Bnip3 as a Dual Regulator of Mitochondrial Turnover and Cell Death in the Myocardium

The Bcl-2 adenovirus E1B 19 kDa-interacting protein 3 (Bnip3) is a pro-apoptotic BH3-only protein associated with the pathogenesis of many diseases, including cancer and cardiovascular disease. Studies over the past decade have provided insight into how Bnip3 induces mitochondrial dysfunction and subsequent cell death in cells. More recently, Bnip3 was identified as a potent inducer of autophagy in cells. However, the functional role of Bnip3-mediated autophagy has been difficult to define and remains controversial. New evidence has emerged suggesting that Bnip3 is an important regulator of mitochondrial turnover via autophagy in the myocardium. Also, studies suggest that the induction of Bnip3-dependent mitochondrial autophagy is a separately activated process independent of Bax/Bak and the mitochondrial permeability transition pore (mPTP). This review discusses the current understanding of the functional role that Bnip3 plays in the myocardium. Recent studies suggest that Bnip3 might have a dual function in the myocardium, where it regulates both mitochondrial turnover via autophagy and cell death and that these are two separate processes activated by Bnip3

Constructive Technology Assessment (CTA) as a tool in coverage with evidence development: the case of the 70-gene prognosis signature for breast cancer diagnostics

Objectives: Constructive Technology Assessment (CTA) is a means to guide early implementation of new developments in society, and can be used as an evaluation tool for Coverage with Evidence Development (CED). We used CTA for the introduction of a new diagnostic test in the Netherlands, the 70-gene prognosis signature (MammaPrint®) for node-negative breast cancer patients. Methods: Studied aspects were (organizational) efficiency, patient-centeredness and diffusion scenarios. Pre-post structured surveys were conducted in fifteen community hospitals concerning changes in logistics and teamwork as a consequence of the introduction of the 70-gene signature. Patient-centeredness was measured by questionnaires and interviews regarding knowledge and psychological impact of the test. Diffusion scenarios, which are commonly applied in industry to anticipate on future development and diffusion of their products, have been applied in this study. Results: Median implementation-time of the 70-gene signature was 1.2 months. Most changes were seen in pathology processes and adjuvant treatment decisions. Physicians valued the addition of the 70-gene signature information as beneficial for patient management. Patient-centeredness (n = 77, response 78 percent): patients receiving a concordant high-risk and discordant clinical low/high risk-signature showed significantly more negative emotions with respect to receiving both test-results compared with concordant low-risk and discordant clinical high/low risk-signature patients. The first scenario was written in 2004 before the introduction of the 70-gene signature and identified hypothetical developments that could influence diffusion; especially the “what-if” deviation describing a discussion on validity among physicians proved to be realistic. Conclusions: Differences in speed of implementation and influenced treatment decisions were seen. Impact on patients seems especially related to discordance and its successive communication. In the future, scenario drafting will lead to input for model-based cost-effectiveness analysis. Finally, CTA can be useful as a tool to guide CED by adding monitoring and anticipation on possible developments during early implementation, to the assessment of promising new technologies

Constructive Technology Assessment (CTA) as a tool in coverage with evidence\ud development: the case of the 70-gene prognosis signature for breast cancer diagnostics

Objectives:\ud Constructive Technology Assessment (CTA) is a means to guide early implementation of new developments in society, and can be used as an evaluation tool for Coverage with Evidence Development (CED). We used CTA for the introduction of a new diagnostic test in the Netherlands, the 70-gene prognosis signature (MammaPrint®) for node-negative breast cancer patients.\ud \ud Methods:\ud Studied aspects were (organizational) efficiency, patient-centeredness and diffusion scenarios. Pre-post structured surveys were conducted in fifteen community hospitals concerning changes in logistics and teamwork as a consequence of the introduction of the 70-gene signature. Patient-centeredness was measured by questionnaires and interviews regarding knowledge and psychological impact of the test. Diffusion scenarios, which are commonly applied in industry to anticipate on future development and diffusion of their products, have been applied in this study.\ud \ud Results:\ud Median implementation-time of the 70-gene signature was 1.2 months. Most changes were seen in pathology processes and adjuvant treatment decisions. Physicians valued the addition of the 70-gene signature information as beneficial for patient management. Patient-centeredness (n = 77, response 78 percent): patients receiving a concordant high-risk and discordant clinical low/high risk-signature showed significantly more negative emotions with respect to receiving both test-results compared with concordant low-risk and discordant clinical high/low risk-signature patients. The first scenario was written in 2004 before the introduction of the 70-gene signature and identified hypothetical developments that could influence diffusion; especially the “what-if” deviation describing a discussion on validity among physicians proved to be realistic.\ud \ud Conclusions:\ud Differences in speed of implementation and influenced treatment decisions were seen. Impact on patients seems especially related to discordance and its successive communication. In the future, scenario drafting will lead to input for model-based cost-effectiveness analysis. Finally, CTA can be useful as a tool to guide CED by adding monitoring and anticipation on possible developments during early implementation, to the assessment of promising new technologies

Constructive Technology Assessment (CTA) as a tool in Coverage with Evidence Development: The case of the 70-gene prognosis signature for breast cancer diagnostics

Objectives: Constructive Technology Assessment (CTA) is a means to guide early implementation of new developments in society, and can be used as an evaluation tool for Coverage with Evidence Development (CED). We used CTA for the introduction of a new diagnostic test in the Netherlands, the 70-gene prognosis signature (MammaPrint(R)) for node-negative breast cancer patients.Methods: Studied aspects were (organizational) efficiency, patient-centeredness and diffusion scenarios. Pre-post structured surveys were conducted in fifteen community hospitals concerning changes in logistics and teamwork as a consequence of the introduction of the 70-gene signature. Patient-centeredness was measured by questionnaires and interviews regarding knowledge and psychological impact of the test. Diffusion scenarios, which are commonly applied in industry to anticipate on future development and diffusion of their products, have been applied in this study.Results: Median implementation-time of the 70-gene signature was 1.2 months. Most changes were seen in pathology processes and adjuvant treatment decisions. Physicians valued the addition of the 70-gene signature information as beneficial for patient management. Patient-centeredness (n = 77, response 78 percent): patients receiving a concordant high-risk and discordant clinical low/high risk-signature showed significantly more negative emotions with respect to receiving both test-results compared with concordant low-risk and discordant clinical high/low risk-signature patients. The first scenario was written in 2004 before the introduction of the 70-gene signature and identified hypothetical developments that could influence diffusion; especially the "what-if" deviation describing a discussion on validity among physicians proved to be realistic.Conclusions: Differences in speed of implementation and influenced treatment decisions were seen. Impact on patients seems especially related to discordance and its successive communication. In the future, scenario drafting will lead to input for model-based cost-effectiveness analysis. Finally, CTA can be useful as a tool to guide CED by adding monitoring and anticipation on possible developments during early implementation, to the assessment of promising new technologie

Use of 70-gene signature to predict prognosis of patients with node-negative breast cancer: a prospective community-based feasibility study (RASTER)

Background: A microarray-based 70-gene prognosis signature might improve the selection of patients with node-negative breast cancer for adjuvant systemic treatment. The main aims of this MicroarRAy PrognoSTics in Breast CancER (RASTER) study were to assess prospectively the feasibility of implementation of the 70-gene prognosis signature in community-based settings and its effect on adjuvant systemic treatment decisions when considered with treatment advice formulated from the Dutch Institute for Healthcare Improvement (CBO) and other guidelines. Methods: Between January, 2004 and December, 2006, 812 women aged under 61 years with primary breast carcinoma (clinical T1–4N0M0) were enrolled. Fresh tumour samples were collected in 16 hospitals in the Netherlands within 1 h after surgery. Clinicopathological factors were collected and microarray analysis was done with a custom-designed array chip that assessed the mRNA expression index of the 70 genes previously identified for the prognostic signature. Patients with a “good” signature were deemed to have a good prognosis and, therefore, could be spared adjuvant systemic treatment with its associated adverse effects, whereas patients with a “poor” signature were judged to have a poor prognosis and should be considered for adjuvant systemic treatment. Concordance between risk predicted by the prognosis signature and risk predicted by commonly used clinicopathological guidelines (ie, St Gallen guidelines, Nottingham Prognostic Index, and Adjuvant! Online) was assessed. Findings: Of 585 eligible patients, 158 patients were excluded because of sampling failure (n=128) and incorrect procedure (n=30). Prognosis signatures were assessed in 427 patients. The 70-gene prognosis signature identified 219 (51%) patients with good prognosis and 208 (49%) patients with poor prognosis. The Dutch CBO guidelines identified 184 patients (43%) with poor prognosis, which was discordant with those findings obtained with the prognosis signature in 128 (30%) patients. Oncologists recommended adjuvant treatment in 203 (48%) patients based on Dutch CBO guidelines, in 265 (62%) patients if the guidelines were used with the prognosis signature, and in 259 (61%) patients if Dutch CBO guidelines, prognosis signature, and patients' preferences for treatment were all taken into account. Adjuvant! Online guidelines identified more patients with poor prognosis than did the signature alone (294 [69%]), and discordance with the signature occurred in 160 (37%) patients. St Gallen guidelines identified 353 (83%) patients with poor prognosis with the signature and discordance in 168 (39%) patients. Nottingham Prognostic Index recorded 179 (42%) patients with poor prognosis with the signature and discordance in 117 (27%) patients. Interpretation: Use of the prognosis signature is feasible in Dutch community hospitals. Adjuvant systemic treatment was advised less often when the more restrictive Dutch CBO guidelines were used compared with that finally given after use of the prognosis signature. For the other guidelines assessed, less adjuvant chemotherapy would be given when the data based on prognosis signature alone are used, which might spare patients from adverse effects and confirms previous findings. Future studies should assess whether use of the prognosis signature could improve survival or equal survival while avoiding unnecessary adjuvant systemic treatment without affecting patients' survival, and further assess the factors that physicians use to recommend adjuvant systemic treatment