Functional relevance of novel p300-mediated lysine 314 and 315 acetylation of RelA/p65

Nuclear factor kappaB (NF-κB) plays an important role in the transcriptional regulation of genes involved in immunity and cell survival. We show here in vitro and in vivo acetylation of RelA/p65 by p300 on lysine 314 and 315, two novel acetylation sites. Additionally, we confirmed the acetylation on lysine 310 shown previously. Genetic complementation of RelA/p65−/− cells with wild type and non-acetylatable mutants of RelA/p65 (K314R and K315R) revealed that neither shuttling, DNA binding nor the induction of anti-apoptotic genes by tumor necrosis factor α was affected by acetylation on these residues. Microarray analysis of these cells treated with TNFα identified specific sets of genes differently regulated by wild type or acetylation-deficient mutants of RelA/p65. Specific genes were either stimulated or repressed by the acetylation-deficient mutants when compared to RelA/p65 wild type. These results support the hypothesis that site-specific p300-mediated acetylation of RelA/p65 regulates the specificity of NF-κB dependent gene expression

Genomic “Dark Matter” in Prostate Cancer: Exploring the Clinical Utility of ncRNA as Biomarkers

Prostate cancer is the most diagnosed cancer among men in the United States. While the majority of patients who undergo surgery (prostatectomy) will essentially be cured, about 30–40% men remain at risk for disease progression and recurrence. Currently, patients are deemed at risk by evaluation of clinical factors, but these do not resolve whether adjuvant therapy will significantly attenuate or delay disease progression for a patient at risk. Numerous efforts using mRNA-based biomarkers have been described for this purpose, but none have successfully reached widespread clinical practice in helping to make an adjuvant therapy decision. Here, we assess the utility of non-coding RNAs as biomarkers for prostate cancer recurrence based on high-resolution oligonucleotide microarray analysis of surgical tissue specimens from normal adjacent prostate, primary tumors, and metastases. We identify differentially expressed non-coding RNAs that distinguish between the different prostate tissue types and show that these non-coding RNAs can predict clinical outcomes in primary tumors. Together, these results suggest that non-coding RNAs are emerging from the “dark matter” of the genome as a new source of biomarkers for characterizing disease recurrence and progression. While this study shows that non-coding RNA biomarkers can be highly informative, future studies will be needed to further characterize the specific roles of these non-coding RNA biomarkers in the development of aggressive disease

Transcriptome-Wide Detection of Differentially Expressed Coding and Non-Coding Transcripts and Their Clinical Significance in Prostate Cancer

Prostate cancer is a clinically and biologically heterogeneous disease. Deregulation of splice variants has been shown to contribute significantly to this complexity. High-throughput technologies such as oligonucleotide microarrays allow for the detection of transcripts that play a role in disease progression in a transcriptome-wide level. In this study, we use a publicly available dataset of normal adjacent, primary tumor, and metastatic prostate cancer samples (GSE21034) to detect differentially expressed coding and non-coding transcripts between these disease states. To achieve this, we focus on transcript-specific probe selection regions, that is, those probe sets that correspond unambiguously to a single transcript. Based on this, we are able to pinpoint at the transcript-specific level transcripts that are differentially expressed throughout prostate cancer progression. We confirm previously reported cases and find novel transcripts for which no prior implication in prostate cancer progression has been made. Furthermore, we show that transcript-specific differential expression has unique prognostic potential and provides a clinically significant source of biomarker signatures for prostate cancer risk stratification. The results presented here serve as a catalog of differentially expressed transcript-specific markers throughout prostate cancer progression that can be used as basis for further development and translation into the clinic

Positioning pharmacists’ roles in primary health care: a discourse analysis of the compensation plan in Alberta, Canada

Abstract Background A comprehensive Compensation Plan for pharmacy services delivered by community pharmacists was implemented in Alberta, Canada in July 2012. Services covered by the Compensation Plan include care planning services, prescribing services such as adapting prescriptions, and administering a drug or publicly-funded vaccine by injection. Understanding how the Compensation Plan was framed and communicated provides insight into the roles of pharmacists and the potential influence of language on the implementation of services covered by the Compensation Plan by Albertan pharmacists. The objective of this study is to examine the positioning of pharmacists’ roles in documents used to communicate the Compensation Plan to Albertan pharmacists and other audiences. Methods Publicly available documents related to the Compensation Plan, such as news releases or reports, published between January 2012 and December 2015 were obtained from websites such as the Government of Alberta, Alberta Blue Cross, the Alberta College of Pharmacists, the Alberta Pharmacists’ Association, and the Blueprint for Pharmacy. Searches of the Canadian Newsstand database and Google identified additional documents. Discourse analysis was performed using social positioning theory to explore how pharmacists’ roles were constructed in communications about the Compensation Plan. Results In total, 65 publicly available documents were included in the analysis. The Compensation Plan was put forward as a framework for payment for professional services and formal legitimization of pharmacists’ changing professional roles. The discourse associated with the Compensation Plan positioned pharmacists’ roles as: (1) expanding to include services such as medication management for chronic diseases, (2) contributing to primary health care by providing access to services such as prescription renewals and immunizations, and (3) collaborating with other health care team members. Pharmacists’ changing roles were positioned in alignment with the aims of primary health care. Conclusions Social positioning theory provides a useful lens to examine the dynamic and evolving roles of pharmacists. This study provides insight into how communications regarding the Compensation Plan in Alberta, Canada positioned pharmacists’ changing roles in the broader context of changes to primary health care delivery. Our findings may be useful for other jurisdictions considering implementation of remunerated clinical services provided by pharmacists

The dual orexin receptor antagonist almorexant induces sleep and decreases orexin-induced locomotion by blocking orexin 2 receptors

Orexin peptides regulate locomotor activity and sleep-wake balance by activating orexin 1 and orexin 2 receptors (OX1R and OX2R). Dual OX1R and OX2R antagonists reduce activity and promote sleep in multiple species, including man. We tested the effects of orexin A and almorexant, a dual OX1R/OX2R antagonist, in C57BL/6J mice and in mice lacking OX1Rs, OX2Rs or both to investigate the roles of the two receptors in orexin-induced locomotion and in sleep/wake regulation. Orexin A induced locomotion primarily by activating OX2Rs as locomotion was increased following intracerebroventricular orexin in OX1R-/- mice but not in OX2R-/- or OX1R-/-/OX2R-/- mice. Almorexant attenuated the orexin A-induced locomotion, demonstrating in vivo that almorexant specifically inhibits the actions of orexin. As in other species, almorexant dose-dependently increased rapid eye movement (REM) and non-REM (NREM) sleep in C57BL/6J mice. Sleep promotion by almorexant was mediated by inhibition of the known OXRs as almorexant was ineffective in OX1R-/-/OX2R-/- mice. Almorexant induced sleep in OX1R-/- mice but not in OX2R-/- mice, demonstrating that antagonism of OX2Rs is sufficient for sleep induction. When almorexant was incubated with the receptors for short periods of time, it behaved as a dual antagonist against orexin A-induced Ca2+ responses. However, with increasing incubation times, almorexant acquired OX2R selectivity confirming the findings from binding assays and further suggesting it may behave as an OX2R antagonist in vivo. Thus, OX2R activation mediates the stimulatory effects of orexin A on locomotion and antagonism of OX2R is sufficient to promote sleep in mice

Using radiogenomics to characterize MRI-guided prostate cancer biopsy heterogenity

25 Background: Current methods for prostate cancer risk stratification are often insufficient to accurately predict outcome after definitive therapy. As tumor multi-focality and genetic heterogeneity can lead to diagnostic prostate biopsy sampling bias, we hypothesize that quantitative imaging with multiparametric (MP)-MRI will more accurately direct targeted biopsies to index lesions associated with highest risk clinical and genomic features, and improve accuracy of current risk classification systems. Methods: Regionally distinct prostate habitats were delineated on MP-MRI (T2w, perfusion and diffusion imaging). Directed biopsies were performed on 17 habitats from 6 patients using MRI-ultrasound fusion. Biopsy location was characterized with 51 radiographic features (including intensity, volume, perfusion, and diffusion paramters). Transcriptome-wide analysis of 1.4 million RNA probes was performed on RNA from each habitat. Genomics features with insignificant expression values ( 0.7). Furthermore, genomic features were found to be significantly enriched for prostate cancer related pathways (p < 0.05), representing a potential biologically meaningful link between imaging and genomic data. Conclusions: MP-MRI-targeted diagnostic biopsies can potentially improve risk classification by directing pathological and genomic analysis to highest risk index lesions. This is the first demonstration of a link between quantitative imaging features (radiomics) with genomic features in MRI-directed prostate biopsies

Evaluating the clinical impact of a genomic classifier in prostate cancer using individualized decision analysis.

BackgroundCurrently there is controversy surrounding the optimal way to treat patients with prostate cancer in the post-prostatectomy setting. Adjuvant therapies carry possible benefits of improved curative results, but there is uncertainty in which patients should receive adjuvant therapy. There are concerns about giving toxicity to a whole population for the benefit of only a subset. We hypothesized that making post-prostatectomy treatment decisions using genomics-based risk prediction estimates would improve cancer and quality of life outcomes.MethodsWe developed a state-transition model to simulate outcomes over a 10 year horizon for a cohort of post-prostatectomy patients. Outcomes included cancer progression rates at 5 and 10 years, overall survival, and quality-adjusted survival with reductions for treatment, side effects, and cancer stage. We compared outcomes using population-level versus individual-level risk of cancer progression, and for genomics-based care versus usual care treatment recommendations.ResultsCancer progression outcomes, expected life-years (LYs), and expected quality-adjusted life-years (QALYs) were significantly different when individual genomics-based cancer progression risk estimates were used in place of population-level risk estimates. Use of the genomic classifier to guide treatment decisions provided small, but statistically significant, improvements in model outcomes. We observed an additional 0.03 LYs and 0.07 QALYs, a 12% relative increase in the 5-year recurrence-free survival probability, and a 4% relative reduction in the 5-year probability of metastatic disease or death.ConclusionsThe use of genomics-based risk prediction to guide treatment decisions may improve outcomes for prostate cancer patients. This study offers a framework for individualized decision analysis, and can be extended to incorporate a wide range of personal attributes to enable delivery of patient-centered tools for informed decision-making