Analysis of the genomic response of human prostate cancer cells to histone deacetylase inhibitors

Histone deacetylases (HDACs) have emerged as important targets for cancer treatment. HDAC-inhibitors (HDACis) are well tolerated in patients and have been approved for the treatment of patients with cutaneous T-cell lymphoma (CTCL). To improve the clinical benefit of HDACis in solid tumors, combination strategies with HDACis could be employed. In this study, we applied Analysis of Functional Annotation (AFA) to provide a comprehensive list of genes and pathways affected upon HDACi-treatment in prostate cancer cells. This approach provides an unbiased and objective approach to high throughput data mining. By performing AFA on gene expression data from prostate cancer cell lines DU-145 (an HDACi-sensitive cell line) and PC3 (a relatively HDACi-resistant cell line) treated with HDACis valproic acid or vorinostat, we identified biological processes that are affected by HDACis and are therefore potential treatment targets for combination therapy. Our analysis revealed that HDAC-inhibition resulted among others in upregulation of major histocompatibility complex (MHC) genes and deregulation of the mitotic spindle checkpoint by downregulation of genes involved in mitosis. These findings were confirmed by AFA on publicly available data sets from HDACi-treated prostate cancer cells. In total, we analyzed 375 microarrays with HDACi treated and non-treated (control) prostate cancer cells. All results from this extensive analysis are provided as an online research source (available at the journal’s website and at http://luigimarchionni.org/HDACIs.html). By publishing this data, we aim to enhance our understanding of the cellular changes after HDAC-inhibition, and to identify novel potential combination strategies with HDACis for the treatment of prostate cancer patients.     

Searching for phenotypic causal networks involving complex traits: an application to European quail

Background

Structural equation models (SEM) are used to model multiple traits and the casual links among them. The number of different causal structures that can be used to fit a SEM is typically very large, even when only a few traits are studied. In recent applications of SEM in quantitative genetics mixed model settings, causal structures were pre-selected based on prior beliefs alone. Alternatively, there are algorithms that search for structures that are compatible with the joint distribution of the data. However, such a search cannot be performed directly on the joint distribution of the phenotypes since causal relationships are possibly masked by genetic covariances. In this context, the application of the Inductive Causation (IC) algorithm to the joint distribution of phenotypes conditional to unobservable genetic effects has been proposed.

Methods

Here, we applied this approach to five traits in European quail: birth weight (BW), weight at 35 days of age (W35), age at first egg (AFE), average egg weight from 77 to 110 days of age (AEW), and number of eggs laid in the same period (NE). We have focused the discussion on the challenges and difficulties resulting from applying this method to field data. Statistical decisions regarding partial correlations were based on different Highest Posterior Density (HPD) interval contents and models based on the selected causal structures were compared using the Deviance Information Criterion (DIC). In addition, we used temporal information to perform additional edge orienting, overriding the algorithm output when necessary.

Results

As a result, the final causal structure consisted of two separated substructures: BW→AEW and W35→AFE→NE, where an arrow represents a direct effect. Comparison between a SEM with the selected structure and a Multiple Trait Animal Model using DIC indicated that the SEM is more plausible.

Conclusions

Coupling prior knowledge with the output provided by the IC algorithm allowed further learning regarding phenotypic causal structures when compared to standard mixed effects SEM applications.     

CLARIFYING APPEALS TO DIGNITY IN MEDICAL ETHICS FROM AN HISTORICAL PERSPECTIVE

Over the past few decades the concept of (human) dignity has deeply pervaded medical ethics. Appeals to dignity, however, are often unclear. As a result some prefer to eliminate the concept from medical ethics, whereas others try to render it useful in this context. We think that appeals to dignity in medical ethics can be clarified by considering the concept from an historical perspective. Firstly, on the basis of historical texts we propose a framework for defining the concept in medical debates. The framework shows that dignity can occur in a relational, an unconditional, a subjective and a Kantian form. Interestingly, all forms relate to one concept since they have four features in common: dignity refers, in a restricted sense, to the 'special status of human beings'; it is based on essential human characteristics; the subject of dignity should live up to it; and it is a vulnerable concept, it can be lost or violated. We argue that being explicit about the meaning of dignity will prevent dignity from becoming a conversation-stopper in moral debate. Secondly, an historical perspective on dignity shows that it is not yet time to dispose of dignity in medical ethics. At least Kantian and relational dignity can be made useful in medical ethics.     

Statistical evidence for two major proteins in freeze-fractured gastric parietal cell tubulovesicles and canaliculus

In a previous work, resting and acid-secreting rabbit gastric mucosa were freeze-fractured and shadowed at 45° with Pt-C. The shadow widths of proteic particles of tubulovesicle and canaliculus membranes were measured and compared. It was concluded that the frequency distributions of widths are significantly different in resting and secreting membranes and that each distribution accounts for several subpopulations of homogenous particles. In the present study, an attempt is made to describe the experimental distributions as a mixture of those of two major proteins, say A and B and their aggregates (AA, AB and BB). The modelling, although simple, gave a very satisfactory statistical fit between observed and computed distributions. The comparison of parameters calculated from histamine and ranitidine experimental data further improves the fits and finally, component A accounts for 69% of the particles. Most replica of A particles are heart-shaped and the median shadow widths are 6.1 and 6.8 nm in canaliculus and tubulovesicles respectively. The component B accounts for 31% of the particles. They mainly appear as small barrels and the median shadow widths are 8.8 and 10.3 nm in canaliculus and tubulovesicles respectively. According to calculated parameters and observed particle replica, the onset of secretion does not change the relative ratio of proteins but changes their shapes. Component A should be the (H⁺, K⁺)ATPase whereas debate on the identity of B is wide open.     

An important step towards completing the rheumatoid arthritis cycle

In the previous issue of Arthritis Research & Therapy data are presented showing that circulating immune complexes containing citrullinated fibrin(ogen) are present in anti-citrullinated protein antibody-positive rheumatoid arthritis patients, and that such immune complexes co-localize with complement factor C3 in the rheumatoid synovium. These results corroborate the idea that citrullination is intimately involved in the pathophysiology of rheumatoid arthritis and complete our model (the rheumatoid arthritis cycle) for the development and chronic nature of this disease.     

The RNA interference pathway: a new target for autoimmunity

Many intracellular macromolecular complexes that are involved in the production or degradation of RNAs are targeted by autoantibodies in systemic autoimmune diseases. RNA interference (RNAi) is a recently characterized gene silencing pathway by which specific mRNAs are either degraded or translationally suppressed. In a recent issue of Arthritis Research and Therapy, Andrew Jakymiw and colleagues reported that the enigmatic Su autoantigen complex contains key components of the RNAi machinery. Anti-Su autoantibodies from both human patients with rheumatic diseases and a mouse model of autoimmunity recognize the endonucleolytic Argonaute and Dicer proteins, both crucial enzymes of the RNAi pathway. These data raise the question of how the anti-Su response is triggered. So far, it is unknown whether molecular modifications may be involved, as has been proposed for other intracellular autoantigens. The implication of RNAi in anti-viral defence may suggest a role for virus infection in this process.