A urine-based methylation signature for risk stratification within low-risk prostate cancer.

BACKGROUND: Prostate cancer overdiagnosis and overtreatment represents a major problem. Many men with low-grade disease on biopsy are undergraded and they harbour high-grade disease at prostatectomy with no reliable way to identify these men. We used a novel urine-based 2-gene methylation test to identify prostate cancers with aggressive features. METHODS: Following a proof of concept study in 100 post-radical prostatectomy tissue samples, urine samples were tested from 665 men at multiple U.S. centers undergoing prostate needle biopsy for elevated prostate-specific antigen (2-10 ng ml(-1)). A prediction model was then developed from a combination of clinical factors and the urine-based markers. It was then prospectively tested for accurate prediction of adverse disease (surgical Gleason score ⩾7 and/or a pathological stage ⩾T3a) using urine from a separate cohort of 96 men before radical prostatectomy. RESULTS: Among pre-prostatectomy men with a biopsy Gleason score <7, 41% had adverse disease of which 100% were correctly identified by the test with a negative predictive value of 100% (95% confidence interval, 86-100%). CONCLUSIONS: This urine-based test accurately identifies men with clinical low-risk disease who do not have adverse pathology in their prostates and would be excellent candidates for active surveillance.

RNA expression in the early characterization of hepatotoxicants in Wistar rats by high-density DNA microarrays.

High-density microarrays are useful tools to study gene expression for the purpose of characterizing functional tissue changes in response to the action of drugs and chemicals. To test whether high-density expression data can identify mechanisms of toxicity and to identify an unknown sample through its RNA expression pattern, groups of male Wistar rats were administered 6 hepatotoxicants. The compounds chosen for this study were microcystin-LR (MLR), phenobarbital (PB), lipopolysaccharide (LPS), carbon tetrachloride (CT), thioacetamide (THA), and cyproterone acetate (CPA). These hepatotoxicants are known to induce adverse liver effects through different mechanisms. Liver mRNA was isolated and used to generate biotinylated cRNA for hybridization to a custom 1,600-rat gene DNA microarray. Treatment correlation matrices analyzed hybridization data from a hepatotoxicant-blinded sample, with gene expression coefficients (GEC) evaluated by means of hierarchical cluster analysis and visual representation as dendrograms. The experimental liver toxicity from the different treatments was confirmed by means of concurrent histopathology, liver enzymes, and bilirubin assays. This toxico genomic analysis identified multiple genes and groups of genes that were affected by the hepatotoxicants on study, indicating that high-density microarray expression data are useful to identify groups of genes involved in toxicity. In addition, the mRNA expression profile of an unidentified sample can be accurately identified when compared with the expression profiles resident in the data set. This study supports the use of gene expression-profiling technology to determine or to predict toxic liver effects.

Assessment of the sensitivity and specificity of oligonucleotide (50mer) microarrays.

To examine the utility and performance of 50mer oligonucleotide (oligonucleotide probe) microarrays, gene-specific oligonucleotide probes were spotted along with PCR probes onto glass microarrays and the performance of each probe type was evaluated. The specificity of oligonucleotide probes was studied using target RNAs that shared various degrees of sequence similarity. Sensitivity was defined as the ability to detect a 3-fold change in mRNA. No significant difference in sensitivity between oligonucleotide probes and PCR probes was observed and both had a minimum reproducible detection limit of approximately 10 mRNA copies/cell. Specificity studies showed that for a given oligonucleotide probe any 'non-target' transcripts (cDNAs) >75% similar over the 50 base target may show cross-hybridization. Thus non-target sequences which have >75-80% sequence similarity with target sequences (within the oligonucleotide probe 50 base target region) will contribute to the overall signal intensity. In addition, if the 50 base target region is marginally similar, it must not include a stretch of complementary sequence >15 contiguous bases. Therefore, knowledge about the target sequence, as well as its similarity to other mRNAs in the target tissue or RNA sample, is required to design successful oligonucleotide probes for quality microarray results. Together these results validate the utility of oligonucleotide probe (50mer) glass microarrays.