Pathology - Theses
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ItemNetwork approaches to understanding biomarker biology( 2017)Common non-communicable diseases such as cardiovascular diseases, chronic respiratory diseases, and diabetes are the leading causes of premature mortality and ill-health worldwide. These are complex diseases that take multiple decades to manifest with myriad genetic, lifestyle, and environmental risk factors. The last decade has seen rapid technological advancements and falling costs to high-throughput omic profiling platforms enabling large-scale studies into the molecular differences between healthy individuals and those that will later develop disease. Epidemiological studies of omic data in population cohorts have identified many new biomarkers of future disease risk and mortality. The end-goal of biomarker research is not only to identify individuals at increased risk of disease, but also to find ways to intervene to reduce that risk. Identification and characterisation of the biological processes these biomarkers participate in or reflect is a fundamental step in the process of clinical translation. This thesis explores the use of network-based approaches for identification and characterisation of aberrant biological processes associated with biomarkers using population cohort multi-omic data. A scalable and efficient method for robust statistical assessment of network module preservation and reproducibility is developed: NetRep. Multi-omic data from three large population biobanks are analysed to identify and characterise biological processes associated with elevated GlycA levels; a heterogeneous NMR signal that has been of recent interest as a biomarker for long-term risk of cardiovascular disease, type II diabetes, and premature mortality. I found that elevated GlycA levels corresponded with the presence of sub-clinical inflammation and increased coordinated expression of a reproducible gene coexpression network module indicative of neutrophil activity. Accordingly, analysis of a population cohort with linked electronic health records showed that elevated GlycA levels had long-term consequences for increased risk of severe infections up to 14-years in the future. To fine-map the GlycA biomarker, I developed accurate imputation models for predicting concentrations of three of the five glycoproteins contributing to the GlycA signal from population-based serum NMR data: alpha-1-acid glycoprotein (AGP), alpha-1 antitrypsin (A1AT), and haptoglobin (HP). Imputation of these three glycoproteins in two large population cohorts with linked electronic health records revealed elevated A1AT had the most severe long-term ramifications for future disease and mortality risk over an 8-year follow-up period. In total, this thesis shows the utility of leveraging population-based omic data for elucidating biomarker biology and provides a useful framework to guide future studies of new and established biomarkers for future disease risk.
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ItemCuproenzyme dysfunction in the pathogenesis of amyotrophic lateral sclerosis and multiple sclerosis( 2016)Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterised by the selective death of motor neurons within the spinal cord and brain. Although the aetiology of the disease is not well understood, inherited genetic mutations account for a small proportion of cases, with Cu,Zn-superoxide dismutase (SOD1) mutations being the most extensively studied. Effective treatment options for ALS do not exist, however, pre-clinical outcomes indicate that therapeutically modulating copper bioavailability in the central nervous system (CNS) may be a feasible treatment strategy for ALS. Therefore, the initial objective of this study was to investigate the significance of copper dyshomeostasis in the progression of a mutant SOD1 mouse model of ALS. We hypothesised that age-related changes to cuproenzymes progress with disease symptoms in SOD1G37R mice compared to age-matched non-transgenic littermates and mice overexpressing wild-type human SOD1. To test this hypothesis, locomotor performance was assessed to track disease progression, then CNS and peripheral tissues were collected at distinct stages of disease for biochemical analyses. Data presented in Chapter 3 provide evidence for copper malfunction in the CNS of ALS mice and indicate that copper malfunction is an early feature of the disease which worsens as symptoms progress. Specifically, a disconnect exists between the abundance and copper-dependent activity of cuproenzymes SOD1 and ceruloplasmin. Next, the therapeutic significance of these changes to SOD1 and ceruloplasmin were assessed. In Chapter 4, data show that overexpressing CTR1 or treating ALS model mice with the copper compound CuII(atsm) extends survival and improves copper bioavailability to SOD1 and ceruloplasmin in the CNS. To ascertain the relevance of outcomes in a broader disease context, we next assessed human cases of sporadic ALS. Data presented in Chapter 5 show that SOD1 and ceruloplasmin dysfunction detected in mice is also evident in sporadic ALS. Significantly, changes to ceruloplasmin are associated with changes to iron homeostasis, where diminished copper- dependent ceruloplasmin activity may contribute to iron overload in the ALS-affected motor cortex and decreased transferrin bound iron in the cerebrospinal fluid. As such, we propose that changes to copper-dependent ceruloplasmin activity in ALS may be the mechanistic basis for two ALS biomarkers and represent the first biochemical evidence for the feasibility of treating ALS, including sporadic ALS, by therapeutically improving copper bioavailability to CNS cuproenzymes. Multiple sclerosis (MS) is a disease characterised by CNS demyelination, with evidence suggesting a link between demyelination and limited copper bioavailability. This is supported by data presented in Chapter 7 from both ALS model mice and MS-affected CNS tissue. We also show that changes to copper, SOD1, ceruloplasmin and myelin-associated proteins are common to ALS and MS, and that modulating copper bioavailability may provide a therapeutic intervention. Overall, data presented in this thesis indicate that: copper malfunction is a feature of ALS and MS; copper malfunction evident in sporadic cases of ALS are recapitulated in mutant SOD1 mouse models of familial ALS; and perturbations to the copper-dependent ceruloplasmin activity may be important to iron accumulation in the ALS-affected motor cortex. The therapeutic implications of these observations are discussed.
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ItemBiomarkers in ductal carcinoma in situ( 2016)Ductal carcinoma in situ (DCIS), a non-invasive form of breast cancer and a non-obligate precursor of invasive carcinoma of the breast, displays heterogeneous behaviour. Most DCIS are adequately managed by local surgical excision alone, but in 20-30% of cases, disease recurrence occurs after local surgical excision either as DCIS or invasive carcinoma. Accurate identification of these two clinical outcome groups at the time of diagnosis is desirable to allow appropriate treatment allocation. In this thesis, genomic and epigenetic alterations in DCIS epithelium, including copy number aberrations, somatic mutations, and DNA methylation were investigated as markers of DCIS biology and outcome. In addition, the expression and significance of LRH-1, a nuclear receptor which acts as a transcription factor, was investigated in both invasive carcinoma and DCIS. Copy number analysis of DCIS of known clinical outcome identified amplification of 20q13 to be associated with disease recurrence, but this was unable to be validated on an independent cohort. Targeted next generation sequencing of a panel of breast cancer-relevant genes revealed that the mutational profile of DCIS was similar to that reported for invasive carcinomas, with the most frequently mutated genes being GATA3, PIK3CA, and TP53. A high prevalence of GATA3 mutations in DCIS was observed and TP53-mutant DCIS was associated with high stromal tumour infiltrating lymphocytes. Mutations of RUNX1 were a novel finding, not previously reported in DCIS. Promoter methylation of a candidate gene panel, consisting predominantly of known tumour suppressor genes, was associated with adverse tumour features in DCIS. Methylation load varied among DCIS cases, suggesting that methylation differs in importance in the tumorigenesis of DCIS, and that assessment of methylation may be useful as a biological classifier of DCIS. Finally, LRH-1 mRNA expression patterns in breast cancers was similar to that reported for breast cancer cell lines and distinct LRH-1 immunohistochemical staining patterns were associated with tumour phenotype in both invasive breast carcinoma and DCIS. The results of this thesis demonstrate that copy number alterations, somatic mutations, DNA methylation, and LRH-1 expression are indicative of DCIS phenotype and hence biology. These markers showed promise as prognostic biomarkers, although validation of their utility was hampered by the small number of pure DCIS cases with both adequate genomic material and long-term clinical outcome data. Nonetheless, the findings of this thesis indicate that assessment of these biomarkers can be performed in routine diagnostic tissue material and provide several avenues for future research.