Expression of prostate-specific antigen (PSA) correlates with poor response to tamoxifen therapy in recurrent breast cancer

Prostate-specific antigen (PSA) is a serine protease which may play a role in a variety of cancer types, including breast cancer. In the present study, we evaluated whether the level of PSA in breast tumour cytosol could be associated with prognosis in primary breast cancer, or with response to tamoxifen therapy in recurrent disease. PSA levels were determined by enzyme-linked immunosorbent assay (ELISA) in breast tumour cytosols, and were correlated with prognosis in 1516 patients with primary breast cancer and with response to first-line tamoxifen therapy in 434 patients with recurrent disease. Relating the levels of PSA with classical prognostic factors, low levels were more often found in larger tumours, tumours of older and post-menopausal patients, and in steroid hormone receptor-negative tumours. There was no significant association between the levels of PSA with grade of differentiation or the number of involved lymph nodes. In patients with primary breast cancer, PSA was not significantly related to the rate of relapse, and a positive association of PSA with an improved survival could be attributed to its relationship to age. In patients with recurrent breast cancer, a high level of PSA was significantly related to a poor response to tamoxifen therapy, and a short progression-free and overall survival after start of treatment for recurrent disease. In Cox multivariate analyses for response to therapy and for (progression-free) survival, corrected for age/menopausal status, disease-free interval, site of relapse and steroid hormone receptor status, PSA was an independent variable of poor prognosis. It is concluded that the level of PSA in cytosols of primary breast tumours might be a marker to select breast cancer patients who may benefit from systemic tamoxifen therapy. © 1999 Cancer Research Campaig

Alzheimer disease models and human neuropathology: similarities and differences

Animal models aim to replicate the symptoms, the lesions or the cause(s) of Alzheimer disease. Numerous mouse transgenic lines have now succeeded in partially reproducing its lesions: the extracellular deposits of Aβ peptide and the intracellular accumulation of tau protein. Mutated human APP transgenes result in the deposition of Aβ peptide, similar but not identical to the Aβ peptide of human senile plaque. Amyloid angiopathy is common. Besides the deposition of Aβ, axon dystrophy and alteration of dendrites have been observed. All of the mutations cause an increase in Aβ 42 levels, except for the Arctic mutation, which alters the Aβ sequence itself. Overexpressing wild-type APP alone (as in the murine models of human trisomy 21) causes no Aβ deposition in most mouse lines. Doubly (APP × mutated PS1) transgenic mice develop the lesions earlier. Transgenic mice in which BACE1 has been knocked out or overexpressed have been produced, as well as lines with altered expression of neprilysin, the main degrading enzyme of Aβ. The APP transgenic mice have raised new questions concerning the mechanisms of neuronal loss, the accumulation of Aβ in the cell body of the neurons, inflammation and gliosis, and the dendritic alterations. They have allowed some insight to be gained into the kinetics of the changes. The connection between the symptoms, the lesions and the increase in Aβ oligomers has been found to be difficult to unravel. Neurofibrillary tangles are only found in mouse lines that overexpress mutated tau or human tau on a murine tau −/− background. A triply transgenic model (mutated APP, PS1 and tau) recapitulates the alterations seen in AD but its physiological relevance may be discussed. A number of modulators of Aβ or of tau accumulation have been tested. A transgenic model may be analyzed at three levels at least (symptoms, lesions, cause of the disease), and a reading key is proposed to summarize this analysis

Using Social Network Analysis to Monitor and Assess the Effectiveness of Knowledge Brokers at Connecting Scientists and Decision-Makers: An Australian case study

Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment Despite growing rhetoric regarding the potential benefits of using knowledge brokers in relation to environmental challenges and decision-making processes, the evidence in support of such claims is mostly anecdotal. This is, in part, due to the lack of established methods to evaluate the effectiveness and efficiency of knowledge brokers. To address this gap we assess the utility of social network analysis (SNA) to evaluate the effectiveness of knowledge brokers in connecting scientists and decision-makers. Specifically, using a case-study approach, we undertake longitudinal SNA over a 12-month period to evaluate the extent to which the knowledge broker developed networks between producers and users of knowledge across different organizations. We also undertook a qualitative survey of scientists (n = 29) who worked in the same organization as the knowledge broker to understand the extent to which the knowledge broker increased the impact of scientific research for decision-making purposes. Results show that the knowledge broker developed an extensive stakeholder network of 192 individuals spanning over 30 organizations. The results of the SNA found that over time this network increased in density and became more cohesive, both key elements underpinning successful knowledge exchange. Furthermore, the qualitative survey found that the knowledge broker also had a positive impact in other ways, including helping researchers understand the operating environments within decision-making agencies and the best approaches for engaging with specific decision-makers. Thus, this study demonstrates the value of SNA for evaluating knowledge brokers and provides empirical support for the use of knowledge brokers in the environmental sector. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment