The goal of this research is to improve the breast cancer screening process based on magnetic resonance imaging (MRI). In a typical MRI breast examination, a radiologist is responsible for visually examining the MR images acquired during the examination and identifying suspect tissues for biopsy. It is known that if multiple radiologists independently analyze the same examinations and we biopsy any lesion that any of our radiologists flagged as suspicious then the overall screening process becomes more sensitive but less specific. Unfortunately cost factors prohibit the use of multiple radiologists for the screening of every breast MR examination. It is thought that instead of having a second expert human radiologist to examine each set of images, that the act of second reading of the examination can be performed by a computer-aided detection and diagnosis system. The research presented in this thesis is focused on the development of a computer-aided detection and diagnosis system for breast cancer screening from dynamic contrast-enhanced magnetic resonance imaging examinations. This thesis presents new computational techniques in supervised learning, unsupervised learning and classifier visualization. The techniques have been applied to breast MR lesion data and have been shown to outperform existing methods yielding a computer aided detection and diagnosis system with a sensitivity of 89% and a specificity of 70%.

Anthracycline- and taxane-based regimens have been the mainstay in treating breast cancer patients using chemotherapy. Yet, the genetic make-up of patients and their tumors may have a strong impact on tumor sensitivity to these agents and to treatment outcome. This study represents a new paradigm assimilating bioinformatic tools with in vitro model systems to discover novel genetic variations that may be associated with chemotherapy response in breast cancer. This innovative paradigm integrates drug response data for the NCI60 cell line panel with genome-wide Affymetrix SNP data in order to identify genetic variations associated with drug resistance. This genome wide association study has led to the discovery of 59 candidate loci that may play critical roles in breast tumor sensitivity to doxorubicin and paclitaxel. 16 of them were mapped within well-characterized genes (three related to doxorubicin and 13 to paclitaxel). Further in silico characterization and in vitro functional analysis validated their differential expression in resistant cancer cell lines treated with the drug of interest (over-expression of RORA and DSG1, and under-expression of FRMD6, SGCD, SNTG1, LPHN2 and DCT). Interestingly, three and six genes associated with doxorubicin and paclitaxel resistance, respectively, are involved in the apoptotic process in cells. A constructed interactome suggested that there is cross-talk at the Nrf-2 oxidative stress pathway between genes associated with resistance to doxorubicin and paclitaxel. This unique GWA approach serves as a proof-of-principle study and systematically investigates targets responsible for variable response to chemotherapy in breast tumor cells and possibly the tumors of breast cancer patients. Overall, the model discovered novel candidate genes that have not been previously associated with doxorubicin and paclitaxel cytotoxicity. Future studies will be directed at illustrating a causative relationship between the observed genomic changes and drug resistance in breast cancer patients undergoing doxorubicin and paclitaxel chemotherapy.

The BCA2 E3 ligase is expressed in a majority of invasive breast cancers. BCA2 has inherent autoubiquitination activity which contributes to cell migration and proliferation processes. Here, ten novel BCA2 binding proteins were found using yeast and bacterial screening. Two of which were human homolog of Rad23 variant A (hHR23a) and 14-3-3σ. In vivo and in vitro assays confirmed that both hHR23a and 14-3-3σ bound BCA2 and were co-expressed with BCA2 in breast cancer cells. Interaction of BCA2 with hHR23a and 14-3-3σ affect the autoubiquitination and auto-degradation activity of BCA2. Multi-ubiquitination of hHR23a-bound BCA2 was dramatically lower than that of free BCA2, this corresponded to increased BCA2 expression and half-life. Furthermore, phosphorylated BCA2 protein was stabilized by interaction with 14-3-3σ, via substrate inhibition of BCA2 autoubiquitination. High expression of BCA2 is correlated with grade in breast cancer and regulation of this E3 ligase’s activity may be important to cancer progression.

BACKGROUND: Breast cancer patients typically present with unhealthy body composition (high fat mass and low muscularity) near diagnosis. These body composition characteristics often worsen during treatment and ultimately contribute to the development of secondary diseases like diabetes and cardiovascular disease in survivorship. Inflammation in overweight or obese individuals is associated with impaired glucose metabolism; the presence of the tumour may lead to greater impairments in glucose metabolism in breast cancer patients. OBJECTIVES AND HYPOTHESES: The objectives of this study were to: 1) evaluate breast cancer patients near the onset of treatment for metabolic measures including an oral glucose tolerance test (OGTT), cytokine profiles, as well as body composition, nutritional status and fitness and, 2) make comparisons between breast cancer patients, age- and BMI-matched females (HM females), and a group of young, non-malignant females with healthy BMIs (HY females) on these measures. We hypothesized that breast cancer patients would demonstrate impaired glucose metabolism relative to HM females, and that this would be attributed to systemic inflammation. We also hypothesized that both breast cancer patients and HM females would present with unhealthy body composition, impaired glucose and lipid metabolism, systemic inflammation, poor fitness and greater caloric intake compared to HY females. METHODS: We evaluated body composition using % body fat (skinfold callipers) and waist circumference. Following collection of fasting blood samples, an OGTT was conducted to assess glucose, insulin, c-peptide and glucagon dynamics. Fasting blood samples were analysed for lipids and pro- and anti-inflammatory cytokines. Incremental exercise tests were conducted to assess VO2peak, and estimated 1-RM tests assessed strength of the biceps, triceps and quadriceps muscles. Baecke and CHAMPS questionnaires provided an indication of habitual physical activity. A 3-day food record was used to analyze daily caloric intake and macronutrient distribution. Breast cancer patients and HM females were compared using paired t-tests. Patients and HM females were compared to HY females using t-tests. Statistical significance was accepted at p < 0.05. RESULTS: Overall, breast cancer patients were overweight (BMI: 28.8 ± 6.0 kg/m2) and presented with abdominal obesity (waist circumference: 94.6 ± 14.0 cm) and dyslipidemia (TAG: 1.84 ± 1.17 mM and HDL-c: 1.08 ± 0.23 mM), indicating risk for metabolic syndrome. Although fasting glucose concentrations did not differ between the 3 groups, breast cancer patients demonstrated higher glucose concentrations at 30 min during an OGTT. Similar to glucose, fasting insulin concentrations did not differ between the 3 groups, but patients demonstrated higher insulin at 150 min during an OGTT. Breast cancer patients had elevated fasting serum c-peptide (2.6 ± 1.2 ng/mL vs. 1.9 ± 0.8 ng/mL, p = 0.005). C-peptide remained elevated in patients compared to non-malignant females during the last hour of the OGTT, indicating that insulin secretion was sustained in breast cancer patients. We observed no difference in serum cytokines between patients and HM females or between patients and HY females. VO2peak, although lower compared to HY females, was similar in patients and HM females. There were no differences in habitual physical activity or nutrition measures between any groups. DISCUSSION AND CONCLUSIONS: Breast cancer patients presented with poorer glucose features during an OGTT compared to HM and HY females. However, systemic inflammation, body composition, energy expenditure and energy intake were similar in breast cancer patients and HM females. Thus, these impairments may be tumour-related. Future studies need to specifically elucidate the effects of the tumour in host glucose metabolism.

Thesis (Ph. D.)--University of Hawaii at Manoa, 1996. / Includes bibliographical references (leaves 136-146). / Microfiche. / xiv, 146 leaves, bound ill., maps 29 cm

Early detection is one of the most important factors for successful treatment of cancer. Currently, scientists are searching for molecular markers that can help identify and predict outcome and chance of recurrence in patients. In this study, we demonstratet he potential impact of Y-Box binding protein-1 (YB-1) as a marker of aggressiveness and cancer recurrence in breast malignancies by screening one of the largest tissue microarrays in North America. YB-1 is an oncogenic transcription/translation factor, which is over-expressed in the majority of malignancies, including breast cancer. In the cohort of 4049 primary breast tumours, we show that YB-1 is a strong marker of aggressiveness, poor survival and cancer recurrence in all subtypes of human breast cancer with a particularly high frequency of expression in the ER negative basal-like and HER-2 breast cancer subtypes. This suggests that targeting YB-1 may provide a new avenue for therapeutic intervention in these breast cancers that are currently challenging to treat. Cox regression multivariate analysis indicates that YB-1 is second only to nodal status as a strong independent prognostic marker for poor outcome and relapse compared to established clinico-pathological biomarkers, including tumour size, age, grade, ER and HER-2 status. This finding suggests that YB-1 has great potential to be in a priority list of biomarkers for identifying the patients with a higher risk of relapse and poor outcome. Subsequently, we find an association between YB-1 and urokinase Plasminogen Activator (uPA) expression in the basal-like subtype. We then show that YB-1 is involved in the regulation of uPA expression. More importantly, silencing YB-1 or uPA results in a significant reduction in cancer cell invasion. As there are no commercially available YB-linibitors we examine the efficacy of BMS-536924, a small molecule inhibitor for activated IGF-1R/IR on SUM149 cells. We demonstrate that activated IGF-1R is associated with poor survival in primary breast tumours and, that BMS-536924 reduces uPA expression through inhibition YB-1 in SUM149 cells. We therefore conclude that YB-1 is a bio-marker for poor survival and relapse. We also indicate that YB-1 has potential use as a molecular marker in a clinical setting. Inhibiting YB-1 may provide an ideal opportunity for targeted therapy in breast cancer.

From the time women suspect that they have breast cancer they may be faced with many decisions about themselves, their treatment, their relationship and their lives. Previous research in this area has focused largely on describing the different ways that patients behave when making decisions about treatment, and women's perspectives of making those decisions after the initial diagnosis of early breast cancer. However, there are no studies that provide an understanding of the range of decisions that women are likely to face and what the experience of making these decisions is like. The aims of this study were to describe the types of decisions women make during early breast cancer and to provide an in-depth understanding of the phenomenon of making decisions during the experience of early breast cancer. Health professionals may be able to use this understanding to improve their relationships with patients and further assist women to make decisions during their experience of early breast cancer.

Human Papillomavirus (HPV) is a small, double stranded DNA tumour virus. Infection with HPV normally results in formation of warts. Certain types of HPV, such as type -16 and -18, are shown to have a causal role in the development of uterine cervical cancer, and are so called high risk type HPV. Recently, a role of HPV in breast cancer has been suggested, although a causal role for HPVs in human breast cancer is yet to be demonstrated. The first part of this study investigates the association of HPV with human breast cancer. The results demonstrate that 48% of breast cancers that occurred in Australian women are HPV positive and they are mainly variants of HPV-18. Further analysis shows that HPV positive breast cancer patients are significantly younger than HPV negative patients, suggesting infection with HPV increases the risk of breast cancer development. This is coincidental with increased risk of HPV infection in sexually active young women and provides evidence that HPV has a role in breast cancer development. The second part of this project investigates the mechanisms by which high risk type HPV oncogenic protein E6, transforms primary human foreskin keratinocytes (natural host cells of HPV). HPV E6 is always expressed in HPV positive cervical carcinoma and results in the degradation of the cellular tumour suppressor protein p53. It is generally believed that HPV E6 contributes to HPV transformation by degradation of p53 protein which leads to cellular immortalisation ? an early step in tumorigenic transformation. Subsequent studies, however, indicate that HPV E6 possesses other functions (such as induction of telomerase activity) which may also be involved in cellular immortalisation. The results of my investigations demonstrate: 1) that degradation of p53 protein is required but is insufficient to immortalise primary cells; 2) that HPV E6 induced telomerase activity is coincidental with an increase in cell culture passage number; 3) that multiple functions of high risk type HPV E6 protein are required for cellular immortalisation. This finding suggests HPV infection is associated with early onset of breast cancer and that multiple functions of high risk type HPV E6 protein are involved in cellular immortalisation. Further study in both of these areas should provide alternative diagnostic markers, leading to prevention and treatment strategies for HPV positive breast cancer and other cancers.

This thesis presents a discursive analysis of accounts of breast cancer screening, risk and prevention. Breast cancer is currently the largest form of cancer death for women in Australia ( and many other Western nations ), but the causes are unknown. Consequently, health promotion has tended to focus on the early detection of the disease. Despite this focus, the currently available techniques for early detection of breast cancer continue to be subject to research and debate. For women at high risk of the disease due to a family history and, in some cases, a genetic predisposition, there is also discussion regarding the best course of preventative action. One option, prophylactic surgery ( or the removal of healthy breasts ), continues to be the topic of both medical and psychological research. In addition to the ongoing medical research and debate around the topics of breast cancer screening, risk and prevention, there has been extensive sociological theorising around the increased societal emphasis on risk more generally. This emphasis on risk has been argued to be one feature of governance in modern liberal democratic societies. Particularly with respect to health - care in such societies, there has been argued to be a shift towards increasing individual responsibility for health and the management of potential illness. A focus on individual responsibility is not necessarily a key feature of contemporary public health approaches. Nevertheless, it has been suggested that the emphasis on risk management, in combination with the prevalence of ' lifestyle ' diseases, has widened the gaze of public health, such that all aspects of individuals ' lives are open to scrutiny and regulation. An inevitable consequence of such shifts is the placing of increased responsibility for health on to individuals. The analysis in this thesis draws on a synthetic discursive approach to examine talk and text around the issues of breast cancer screening, risk and prevention, in light of these shifts in conceptualisations of health and health - care, and the medical debate surrounding detection and prevention techniques. In particular, three analytic chapters are concerned with three sets of data : media accounts of prophylactic mastectomy ; pamphlets promoting breast cancer screening ; and women ' s focus group talk. The analysis focuses on the discursive themes, ideological dilemmas, and subject positions deployed in the data. The following analytic findings are discussed : - the repeated positioning of individuals as ' patients without symptoms ', who are required to engage in risk management in order to prevent their ( inevitable ) future illness ; - the positioning of women in terms of traditional notions of femininity and mothering ; - the construction of a dilemmatic relationship between individuals and medical experts, whereby individuals are positioned as responsible for their own health and illness prevention, while simultaneously being reliant on medical experts who are sometimes wrong ; - the negotiation and flexible management of notions of responsibility, emotion and health behaviours in women ' s talk. The final chapter in the thesis considers implications of the analysis for public health and health promotion, and for a critical ( public ) health psychology. / Thesis (Ph.D.)--School of Psychology, 2006.

This thesis proposes four novel geometric neurodynamical classifier models, namely GBAM, Lie-derivative, Lie-Poisson, and FAM, applied to breast cancer detection. All these models have been published in a paper and/or in a book form. All theoretical material of this thesis (Chapter 2) has been published in my monographs (see my publication list), as follows: 2.1 Tensorial Neurodynamics has been published in Natural Biodynamics (Chapters 3, 5 and 7), Geometrical Dynamics of Complex Systems; (Chapter 1 and Appendix), 2006) as well as Applied Differential Geometry:A Modern Introduction(Chapter 3) 2.2 GBAM Neurodynamical Classifier has been published in Natural Biodynamics (Chapter 7) and Neuro-Fuzzy Associative Machinery for Comprehensive Brain and Cognition Modelling (Chapter 3), as well as in the KES–Conference paper with the same title; 2.3 Lie-Derivative Neurodynamical Classifier has been published in Geometrical Dynamics of Complex Systems; (Chapter 1) and Applied Differential Geometry: A Modern Introduction (Chapter 3); 2.4 Lie-Poisson Neurodynamical Classifier has been published in Geometrical Dynamics of Complex Systems; (Chapter 1) and Applied Differential Geometry: A Modern Introduction (Chapter 3); 2.5 Fuzzy Associative Dynamical Classifier has been published in Neuro-Fuzzy Associative Machinery for Comprehensive Brain and Cognition Modelling (Chapter 4), as well as in the KES-Conference paper with the same title. Besides, Section 1.2 Artificial Neural Networks has been published in Natural Biodynamics (Chapter 7) and Neuro-Fuzzy Associative Machinery for Comprehensive Brain and Cognition Modelling (Chapter 3). Also, Sections 4.1. and 4.5. have partially been published in Neuro-Fuzzy Associative Machinery for Comprehensive Brain and Cognition Modelling (Chapters 3 and 4, respectively) and in the corresponding KES–Conference papers. A. The GBAM (generalized bidirectional associative memory) classifier is a neurodynamical, tensor-invariant classifier based on Riemannian geometry. The GBAM is a tensor-field system resembling a two-phase biological neural oscillator in which an excitatory neural field excites an inhibitory neural field, which reciprocally inhibits the excitatory one. This is a new generalization of Kosko’s BAM neural network, with a new biological (oscillatory, i.e., excitatory/inhibitory)interpretation. The model includes two nonlinearly-coupled (yet non-chaotic and Lyapunov stable) subsystems, activation dynamics and self-organized learning dynamics, including a symmetric synaptic 2-dimensional tensor-field, updated by differential Hebbian associative learning innovations. Biologically, the GBAM describes interacting excitatory and inhibitory populations of neurons found in the cerebellum, olfactory cortex, and neocortex, all representing the basic mechanisms for the generation of oscillating (EEG-monitored) activity in the brain. B. Lie-derivative neurodynamical classifier is an associative-memory, tensor-invariant neuro-classifier, based on the Lie-derivative operator from geometry of smooth manifolds. C. Lie-Poisson neurodynamical classifier is an associative-memory, tensor-invariant neuro-classifier based on the Lie-Poisson bracket from the generalized symplectic geometry. D. The FAM-matrix (fuzzy associative memory) dynamical classifier is a fuzzy-logic classifier based on a FAM-matrix (fuzzy phase-plane). All models are formulated and simulated in Mathematica computer algebra system. All models are applied to breast cancer detection, using the database from the University of Wisconsin and Mammography database. Classification results outperformed those obtained with standard MLP trained with backpropagation algorithm. / Thesis (Ph.D.) -- University of Adelaide, School of Mathematical Sciences, 2008