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Conventional breast-cancer prevention strategies tend to focus on the reduction of physical breast-cancer risk factors while neglecting psychosocial factors potentially associated with its development. Yet, there is a wealth of evidence linking psychosocial factors such as the occurrence of and maladaptive coping with bereavement and other stressful life events, certain personality traits, and a lack of social support, to breast-cancer incidence, survival and mortality.This thesis aimed to design, implement and evaluate an electronic Coping-Enhancement Programme for the Bereaved (CEPB), addressing such psychosocial factors. Furthermore, participants’ experiences of the programme were to be explored. An experimental 2x2 independent measures design with triangulation was used, employing qualitative and quantitative methodology. Participants’ experiences were elicited qualitatively through blogs and message boards. The two independent variables were (1) emotional-expression-and-stress-reduction (EESR), and (2) psycho-education. Dependent variables were: (1) maladaptive coping with bereavement, (2) maladaptive coping with stressful life events, (3) social support, and (4) awareness of the connections between psychological and physical health. An additional dependent variable was conformity. A Web site containing message boards and blogs was created. Thirty-one women completed a psychological screening form and were then randomly assigned to one of four conditions (EESR-only, psycho-education-only, EESR-plus-pyscho-education, or the control group who received no intervention). They participated in online exercises designed to aid emotional expression and stress reduction (‘Art and Laughter for Wellbeing’) and/or received psycho-education through the reading of autobiographical accounts of breast-cancer sufferers. Participants were analysed on the dependent variables three times: before the programme to obtain a baseline measurement, after the programme, and at six-week follow-up. Thematic analysis was used to illustrate the process of the CEPB, as well as to confirm or disconfirm quantitative results. Analyses of covariance revealed that after the programme, taking part in ‘Art and Laughter for Wellbeing’ was associated with lower maladaptive coping with bereavement, while reading autobiographical accounts of breast-cancer sufferers was associated with lower maladaptive coping with stressful life events. Participation in both conditions was associated with higher levels of social support, and taking part in either condition was associated with lower levels of conformity. The latter effect persisted at follow-up. Mixed analyses of variance showed changes over time in three dependent variables. The CEPB was generally viewed as useful, helpful and enjoyable by participants. Implications for future research are discussed, and a biopsychosocial model of breast-cancer prevention is proposed.

When treating patients with cancer, the ability to predict a patient’s response to treatment is an important tool to allow therapy to be tailored for best outcome. Therefore, the need exists for a test to forecast a patient’s response using a sample that is readily accessible, and provides an accurate reflection of a patient’s response to a disease or treatment. Profiling biological fluids, such as plasma or urine, has gained considerable interest in recent years. This is because these fluids are readily available and are expected to provide an accurate representation of a patient’s response to treatment. As such, much effort has been put into finding biomarkers or prognostic indicators. Abnormal protease activity has been linked to the progression of cancer due to their involvement in several processes vital to the survival and proliferation of the disease. These include metastasis, resistance to apoptosis and angiogenesis, amongst others. In addition, dysregulated protease activity has been linked to poor response to chemotherapy as well as tumour regrowth following radiotherapy. Therefore, an increased understanding regarding the activity of a patient’s proteases may provide the clinician with more information as to how best to treat the patient. Therefore, monitoring protease activity has been suggested as a potential marker to predict a patient’s response to cancer treatment. Most enzyme activity assays are currently performed by fluorescence spectroscopy. However, these workflows suffer from limited sensitivity and linear range. Therefore, an alternative, more sensitive assay is required. Mass spectrometry (MS) is a highly sensitive analytical technique routinely used to quantify changes in biological systems. As such, MS has the potential to be used in enzyme activity assays. This study illustrates the development of a novel MS based method to monitor the activity of target enzymes in plasma; specifically asparaginyl endopeptidase (AEP) and caspase-3 using mass spectrometry. These enzymes have been linked to poor chemotherapeutic response in childhood leukaemia and tumour regrowth post-radiotherapy respectively. This project will describe the development and optimisation of each stage of a five step sample preparation and analysis method. This includes the design of enzyme substrates designed to be cleaved by the target enzyme, whilst reducing the effect of other enzymes acting on this substrate, how best to enrich samples for these target peptides, as well as determining the best MS technique to monitor these peptides. In addition, this project describes a comparison between this assay and an existing fluorescence assay when monitoring AEP activity in biological samples such as plasma and whole cell lysates. The application of this method in quantifying caspase-3 activity in plasma samples is also examined.

Clustered failure time data often arise in biomedical and clinical studies where potential correlation among survival times is induced in a cluster. In this thesis, we develop a class of marginal models for right censored clustered failure time data and propose a novel generalized estimating equation approach in a likelihood-based context. We first investigate a semiparametric proportional hazards model for clustered survival data and derive the large sample properties of the regression estimators. The finite sample studies demonstrate that the good applicability of the proposed method as well as the substantial efficiency improvement in comparison with the existing marginal model for clustered survival data. Another important feature of failure time data we will consider in this thesis is a possible fraction of cured subjects. To accommodate the potential cure fraction, we consider a proportional hazards mixture cure model for clustered survival data with long-term survivors and develop a set of estimating equations by incorporating working correlation matrices in an EM algorithm. The dependence among the cure statuses and among the survival times of uncured patients within clusters are modeled by working correlation matrices in the estimating equations. For the parametric proportional hazards mixture cure model, we show that the estimators of the regression parameters and the parameter in the baseline hazard function are consistent and asymptotically normal with a sandwich covariance matrix that can be consistently estimated. A numerical study presents that the proposed estimation method is comparable with the existing parametric marginal method. We also extend the proposed generalized estimating equation approach to a semiparametric proportional hazards mixture cure model where the baseline survival function is nonparametrically specified. A bootstrap method is used to obtain the variances of the estimates. The proposed method is evaluated by a simulation study from which we observe a noticeable efficiency gain of the proposed method over the existing semiparametric marginal method for clustered failure time data with a cure fraction. / Thesis (Ph.D, Mathematics & Statistics) -- Queen's University, 2013-01-30 21:23:48.968

Apoptosis is a regulated "programme" by which cells are induced to die in a manner which does not result in pathological inflammatory reactions, and involves dismantling of the cell into membrane-bound fragments that are removed by phagocytosis. This process is induced in order to remodel tissues and maintain homeostasis in cell numbers. Apoptosis may be induced via many pathways, many of which are redox-regulated, and is dysregulated in cancer cells, mainly due to mutational inactivation of certain pathways. Cancer cells also have a non-linear response to redox imbalance, a potentially exploitable characteristic for the therapeutic selective induction of apoptosis in cancer cells in mixed cell populations. Model cell culture systems are required for the selective toxicity testing of anti-cancer drugs, many of which work by inducing redox stress. In the current study, hydrogen peroxide was selected as the redox stress-inducing agent, and the test cells were an immortal, non-invasive breast epithelial cell line (MCFlOA) and its rastransfected, pre-malignant derivative (MCF10AneoT). A reliable, sensitive, cost effective and least time-consuming system for detection of apoptosis in such a system was sort and two novel methods, cytochrome c release and caspase-3 activity assays, were finally selected and compared with results seen by conventional DNA laddering and morphological examination at the light and electron microscopic level. No single procedure was found to be reliable individually. For the model system used, a combination of electron microscopy and DNA laddering was sufficient for simply detecting apoptotic cell death and necrosis. The caspase activity assay distinguished between apoptosis and necrosis, and cytochrome c release proved the most sensitive indicator of cell response. However, since cytochrome c release may be reversible and may not necessarily proceed to the downstream events of apoptosis in the time frame used in the current assays, it is not certain that cytochrome c release ultimately leads to apoptosis. However, three forms of cytochrome c were observed on western blots, the nature and significance of which remains to be determined. A comparison of the results of different methods allowed a model for the sequence of specific apoptotic events to be proposed. / Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 2000.

Our hypothesis is that the polyamine biosynthetic pathway, a pathway essential in many cellular functions, is modulated by NSAIDs and that this is, at least in part, how NSAID chemoprevention is mediated. An <i>in vitro </i>model of colorectal cancer was used: two cell lines one of which is COX positive and one COX negative to determine the effects of a range of selective and non-selective NSAIDs on various reactions within the polyamine pathway.  NSAIDs are cytotoxic to colorectal cancer cells regardless of their COX expression.  NSAID-mediated inhibition of cell growth is accompanied by inhibition of ODC activity, partial depletion of polyamine concentrations and up-regulation of polyamine catabolism. In order to investigate the importance of polyamine metabolism, a specific polyamine inhibitor α-difluoromethylornithine (DFMO) was used in combination with the NSAIDs.  DFMO <i>per se </i>is not toxic to cells and it does not enhance NSAID mediated toxicity.  DFMO in combination with the NSAIDs did cause increased catabolic activity and more sustained polyamine depletion than either alone, however no additional decrease in ODC activity was observed.  This suggests that NSAID toxicity is not enhanced by DFMO in this <i>in vitro </i>model. Analysis of the mode of death indicated that the NSAIDs caused apoptotic cell death, confirmed through biochemical and morphological studies and that the NSAIDs affected gene expression of key enzymes in the polyamine biosynthetic pathway. Our findings suggest that modulation of the polyamine pathway by NSAIDs is at least part of the mechanism of action involved in cancer chemoprevention. Therefore modulation of the polyamine pathway may be useful for design of new chemopreventative drugs.

It is imperative that the cancer research community has the means with which to effectively locate, access, manage, analyse and interpret the plethora of data values being generated by novel technologies. This thesis addresses this unmet requirement by using pancreatic cancer and breast cancer as prototype malignancies to develop a generic integrative transcriptomic model. The analytical workflow was initially applied to publicly available pancreatic cancer data from multiple experimental types. The transcriptomic landscape of comparative groups was examined both in isolation and relative to each other. The main observations included (i) a clear separation of profiles based on experimental type, (ii) identification of three subgroups within normal tissue samples resected adjacent to pancreatic cancer, each showing disruptions to biofunctions previously associated with pancreatic cancer (iii) and that cell lines and xenograft models are not representative of changes occurring during pancreatic tumourigenesis. Previous studies examined transcriptomic profiles across 306 biological and experimental samples, including breast cancer. The plethora of clinical and survival data readily available for breast cancer, compared to the paucity of publicly available pancreatic cancer data, allowed for expansion of the pipeline’s infrastructure to include functionalities for cross-platform and survival analysis. Application of this enhanced pipeline to multiple cohorts of triple negative and basal-like breast cancers identified differential risk groups within these breast cancer subtypes. All of the main experimental findings of this thesis are being integrated with the Pancreatic Expression Database and the Breast Cancer Campaign Tissue Bank bioinformatics portal, which enhances the sharing capacity of this information and ensures its exposure to a wider audience.

Cell competition leads to elimination of a viable cell population, by fitter cells. Despite over forty years of research, the molecular mechanisms of competition in mammals are poorly understood. During my PhD I have investigated the mechanisms of competition by exploring an established mammalian cell culture system, in which wild-type MDCK cells eliminate scribble-deficient cells, and I have also developed a novel cell culture system to model mammalian competition. My work contributed to the discovery that scribble-deficient cells are eliminated not by biochemical exchange among cells, but by mechanical compaction. We termed this phenomenon mechanical competition. I employed transcriptional profiling to determine the molecular signature of mechanical losers, and identified activation of p53 signalling as their hallmark. My colleagues and I then demonstrated that elevation of p53 is both necessary and sufficient to trigger mechanical competition. In further investigating the mechanisms of mechanical competition, I found that compaction activates ROCK in scribble-deficient cells, and that this is required for their elimination. Inhibition of Src signalling in mechanical losers also protected them form out-competition, and integrin signalling is another pathway likely involved in mechanical competition. While investigating p53 competition, we observed that p53-high and p53-low cells engage in directional migration, with p53-high cells always at the migrating front. As a side-project, I investigated the role of p53 in directional migration, by exploring an established model with a single leader cell and multiple followers. We established a method to generate multinucleated leaders on demand. By creating leaders from p53-deficient cells, I established that p53 signalling is required for some, but not all multinucleated cells to trigger collective migration, thus implicating p53 signalling in a type of migration involved in wound healing. Finally, I successfully modelled p53-driven mechanical competition in a differentiated primary tracheal epithelial cell culture, thereby establishing a novel system to study mammalian competition, and also proving that p53 competition is conserved between different mammalian epithelia. Considering the involvement of p53, mechanical competition may play a major role in cancer.

Hypoxia (low tissue oxygenation) is an important signalling cue for many cell types. The study of its effects has direct relevance to surgery since hypoxic gradients are generated with every cut. On a cellular level, changes in molecular oxygen are sensed by the Hypoxia-Inducible Factors (HIFs). The HIFs are a family of transcription factors that are master regulators of over 100 genes and can effect changes in multiple cellular processes including migration, survival and differentiation. The broad nature of the response to hypoxia means that study of the HIF system is also important in cancer; where many tumour cells have found ways of subverting the HIF response to ensure their continued growth and survival. This thesis explores the role of hypoxia and the HIF system in the regulation of migration, survival and differentiation in both cancer and stem cells. The first experimental chapter examines the role of hypoxia and the HIF system in the regulation of migration and three-dimensional organisation in several cancer cell lines. Using biochemical and functional assays, the HIF system is shown to exert a pleiotropic effect across a panel of cancer cell lines. In particular, HIF 1α is shown to activate proliferation in a prostate cancer cell line in findings that may be useful to inform future clinical strategies for the management of this disease. In the second experimental chapter, the first epigenetic mechanism involving histone modification for the specific regulation of HIF 2α expression is characterised. Here the family with sequence similarity 60, member A (Fam60a) protein is shown to repress expression of the HIF 2α gene through its association with the class 1 Sin3-HDAC co-repressor complex, achieving specificity by co-operation with the SP1 transcription factor. This novel mechanism is demonstrated to be important in the regulation of the basal expression of HIF 2α. Modification of HIF 2α expression through this mechanism is shown to alter cell migration, three dimensional organisation and angiogenesis in vitro. The clinical importance of these findings is demonstrated in a series of 45 patients suffering from colorectal cancer of known stage. In this cohort, the reciprocal relationship between Fam60a and HIF 2α is maintained, and both are identified as potential novel biomarkers for the development of this disease. In the final experimental chapter, the role of hypoxia in the regulation of differentiation is explored. These effects are documented in mesenchymal progenitors primarily derived from human fat. Here, hypoxia is shown to regulate differentiation in a context-dependent manner, promoting osteogenic and retarding adipose and neural differentiation in-vitro. The roles of Fam60a and HIF 2α are explored in this system. These data may be useful in optimising future surgical engraftment of these cells for regenerative purposes.

Solid cancer tumors must recruit new blood vessels for growth and maintenance. Discovering drugs that block this tumor-induced development of new blood vessels (angiogenesis) is an important approach in cancer treatment. However, the complexity of angiogenesis and the difficulty in implementing and evaluating medical changes prevent the discovery of novel and effective new therapies. This paper presents a massively parallel computational search-based approach for the discovery of novel potential cancer treatments, using a high fidelity simulation of angiogenesis. Discovering new therapies is viewed as multi-objective combinatorial optimization over two competing objectives: minimizing the medical cost of the intervention while minimizing the oxygen provided to the cancer tumor by angiogenesis. Results show the effectiveness of the search process in finding simple interventions that are currently in use and more interestingly, discovering some new approaches that are counterintuitive yet effective. Distributed systems are becoming more prevalent as the demand for connectivity increases. Developers are faced with the challenge of creating software systems that meet these demands and adhere to good software practices. Technologies of today aid developers in this, but they may cause applications to suffer performance problems and require developers to abandon basic software concepts, such as modularization, performance, and maintainability. This work presents the Vitruvian framework that provides solutions to common distribution goals, and distributes applications using replication and transparency at varying stages of application development.