome-wide significant association with TENM4, a key driver of early mesodermal development, and suggestive association with PTN, which is functionally related and plays a key role in angiogenesis. The primary analyses are complemented by exploratory assessment of rare genetic variation in bicuspid aortic valve (BAV) using panel sequencing in 177 patients. Rare variants might cause, or modify phenotype in BAV, but the clinical utility of panel sequencing remains poor. A further complementary study investigates the interaction of haemodynamics with aortic cellular phenotype, using microarray assessment of aortic endothelial cell transcriptomic response to shear stress pattern. Several genes of interest in atherosclerosis and aortic disease are differentially expressed with shear stress pattern, such as FABP4, ANGPT2, FILIP1, KIT, DCHS1, TGFBR3 and LOX. This work yields new insights into aortic phenotype, identifies key loci which might determine aortic traits and explores the complex interdependence of genetics, haemodynamics and environmental variables in aortic biology.Open Acces

The Shared Genetic Architecture of Modifiable Risk for Dementia and its Influence on Brain Health

Targeting modifiable risk factors for dementia may prevent or delay dementia. However, the mechanisms by which risk factors influence dementia remain unclear and current research often ignores commonality between risk factors. Therefore, my thesis aimed to model the shared genetic architecture of modifiable risk for dementia and explored how these shared pathways may influence dementia and brain health. I used linkage disequilibrium score regression and genomic structural equation modelling (SEM) to create a multivariate model of the shared genetics between Alzheimer’s disease (AD) and its modifiable risk factors. Although AD was genetically distinct, there was widespread genetic overlap between most of its risk factors. This genetic overlap formed an overarching Common Factor of general modifiable dementia risk, in addition to 3 subclusters of distinct sets of risk factors. Next, I performed two multivariate genome-wide association studies (GWASs) to identify the risk variants that underpinned the Common Factor and the 3 subclusters of risk factors. Together, these uncovered 590 genome-wide significant loci for the four latent factors, 34 of which were novel findings. Using post-GWAS analyses I found evidence that the shared genetics between risk factors influence a range of neuronal functions, which were highly expressed in brain regions that degenerate in dementia. Pathway analysis indicated that shared genetics between risk factors may impact dementia pathogenesis directly at specific loci. Finally, I used Mendelian randomisation to test whether the shared genetic pathways between modifiable dementia risk factors were causal for AD. I found evidence of a causal effect of the Common Factor on AD risk. Taken together, my thesis provides new insights into how modifiable risk factors for dementia interrelate on a genetic level. Although the shared genetics between modifiable risk factors for dementia seem to be distinct from dementia pathways on a genome-wide level, I provide evidence that they influence general brain health, and so they may increase dementia risk indirectly by altering cognitive reserve. However, I also found that shared genetics risk between risk factors in certain genomic regions may directly influence dementia pathogenesis, which should be explored in future work to determine whether these regions represent targets to prevent dementia

The evolution of the mammal placenta — a computational approach to the identification and analysis of placenta-specific genes and microRNAs.

The presence of a placenta is an important synapomorphy that defines the mammal clade. From the fossil record we know that the first placental mammal lived approximately 125 million years ago, with the chorioallantoic placenta evolving not long after. In this thesis a set of 22 complete genomes from Eutherian, non-Eutherian and outgroup species are compared, the aim being to identify protein-coding and regulatory alterations that are likely to be implicated in the emergence of mammal placenta in the fossil record. To this end we have examined the roles played by positive selection and miRNA regulation in the evolution of the placenta. We have identified those genes that underwent functional shift uniquely in the ancestral placental mammal lineage and that are also heavily implicated in disorders of the placenta. Carrying out a thorough analysis of non-coding regions of the 22 genomes included in the study we identified a cohort of miRNAs that exist only in placental mammals. Many of the placenta related genes described above have multiple predicted “placenta-specific” miRNA binding sites. Together these results indicate a role for both adaptation in protein-coding regions and emergence of novel noncoding regulators in the origin and evolution of mammal placentation