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Background
Prostate cancer (PCa) is a very heterogeneous disease with respect to clinical outcome. This study explored differential DNA methylation in a priori selected genes to diagnose PCa and predict clinical failure (CF) in high-risk patients.
Methods
A quantitative multiplex, methylation-specific PCR assay was developed to assess promoter methylation of the APC, CCND2, GSTP1, PTGS2 and RARB genes in formalin-fixed, paraffin-embedded tissue samples from 42 patients with benign prostatic hyperplasia and radical prostatectomy specimens of patients with high-risk PCa, encompassing training and validation cohorts of 147 and 71 patients, respectively. Log-rank tests, univariate and multivariate Cox models were used to investigate the prognostic value of the DNA methylation.
Results
Hypermethylation of APC, CCND2, GSTP1, PTGS2 and RARB was highly cancer-specific. However, only GSTP1 methylation was significantly associated with CF in both independent high-risk PCa cohorts. Importantly, trichotomization into low, moderate and high GSTP1 methylation level subgroups was highly predictive for CF. Patients with either a low or high GSTP1 methylation level, as compared to the moderate methylation groups, were at a higher risk for CF in both the training (Hazard ratio [HR], 3.65; 95% CI, 1.65 to 8.07) and validation sets (HR, 4.27; 95% CI, 1.03 to 17.72) as well as in the combined cohort ( HR, 2.74; 95% CI, 1.42 to 5.27) in multivariate analysis.
Conclusions
Classification of primary high-risk tumors into three subtypes based on DNA methylation can be combined with clinico-pathological parameters for a more informative risk-stratification of these PCa patients.
Background: RNA-seq and its variant differential RNA-seq (dRNA-seq) are today routine methods for transcriptome analysis in bacteria. While expression profiling and transcriptional start site prediction are standard tasks today, the problem of identifying transcriptional units in a genome-wide fashion is still not solved for prokaryotic systems.
Results: We present RNASEG, an algorithm for the prediction of transcriptional units based on dRNA-seq data. A key feature of the algorithm is that, based on the data, it distinguishes between transcribed and un-transcribed genomic segments. Furthermore, the program provides many different predictions in a single run, which can be used to infer the significance of transcriptional units in a consensus procedure. We show the performance of our method based on a well-studied dRNA-seq data set for Helicobacter pylori.
Conclusions: With our algorithm it is possible to identify operons and 5'- and 3'-UTRs in an automated fashion. This alleviates the need for labour intensive manual inspection and enables large-scale studies in the area of comparative transcriptomics.
Mitochondrial structure and function is emerging as a major contributor to neuromuscular disease, highlighting the need for the complete elucidation of the underlying molecular and pathophysiological mechanisms. Following a forward genetics approach with N-ethyl-N-nitrosourea (ENU)-mediated random mutagenesis, we identified a novel mouse model of autosomal recessive neuromuscular disease caused by a splice-site hypomorphic mutation in a novel gene of unknown function, DnaJC11. Recent findings have demonstrated that DNAJC11 protein co-immunoprecipitates with proteins of the mitochondrial contact site (MICOS) complex involved in the formation of mitochondrial cristae and cristae junctions. Homozygous mutant mice developed locomotion defects, muscle weakness, spasticity, limb tremor, leucopenia, thymic and splenic hypoplasia, general wasting and early lethality. Neuropathological analysis showed severe vacuolation of the motor neurons in the spinal cord, originating from dilatations of the endoplasmic reticulum and notably from mitochondria that had lost their proper inner membrane organization. The causal role of the identified mutation in DnaJC11 was verified in rescue experiments by overexpressing the human ortholog. The full length 63 kDa isoform of human DNAJC11 was shown to localize in the periphery of the mitochondrial outer membrane whereas putative additional isoforms displayed differential submitochondrial localization. Moreover, we showed that DNAJC11 is assembled in a high molecular weight complex, similarly to mitofilin and that downregulation of mitofilin or SAM50 affected the levels of DNAJC11 in HeLa cells. Our findings provide the first mouse mutant for a putative MICOS protein and establish a link between DNAJC11 and neuromuscular diseases.
Quantitation of Glucocorticoid Receptor DNA-Binding Dynamics by Single-Molecule Microscopy and FRAP
(2014)
Recent advances in live cell imaging have provided a wealth of data on the dynamics of transcription factors. However, a consistent quantitative description of these dynamics, explaining how transcription factors find their target sequences in the vast amount of DNA inside the nucleus, is still lacking. In the present study, we have combined two quantitative imaging methods, single-molecule microscopy and fluorescence recovery after photobleaching, to determine the mobility pattern of the glucocorticoid receptor (GR) and the mineralocorticoid receptor (MR), two ligand-activated transcription factors. For dexamethasone-activated GR, both techniques showed that approximately half of the population is freely diffusing, while the remaining population is bound to DNA. Of this DNA-bound population about half the GRs appeared to be bound for short periods of time (similar to 0.7 s) and the other half for longer time periods (similar to 2.3 s). A similar pattern of mobility was seen for the MR activated by aldosterone. Inactive receptors (mutant or antagonist-bound receptors) show a decreased DNA binding frequency and duration, but also a higher mobility for the diffusing population. Likely, very brief (<= 1 ms) interactions with DNA induced by the agonists underlie this difference in diffusion behavior. Surprisingly, different agonists also induce different mobilities of both receptors, presumably due to differences in ligand-induced conformational changes and receptor complex formation. In summary, our data provide a consistent quantitative model of the dynamics of GR and MR, indicating three types of interactions with DNA, which fit into a model in which frequent low-affinity DNA binding facilitates the search for high-affinity target sequences.
How do physico-chemical stimulus features, perception, and physiology relate? Given the multi-layered and parallel architecture of brains, the question specifically is where physiological activity patterns correspond to stimulus features and/or perception. Perceived distances between six odour pairs are defined behaviourally from four independent odour recognition tasks. We find that, in register with the physico-chemical distances of these odours, perceived distances for 3octanol and n-amylacetate are consistently smallest in all four tasks, while the other five odour pairs are about equally distinct. Optical imaging in the antennal lobe, using a calcium sensor transgenically expressed in only first-order sensory or only second-order olfactory projection neurons, reveals that 3-octanol and n-amylacetate are distinctly represented in sensory neurons, but appear merged in projection neurons. These results may suggest that within-antennal lobe processing funnels sensory signals into behaviourally meaningful categories, in register with the physico-chemical relatedness of the odours.